Metabolism and Medicine: The Metabolic Landscape of Health and Disease (Volume 2) (Foundations of Biochemistry and Biophysics) 2021027983, 2021027984, 9780367699925, 9780367712297, 0367699923

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Metabolism and Medicine

Foundations of Biochemistry and Biophysics This textbook series focuses on foundational principles and experimental approaches across all areas of biological physics, covering core subjects in a modern biophysics curriculum. Individual titles address such topics as molecular biophysics, statistical biophysics, molecular modeling, single-molecule biophysics, and chemical biophysics. It is aimed at advanced undergraduate- and graduate-level curricula at the intersection of biological and physical sciences. The goal of the series is to facilitate interdisciplinary research by training biologists and biochemists in quantitative aspects of modern biomedical research and to teach key biological principles to students in physical sciences and engineering. Authors are also welcome to contact the publisher (Physics Editor, Carolina Antunes: [email protected]) to discuss new title ideas. Light Harvesting in Photosynthesis Roberta Croce, Rienk van Grondelle, Herbert van Amerongen, Ivo van Stokkum (Eds.) An Introduction to Single Molecule Biophysics Yuri L. Lyubchenko (Ed.) Biomolecular Kinetics: A Step-by-Step Guide Clive R. Bagshaw Biomolecular Thermodynamics: From Theory to Application Douglas E. Barrick Quantitative Understanding of Biosystems: An Introduction to Biophysics Thomas M. Nordlund Quantitative Understanding of Biosystems: An Introduction to Biophysics, Second Edition Thomas M. Nordlund, Peter M. Hoffmann Entropy and Free Energy in Structural Biology: Thermodynamics, Statistical Mechanics And Computer Simulation Hagai Meirovitch Metabolism and Medicine: Two Volume Set Brian Fertig https://www.crcpress.com/Foundations-of-Biochemistry-and-Biophysics/book-series/CRCFOUBIOPHY

Metabolism and Medicine The Metabolic Landscape of Health and Disease Volume 2

Brian J. Fertig, M.D., F.A.C.E. Associate Professor, Robert Wood Johnson Medical School Chairman, Department of Diabetes & Endocrinology, Hackensack Meridian Health @ JFK University Medical Center Founder Diabetes & Osteoporosis Center, Piscataway, N.J.

First edition published 2022 by CRC Press 6000 Broken Sound Parkway NW, Suite 300, Boca Raton, FL 33487-2742 and by CRC Press 2 Park Square, Milton Park, Abingdon, Oxon, OX14 4RN © 2022 Brian Fertig CRC Press is an imprint of Taylor & Francis Group, LLC Reasonable efforts have been made to publish reliable data and information, but the author and publisher cannot assume responsibility for the validity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may rectify in any future reprint. Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or utilized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopying, microfilming, and recording, or in any information storage or retrieval system, without written permission from the publishers. For permission to photocopy or use material electronically from this work, access www​.copyright​.com or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923, 978-750-8400. For works that are not available on CCC please contact mpkbookspermissions​@tandf​.co​​.uk Trademark notice: Product or corporate names may be trademarks or registered trademarks and are used only for identification and explanation without intent to infringe.

Library of Congress Cataloging-in-Publication Data Names: Fertig, Brian, author. Title: Metabolism and medicine / Brian Fertig, M.D., Robert Wood Johnson Medical School, Department of Diabetes & Endocrinology Hackensack Meridian, Health @ JFK University Medical Center. Description: First edition. | Boca Raton : CRC Press, 2022. | Series: Foundation of biochemistry and biophysics | Includes bibliographical references and index. Identifiers: LCCN 2021027983 (print) | LCCN 2021027984 (ebook) | ISBN 9780367699925 (hardback) | ISBN 9780367712297 (paperback) | ISBN 9781003149897 (ebook) Subjects: LCSH: Metabolism--Disorders. | Human body--Microbiology. Classification: LCC RC627.5 .F47 2022 (print) | LCC RC627.5 (ebook) | DDC 616.3/9--dc23 LC record available at https://lccn.loc.gov/2021027983 LC ebook record available at https://lccn.loc.gov/2021027984 ISBN: 9780367699925 (hbk) ISBN: 9780367712297 (pbk) ISBN: 9781003149897 (ebk) DOI: 10.1201/9781003149897 Typeset in Times by Deanta Global Publishing Services, Chennai, India

Dedicated to my wife, Eileen, and my son, Matthew, without whom none of this would have even mattered.

Contents Prologue.......................................................................................................................................................................................... xv Acknowledgments.........................................................................................................................................................................xvii Author............................................................................................................................................................................................xxi Personal Statements.....................................................................................................................................................................xxiii 1. Introduction to Metabolism: A New Model for Medicine................................................................................................... 1 Abbreviations............................................................................................................................................................................ 1 1.1 Brief History of Metabolism and the Complex Personalities of the Scientists Who Shaped It.................................... 2 1.2 Opening Remarks.......................................................................................................................................................... 4 (Biology, Introductory Level) ....................................................................................................................................... 4 1.3 Metabolism Fuels Biological Motors and Engines........................................................................................................ 4 (Physics, Introductory Level)......................................................................................................................................... 4 (Biology/Biological Chemistry, Clinical Level)............................................................................................................ 5 1.4 Metabolic Pathways and Cellular Respiration .............................................................................................................. 5 (Biological Chemistry, Introductory Level)................................................................................................................... 5 1.4.1 Metabolic Modes of Energy Production.......................................................................................................... 7 (Physics and Quantum Biology Introductory Level)....................................................................................... 7 1.4.2 Metabolic Cycles and Metabolic Rate............................................................................................................. 8 (Biological Metabolism and Translational Medicine, Introductory Level)..................................................... 8 (Physics Metabolism and Translational Medicine, Introductory/Intermediate Level)..................................... 8 (Biological Chemistry and Translational Medicine,Introductory/Intermediate Level).................................... 9 1.4.3 Metabolic Rate, Metabolic Efficiency, and Cellular Respiration in Clinical Medicine................................ 10 (Clinical Biological Physiology/Exercise Physiology, Introductory Level).................................................. 10 1.5 Biological Entropy Production Rate and Aging.......................................................................................................... 13 (Biophysics, Metabolism, and Physiology, Introductory Level).................................................................................. 13 1.5.1 Biological Entropy Production Rate and Pharmacological Implications ..................................................... 14 (Metabolism and Translational Medicine, Introductory Level)..................................................................... 14 1.6 Key Bioenergetics Concepts........................................................................................................................................ 14 (Basic Concept of Metabolism, Introductory Level)................................................................................................... 14 1.7 Dysfunction in Electron Transport System, Mitochondrial Function, and its Importance in Chronic Disease......... 16 (Metabolism and Physiology, Translational Medicine, Introductory Level)............................................................... 16 1.7.1 Biochemistry of the Electron Transport System............................................................................................ 17 (Biochemistry, Medium Difficulty)................................................................................................................ 17 Basics of the Electron Transport Chain.......................................................................................................... 17 1.7.2 Biochemical Characteristics of Electron Transport Chain Dysfunction....................................................... 17 (Mechanism of ROS Generation Through ETC, Introductory Level)........................................................... 17 1.7.3 Clinical Perspective of Electron Transport System Dysfunction.................................................................. 18 (Mitochondrial Dysfunction, Metabolic Homeostasis, and Onset of Chronic Diseases of Aging, Clinical Level)............................................................................................................................... 18 1.7.4 Influence of Glucose and Lipid Metabolism on the Function of the Electron Transport System................. 18 (Biochemistry, Intermediate Level)................................................................................................................ 18 1.7.5 Redox Potential and Its Importance in Biochemical Reactions.................................................................... 20 1.7.6 Clinical Application and Examples of Redox State to Insulin Resistance and Type 2 Diabetes.................. 21 1.7.7 Contributions of Macronutrients to Redox Potential, Proton Motive Force, and Oxidative Stress.............. 23 1.7.8 Elevated Fatty Acid Metabolism and Its Relevance in Aging and Chronic Diseases................................... 24 1.7.9 Targeting the Electron Transport System for the Treatments of Metabolic Disease.................................... 25 1.7.9.1 Improving Mitochondrial Metabolism.......................................................................................... 25 1.7.9.2 Manipulation of Mitochondrial Redox System for Therapeutic Implications: Pharmacologic Intervention.......................................................................................................... 26 1.7.10 Conclusion...................................................................................................................................................... 26 1.8 Ketone Bodies in Metabolism in Health and Disease................................................................................................. 27 (Metabolism and Physiology, Ketones, Introductory Level)....................................................................................... 27 1.8.1 Ketone Bodies are “Super Fuels” and Electron Scavengers.......................................................................... 28 vii

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Contents 1.8.2

Role of Ketone Bodies in Starvation............................................................................................................. 28 (Molecular Biology, Intermediate Level)....................................................................................................... 28 1.8.3 Benefits and Dangers of Ketosis in Diabetes................................................................................................. 29 (Molecular Biology, Intermediate Level)....................................................................................................... 29 1.8.4 Potential Benefits of Ketosis in Non-Diabetic Diseases................................................................................ 30 (Biochemistry, Introductory Level)................................................................................................................ 30 1.8.5 Yin-Yang Perspectives on Ketone Body Metabolism ................................................................................... 31 (Biochemistry, Intermediate Level)................................................................................................................ 31 1.8.6 Conclusions.................................................................................................................................................... 32 1.9 Energy Sensors and Fuel Gauges................................................................................................................................. 32 (Metabolic Physiology and Translational Medicine, Introductory Level)................................................................... 32 1.9.1 Energy Sensors, Circadian Biology, and Metabolic Homeostasis................................................................. 32 (Metabolic Physiology and Circadian Biology, Translational Medicine, Intermediate Level)...................... 32 1.9.2 Parameters of Diet and an ETC Mechanistic Model of Human Metabolic Health and Disease.................. 33 (Circadian Biology and Translational Medicine, Introductory Level)........................................................... 33 1.10 The Genesis of Accelerated Aging and Chronic Diseases of Aging........................................................................... 36 (Clinical Pathophysiology, Introductory Level)........................................................................................................... 36 1.10.1 Insulin Resistance, Diet, Peripheral Clocks, and Metabolism...................................................................... 36 (Metabolism, Circadian Biology, Clinical Physiology, and Pathophysiology, Introductory Level).............. 36 1.10.2 Insulin Resistance and Hyperinsulinemia: The Chicken or the Egg?........................................................... 36 (Metabolic Physiology, Introductory Level).................................................................................................. 36 1.10.3 The Protective Role of Visceral Adiposity.................................................................................................... 37 (Obesity, Translational Medicine).................................................................................................................. 37 1.10.4 Loss of or Lipolysis of VAT and Autonomic Dysfunction: An Unrecognized Parameter of Premature Chronic Disease and Mortality.................................................................................................... 38 (Obesity, Translational Medicine).................................................................................................................. 38 1.10.5 An Anecdote for Current Times: Obesity and SARS-CoV-2 in Pulmonary Fibrosis................................... 38 1.10.6 Endotoxicosis and Insulin Resistance............................................................................................................ 39 1.10.7 Visceral Adiposity at the Intersection of an Inflammatory Diet and Insulin Resistance ............................. 40 (Clinical Metabolism, Translational Medicine)............................................................................................. 40 1.11 Models of Chronic Diseases in Medicine as Metabolic Disorders............................................................................. 41 (Clinical Metabolism/Translational Medicine)............................................................................................................ 41 1.11.1 The Warburg Effect: A Modern Perspective of an Old Hypothesis.............................................................. 41 1.11.2 An Extension of Brownlee’s Unifying Hypothesis........................................................................................ 42 1.11.3 The Warburg Effect and the Extension of the Unifying Hypothesis: A Broader Unifying Pathobiology................................................................................................................................... 43 1.12 Concluding Remarks.................................................................................................................................................... 44 References............................................................................................................................................................................... 46 2. The Stress Response: From Health to Disease................................................................................................................... 49 Abbreviations.......................................................................................................................................................................... 49 Chapter Overview.................................................................................................................................................................... 49 2.1 What Is Stress?............................................................................................................................................................. 51 2.1.1 The Interdisciplinary Nature of Stress.......................................................................................................... 54 2.2 The Stress Response.................................................................................................................................................... 54 2.2.1 Homeostasis, Allostatic Load, and Allostatic Overload................................................................................ 54 2.2.2 The Stress Paradox......................................................................................................................................... 58 2.2.2.1 The Impact of Social Networks on the Stress Paradox................................................................. 59 2.2.2.2 A Clinical Example of the Stress Paradox.................................................................................... 59 2.2.3 Stress through the Physiological Fitness Landscape..................................................................................... 62 2.2.4 The Effects of Stress on Synchronized Physiology and Metabolism............................................................ 62 2.3 A Modern-Day Stress Response Model....................................................................................................................... 64 2.3.1 The Metabolic Demand of Stress.................................................................................................................. 64 2.3.2 The Uncertainty Reduction Model................................................................................................................ 65 2.4 The Neural Circuitry of Stress..................................................................................................................................... 66 2.4.1 Interconnections............................................................................................................................................. 66 2.4.2 Neuroendocrine Response to Stress and Insulin Resistance......................................................................... 66 2.4.3 Stress and Norepinephrine............................................................................................................................. 67 2.4.4 The Neural Circuitry of Uncertainty............................................................................................................. 68

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2.4.5 Uncertainty and Chronic Anxiety................................................................................................................. 69 2.4.6 The Neural Circuitry of Energy Expenditure under Stress........................................................................... 70 2.5 Motivation and Reward................................................................................................................................................ 71 2.5.1 The Neural Circuitry of Reward.................................................................................................................... 72 2.5.2 The Reward Circuitry, Stress, and the Uncertainty Model........................................................................... 74 2.5.3 Gender Differences in Response to Stressors................................................................................................ 75 2.5.4 Possible Interventions for Addictions............................................................................................................ 76 2.6 Synaptic Plasticity........................................................................................................................................................ 76 2.6.1 Long-Term Potentiation (LTP)....................................................................................................................... 76 2.6.2 Long-Term Depression (LTD)........................................................................................................................ 77 2.6.3 Synaptic Plasticity, Will Power, and Consciousness..................................................................................... 78 2.6.4 Quantum Consciousness through the Lens of the Prefrontal Cortex............................................................ 78 2.7 Toward Integration of Physical Concepts into Medical Practice................................................................................ 80 2.7.1 Stress and the Control Parameters................................................................................................................. 81 2.7.1.1 The Entanglement of the Stress Response and Biology of Time.................................................. 81 2.7.1.2 The Influence of Stress on the Microbiota.................................................................................... 84 2.7.2 The Physiological Fitness Landscape as a Clinically Useful Model............................................................. 88 2.7.3 Improving Clinical Practice by Integrating Physical and Chemical Concepts with Biology....................... 88 2.7.4 Mediators of the Shift from Health to Disease.............................................................................................. 90 2.7.5 Implementation of the Physiological Fitness Landscape Model in Clinical Practice................................... 94 2.8 Take-Home Messages.................................................................................................................................................. 97 References............................................................................................................................................................................... 98 3. Nuclear Hormone Receptors: Mediators of Dynamic (Patho)physiological Responses............................................... 105 Abbreviations........................................................................................................................................................................ 105 Chapter Overview.................................................................................................................................................................. 106 3.1 Historical Context...................................................................................................................................................... 107 3.2 Introduction................................................................................................................................................................ 108 3.2.1 Nuclear Hormone Receptor Structure......................................................................................................... 109 3.2.2 Nuclear Hormone Receptor Classifications................................................................................................. 109 3.3 NHRs Sense and Modulate Use of Energy.................................................................................................................111 3.3.1 Nuclear Hormone Receptors in Lipid Homeostasis.....................................................................................111 3.3.2 NHRs in Glucose Metabolism......................................................................................................................116 3.3.3 NHRs and Redox Homeostasis.....................................................................................................................118 3.3.4 NHRs in the Response to Exercise.............................................................................................................. 120 3.4 Nuclear Hormone Receptors Integrate Environmental Signals in a Timely Manner............................................... 121 3.5 Nuclear Hormone Receptors Are Important Pharmacological Targets with Clinical Applications......................... 122 3.6 Summary.................................................................................................................................................................... 122 3.7 Bile Acid Metabolism—A Pivotal Crossroad between Nutrient Signaling and Circadian Networking.................. 123 References............................................................................................................................................................................. 126 4. The Biology of Time: How Molecular Clocks Make Living Cells Tick..........................................................................131 Abbreviations.........................................................................................................................................................................131 Chapter Overview.................................................................................................................................................................. 133 4.1 Historical Context...................................................................................................................................................... 134 4.2 Introduction................................................................................................................................................................ 136 4.3 Physical Time, Biological Time, and Physiological Aging....................................................................................... 137 4.3.1 Physical Time Applied to Biology............................................................................................................... 137 4.3.2 Biological Time............................................................................................................................................ 139 4.3.3 Measuring Time............................................................................................................................................142 4.4 Biological Clocks, Metabolism, and ATP................................................................................................................. 144 4.5 Molecular Clocks Keep Biological Time...................................................................................................................147 4.6 Cellular and Organ System Clock Organization....................................................................................................... 148 4.6.1 The Suprachiasmatic Nucleus (SCN).......................................................................................................... 148 4.6.2 Clock Synchronization: External Cues.........................................................................................................151 4.6.2.1 Light (SCN)..................................................................................................................................151 4.6.2.2 Food: Feeding/Fasting Cycles (Liver, Pancreas, Adipose Tissue, Skeletal Muscle).................. 152 4.6.3 Exercise, Stress, and Hypoxia...................................................................................................................... 154 4.6.3.1 Exercise....................................................................................................................................... 154

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Contents 4.6.3.2 Stress............................................................................................................................................ 155 4.6.3.3 Hypoxia....................................................................................................................................... 155 4.6.4 Phase Shifts.................................................................................................................................................. 156 4.7 Hormones Display Circadian Rhythmicity............................................................................................................... 156 4.8 Chronobiology and Nuclear Hormone Receptors...................................................................................................... 158 4.8.1 Steroid Receptors......................................................................................................................................... 158 4.8.1.1 Glucocorticoid Receptor (GR)..................................................................................................... 158 4.8.2 Retinoid X Receptor (RXR) Heterodimeric Receptors............................................................................... 159 4.8.2.1 Thyroid Hormone Receptor (TR)................................................................................................ 159 4.8.2.2 Farnesoid X Receptor (FXR)...................................................................................................... 159 4.8.2.3 Constitutive Androstane Receptor (CAR)-Xenobiotic Metabolism............................................ 160 4.8.3 Lipid Sensors................................................................................................................................................ 160 4.8.3.1 Retinoid-Related Orphan Receptor (RORs)................................................................................ 160 4.8.3.2 Peroxisome Proliferator-Activated Receptors (PPARs).............................................................. 162 4.8.3.3 Peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α)..................... 162 4.8.3.4 Rev-erbs: A Family of Nuclear Hormone Receptors.................................................................. 162 4.8.4 Nuclear Hormone Receptors in Metabolism and as Exercise Mimetics..................................................... 162 4.9 Synchrony and Desynchrony of Environmental and Internal Timing: Clocks and Disease States.......................... 163 4.9.1 Metabolism Explained by Scales of Time and Space.................................................................................. 164 4.9.2 Common Causes of Circadian Disruption....................................................................................................167 4.9.3 Sleep............................................................................................................................................................. 168 4.9.4 Circadian Interactions with Nutrient Balance in Health and Disease..........................................................170 4.9.5 Glucose, Insulin, and Metabolic Disease.....................................................................................................172 4.9.6 Cyclical Insulin Resistance and the Role of Forkhead Box O (FOXO) Transcription Factors....................175 4.9.7 Circadian Misalignment of Endogenous Oscillating Cycles Contribute to Metabolic Disease and Chronic Disease of Aging..................................................................................................................... 177 4.9.8 Nocturnal Eating and Insulin Resistance.....................................................................................................178 4.9.9 Redox Status and Circadian Rhythms..........................................................................................................181 4.9.10 Adrenal Insufficiency................................................................................................................................... 182 4.9.11 Cortisol, Cushing’s, and Obesity................................................................................................................. 182 4.10 Therapeutic Interventions: Fitness Landscape Model............................................................................................... 183 4.11 Future Advances in Circadian Biology and Circadian Medicine.............................................................................. 183 4.12 Take-Home Messages................................................................................................................................................ 183 References............................................................................................................................................................................. 186

5. Calorie Restriction, Intermittent Fasting, Ketogenic Fasting, and Time-Restricted Feeding.....................................191 Abbreviations.........................................................................................................................................................................191 Chapter Overview...................................................................................................................................................................191 5.1 Philosophical and Mechanistic Perspectives............................................................................................................. 192 5.1.1 Physical and Biological Systems.................................................................................................................. 192 5.1.2 Longevity, Aging, and Chronic Diseases.................................................................................................... 193 5.2 Stress Responses to Calorie Restriction.................................................................................................................... 193 5.2.1 Hormesis, Vitalizing Stress, and Devitalizing Stress.................................................................................. 193 5.2.2 Cell Stress Leading to Allostatic Overload................................................................................................. 194 5.2.3 Metabolic Rate and Take-Over Threshold.................................................................................................. 195 5.3 Energy Signals and Metabolic Response................................................................................................................... 196 5.3.1 Energy Sensing Functions of AMPK and SIRT1........................................................................................ 196 5.3.1.1 The Role of AMPK in Mitochondrial Biogenesis....................................................................... 196 5.3.1.2 AMPK, Mitochondrial Function, and Fitness............................................................................. 197 5.3.1.3 The Role of PGC1α in the Activation of Downstream Transcription Factors............................ 198 5.3.1.4 The Role of FOXO and Stress Resilience Programs................................................................... 198 5.3.1.5 FOXO Transcription Factors and Autophagy.............................................................................. 198 5.3.1.6 FOXO Regulation of Cellular Metabolism.................................................................................. 201 5.3.1.7 The Importance of Circadian Fluctuations in Insulin Signaling and FOXO Activation............ 202 5.4 Mechanistic Insights of Insulin Resistance at the Cellular Level............................................................................. 204 5.4.1 Nodes of Insulin Signaling.......................................................................................................................... 205 5.4.2 The Role of GSK3 in Cell Resistance.......................................................................................................... 206 5.4.3 The Role of mTOR in Cell Resistance......................................................................................................... 207 5.5 Circadian Insulin Signaling....................................................................................................................................... 209

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Contents 5.5.1 5.5.2 5.5.3

Hormesis and Circadian Insulin Signaling.................................................................................................. 209 Circadian Insulin Resistance and Cell Redox Stress Resistance Programs.................................................210 Transition from Circadian to Chronic Non-Cyclical Insulin Resistance.....................................................211 5.5.3.1 Energy Sensor Responses to Non-Cyclical Insulin Resistance...................................................211 5.5.3.2 Nocturnal Eating, Overconsumption, and the Development of Metabolic Disease................... 212 5.6 Ketone Body Metabolism.......................................................................................................................................... 213 5.6.1 Evolutionary Insights into Ketone Body Metabolism..................................................................................214 5.6.1.1 Fasting, Ketogenesis, and Cognition............................................................................................214 5.6.2 Ketosis—A Danger or a Health Signal?...................................................................................................... 215 5.6.3 Approaches to Achieve Ketosis....................................................................................................................216 5.6.3.1 Beta-Hydroxybutyrate Esters as a Metabolic Performance Enhancer for Military Use..............216 5.6.3.2 Beta-Hydroxybutyrate Esters as a Metabolic Performance Enhancer in Athletes......................216 5.6.4 How Long Can Human Health and Survival Endure Fasting?.....................................................................216 5.7 Chronic Overnutrition.................................................................................................................................................217 5.7.1 The Role of Metabolic Flexibility in Insulin Sensitivity..............................................................................217 5.7.2 Ectopic Lipid Deposition during Chronic Overnutrition..............................................................................218 5.8 Take-Home Messages................................................................................................................................................ 221 References............................................................................................................................................................................. 222 6. The Microbiota in Symbiotic Entanglement with Human Metabolism........................................................................ 225 Abbreviations........................................................................................................................................................................ 225 Chapter Overview.................................................................................................................................................................. 226 6.1 The Microbiota and Human Liaison: Better Together.............................................................................................. 227 6.1.1 Overview and Importance of the Gut Microbiota....................................................................................... 227 6.1.2 The Relationship of the Gut Microbiota and the Human Host.................................................................... 227 6.1.3 The Microbial Flora: Impacts and Implications of an Altered Microbiota Composition........................... 228 6.1.3.1 The Microbiota Composition: A Bellwether of Health............................................................... 228 6.1.3.2 Microbiota-Mediated Inflammation............................................................................................ 230 6.1.4 Genetics........................................................................................................................................................ 232 6.1.5 Epigenetic Systems...................................................................................................................................... 232 6.1.6 The Ecology of the Microbiota and the Supraorganism.............................................................................. 233 6.2 The Supraorganism.................................................................................................................................................... 234 6.2.1 Co-Development: From Birth through Life................................................................................................. 234 6.2.2 The Gastrointestinal Tract: Where Microbiota Meets Host........................................................................ 235 6.2.3 The Microbiota and the Immune System: More Than Just Flagging Good versus Bad............................. 235 6.2.4 The Nervous System: Two Brains................................................................................................................ 238 6.2.5 The Hypothalamic-Pituitary-Adrenal (HPA) Axis: A Lifeline in Times of Need...................................... 240 6.2.6 Impacts on Host Metabolism....................................................................................................................... 240 6.2.7 Co-Evolution: Commensalism and Beyond................................................................................................. 241 6.3 Control and Order Parameters................................................................................................................................... 243 6.3.1 Extrinsic Control Parameters....................................................................................................................... 243 6.3.1.1 Diet.............................................................................................................................................. 244 6.3.1.2 Psychogenic Factors.................................................................................................................... 244 6.3.1.3 Physical Factors........................................................................................................................... 244 6.3.1.4 Circadian Behaviors.................................................................................................................... 244 6.3.2 Intrinsic Order Parameters........................................................................................................................... 244 6.3.2.1 Hypothalamic-Pituitary-Adrenal (HPA) Axis............................................................................ 244 6.3.2.2 Autonomic Branches of the Central Stress Response................................................................. 244 6.3.2.3 Immune Responses...................................................................................................................... 244 6.3.3 The Microbiota as an Extrinsic Control Parameter and Intrinsic Order Parameter................................... 244 6.3.4 Extrinsic Control Parameters and Targeted Interventions.......................................................................... 247 6.3.4.1 Stress and The Microbiota........................................................................................................... 247 6.3.4.2 Circadian Rhythms: Biological Blueprints for Host and Microbiota Activity............................ 249 6.3.4.3 Diet: Where It All Begins............................................................................................................ 250 6.3.5 Intrinsic Order Parameters through the Lens of the Innate Immune System............................................. 262 6.3.6 Integration of Bottom-Up and Top-Down Order and Control Parameters.................................................. 262 6.3.7 New Prospects.............................................................................................................................................. 265 References............................................................................................................................................................................. 266

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7. The Role of Insulin Resistance in Metabolic Disease...................................................................................................... 275 Abbreviations........................................................................................................................................................................ 275 Chapter Overview.................................................................................................................................................................. 276 7.1 Physiological Role of Insulin in Classical Insulin Targeted Tissues......................................................................... 277 7.2 Insulin Resistance under Healthy and Pathologic Conditions................................................................................... 277 7.3 Historical Context of Insulin Resistance................................................................................................................... 278 7.3.1 History of Syndrome X................................................................................................................................ 279 7.3.2 Insulin Resistance Has Many Effects on the Body..................................................................................... 280 7.3.3 Spotlight on C. Ronald Kahn and Critical Nodes in the Insulin Signaling Pathway.................................. 282 7.3.4 Spotlight on Gerald Shulman...................................................................................................................... 283 7.3.5 Spotlight on Philipp Scherer’s Work on Ceramides and Inflammation...................................................... 284 7.3.6 Ceramides, Ectopic Lipids, and ROS.......................................................................................................... 285 7.3.7 Chronic Diseases of Aging as Manifestations of Insulin Resistance.......................................................... 286 7.4 Foundational Concepts of Insulin Resistance........................................................................................................... 289 7.4.1 Insulin Resistance and Metabolic Flexibility.............................................................................................. 289 7.4.1.1 Clinical Tools: The Respiratory Quotient................................................................................... 289 7.4.1.2 Dyssynchronous Insulin Signaling and the Loss of Metabolic Flexibility................................. 290 7.4.1.3 The Development of Pathogenic Hyperinsulinemia and Insulin Resistance.............................. 290 7.4.1.4 Ectopic Lipid Accumulation and Insulin Resistance.................................................................. 291 7.4.2 The Role of Free Radicals and Oxidative Stress in Insulin Resistance...................................................... 292 7.4.3 Implications of Insulin Resistance across Different Tissues of the Body................................................... 293 7.4.4 The Relationship between Mitochondrial Dysfunction and Insulin Resistance......................................... 294 7.4.5 Control Parameters of Insulin Signaling..................................................................................................... 296 7.4.5.1 Insulin Resistance and Alzheimer’s Disease............................................................................... 296 7.4.5.2 Insulin Resistance and Cardiovascular Disease.......................................................................... 296 7.4.6 The Role of Insulin Signaling Dysregulation in Cancer............................................................................. 297 7.5 Bioenergetics and the Basis for the Development of Insulin Resistance................................................................... 297 7.5.1 Cellular Bioenergetics under Normal Physiological Conditions................................................................. 297 7.5.2 The Role of Mitochondria in Cellular Bioenergetics................................................................................... 298 7.5.3 Mitochondrial Function and Insulin Resistance.......................................................................................... 298 7.5.4 Pyruvate Dehydrogenase Enzyme Complex May Be the Key to Fighting Insulin Resistance................... 299 7.5.4.1 Role of PDH in Energy Production and Insulin Resistance........................................................ 299 7.5.4.2 Yin and Yang of Glyceroneogenesis in Patients with Insulin Resistance................................... 300 7.6 Insulin Signaling and the Link to Cancer.................................................................................................................. 302 7.6.1 The Role of Insulin Resistance and Mitochondrial Dysfunction in the Pathogenesis of Cancer............... 302 7.6.2 Insulin Signaling, Cancer, and Bioinformatics, Defining Simple Rules..................................................... 303 7.7 Accelerated Cognitive Decline, Alzheimer’s Disease, and Insulin Resistance........................................................ 303 7.7.1 Effects of Insulin Resistance on Microtubule Dynamics............................................................................ 304 7.7.2 Impaired Insulin Signaling, Neurofibrillary Tangles, and Amyloid Plaques.............................................. 304 7.7.3 Brain Glucose Metabolism and Alzheimer’s Disease................................................................................. 304 7.7.4 Therapeutic Strategies for Treatment........................................................................................................... 305 7.7.5 Bioenergetics, PDK, and Alzheimer’s Disease............................................................................................ 305 7.8 Integrated Systems Biology Approach to Human Health and Disease..................................................................... 305 7.8.1 Osteocalcin and Insulin Signaling............................................................................................................... 306 7.8.2 Adiponectin, Leptin, and Insulin Signaling................................................................................................ 306 7.8.2.1 Leptin and Circadian Insulin Signaling...................................................................................... 307 7.9 Symmetry, Neuroendocrinology, and Insulin Resistance......................................................................................... 307 7.9.1 Order and Control Parameters in Insulin Resistance.................................................................................. 308 7.9.2 Insulin Resistance as a Chronic Control Parameter.................................................................................... 308 7.9.3 Stress as an Allostatic Response: Corticotropin Releasing Hormone and Growth Hormone as Antagonizers of Insulin Action.....................................................................................................................310 7.9.4 Prolonged Stress Response Resulting in Allostatic Load.............................................................................311 7.9.5 Targeting Upstream Control Parameters to Treat Disease...........................................................................311 7.10 Chapter Take-Home Messages...................................................................................................................................311 References..............................................................................................................................................................................312 8. Mitochondrial Function and Dysfunction and Insulin Resistance................................................................................ 323 Abbreviations........................................................................................................................................................................ 323 Chapter Overview.................................................................................................................................................................. 323

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8.1

Mitochondrial Dysfunction and Aging...................................................................................................................... 323 8.1.1 Air Hunger as a Sign of Mitochondrial Dysfunction.................................................................................. 324 (Clinical, Introductory Level)...................................................................................................................... 324 8.1.2 Supplements for Mitochondrial Health........................................................................................................ 325 (Clinical, Introductory Level)...................................................................................................................... 325 8.1.2.1 L-Carnitine Transfers Fuel into the Mitochondria...................................................................... 325 8.1.2.2 B Vitamins Are Essential for Energy Production....................................................................... 326 8.1.2.3 Alpha-Lipoic Acid and Dihydrolipoate Recharge Other Antioxidants....................................... 326 8.1.2.4 Coenzyme Q10 May Counter Myalgias...................................................................................... 327 8.1.2.5 Vitamin D Promotes Mitochondrial Function Mediated by Both Anti-inflammatory and Insulin Sensitizing Effects.................................................................................................... 327 8.1.2.6 Benefits and Dangers of Peroxisome Proliferator-Activated Receptor ɣ Supplementation........ 327 8.1.2.7 Dimethyl Fumarate Stimulates Antioxidant Genes.................................................................... 330 8.1.2.8 Vitamin K Maintains Calcium Homeostasis and Improves Insulin Sensitivity......................... 330 8.1.2.9 Minerals and Trace Elements.......................................................................................................331 8.2 Linchpin Concepts Connecting Mitochondrial Dysfunction to Chronic Diseases of Aging.....................................331 8.2.1 Mitochondria: The Bioenergetic Powerhouse of the Cell.............................................................................331 8.2.2 Mitochondria: Structure, Function, and Pathophysiology........................................................................... 333 Electron Transport System........................................................................................................................... 333 8.2.2.1 Mitochondrial Function............................................................................................................... 336 Role of Mitochondria in Glucose Metabolism............................................................................................. 336 Role of Mitochondria in the Metabolism of Other Organic Molecules....................................................... 337 Role of Mitochondria in Redox Homeostasis.............................................................................................. 337 Antioxidant Defense System and Mitochondrial Dysfunction.................................................................... 339 8.2.2.2 Influence of Nutrient/Diet on Mitochondrial Function............................................................... 339 8.2.3 Intertwined Relationship Between Mitochondrial Dysfunction and Insulin Resistance............................ 340 8.2.3.1 The Evolution of Insulin Resistance in Insulin-Responsive Metabolic Tissues......................... 340 8.2.3.2 Overconsumption, Mitochondrial Dysfunction, and Insulin Resistance.................................... 342 8.2.3.3 Circadian Disturbances, Insulin Resistance, and Mitochondrial Dysfunction........................... 343 8.2.4 Metabolism of Macronutrient Substrates and Insulin Resistance............................................................... 345 8.2.4.1 Cellular Lipid Deposition, Mitochondrial Dysfunction, and Insulin Resistance........................ 345 8.2.4.2 Role of Intracellular Fatty Acid Metabolites in Insulin Resistance............................................ 346 8.2.4.3 Fatty Acid Metabolism, Mitochondrial Function, and Insulin Resistance................................. 346 8.2.4.4 Influence of Timing and Fuel Selection on Metabolic Flexibility and Mitochondrial Function............................................................................................................... 346 8.2.4.5 Is Mitochondrial Dysfunction a Cause or Consequence of Insulin Resistance?........................ 348 8.2.5 Future Perspectives...................................................................................................................................... 349 8.3 Chapter Take-Home Messages.................................................................................................................................. 349 References............................................................................................................................................................................. 350 9. Chronic Diseases of Aging as Metabolic Disorders......................................................................................................... 355 Abbreviations........................................................................................................................................................................ 355 Chapter Overview.................................................................................................................................................................. 356 9.1 The Role of Metabolism in the Chronic Diseases of Aging...................................................................................... 356 9.1.1 The Relationship of Mitochondrial Dysfunction and Insulin Signaling in Metabolic and Chronic Diseases of Aging........................................................................................................................................ 356 9.1.1.1 The Interdependent Relationship of Obesity, Inflammation, and Insulin Signaling in Cancer..................................................................................................................... 359 9.1.1.2 Quest for the Truth...................................................................................................................... 361 9.2 Cancer as a Metabolic Disease?................................................................................................................................. 361 9.2.1 Obesity and Cancer...................................................................................................................................... 362 9.2.2 Insulin Signaling and the Warburg Effect................................................................................................... 363 9.2.3 Oncogenic Signaling and the Warburg Effect............................................................................................. 364 9.2.4 Anaplerosis: Connecting the Warburg Effect and Mitochondrial Function in Proliferating Cells............. 365 9.2.5 Targeting Carbohydrate Metabolism for Cancer Therapy........................................................................... 365 9.2.6 Targeting Amino Acid Metabolism in Tumorigenesis................................................................................ 367 9.2.7 Targeting Lipid Metabolism in Tumors....................................................................................................... 368 Targeting Cholesterol Metabolism............................................................................................................... 369 Targeting Fatty Acid Metabolism................................................................................................................. 369

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Contents 9.2.8

Targeting Whole-Body Metabolism (Systemic) for Cancer Management.................................................. 370 Fasting��������������������������������������������������������������������������������������������������������������������������������������������������������� 371 Ketogenic Diets............................................................................................................................................ 371 Caloric Restriction....................................................................................................................................... 372 The Microbiome and Cancer Treatment...................................................................................................... 372 9.2.9 Repurposing Metabolism-Related Drugs to Fight Cancer.......................................................................... 372 Metformin.................................................................................................................................................... 372 Non-Steroidal Anti-Inflammatory Drugs (NSAIDs).................................................................................... 373 9.2.10 Conclusion and Future Perspectives............................................................................................................ 373 9.3 Alzheimer’s Disease: Another Chronic Metabolic Disease...................................................................................... 375 9.3.1 Amyloid Beta and Synaptic Dysfunction.................................................................................................... 375 9.3.2 The Shared Pathogenesis of Insulin Resistance and Alzheimer’s Disease................................................. 375 9.3.2.1 Dyslipidemia................................................................................................................................ 376 9.3.3 The Role of Amylin in Amyloid Beta Accumulation.................................................................................. 377 9.3.4 Alzheimer’s Disease and the Reverse Warburg Effect................................................................................ 378 9.3.5 Insulin Resistance, Mitochondrial Dysfunction, and Oxidative Stress in Alzheimer’s Disease................ 378 9.3.6 The Brain’s High Energy Requirements Make It Susceptible to Mitochondrial Dysfunction.................... 378 9.3.7 Insulin Resistance and Cognitive Decline................................................................................................... 379 9.3.8 Molecular and Genetic Contributors to Alzheimer’s Disease Pathology.................................................... 380 9.3.8.1 The GSK3 Hypothesis of Alzheimer’s Disease.......................................................................... 380 9.3.9 Pharmacologic Therapies for Alzheimer’s Disease..................................................................................... 381 9.4 Metabolic Cardiomyopathy....................................................................................................................................... 383 9.4.1 An Overview................................................................................................................................................ 383 9.4.2 Physiological Cardiac Hypertrophy............................................................................................................. 383 9.4.3 Pathological Cardiac Hypertrophy.............................................................................................................. 384 9.4.3.1 Diabetic and Metabolic Cardiomyopathy.................................................................................... 385 9.4.4 Non-ischemic Dilated Cardiomyopathy...................................................................................................... 386 9.4.5 Ischemic Dilated Cardiomyopathy.............................................................................................................. 387 9.4.6 Vascular Atherosclerosis.............................................................................................................................. 387 9.4.6.1 Lipoproteins, Cholesterol, and Vascular Atherosclerosis........................................................... 387 9.4.6.2 Current Therapies........................................................................................................................ 390 9.4.6.3 Prospective of New Therapies..................................................................................................... 390 9.4.7 Metabolic Pharmacotherapy of Heart Disease............................................................................................ 391 9.4.7.1 Metformin.................................................................................................................................... 391 9.4.7.2 Fibrates, TZDs, and Vitamin D................................................................................................... 391 9.4.7.3 Trimetazidine.............................................................................................................................. 392 9.5 The Physiological Fitness Landscape: A New Model of Personalized Precision Medicine..................................... 393 9.6 Summary.................................................................................................................................................................... 400 9.7 Take-Home Messages................................................................................................................................................ 401 References............................................................................................................................................................................. 402 Epilogue .......................................................................................................................................................................................413 Index..............................................................................................................................................................................................417

Prologue The overarching purpose of this book is to promote a deeper understanding of metabolism from the integrated perspectives of the laws of physics and biological chemistry in states of health and disease. The book’s first volume has looked through the lens of multiple disciplines of modern physics to acquaint the beauty and organizational perfection of living systems. Volume two now seeks to connect these insights with the causes of this perfection going awry, in the context of unhealthy human lifestyles and behaviors, as well as gradual degradation due to natural processes of aging. While the relevance is not intended to provide “cookbook algorithms”, the hope is to buttress the reader’s scientific creativity and outline the links between art and science that strengthen problemsolving in patient care. Moreover, we propose and describe a powerful model for the future of medicine, the Physiological Fitness Landscape. This mathematical model represents a practical implementation of a precision personalized scale of medicine. It offers the potential to provide the optimal intervention, which is both patient-specific and disease-specific, and changes over time as a result of both the aging processes and pharmacological or lifestyle interventions. Despite the scientific scale of complexity and a large swath of scientific territory covered in this book, there is conceptual simplicity in all of the book’s messages. One such message is the loss over time of free will, the freedom to act as we please; this becomes the case when voluntary behaviors develop unhealthy patterns. These behaviors elicit biological responses that become feedforward and bidirectional inputs into a matrix of inextricably intertwined self-exacerbating behavioral and organic driven parameters of disease. It becomes unavoidably frustrating when behaviors that were initially voluntary in an otherwise mentally competent person become pathobiologically rooted and progressively involuntary. The overshoot and example in the two paragraphs that follow may be viewed from the different perspectives of each of the chapters presented in this second volume. For example, a pattern of dietary excess is classically recognized to be an extrinsic contributor to chronic disease. However, other unhealthy behaviors, whether they are initiating or not, also become inescapable components in a pathogenic web. In particular, these include poor quality or timing of diet, other abnormal circadian patterns such as sleep, rest, and activity, and prolonged exaggerated stress responses. Further, an altered compositional pattern and reduced diversity of the microbiota is a central nexus to the intrinsic control parameters of disease, particularly redox and inflammatory stress, mitochondrial dysfunction, and insulin resistance (in

metabolic tissues responsive to insulin signaling for glucose and lipid energy homeostasis). The following mechanistic overshoot is illustrative of one way to describe how human behaviors (extrinsic control parameters of disease) promote biological responses (intrinsic control parameters of disease), which in turn ingrain a wider range of unhealthy behaviors, thus amplifying biological factors. Consequently, there evolves a feedforward potentiation of one another’s pathogenic contributions within a matrix of metabolic and chronic disease. Take for instance dietary excess, which exceeds mitochondrial bioenergetic capacity. This leads to superoxide formation and a proinflammatory response, which may become systemic. Inflammatory cytokinemia may also result from disturbing effects of the diet on microbiota health. Moreover, proinflammatory cytokines consequently affect the limbic system in the brain that reduces the threshold for the perception of a threatening stress response. This stress response disturbs the quality of the diet, virtually always. It also disturbs the timing of the diet, as well as the sleep–wake cycle and other circadian behaviors. Additionally, the chronically activated HPA axis and autonomic branches of the stress response together cause immune suppression that contributes to further disruption of the microbiota, greater severity of the systemic inflammatory milieu, cell redox stress, mitochondrial dysfunction, and insulin resistance. This second volume of the book will provide numerous examples of relevance to the main theme of the book, namely that metabolism is not only a key functional difference between living and non-living matter, but also that metabolism is positioned at the center between health and disease. Its organizational perfection leading to organism-wide synchronization of biological processes can be disturbed by various voluntary and involuntary mechanisms causing pathological transformations. Key to our understanding of these transformations and their inherent risks is the concept of a stress response. A fundamental insight into the quantitative and qualitative description of stress response can be gained by the introduction of the Physiological Fitness Landscape whereby control parameter changes illicit not always proportional changes of the physiological fitness level. These changes can restore homeostasis, lead to allostasis or drive the system to allostatic overload. It is my belief that proper incorporation of mathematical models, such as the Physiological Fitness Landscape, will transform the practice of medicine bringing it much closer to a datadriven branch of science than we have ever imagined. I invite your mind to new exciting ideas and embark on this journey into the future of medicine with me.

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Acknowledgments There are numerous individuals to whom I owe a huge debt of gratitude for their assistance on this journey of discovery. I list and acknowledge their many positive effects on my development as a scientist and a writer, as well as their contributions to these two volumes. First and foremost, my dynamic editorial team with multidisciplinary expertise did much of the heavy lifting needed to bring this project to completion. This amazing group of talented individuals was led by Gail Ferstandig Arnold, Ph.D. (Research Professor, Chemistry and Chemical Biology) who served as Associate Director, Graduate Studies and Academic Affairs as well as Associate Director, Institute for Quantitative Biomedicine (IQB), at Rutgers State University of New Jersey. Seeking editorial assistance through various Sections of the Science Division at Rutgers, I was referred to Gail in the IQB, and have had the pleasure of knowing her for about six or seven years. Gail should be credited for getting the ball moving towards the eventual amassment of an extraordinarily talented team of contributing editors. The process started with several graduate students who helped track down references for areas involving Volume 2. Moreover, Gail, upon her retirement from Rutgers, accepted my offer to personally apply her talented hand to the active editing of various important areas in Volume 2. Gail also has the essential skillset as an administrative coordinator. She has been vital for maintaining the coordinated activation of a robust team of editing and graphic design contributors. Gail’s attitude is inspirational, and I couldn’t thank her enough for this. A major role in compiling material for Volume 1 was played by Dr. Shashidhar Rao, who has impressive experience in the pharma industry. A physical chemist with a penchant for biological chemistry, Shashidhar became the first senior scientist recruited to the project, at Gail’s direction. Shashidhar Rao, a Rutgers scientist, was quite interested and capable of extending and assimilating his solid foundation of molecular chemistry to the realm of living systems. Shashi came on board about 6 years ago, helping with the revision of the Biological Thermodynamics Chapter in Volume 1. He taught me a lot about the dynamic chemistry of physical systems which is crucial for conveying analogies and relationships to living systems. Throughout the course of the ensuing years, his fastidious work ethic was valuable for proofreading and following up on missing elements. A couple of years later, Dr. Jack Tuszynski revisited the chapter to revise it to its current form. Shashidhar, always a gentleman, remained a loyal and stalwart partner, helping wherever he could, and has remained a strong contributor during the past six years. Yasmin Zakiniaeiz (Yale Neuroscience postdoctoral fellow who has served as the Editor-in-Chief of the Yale Journal of Biology and Medicine) was a stalwart of reliability and solid content and presentation editor of both text and graphic design. Her major role focused on the comprehensive editing of the

Stress Response Chapter. Yasmin, a natural self-starter who requires very little direction, continuously searched for voids and weaknesses anywhere in the book and took initiative to inform me as she was already taking steps to fill in these gaps, or asking the right questions. The more urgent the demand, the more she stepped into the role, sacrificing her personal time in the evenings, nights, and weekends. Melissa Monsey (who served on the board of the Yale Journal of Biology and Medicine for several years and was an issue editor for journal issues on topics such as obesity, psychology, and psychiatry) served as an Organizer-in-Chief of sorts, helping to delegate editorial work where needed. Melissa was also my liaison for communications with outside experts, for whom she organized attachments and other work. Her organizing role helped prevent many important issues and pieces of work from slipping through the cracks. Melissa works at a high level and was my “right hand”. She comprehensively edited the Calorie Restriction Chapter. Bal Krishna Chaube, Abhishek Kumar Singh, and Sonal Shree are superb postdocs, who came to the US on J1 visas to do research at Yale University in various fields of metabolism. Abhishek’s work focuses on endothelial metabolism and cardiovascular metabolic diseases. Sonal specializes in molecular biophysics and biochemistry, while Bal’s interest predominantly is in the field of metabolic oncology. Abhishek, Sonal, and Bal were very helpful for technical content editing in various sections of the book. Bal was particularly generous in donating many hours of his time with phone discussions. During the course of these discussions, he would elucidate for my understanding complex but crucial components of metabolic pathways. The selfless work of these three talented postdocs is vastly appreciated. Special thanks to Gerald Shulman and Philipp Scherer who directed me to Varman Samuel and Steve Mittelman, respectively. Steve Mittelman (M.D., Ph.D.) is a UCLA professor of pediatrics and endocrinologist, a world-renowned expert in the physiology of obesity and cancer. Varman Samuel (M.D., Ph.D.) is an associate professor and the section chief of endocrinology at the Yale Medical School, VA. Varman and Steve were both vital to the enrichment and content editing of the material connecting metabolism to insulin resistance. Special thanks also must be given to Bart Staels who provided vital editorial revisioning of the Nuclear Hormone Receptor Chapter. Bart Staels (Ph.D.) is professor of pharmacy at the University of Lille, France, and director of the INSERM Unit UMR 1011. He is one of the highest-cited researchers in the world in the NHR area. Emily Manoogian, a postdoctoral fellow at the Salk Institute for Biological Studies was a huge help and crucial for the cohesion and content editing of the Circadian Biology of Time Chapter. Michelle Hanlon, with excellent technical skills, greatly contributed to the graphical and editorial aspects of both

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xviii volumes of the book. My deep appreciation also goes to Perrin Beatty, Tiffany Louie, Jennifer (Kaplan) Goodell, Zhao Wang, Malcolm Watford, Cecile Martin, Olivia Tuma, Jacob Smith, Julie Meade, Chris Stewart, Luisa Torres, Nico Ekanem, Ryan Mischel and Rebecca Paszkiewicz, all of whom were vital to the project and could be counted on for their expertise and scientific rigor. Beyond technical support, I’d like to acknowledge my intellectual mentors in the field of medicine, who helped shape my understanding of the complexities of the human body. Dr. John Hogenesch is an Ohio Eminent Scholar and professor of Pediatrics at Cincinnati Children’s Hospital Medical Center in the Divisions of Human Genetics and Immunobiology within the UC Department of Pediatrics. His lab studies genome biology with a focus on the molecular mechanisms of circadian rhythms in mammals. Dr. Hogenesch discovered several new bHLH-PAS transcription factors, including the hypoxia-inducible factors, as well as the core clock components, Npas2, Bmal2, Rora, and Bmal1, the only required component of the mammalian circadian clock. Dr. Hogenesch also pioneered the discovery of clock-regulated gene expression in plants, flies, mice, and man. As a genome biologist, Dr. Hogenesch’s lab applies and integrates various disciplines including bioinformatics, genomics, molecular and cellular biology, and genetics. I attended and presented a poster at the Salk Institute 2017 Biology of Time Conference where I had a culturally enriching experience of widening perspectives in the field of circadian biology. The conference was dedicated to the 2017 Nobel Prize in Physiology or Medicine, awarded to Jeffrey C. Hall, Michael Rosbash, and Michael W. Young, for their discoveries of molecular mechanisms that control circadian rhythms. Additionally, the event was serendipitously timed to the writing of my Metabolism in Medicine book. There, I also had the fortunate and delightful experience of meeting John personally. He is one of the brilliant and pioneering scientists in this field, who discovered some of the core clock molecular components. John generously reviewed my work, still in need of content and enhancement editing. He offered the support of his top and right-hand postdoc Lauren Frances to juggle her day job responsibilities, with those required to marshal the clarity of the biology of time chapter. John emphatically endorsed the need for scientific writing, to the extent that is possible, at a tenth-grade level. He explained that it turns out that even advanced PhDs prefer to read at this level. He even referred me to two short paperback books, which he said in his lab have “rabbit ears”. The goal of these books is to make the content attractive, clear, and readable. I am grateful for John’s interest and help. Don Mender (Lecturer in Psychiatry at Yale University, with expertise in integrative quantum physics) and Lloyd Demetrius (mathematician and theoretical biologist at the Max Planck Institute for Molecular Genetics at Berlin, Germany, and in the Department of Organismic and Evolutionary Biology at Harvard University) influenced my interest in studying quantum physics in the context of its possible profound role in living systems. The idea of using modern disciplines of physics to explain the exquisite and beautiful organizational perfection of biology and living systems struck me as being plausibly rooted in the concept of quantum metabolism. This term was coined

Acknowledgments by Lloyd Demetrius and promoted in several papers on the topic including some co-authored with Jack Tuszynski. I had the fortunate opportunity to meet with Lloyd at a Princeton luncheonette, where he explained the phenomenon, which to me was cryptic based on just reading the papers. However, Lloyd’s interest as a mathematician was to only accept the implications of this phenomenon as far as the math would take it. His interest in this area was at a fundamental science level, very detached from clinical medicine, where my interests lie. This experience epitomized, even galvanized my frustration that such brilliance can be so dispassionate toward extending these ideas to a broader world, where it can potentially have a massive and tangible impact. Nevertheless, by the end of our meeting, Lloyd provided a glimmer of hope when he endorsed Jack Tuszynski as an extraordinary talent with practical interests, and to whom he was grateful for including the concept of quantum metabolism in his medical student course series, The Future of Medicine. Malcolm Watford, D.Phil (Professor of Biochemistry and Nutritional Sciences and Director, George H. Cook Scholars Program, Rutgers) is an unusual talent in the field of metabolism. Conveniently, he has been right in my backyard for almost thirty years, only a mile down the road from my office. It was only about a year ago that I introduced myself to Malcolm and supplicated his help. He was warm, humble, and welcoming, immediately giving a sense of family upon meeting him. After talking for about two hours, Malcolm’s skill for good conversation was saliently apparent. A direct disciple of Sir Hans Krebs, having trained under him as a postdoctoral fellow at Oxford University in the UK, Malcolm is replete with the accomplishments, knowledge, and insights that one would expect from a researcher with such an impressive pedigree that also includes Otto Warburg (of whom Hans Krebs was a student). The concept of the Warburg effect, the role of Malcolm’s contribution of glutamine metabolism to this effect, his explanation of the stages of starvation, and of course, Krebs’s TCA cycle, the central hub of biochemical metabolism, all exemplify core relevance connecting this book’s message to human health and disease. Malcolm’s editorial augmentation of this book includes his elite level of content critique, in addition to his sharing valuable and engaging personal stories and anecdotes of Hans Krebs, a seminal pioneer of biological chemistry. I am profoundly grateful to Malcolm for allowing me to enlist his unusual expertise and historical gravitas for the purpose of perfecting this book’s message regarding biochemical aspects of metabolism. The late great Bruce McEwen (Alfred E. Mirsky Professor and head of the Harold and Margaret Milliken Hatch Laboratory of Neuroendocrinology at the university) was a major influence and inspiration for me. The terms allostatic load and overload were coined by Bruce, a stress biology endocrinologist Ph.D. from The Rockefeller Institute in NYC. Sadly, Bruce passed away January 2, 2020. I was privileged to be influenced by this true member of the scientific pantheon in the understanding of the stress response, who became a powerful collaborator and mentor. While these concepts apply to hormonal, autonomic, and immune system responses to psychogenic stress, they are also inextricably intertwined with the metabolism of mitochondrial bioenergetics and of insulin

Acknowledgments resistance. Moreover, the notion of stress is applicable to all hierarchical scales of living systems. In a general sense, stress should be considered the most fundamental driving parameter for the evolution of both health and disease, in humans and in fact all biological systems. This critical insight should further be invoked in diagnostic medicine, whereby the cardiac stress test can be viewed as a prototype for diagnostic stress testing. Accordingly, tissue and disease-specific metabolic stress testing that span the domain of all subspecialties of medicine should ultimately become employed as a new standard of care. An epiphany, under the direction of another collaborating mentor, Jack Tuszynski, was to attach the concepts of allostatic load and overload to a metabolic/physiologic fitness landscape model, adapted from physics. This potentially transformative computerized mathematical model provides a precision personalized scale of medicine. My explorative journey into modern disciplines of physics, as well as of physical and biological chemistry, sought a deeper understanding of metabolism through the prism of a different lens. Too often people’s health problems lie outside the fragmented and compartmentalized toolkits of applied science. The goal was to gain the insights needed, that lie beyond our currently available skillsets and knowledge, to truly help people. After seven years of self-learning and writing, the feeling of consternation and the inevitable failure to quench the thirst for this unrequited pursuit, help arrived to rekindle my optimism. I, therefore, wish to express my thanks to Dr. Jack Tuszynski (Allard Chair and Professor in Experimental Oncology in the Department of Oncology at the University of Alberta’s Cross Cancer Institute, and a Professor in the Department of Physics) who has indeed

xix reinforced my understanding of physics, biology and medicine as a rich and powerful playground with a real capacity for transforming medicine to levels currently unimaginable, gauged in the context of historical and present-day standards. Jack’s expertise in biophysics, solid-state physics, as well as in the areas of electromagnetism and quantum physics, including the evolving and potentially explosive field of quantum biology, helped me bridge the enormous gap between physics and medicine. Even more special about Jack is his selfless dedication to advancing science, his humility, and an extraordinary generosity of his personal knowledge and insights. I have now had the amazing privilege of working with Jack over the span of four and a half years, including several hundreds of hours of stimulating conversations about physics and medicine. Taken together with his eloquent editorial revisions of this book, he made possible the metamorphosis of this project from failure to magnum opus. I am infinitely grateful for his taking me under his wing and believing that this work will be a valuable scientific contribution to medicine. Last but not least, I wish to express my profound appreciation to Drs. Ralph Defronzo, C. Ronald Khan, Gerald Reaven, Alessio Fasano, Jeffrey Bland, Jeffrey Mechanic, Gerald Shulman, Phil Scherer, and Barbara Corkey, all of whom inspired and influenced me, and gave me numerous insights into the complexities of human physiology. Having benefited enormously from the depth of knowledge of the numerous individuals mentioned and acknowledged above, it is nevertheless important for me to take full responsibility for the entirety of the book’s contents, including any mistakes, faults, or omissions that the reader might find.

Author Brian J. Fertig, M.D., F.A.C.E., is the Founder and President of the Diabetes & Osteoporosis Center in Piscataway, New Jersey (https://siomar2.wixsite.com/diabandosteocenter), established in 1994. Dr. Fertig’s experience in diabetes, endocrinology and metabolism, including internship, residency, fellowship, and private practice, spans a period of 34 years. Dr. Fertig is also an Associate Professor at Robert Wood Johnson Medical School and the Chairman of the Department of Diabetes & Endocrinology at Hackensack Meridian Health—JFK University Medical Center. His passion for patient care and for finding the root problems of disease was his motivation and purpose for writing a two volume book series titled Metabolism and Medicine. On his exploratory journey, Dr. Fertig discovered modern conceptual tools to improve the problem-solving skill sets of great utility for him, his practitioner colleagues, and the next generation of healthcare providers. His genuine concern for the future of medical student education is one of the main

factors that motivated him to write this book. Additionally, he is also concerned with the need for interdisciplinary expertise to augment the execution of patient care, but particularly in light of an expanding reliance on Nurse Practitioners and Physician Assistants. His philosophy is based on the concept that the greater the network of interdisciplinary scientific and clinical expertise, the greater the collective skill set and hence the benefit to the patient. The ever-increasing use of bioinformatics paves the way toward personalized-scale medicine. However, the way forward for medicine should also include skillful adaptation of methods developed in physics, which will allow quantification of therapeutic solutions with unprecedented precision. Since physics has a tendency to generalize empirical observations to formulate laws of nature while biology takes pains to tease out detailed specificities, the marriage of the two fields promises the most enlightened future direction for medicine as both an art and a science.

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Personal Statements “A comprehensive and original opus linking metabolism with disease and preventative directions for the future. A must-read for experts and students alike”.

“An insightful and comprehensive summary of the state of the field! This should appeal to both a novice as well as to an expert. Well written and authoritative in all areas”.

Michael Houghton, Ph.D. 2020 Nobel Laureate Medicine and Physiology Professor at the Department of Medical Microbiology and Immunology Li Ka Shing Applied Virology Institute University of Alberta Edmonton, Canada

Philipp E. Scherer, Ph.D. Professor, Department of Internal Medicine Gifford O. Touchstone Jr. and Randolph G. Touchstone Distinguished Chair in Diabetes Research Director, Touchstone Diabetes Center Interim Chair, Department of Cell Biology The University of Texas Southwestern Medical Center Texas, USA

“Metabolism and Medicine by Dr. Brian Fertig is an unparalleled adventure into the fabric of physical law and medical impressionism, impelled by metaphysical questions and doubts to fashion new approaches to physiological questions in health and disease. This book is dense with science, synthesis, and interpretation, leaving the reader with just the right measure of resolve to learn even more. I strongly recommend Dr. Fertig’s opus for those still interrogating metabolism and medicine for satisfying answers”.

Jeffrey I. Mechanick, M.D., F.A.C.P., F.A.C.N., E.C.N.U., M.A.C.E. Professor of Medicine Medical Director, The Marie-Josee and Henry R. Kravis Center for Cardiovascular Health Director, Metabolic Support, Division of Endocrinology, Diabetes and Bone Disease Icahn School of Medicine at Mount Sinai New York, USA Past President of the American Association of Clinical Endocrinologists Prof. Mechanick served as: President of the American College of Endoc​rinol​ogy, ​Presi​dent ​of th​e Amer​ican A​ssoci​ation​ of Clinical Endocrinologists, President of the American Board of Physician Nutrition Specialists, Member of the President’s Council on Fitness, Sports and Nutrition – Science Board He is Editor-in-Chief Emeritus, President’s Council on Fitness, Sports and Nutrition Elevate Health, Chair, Board of Visitors, College of Computer, Mathematical, and Natural Sciences, University of Maryland, Chair, Physicians Engagement Committee, American Society for Parenteral and Enteral Nutrition

Dr. Philipp Scherer is the first scientist to win what could be called the “Triple Crown” of diabetes research recognition – adding the top Asian award (the 2018 Manpei Suzuki. International Prize for Diabetes Research) to the American and European ones in recognition of his discovery of adiponectin, a hormone released by fat cells, and subsequent research into the hormone’s role in fending off diabetes. His research has “deepened and widened our understanding of diabetes, obesity and energy homeostasis,” “This transdisciplinary book beautifully tells the story of the dynamics of life in health and disease. In an unprecedented tour de force, Brian Fertig connects fundamental physicochemical mechanisms to the dynamics of metabolism. A mindboggling book, for everyone to read!”

Bart Staels, Ph.D. Professor of Pharmacology (‘classe exceptionnelle’) University Lille, Inserm, CHU de Lille, U1011-EGID Institut Pasteur de Lille Lille, France Prof. Staels has been awarded the Young Investigator Award of the European Atherosclerosis Society, the Bronze Medal of the CNRS and the Lifetime Achievement Award of the British Atherosclerosis Society, the pharmaceutical “Barré” 2007 prize from the Faculté de Pharmacie of Montreal, and the French “JP Binet” prize from the Fondation pour la Recherche Médicale.

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Personal Statements “Dr. Fertig elegantly captures the complexity of metabolism, showing us how our physiology is intimately integrated from the quantum level to the whole organism. Insightful, comprehensive, and thoughtful, these books will enlighten the beginner and expert alike!”

Steven D. Mittelman, M.D., Ph.D. Chief, Division of Pediatric Endocrinology Interim Chief, Division of Pediatric Genetics Professor of Pediatrics Solomon A. and Maria M. Kaplan Chair of Pediatric Endocrinology UCLA Mattel Children’s Hospital, David Geffen School of Medicine California, USA Prof. Mittelman served as the Fellowship Director and Director of the Keck/Caltech Combined MD/PhD Program. “Brian Fertig has melded a thought-provoking and eclectic blend of physics, physiology, psychology and philosophy into a highly original work of great scope and depth.”

Frederick S. Kaplan, M.D. Isaac and Rose Nassau Professor Chief of the Division of Molecular Orthopaedic Medicine University of Pennsylvania School of Medicine Pennsylvania, USA “This is a masterpiece! A truly unique point of view that should make all physicians THINK more as they care for their patients. I know you’ve been working hard for a long time on this and want to let you know—you’ve succeeded.”

Stan Schwartz, M.D. Emeritus Associate Professor of Medicine University of Pennsylvania Pennsylvania, USA “Before the Sars-COV-2 pandemic enveloped the world, many who study metabolism, dismayed by the increasing prevalence of obesity and related diseases, observed an epidemiological transition from infectious to metabolic diseases. At the time of this writing, nearly three million people around the world have died from COVID-19 and perhaps proving that aphorism false. But we now know that obesity, insulin resistance and diabetes are important risk factors for developing severe COVID-19 disease and, when the pandemic is contained, will remain important health concerns in nearly all countries. In these two volumes, Fertig has tackled the numerous complex pathways that comprise ‘metabolism’. Most scientists spend careers studying one of these

pathways. Here, Fertig has compiled the work of many into a comprehensive work that is scholarly yet accessible. It is a love letter to the field, including important historical perspectives and key contributions of the physician scientists that have blazed the way. And, this work also provides an intricate framework with which to understand the coming tide of ‘-omic’ data.”

Varman Samuel, M.D., Ph.D. Associate Professor of Medicine (Endocrinology) Yale University Section Chief VA Connecticut Healthcare System Connecticut, USA “In Metabolism and Medicine, Brian Fertig provides an innovative, thought-provoking approach that unravels the pathophysiology of common metabolic diseases by relating them to basic physiochemical processes. A must read for everyone in the fields of endocrinology, diabetes, and metabolism.”

Ralph A. DeFronzo, M.D. Professor of Medicine Chief, Diabetes Division University of Texas Health Science Center Texas, USA “Dr. Brian Fertig demonstrates a great talent for combining knowledge in biology and physics with his own clinical expertise. He conceptualizes a mathematical model of a physiological fitness landscape based on energy economy, biological clock synchronization, and stress management. Thus, the model allows informed predictions for a precision personalized scale of medicine. In this book, the contours are shown of an upcoming revolution in the medical science comparable with that of information technology. The narrative captivates and is enriched with case studies, anecdotes, clear illustrations with summarizing captions, that all present a pleasant surprise to the innocent reader in a thought-provoking manner. Highly recommended!”

E. Ronald de Kloet, Ph.D. Head Department of Medical Pharmacology Leiden University Leiden, the Netherlands “Dr. Fertig’s book is a must-read for anyone interested in gaining up-to-date knowledge about circadian optimization of human metabolism. In particular, the section on Circadian Biology, and the Biology of Time, captures the core of the chronophysiology perspective on human metabolism. These complex concepts are explained in a clear and cohesive fashion. The interdisciplinary metabolic perspective of biological time and aging is very engaging and provides an elucidating insight

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Personal Statements into this emerging field. This book has profound value to both researchers and clinicians.”

Satchidananda Panda, Ph.D. Professor Salk Institute for Biological Studies California, USA “This is a wonderful book providing a comprehensive overview of metabolism from biological processes to pathophysiology. Undoubted, it will interest both basic scientists and clinicians. It provides a wealth of information in a clear and highly readable format. I especially enjoyed reading Chapter 8, which deals with the gut microbiota in health and disease. The chapter contains an enormous and highly readable account of this rapidly evolving area of research. The topic is of relevance to many disciplines including endocrinology, cardiology, neurology, psychiatry and immunology.”

Ted Dinan, Ph.D. Professor of Psychiatry Microbiome Alimentary Pharmacobiotic Center University College Cork Cork, Ireland Prof. Dinan was Chair of Clinical Neurosciences and Professor of Psychological Medicine at St. Bartholomew’s Hospital, London. Prof. Dinan is a pioneer of gut microbiota research focusing on the influence of the brain function and development including the regulation of the hypothalamic-pituitaryadrenal axis in situations of stress. He was awarded the Melvin Ramsey Prize for this research into the biology of stress. “It is both intriguing and gratifying to see that the quantum theory of consciousness has influenced modern thinking about metabolic processes in important ways, as shown in Brian Fertig’s work. This book remarkably connects basic physiology to clinical medicine.”

Stuart Hameroff, MD Professor, University of Arizona Pioneer in the science of consciousness, organizer of the annual TSC conferences and co-creator of the PenroseHameroff model of consciousness (Orch OR)

“A single author text is a rarity of late—especially one so comprehensive. These books combine text that is available to both novice and expert and provide insights to the history and personalities connected with discovery. Bravo to Dr. Fertig.”

Mark M. Rasenick Distinguished Professor of Physiology & Biophysics and Psychiatry Director, Biomedical Neuroscience Training Program Research Career Scientist, Jesse Brown VAMCU, Illinois Chicago College of Medicine Dr. Rasenick’s research, among many other contributions, was critical for the identification of G protein coupled receptors, the most pervasive and largest group of transmembrane receptors, important for hormonal and neurotransmitter signaling, physiology and behavior. “This is a must-read for anyone interested in the intersection between physics and medicine, especially related to the understanding how applications of modern physical concepts may help achieve optimum health.”

Deepak Chopra, MD The Chopra Foundation Chopra Global DeepakChopra.com “What a monumental work! It reads very well and is a wonderful history of the understanding and development of human metabolism and physiology in health and disease. How you put all this together astounds me, and I congratulate you. I would recommend the 2 volumes for any student of the history of science and especially to those interested in the field of metabolism and it’s development, as well as to people active in the field.” Seth Braunstein MD, PhD Emeritus Associate Professor Medicine University of Pennsylvania (Perleman) School of Medicine Past Director Diabetes Program University of Pennsylvania (Perleman) School of Medicine

1 Introduction to Metabolism: A New Model for Medicine

Abbreviations AcAc ACE2 AGE AHR AMPK ATGL ATP BCAA BHB CoA COPD CPT-1 CoQ CRY cyt c CYP DAMP DAG DCA DNP e ETC ETF EPR ETS FAO FET FMN GAPDH GFAT GLcNAc Gln Glu GTP H+ H2O HIF1a HK HMG CoA

acetoacetate angiotensin-converting enzyme 2 advanced glycation end product aryl hydrocarbon receptor AMP-activated protein kinase adipose triglyceride lipase adenosine triphosphate branched-chain amino acids β-hydroxybutyrate coenzyme A chronic obstructive pulmonary disease carnitine-palmitoyltransferase-1 coenzyme Q cryptochrome cytochrome c cytochrome P450 danger-associated molecular pattern diacylglycerol dichloroacetate dinitrophenol electron electron transport chain electron transferring flavoprotein entropy production rate electron transport system fatty acid oxidation forward electron transfer flavin mononucleotide glyceraldehyde 3-phosphate dehydrogenase glutamine fructose-6-phosphate amiotransferase N-Acetylglucosamine glutamine glutamic acid guanosine-5’-triphosphate protons water hypoxia-inducible factor hexokinase 3-hydroxy-3-methylglutaryl coenzyme A

DOI: 10.1201/9781003149897-1

LBK1 LPS MCD MCP-1 NFkB NHR O2 P PAMPs PARP PDH PDC PFK PGC1α PKC Pi POP PPP PXR RET ROS SAT SDH SFA SIRT1 SKI SOD1 TCA cycle TLR UCP1 Upd VAT

liver kinase B 1 lipopolysaccharide malonyl CoA decarboxylase monocyte chemotactic protein-1 nuclear factor kappa-light-chain-enhancer of activated B cells nuclear hormone receptor oxygen phosphate pathogen-associated molecular patterns poly (ADP-ribose) polymerase pyruvate dehydrogenase pyruvate dehydrogenase complex phosphofructokinase peroxisome proliferator-activated receptor gamma coactivator 1-alpha protein kinase C inorganic phosphate persistent organic pollutant pentose phosphate pathway pregnane X receptor reverse electron transfer reactive oxygen species subcutaneous adipose tissue succinate dehydrogenase saturated fatty acid sirtuin 1 Sloan Kettering Institute superoxide dismutase in the cytoplasm tricarboxylic acid cycle toll-like receptor uncoupling protein 1 uridine diphosphate glucose visceral adipose tissue

Metabolism involves interrelated contributions from mitochondrial function and insulin signaling, the biology of time, cycling of energy sensors and the family of nuclear hormone receptors, the stress response, diet, and the gut microbiome. Disruptions in any of these factors can lead to disease (Figure 1.1).

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Metabolism and Medicine was due to an impairment in cellular respiration. This is presently referred to as dysfunctional mitochondria. Mitochondria are organelles that convert oxygen and other reagents into an energy source, adenosine triphosphate (ATP), through the process of cellular respiration.

FIGURE 1.1  Metabolic function and dysfunction result from the complex interactions between and among systems of the body. Factors such as the stress response, circadian biology, nuclear hormone receptor function, dietary intake, microbiota composition, and insulin signaling all represent interconnected parameters affecting human health and disease. These systems have a complex and interwoven relationship that can either support mitochondrial function and homeostasis or result in a state of mitochondrial dysfunction that ultimately leads to chronic disease. Otto Heinrich Warburg by Georg Pahl. Source: licensed with CC BY-SA 3.0.

1.1 Brief History of Metabolism and the Complex Personalities of the Scientists Who Shaped It

Sir Hans Krebs (1900–1981) was a student of Otto Warburg, who taught him how to measure mitochondrial oxygen consumption. Krebs became known as an architect of metabolic cycles. At the young age of 31 he discovered the urea cycle. At the time, it had been known that urea was produced in the liver as a means of excreting nitrogen, a metabolic waste, but Krebs defined the details of the pathway. The pioneering research produced by Krebs many decades ago has recently flourished in the form of systems biology, which analyzes the complex pathways in metabolism, signaling, and other cellular processes.

Louis Pasteur (1822–1895), microbiologist and chemist. Source: licensed with CC BY 4.0.

Louis Pasteur (1822–1895) showed that glucose fermentation to lactic acid by the anaerobic glycolysis pathway is suppressed in the presence of oxygen. Otto Warburg (1883–1970), who followed Pasteur, studied the function of respiratory enzymes and proposed that cancer cells largely become reliant on rapid glucose fermentation to lactic acid, an energy requirement of cancer cell replication. He also posited that the underlying patho-etiology of what became known as the Warburg effect

Sir Hans Krebs. Source: licensed from Science Source Images.

Soon after his great discovery, the Nazis forbade Krebs from practicing medicine in Germany because of his Jewish

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Introduction to Metabolism heritage. Despite this discrimination and adversity, the value of the urea cycle received worldwide recognition by the scientific community. His acceptance as a Biochemistry fellow at the University of Cambridge rescued him from Nazi Germany where he would have faced persecution, imprisonment, and possibly death in a concentration camp, along with the six million Jews who perished in the Holocaust. He not only survived those troubled times, but thrived: his signature achievement, the “Krebs cycle”, won the Nobel Prize in Physiology or Medicine in 1953. The Krebs cycle is the central metabolic hub which integrates the convergence of macronutrient resources into bioenergetic cell respiration. It is worth noting that like Krebs, Warburg was also of Jewish descent. However, Warburg’s mother was Protestant, and both he and his father converted to Christianity. Although he was banned by the Nazis from teaching, he was not entirely forced from his research career. Indeed, Warburg was a controversial figure: he was a German patriot throughout his life and even applied to obtain “full” German status during the Nazi rule. Bizarrely, this status was granted personally to him by Adolf Hitler. Otto Warburg was a close friend of another Jewish-German scientist of global stature, Albert Einstein, who greatly influenced Warburg in his research, but sadly not in his political views. Since this short historical comment focuses on metabolism and metabolic processes involving energy transduction, mentioning Einstein (1879–1955) in this connection is relevant. One of the greatest discoveries Einstein made involved the equation linking mass with energy, namely the famous E = mc2 formula. Einstein was born in Ulm, Germany but rejected German militarism, which was rampant during his youth and adulthood. For this reason, at the age of 16, he left for Switzerland and renounced his German citizenship. The formula mentioned above was instrumental in our understanding of nuclear reactions, which led to the harnessing of nuclear energy with both positive and negative consequences in the form of nuclear power plants but also nuclear weapons. The latter development caused Einstein, who was a committed pacifist, a great amount of grief.

In this story of German–Jewish Nobel Prize winners who strongly influenced the science of metabolism, we should also mention Fritz Haber (1868–1934). He was born in Breslau, Prussia (now Poland) into an influential Jewish family. Like Warburg, Haber converted to Christianity possibly to advance his career, and was not only a great German patriot but a dubious military hero in the German army fighting on the Western front in World War I. In fact, he is sometimes referred to as the “father of chemical warfare”, having invented some of the early chemical weapons and even participated in their release in the Second Battle of Ypres, Belgium. To his credit, he made hugely positive contributions to chemistry, which included the discovery of the synthesis of ammonia that led to the industrial scale production of fertilizers. Here again we see the double-edged sword of an invention that can lead to both positive and negative applications in practice. On one hand, his work led to massive improvements in the yields of agricultural production, for which he was awarded a Nobel Prize in chemistry. On the other hand, his invention was applied to the development of explosives at an industrial scale. To Haber’s credit, when Hitler came to power in 1933, Haber resigned his academic position in Berlin and fled from Germany. He accepted the position of director of what is now the Weizmann Institute of Science in Rehovot, Israel. Unfortunately, Haber died on his way to Rehovot. Through the lives of these four eminent scientists, all German Jews, we see an illustration of the different choices made in the face of adversity. Their personal decisions had impactful outcomes on the contributions to the science of energy conversion (metabolic and otherwise), and each of these intellectual giants represented a different but overlapping area of science: physics (Einstein), chemistry (Haber), biochemistry (Krebs), and cell biology and biochemistry (Warburg).

Alfred P. Sloan, Jr. (Image licensed from Getty Images).

Fritz Haber. Source: licensed from Science Source Images.

Fast forward to 1945 and the end of World War II. Another confluence of physics, engineering, and philanthropy occurred through which, over the next 75 years great advances in the

4 fight against cancer have been made possible. That eventful year, General Motors executive Alfred Sloan, Jr., and engineer Charles Kettering announced the formation of a cancer research center which is now called the Sloan Kettering Institute (SKI) after them. The Sloan Kettering Institute is the experimental research arm of Memorial Sloan Kettering Cancer Center located in New York City. Since its inception, it has had a mission centered on solving the cancer problem championing a scientific approach. Both Sloan and Kettering hoped to translate the organizational skills honed in the automobile industry into oncology research at the highest international level. Prophetically, Mr. Kettering uttered the following words: “I am inclined to feel we can apply some of our time-tried techniques to this age-old problem”. It should be mentioned with candor that Alfred Sloan Jr., being first and foremost a shrewd businessman, embroiled himself in controversy by supporting the industrial operation of General Motors in Germany up until the outbreak of World War II with some of the production benefitting the German military effort. However, he has redeemed himself by becoming a philanthropist, a foremost captain of the booming post-war American industrial sector, and, of course, a co-founder of the SKI. Over the course of its 75-year history, SKI has produced cuttingedge advances in our understanding of both cancer biology and medical oncology. SKI scientists have discovered cancerrelated genes, mapped signaling pathways that control cancer cell initiation and progression, and identified the cell types involved in both mounting and repressing immune responses. Equally importantly, SKI researchers have pioneered clinical advances in cancer treatment, from chemotherapy and radiation therapy to targeted therapy to immunotherapy.

Metabolism and Medicine cardiomyopathy, all of which are rooted in metabolic pathology. In fact, Alzheimer’s disease is dubbed by some medical researchers, “diabetes type 3”, since the same insulin resistance and metabolic underpinnings are very similarly shared by the above-mentioned diseases, which are currently misunderstood as disparate pathogenic states. It should, therefore, be recognized that the same pathogenic soil generates a common matrix susceptibility state. Furthermore, what determines why one person will succumb to one disease yet another to a different disease is mainly the individual genetic predispositions amplified by detrimental lifestyle choices.

1.2 Opening Remarks (Biology, Introductory Level) The word metabolism (Greek: “change”) refers to the balance of energy as the sum of all chemical reactions that occur in a living system. It is the defining characteristic of a living system that distinguishes it from an inanimate physical system. Energy is extracted from nutrients obtained from the external environment and is utilized within the organism for the biosynthesis of molecules and other functions. The biochemical reactions of metabolism are organized into functional pathways whereby the product of one reaction becomes the substrate for the next; every product or substrate is a metabolite. Metabolism is carried out by thousands of enzyme-catalyzed reactions occurring simultaneously in cells and includes the inter-conversion of metabolic fuels in either anabolic or catabolic pathways. Molecules in these pathways are in continuous flux as the organism seeks to attain the balance of energy inputs and outputs. Maintaining this energetic stability or steady state of metabolic fluxes is called homeostasis. Organismwide stability and its long-term survival are achieved through plasticity (flexibility) by a myriad of networks of biochemical pathways. All of the metabolic pathways are organized to achieve two main goals essential for maintaining biological structure and function. The first is to extract energy from food as ATP, the main energy currency of the cell. The second goal of metabolism is to perform biological functions that require energy, for example, biosynthesis, molecular motor activity, and ion transport.

1.3 Metabolism Fuels Biological Motors and Engines (Physics, Introductory Level)

Charles Kettering. Source: licensed from Science Source Images.

Finally, it is consistent with this book’s message that cancer metabolism is not unique among the chronic diseases of aging, such as Alzheimer’s disease, cardiovascular disease, and

The physiological purpose of metabolism is to maintain a living state. Metabolic processes can be viewed as fueling the biological engine of a living system by transforming energy into thermodynamic work, which is in accordance with the first law of thermodynamics. This metaphorical biological engine includes mitochondria (combustion chamber), machinery for the production of ATP and its hydrolysis, molecular motors fueled by ATP, and all moving component parts formed at micro- and macroscopic scales (Figure 1.2). One example is

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FIGURE 1.2  Principles of the first law of thermodynamics, comparing machine engines and biological motors. *ATP = adenosine triphosphate.

the work done using the potential energy of ATP by muscle contraction, mediated by molecular motors causing the sliding movement of interconnected thin and thick protein filaments with respect to each other. Biological motors are central force generation elements to the machinery of living systems, just as mechanical motors are to a car engine. In both cases, the motor is responsible for converting one form of energy (stored in chemical bonds) into a mechanical force that generates motion involving translational or rotational kinetic energy. An organism may therefore be considered not only a biological engine but a complex structure composed of several types of biological engines, as well as motors intricately coordinated into a single larger system. This sophisticated coordination is achieved by metabolic networks running across the living system such as the human body. Metabolic networks are best understood as the conduits for the flow of energy through a living system.

(Biology/Biological Chemistry, Clinical Level) Cellular networks communicate through biochemical reactions, such as phosphorylation of proteins in a signaling pathway. Energy-requiring activities such as the “fight-orflight” response or the chronic inflammatory process of disease, calibrate available energy away from these networks for other life-sustaining functions. Accordingly, a number of pathways are compromised due to the diversion of energy from the network, which leads to the loss of metabolic redundancy, reduces resilience, and ultimately results in pathology and senescence. As the pathological process progresses, vastly reduced levels of metabolic redundancy eventually become a single metabolic tendril, which represents life support for the most important biological function, survival. Hence, disturbed metabolism is implicit as the cause and/or consequence of any disease state. A high capacity for metabolic flexibility, such as

shifting energy resources based on availability, is a hallmark of allostatic fitness and health.

1.4 Metabolic Pathways and Cellular Respiration (Biological Chemistry, Introductory Level) Metabolic pathways may be categorized as either catabolic or anabolic. Catabolic pathways degrade large molecules into simpler ones, such as the breakdown of macronutrients (carbohydrates, fats, and proteins) from food sources into smaller units. During this process the cleavage of chemical bonds releases energy. Such pathways include glycolysis and the TCA cycle (see Figure 1.3 for a detailed review of these pathways). Conversely, anabolic pathways coalesce smaller molecules into larger ones with the associated creation of chemical bonds using the energy captured by catabolic pathways. In order to function, the human body requires its equivalent in weight of ADP converted into ATP daily. This conversion of ADP takes place in the mitochondria, the power plants of the cell. Standard textbook teaching is that mitochondria occupy up to 25% of the cell volume, and each cell has several thousand mitochondria. However, mitochondria content is not the same in every cell; it varies with cell and tissue type. It is within these organelles that the majority of caloric fuel is oxidized, using the energy to produce ATP. Since more than 95% of the oxygen consumed by humans is used for this purpose, breathing ultimately occurs at the cellular level in the form of cellular respiration (the biochemical conversion of nutrient energy into ATP). The electron transport chain’s (ETCs) of mitochondria act as conveyor belts for transferring electrons from energy extracted from food to the high-energy phosphate bonds in ATP. In this manner, the bioenergetics of living

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FIGURE 1.3  Detailed depiction of the catabolic pathways of glycolysis and the TCA cycle. *CoA = coenzyme A; HK = hexokinase; P = phosphate; PFK = phosphofructokinase; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

organisms is driven by the energy in food being stored in pairs of electrons that make carbon-carbon and carbon-hydrogen chemical bonds. Such bonds have covalent properties. Mitochondria have two membranes, a convoluted inner membrane (crista) and a smooth outer membrane. Electron transfer (in the form of quantum tunneling) occurs along with the complexes of the ETC, which are embedded within the

Metabolism and Medicine inner mitochondrial membrane. The transfer of electrons through each of these complexes pumps hydrogen protons to the outside of the inner mitochondrial membrane. Movement of hydrogen protons at the end of the ETC across the membrane depolarizes the electrochemical gradient (brings the electrochemical charge closer to neutral), driving the synthesis of ATP. Concomitantly, pairs of ionized hydrogen protons and electrons combine with molecular oxygen as part of a reduction reaction to form water (see Figure 1.4 for a detailed depiction of the ETC). These two processes are the basis of cellular respiration. This ETC mode of energy production occurs through the process of oxidative phosphorylation. An alternative way of producing energy is the cytosolic process of glycolysis, also called “substrate-level phosphorylation”, whereby a phosphate group is transferred from substrates (reagents) to an ADP molecule, forming an ATP molecule. Similarly, in the TCA cycle, one molecule of guanosine-5’-triphosphate (GTP) is generated during the conversion of succinyl CoA to succinate. This GTP is ultimately used to produce ATP. One molecule of ATP can be classified as one quantum of biological energy. Glycolysis yields two net molecules of ATP per unit of glucose substrate. In contrast, when glycolysis and oxidative phosphorylation pathways are combined, the amount of total energy produced per unit of glucose substrate is 16-to-19-fold greater (~30 to 32 molecules of ATP produced from one glucose molecule) (Figure 1.5). Mitochondrial oxidative phosphorylation directly correlates to the volume of oxygen consumption due to its bioenergetic efficiency and large contribution to the overall metabolic rate. In the case of cancer, glycolytic metabolism is less efficient in the sense of energy produced per unit of glucose substrate. Thus, to meet their metabolic demand, cancer cells hijack the metabolic machinery of the host to consume available glucose which can lead to cachexia (muscle wasting) at the later stage of cancer. However, some cancers, such as breast cancer,

FIGURE 1.4  Electron transport chain. Complexes I to IV are shown as a series of electron transporters within the inner mitochondrial membrane. Protons are pumped from the mitochondrial matrix out into the intermembrane space creating an electrochemical gradient. NADH donates electrons to Complex I (NADH oxidoreductase) and FADH2 donates electrons to Complex II (succinate dehydrogenase). These electrons ultimately flow through Complex III (cytochrome C oxidoreductase) and complex IV (cytochrome c oxidase). The electrons are finally accepted by free oxygen. Electron transport requires chains of redox reactions, with a small amount of free energy used at three sites to transport protons (H+) across the inner mitochondrial membrane. There is debate in the literature on the exact balance of protons in the electron transport chain. The currently accepted model is presented in this figure. Source: adapted from (1). *ATP = adenosine triphosphate; CoQ = coenzyme Q; cyt c = cytochrome c; e = electron; FAD = the oxidized form of flavin adenine dinucleotide; FADH2 = the reduced form of flavin adenine dinucleotide; H+ = protons; H2O = water; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; O2 = oxygen; Pi = inorganic phosphate.

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FIGURE 1.5  Metabolic pathways utilizing substrate-level phosphorylation (glycolysis and the TCA cycle) and oxidative phosphorylation (Electron Transport Chain, ETC). The ETC produces much more ATP per unit glucose than glycolysis or the TCA cycle. Source: adapted from (2). *ATP = adenosine triphosphate; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

actually seem to have upregulated oxidative phosphorylation, as they rely more on fatty acids. The associated adipose tissue lipolysis in these cases is an alternate cause of cancer cachexia.

1.4.1 Metabolic Modes of Energy Production (Physics and Quantum Biology Introductory Level) Metabolism can manifest itself in two main forms: classical and quantum, but is typically a hybrid of both forms. The most efficient level of metabolic functioning occurs when the quantum mode of energy production is utilized by an organism, which means perfect synchronization across the biological system. In the case of a 100% quantum mode, the biological system would be in a virtually timeless state due to zero entropy production which accompanies an ideal perfectly cyclical process. Since heat is energy in transit, it can either be transferred from one system to another (harnessed in molecular bonds as potential energy in a thermally catalyzed reaction, for example) for useful purposes (i.e., to do the energy requiring work of a biological system), or more commonly, is dissipated into the environment unable to do useful work. Hence, when no heat is lost to the surroundings, the maximum amount of energy from nutrient substrate is transformed into the work of maintaining biological homeostasis; the biological system would be unchanged over time as the process is perfectly cyclical. In this hypothetical ideal case, aging would not occur because aging itself is an inefficient entropy-producing process whose rate can be viewed as a function of energy dissipated as heat. An associated aspect of aging is the system’s wear and tear, i.e. an accumulated damage to the structure and function of the organism's “moving parts” largely due to the damaging effects of oxidation (loss of electrons). Quantum metabolism is a hypothetical maximally efficient mode of energy production for a never-aging biological system. On the

other end of the metabolic spectrum is the classical mode of energy production; the transformation of energy from food is highly inefficient, with the majority of heat lost to the surroundings, and the related damage to the structural integrity of cells, organs, and tissues. The state of optimal human health is sustained by a composite involvement of quantum and classical metabolism. While heat production in the classical mode is metabolically inefficient, some heat is necessary to maintain constant physiologic body temperature and to catalyze numerous biochemical reactions. This combination of quantum and classical mode is inherently characterized by a lack of absolute synchronization of biological processes and physiology. In a hypothetical state whereby our metabolism is entirely in the quantum mode, biological processes and physiology would occur in the absence of heat generation, like a perpetual motion machine. In this case, molecular collisions, which are the cause of friction and thus of heat in a physical or biological system, would not occur. Molecular collisions can bring a moving physical system to a stop and can also degrade the synchronized coordination of a biological system. Degrading synchronization accelerates the passage of time, reducing health and shortening life span. Indeed, the amount of heat lost from a system during bioenergetic metabolism parallels the rate of aging. We propose that this phenomena is a biological application of Einstein’s theory of special relativity (see Volume 1, Chapter 3).

HIGHLIGHTS OF CLASSICAL BIOENERGETIC METABOLISM VERSUS QUANTUM METABOLISM (QM) • In the classical regime of bioenergetic metabolism, an intrinsic property is energy conversion to heat that is lost from the system. This energy is unable to be used for useful purposes, i.e., the production or utilization of ATP to perform physiology, and the amount often exceeds that which is required for maintenance of physiological thermogenesis. • In the classical regime of metabolism, heat produced that is beyond physiological needs promotes inflammatory and redox stress. • Inflammatory and redox stress generated by metabolic reactions can be directly related to the entropy production rate (redox stress) with associated heat loss (inflammatory stress) of a physical system including its immediate environment, thus tending a far-from-equilibrium biological system, a human organism, towards thermodynamic equilibrium. • Redox stress (and associated inflammation) is the most fundamental driver of accelerated pace of aging and the chronic diseases of aging.

Heat is a cardinal feature of inflammation. Inflammation results from increased reactive oxygen species (ROS). ROS are formed when oxygen molecules collide with free electrons in the mitochondria. ROS drive the aging process by

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activating NFkB and a cascade of inflammatory signaling, and also through collisions with cell membranes and cytoplasmic proteins, compromising biological structure and associated functions. In contrast to classical systems, a quantum system is virtually frictionless and generates no heat. It is maintained by waves of energy (“quantum wave function”) that collapse in the presence of heat. Taken together, in a quantum biological system, as in the case of quantum metabolism (see Volume 1, Chapter 3), many molecules of ATP are produced in a synchronized and coherent mode that are correlated over space and time. Time in this quantum system stands essentially still while ATP is produced in synchrony. This mode of energy production is maximally efficient, as defined by the amount of ATP produced per oxygen molecule consumed and heat lost. As humans and other living systems age and increasingly lose the capacity for a quantum synchronized metabolic state of health, synchronization of metabolic physiology in a classical circadian biological sense, is maintainable. Circadian biology as the organizing principle for sustaining health, despite the loss of a quantum mode of energy production, prevents an exponential acceleration of the aging process. The loss of synchronization of metabolic pathways that shorten health span and physical lifespan is promoted by many self-amplifying feedforward pathological processes across molecular, cellular, and systems biology hierarchical scales. Psychogenic stress is a fundamental component in the pathogenesis of human disease, interwoven in a fabric of disturbed gut microbiota and circadian biological health. Loss of synchronization in metabolic pathways accelerates entropy production rate, which is proportional to heat lost and the inability to do useful work, producing aging.

SIDEBAR 1.1: QUANTUM AND CLASSIC METABOLISM TAKE-HOME POINTS Quantum Energy Production • • • • •

Most efficient Zero entropy production Perfect synchronization No heat lost Maximal energy from nutrients • Complete homeostasis • System unchanged • Timeless = no aging

Classic Energy Production • Inefficient (relative to quantum energy production) • Entropy production • Lack of quantum synchrony (synchrony in a classical sense) • Heat lost • Energy from nutrients • Loss of homeostasis • Acceleration of aging

We propose that quantum energy production and classical metabolism exist in hybrid states in human health.

1.4.2 Metabolic Cycles and Metabolic Rate (Biological Metabolism and Translational Medicine, Introductory Level) The metabolic cycle is the most fundamental of all living system cycles. It underlies the energy supply required to maintain all other cycles, including the transcription of biological

clocks in cells. Hence, the metabolic cycle is responsible for the circadian behavior of the organism. Time and metabolism are closely linked. Cycle time is a variable that is inversely proportional to metabolic rate. Metabolic rate is the rate of conversion of nutrient substrates into ATP. Nutrient substrates may come from the diet or from body storage depots of fat or glycogen.

(Physics Metabolism and Translational Medicine, Introductory/Intermediate Level)

SIDEBAR 1.2: METABOLIC RATE AND ALLOMETRIC SCALING LAW The metabolic rate of living species can be evaluated using concepts of allometry, or biological scaling, which examines how components of a living organism change in relation to size. Here, we can use an allometric scaling law that highlights the mathematical relationship between metabolic rate (MR) to body weight (W). Each species has its own proportionality constant, α, but most species have the same scaling exponent β, typically 3/4, such that MR = ∼αWβ. The 3/4 scaling exponent is characteristic of the quantum mode of metabolism, while the classical mode typically has an isometric scaling exponent of one, where MR and W are linearly proportional to each other. Both the aging processes and metabolic diseases result in a tendency toward isometry as a result of the loss of synchronization of metabolic processes across scales, and poor transport of oxygen and nutrients. This is consistent with the prototypical metabolic disease states of insulin resistance and diabetes, whereby insulin signaling induced glucose uptake and glycosylated hemoglobin induced oxygen uptake into cells is impaired. Consequently, the gradual shift of the scaling exponent from 3/4 to one would indicate metabolic disease state development and can be used as a diagnostic tool. It is also expected that normal aging processes cause a gradual shift toward isometry. In both cases, efficiency of metabolic energy production is compromised and it results in a gradual loss of quantum coherence with concomitant entropy generation and heat production. Hence, longevity is thought to correlate with slow MR, in the special quantum sense of increased metabolic efficiency, that less ATP is required per unit of body mass. This is underpinned by the proper timing, quality, and quantity of activity/exercise, diet, and stress coupled with genetic and socio-economic factors. Monitoring the metabolic rates of individuals as functions of weight over time could be a precise diagnostic tool for the onset and progression of diseases and conversely, a return toward a quantum scaling exponent of 3/4 could be prognostic of healing processes taking hold. These scaling laws offer a quantitative tool in monitoring the metabolic health of individuals as they age and become susceptible to disease if not aware of the change in the metabolic demands of the body with the passage of time.

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(Biological Chemistry and Translational Medicine,Introductory/Intermediate Level) Cellular metabolism involves organized networks of mitochondrial enzymatic oscillations and oxidation reactions. Every oxidation reaction is coupled to a reduction reaction, and this combination is referred to as a redox reaction (Figure 1.6). Disturbed redox occurs when unregulated transfer of electrons creates free radicals (loss of an odd number of electrons). The collision and uptake of these unpaired electrons by oxygen molecules generates reactive oxygen species. ROS’s subsequent interactions with and modification of other molecules of the cell, such as cell membranes and cytoplasmic proteins, leads to the “stealing” of electrons. This often causes a chain reaction that damages the structural integrity of the cell and function of cell biology. The recombination of ROS can lead to the formation of hydrogen peroxide, which can cross lipid membranes, causing wide-spread damage. The human nervous system, which is a biological system, may engage in a quantum mode of synchronization that spans the entire body. The cognitive reflexes linking the brain to the extremities lead to system-wide functioning. We have discussed at length common examples of what this orchestration can achieve, such as the impossible save by a professionalhockey goalie or an amazing return of a 150 mph serve by a championship-level tennis player (see Volume 1, Chapter 3). These and many other examples of the full scale of the human potential illustrate physiological manifestations of quantum coherence at a macroscopic scale. Quantum metabolism occurs over wide spatial areas virtually simultaneously. Initially at a cellular level, quantum coherence can be seen in the way metabolic enzymes engage in periodic activity, which is orchestrated across mitochondria in a cell. Quantum coherence then spreads across many cells within a tissue, and in all tissues and organs across an organism. The oscillation frequency of these processes correlates with the metabolic rate, which is relatively slow in the cells of tissues in a given system. However, metabolic rate is considerably more rapid and less efficient for mitochondrial oxidative

FIGURE 1.6  An example of an oxidation-reduction (redox) reaction. Every oxidation reaction is coupled with a reduction reaction that involves the transfer of electrons between two compounds. In an oxidation reaction, a compound loses electrons. In a reduction reaction, there is a gain of electrons. *e- = electron.

phosphorylation. Earlier, we discussed how the metabolic efficiency in the quantum mode of energy production is much greater than in the classical mode. The maximum efficiency achieved in the quantum regime applies across the scales of biological organization due to intra- and inter-cellular synchronization of energy production processes. In the quantum mode, we can say that time is maximally dilated and aging is relatively slow, in contrast to the classical mode, with declining physiological health. In the classical mode, metabolic cycles of energy production are characterized by an increase in metabolic rate, but a reduction in metabolic efficiency. This reduction in metabolic efficiency is due to the shorter cycle time and greater production of ATP. The greater the percentage of mitochondrial electron transport chains operating in the quantum mode, the more efficient the biological engines become, with the least amount of wear and tear incurred. Conversely, the inefficiency of the classical mode of energy production causes inflammation and redox damage of molecular cell structures.

HIGHLIGHTS OF CLASSICAL BIOENERGETIC METABOLISM VERSUS QUANTUM METABOLISM (QM) • MR= the rate of energy production (substrate to product) per unit time in the classical regime vs MR= the rate of energy production per unit time as a product of mass in the quantum regime. • Accordingly, in the classical regime (and classical teaching of metabolism) a fast metabolic rate in terms of efficiency of energy production engages Ox Phos. • Glycolytic production of ATP is much faster than mitochondrial Ox Phos per cycle of substrate conversion to product, however it is much less efficient in terms of the amount of ATP produced per molecule of glucose consumed. • The efficiency of nutrient fuel mitochondrial oxidation is gauged by the P:O ratio, i.e. the amount of ATP produced per oxygen consumed. This ratio is higher for glucose oxidation (coupled to glycolytic metabolism) than for fatty acid oxidation.

Although the classical regime of mitochondrial oxidative phosphorylation is inefficient and causes damage, it nonetheless is an essential metabolic foundation for human physiology. Ironically, low levels of electron slippage from the respiratory chain that mediate oxidative stress and structural injury can also induce antioxidant effects and cell repair. This is an optimal adaptive response consistent with the notion of hormesis. Moreover, a hybrid state of quantum and classical metabolism at some optimal ratio that is biologically feasible underpins maximal fitness function. Such an optimal ratio may translate into prolonged human health and lifespan. The ratio of quantum: classical metabolic regimes of energy production parallels the rate of biological time and aging relative to physical cycles of time. Biological time runs slowest in the context of maximum physiological health; metabolic rate and aging are lower when in the quantum mode of energy production.

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Conversely, the greater the relative contribution of the classical mode, the more rapid the process of aging. Optimum physiologic health may be described as having a low metabolic rate and high metabolic efficiency in the quantum sense. Food overconsumption leads to a conversion from the quantum to the classical mode of ATP production, decreasing metabolic rate and health. The classical mode causes hunger, and vice versa. For example, obese individuals require more energy to maintain metabolic activity, representing a reduced efficiency in the organization of the biological system. Insulin resistance in obesity is closely related to mitochondrial dysfunction. Further, patients with insulin resistance can have impaired satiety (feelings of fullness), rooted in the arcuate nucleus of the brain. This causes obese individuals to have greater appetites and consume more calories. Caloric excess overloads mitochondria, induces oxidative stress, and promotes insulin resistance. This creates a self-amplifying loop of increased hunger, overeating/obesity, mitochondria dysfunction, and the classical mode. Classical metabolism is correlated with oxidative and inflammatory stress, and associated mitochondrial dysfunction. In contrast, eating in moderation is both necessary and sufficient for the quantum regime. The shift from quantum to classical metabolism is referred to as the takeover threshold. This may result directly from dietary surplus, or from within the body, particularly fat deposits in cells not meant to store fat. This causes an excess supply of electrons to the respiratory chain, resulting in mitochondrial dysfunction, driving a feedforward self-amplification of bioenergetic disease. Following the onset and progression of mitochondrial dysfunction, energy substrates increasingly rely on the anaerobic pathway of glycolysis in the cytoplasm, despite the presence of oxygen. This process is referred to as aerobic glycolysis.

HIGHLIGHTS OF CLASSICAL BIOENERGETIC METABOLISM VERSUS QUANTUM METABOLISM (QM) • In comparison to the classical regime of bioenergetics, in the quantum regime MR utilizing Ox Phos (coupled to glycolysis when glucose is the substrate) is much slower as a consequence of its greater efficiency. • In the quantum regime, this greater efficiency is largely a consequence of ATP production, with a higher P:O ratio coherently synchronized in time and correlated across an area of mass. • In the quantum regime there is greater efficiency of energy metabolism on a second level; more of the biochemical energy released from the hydrolysis of ATP is transformed into biological work. • Thus, less energy is lost as unusable heat in the process of producing ATP, and its utilization. • The lower P:O ratio associated with QM equates to lower amounts of redox and inflammatory stress, and thus a slower pace of biological aging, and reduced prevalence of chronic disease states of aging.

• The lower percentage of infrared heat loss with hydrolysis of ATP heralds greater physiological performance.

SIDEBAR 1.3: METABOLIC RATE FROM CLASSICAL AND QUANTUM PERSPECTIVES Metabolic rate (MR) is conventionally defined as the amount of ATP produced per unit time. Specific metabolic rate (SMR), on the other hand, is defined as the amount of ATP produced per unit time per unit mass (M) of the system. In other words, specific metabolic rate is metabolic rate divided by mass, or mathematically speaking: SMR=MR/M. In the quantum mode MR is slow because the correlated state of energy production has maximum efficiency requiring a lower energy input. Conversely, in the classical mode the amount of ATP produced per unittime per unit mass (SMR) is fast because the quantity of mass is relatively small, and the quantity of time relatively large, i.e. the ratio of units mass/time is small (comparative to a much higher quantity as a ratio in a quantum sense). Such a fast rate of ATP production in a classical system may be optimal for meeting metabolic demands. However, it often comes at the cost of increased oxidative and inflammatory stress, including pathological conditions such as thyrotoxicosis. In this state, appetite is ravenous and food consumption exceeds the capacity of the electron transport chain, thus resulting in reactive oxygen species being produced in pathological amounts. Chronic moderate exercise actually slows heart rate and lowers blood pressure by increasing the efficiency of ATP production. This may be a function of the higher ratio of glucose and ketone bodies relative to fatty acids as bioenergetic substrates that have greater energetic efficiency. This allows for the slow heart rate because more ATP is available per unit time. Additionally, when the intensity of exercise does not exceed what is appropriate for the level of physical conditioning, less oxidative stress is generated. This is beneficial to mitochondrial functional capacity. However, high intensity exercise that is inappropriate for the level of conditioning may be potentially detrimental to mitochondrial function; dysfunctional mitochondriaprohibit coupling of glycolytic and mitochondrial glucose metabolism. In such cases, mitochondria may also have less accommodative capacity for ketone metabolism.

1.4.3 Metabolic Rate, Metabolic Efficiency, and Cellular Respiration in Clinical Medicine (Clinical Biological Physiology/Exercise Physiology, Introductory Level) What are the connections between exercise physiology, VO2 max/submax, and the broader notion of stress testing with applicability to all subspecialty fields of clinical medicine?

Introduction to Metabolism The metabolic rate typically parallels oxygen consumption. VO2 max and VO2 submax are the maximum and sub-maximum volume of oxygen consumption per kilogram of body weight per minute, respectively. As VO2 max/submax declines, so does the metabolic rate (amount of ATP production per unit time per unit mass) and metabolic efficiency (amount of ATP produced as a ratio of oxygen consumed). Importantly, the concept of VO2 max can be used beyond the research and sports settings, and has real-world applications in clinical medicine.

SIDEBAR 1.4: OXYGEN CONSUMPTION AND ALLOSTASIS The physical exertion required to assess maximum or submaximum oxygen consumption obligates the increase in heart rate necessary for delivering oxygen from air inhaled into the lungs to the mitochondrial respiratory chains in skeletal and cardiac muscle. This exemplifies the principle of allostasis, stability through change, to maintain homeostasis. Fundamental to the notion of allostasis is stress, which applies to all hierarchical scales of a biological system, from molecular cell biology to the psychogenic perception of stress. The notion of allostatic load represents the threshold beyond which allostatic overload is reached; allostatic overload represents disease. The terms allostatic load and overload were coined by Bruce McEwen, a Biology Endocrinologist Ph.D. from The Rockefeller Institute in NYC. Sadly, Bruce recently passed away. I was privileged to be influenced by a true pantheon in the field of the stress response. He was a powerful collaborator and mentor. While these concepts apply to hormonal, autonomic, and immune system responses to psychogenic stress, they are inextricably intertwined in mitochondrial bioenergetic function and dysfunction. These concepts are extensively discussed in this volume (See Chapter 9). In the future, VO2 max and VO2 submax may be powerfully informative and complementary vital signs predictive of chronic disease states of aging, including cardiac and vascular disease, cancers, Alzheimer’s disease, and accelerated cognitive decline of aging, among other causes of premature mortality. The ideal VO2 max or VO2 submax is achieved by measuring the oxygen and carbon dioxide concentrations in the air the patient has exhaled while exercising on a stationary bike or treadmill. The major determining parameters of VO2 max or VO2 submax are age, resting heart rate, waist circumference (in centimeters), and a physical activity index (determined by estimates of the frequency, intensity, and duration of routine exercise). In the context of sports medicine and training, VO2 max is a measure of exercise conditioning and endurance capacity. Endurance capacity is a function of the tolerance of exercise intensity and duration. The expression of physical tolerance largely has to do with air hunger (i.e., the sensation of not being able to breathe sufficient air), muscle fatigue, and sometimes the sensation of a racing heart, as well as the amount of time for these symptoms to return to resting levels after stopping exercise. The typical symptoms of impaired VO2 max or VO2 submax are exaggerated air hunger

11 and muscle fatigue relative to the intensity and duration of physical exercise. Exercise tolerance is mostly dependent on lung function and cardiac and skeletal muscle conditioning. While breathing begins in the lungs, the pumping action of the heart is an essential contributor to gas exchange in the lungs. The circulatory system relays oxygen and carbon dioxide to and from the body’s cells, respectively. Within these cells are the mitochondrial metabolic pathways and respiratory chains. Delivery of oxygen by the circulatory system to these cells allows the mitochondrial metabolic pathways and respiratory chains to go into action producing ATP. The efficiency and capacity of this process to deliver oxygen to ATP-producing cells ultimately determines metabolic fitness. Most cardiac stress tests for myocardial ischemia involve a low level of exercise on a treadmill or stationary bike for 8–12 minutes. This test can reveal impaired delivery of oxygenated blood, which is a sign of obstructive vascular disease. It can also detect myocardial disease. Both vascular and cardiac disease are fundamentally metabolic disorders (see Chapter 9, Section 9.4) rooted in mitochondrial dysfunction. Myocardial disease happens when the respiratory apparatus of the mitochondria is unable to utilize oxygen to produce sufficient ATP to meet metabolic demands. Because of the connection between VO2 max/VO2 submax with mitochondrial dysfunction, abnormalities in these measurements can hint at a wide spectrum of the chronic diseases of aging. The impact of exercise on metabolic function is a doubleedged sword. Exercise has many positive impacts on health: it improves VO2 max/submax, mitochondrial function, insulin sensitivity, and promotes healthy aging. However, high intensity exercise can also promote these same pathological conditions during morbid or premorbid disease states. For example, while air hunger and impaired VO2 max or VO2 submax compensate for the reduced ability to utilize oxygen for ATP production in several metabolic disease states, it is ultimately the overspill of oxygen that creates a feedforward cycle of metabolic disease. Therefore, exercise should be prescribed on a personalized scale. During high intensity physical exertion, VO2 max can be used as a stress test for the cardiopulmonary, vascular, muscular, and skeletal systems. The physical and metabolic demands are imposed on these main systems during exercise, with minor involvement from all tissues and organ systems of the body. During strenuous exercise, contractile cells in skeletal and cardiac muscles have high metabolic demands for ATP production. The assessment of VO2 max or VO2 submax provides valuable information about a patient’s bioenergetic potential, which can be used to infer the patient’s metabolic rate. This can be coupled with localized biopsy and kits to assess mitochondrial structure and function, as well as tissue-specific redox and inflammatory stress, to detect divergence of metabolic rate from VO2 max/submax in disease states. Together, these measures can help determine the relative vulnerability state of any given organ system or tissue. Examples of less-invasive stress testing include a lipid profile or C-peptide (endogenous form of circulating insulin) obtained in the postprandial absorptive state.

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*AD = Alzheimer’s disease; COPD = chronic obstructive pulmonary disease; VO2 max = maximum volume of oxygen consumption per kilogram of body weight per minute.

SIDEBAR 1.5: CLINICAL CONSIDERATIONS REGARDING VO2 MAX TESTING, METABOLIC RATE, AND DISEASE STATES In athletes, the volume of oxygen consumption is commonly measured as VO2 max. Metabolic rate, however, does not always correlate with VO2 max rates, which are quite divergent in disease states. Clinicians equate high metabolic rate with high oxidative stress (e.g. hyperthyroidism). Typically, parameters such as VO2 max or VO2 submax that assess liters of O2 consumed per kilogram of

body weight per minute are used as a measure of fitness. They act as the fundamental order and control parameters to quantify susceptibility of disease states. For example, the reciprocally related insulin resistance and mitochondrial dysfunction can be connected via impaired VO2 max, based on the premise of metabolic efficiency as a measure of physical fitness, with its loss being fundamental to senescence and chronic disease. On a more topical level, we now consider the above concepts within the context of COVID-19 and its effects on pulmonary

Introduction to Metabolism function and metabolism. COVID-19 has an acute phase from which patients typically recover. However, some patients enter a chronic phase of the disease where pulmonary function may be deconditioned or damaged from a fibro-inflammatory process. Symptoms may include persistence of cough or shortness of breath, the latter especially during exertion, or while talking or eating. Moreover, when the lungs are compromised, patients feel fatigued, and sarcopenia and other adverse sequelae may occur. An important question is why? The lungs are a macro-respiratory system which nourishes the cellular respiration processes of all organ systems and tissues with oxygen. This allows maximum combustion of the hydrocarbon skeleton of dietary macronutrients to the breakdown products of CO2 and H2O accompanying the bioenergetic transformation of energy to the currency of ATP. ATP allows cells to carry out the energy-demanding functions of cell differentiation, and the coordinated orchestration of systems biology. In the absence of sufficient oxygen supply to cells, VO2 max/submax declines, as does mitochondrial function. It follows that there is greater reliance on anaerobic metabolism through the glycolysis pathway for the production of ATP. The glycolytic metabolism of glucose is incomplete and its generation of ATP is only a fraction of mitochondrial oxidation. Furthermore, the unavailability of oxygen results in impaired oxidative metabolism of lipids, which leads to ectopic fat deposition in many tissues systemically. This results in lipotoxicity and free radical damage of cell structures and function, including mitochondria. Either inadequate delivery of oxygen to mitochondria, or molecular structural damage of the organelle, cause dysfunctional oxidative bioenergetics, thus diminishing biological work. Consequently, physiological processes such as cognitive functions, or ambulation and other activities requiring muscle contraction, are more difficult to perform, causing fatigue and weakness. Analogous to this is a high performance internal combustion engine in the absence of sufficient oxygenation; its gasoline petroleum fuel is incompletely combusted to CO2 and H2O. Accordingly, the engine loses torque, power, and gas efficiency. Dysfunctional mitochondrial metabolism also often presents with the chronic diseases of aging. For example, chronic obstructive pulmonary disease (COPD) is associated with lung cancer. High level exposure of lung tissue to oxygen beyond the cells ability to utilize it for ATP production results in oxidative and inflammatory stress and potential oncogenic mutations. Subsequently, there is an upregulation of aerobic glycolysis (i.e., the Warburg effect) to support bioenergetic requirements and unregulated cell proliferation.

1.5 Biological Entropy Production Rate and Aging (Biophysics, Metabolism, and Physiology, Introductory Level) The slowest possible rate of aging is associated with a minimum amount of redox disturbance, inflammation, or entropy production rate (EPR; Figure 1.7). EPR is equivalent to the pace of biological aging. Regardless of the pace of aging, advancing age is

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FIGURE 1.7  Entropy is cyclical when the state function (S) = 0. When entropy S > 0, time passes and aging occurs.

accompanied by increased redox and inflammatory stress. These two bidirectionally-activating processes are the driving force of biological aging. For example, as part of an inflammatory process, heat is lost from biochemical bonds, and there is an accompanying increase in EPR. Increased EPR collapses the quantum metabolic mode of energy production. Redox and inflammatory stress degrade mitochondrial structure and function, decreasing the efficiency of classical bioenergetics. Chronic caloric insufficiency or excess, poor nutrient quality and/or timing, disruption of other circadian behaviors, and prolonged psychogenic stress promote these pathological changes in metabolism. These external factors that shape metabolic health become interwoven to cause a complex disease state. A living system consists of biological cycles. This is the basic strategy for sustaining life in the physical universe to resist the arrow of time. Figure 1.7 uses a circle to illustrate the idea of a perfect cycle in a quantum biological system: an idealized zero entropy system with no heat generation or aging. This is the living equivalent of the perpetual motion machine. The rate of aging can be represented as divergence from the original starting point, with unavoidable acceleration as death approaches. Along the course of aging, organizational complexity is lost, which is equivalent to metabolic disease. Premature chronic diseases of aging such as cancer, neurodegenerative diseases, and cardiovascular diseases can be viewed as an acceleration of this process. In the case of caloric excess overloading the electron transferring potential of mitochondria, electron slippage and formation of superoxide modify the molecular components of mitochondria. Healthy levels of superoxide have physiological roles in thermogenesis and body temperature regulation. However, pathologically elevated levels of superoxide may reduce the generation of ATP by uncoupling the mitochondrial membrane gradient potential from the production of ATP. This causes cell energy stress. On the other hand, uncoupling the mitochondrial membrane gradient potential from producing ATP may be a therapeutic option in metabolic diseases such as obesity and diabetes. For example, energy lost to heat cannot be captured as ATP. This bioenergetic inefficiency drives mitochondria to increase the use of pyruvate, which increases glucose oxidation. Glucose oxidation is a form of diabetic glucose regulation. Further, glucose oxidation promotes weight loss by increasing caloric expenditure, much of it being lost as heat. That is not to say that uncoupling ATP production from the mitochondrial proton gradient is a safe treatment for obesity.* * An experimental drug from the 1930s, 2,4 dinitrophenol (DNP), caused hyperthermia, mitochondrial dysfunction, glycolysis pathway-mediated lactic acidosis, and a high mortality rate. DNP is sometimes sold online by disreputable vendors as a weight loss aid. This has led to a considerable number of deaths.

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1.5.1 Biological Entropy Production Rate and Pharmacological Implications (Metabolism and Translational Medicine, Introductory Level) What is a newly understood connection of exercise physiology of resistive training to weight loss? How do near future diabetic therapies invoke the field of mitochondrial medicine?

Bruce Spiegelman of Harvard University discovered that resistance training causes skeletal muscle to release a hormone called “Irisin”. Irisin promotes the conversion of white adipose tissue (fat storage) to beige adipose tissue (fat burning, thermogenesis). The fat burning mechanism of beige adipose tissue is largely due to an upregulated activity of uncoupling protein 1 (UCP1) (3). Another compound of value for metabolic control is dichloroacetate (DCA). The pyruvate dehydrogenase complex (PDC) is inhibited by pyruvate dehydrogenase kinase (PDK 1-4). DCA inhibits phosphorylation of PDK1-4, ultimately disinhibiting PDC. This has therapeutic utility in diabetes and certain types of cancers, where DCA restores decarboxylation of pyruvate to acetyl-CoA and subsequent mitochondrial oxidation process. Restoration of PDC activity attenuates compensatory overproduction and buildup of lactic acid (Figure 1.8). Simultaneously targeting ATP uncoupling in a safe manner and upregulating PDC activity may be viable treatments for the management of both obesity and type 2 diabetes. Chronotropy (the extent of upregulation and timing of drug activity) is vitally important to the safety and success of metabolic disease management. The importance of glucose combustion in mitochondria is discussed in detail in the Calorie Restriction Chapter (Chapter 5) and in the Linchpin Concepts Connecting Mitochondrial Dysfunction to Chronic Diseases of Aging

section of Chapter 8 (Section 8.3). However, glucose metabolism can be impaired in many chronic diseases, which are discussed in the circadian biology chapter (“Biology of Time”, Chapter 4), the Insulin Resistance discussion, and other sections. The breakdown of daily circadian cycling of insulin secretion and peripheral insulin signaling occurs in many chronic diseases of aging. Therefore, insulin resistance can cause upregulated glucose oxidation in skeletal muscle and liver during the nocturnal phase. Insulin resistance can lead to release of fatty acids from adipose tissue, followed by ectopic fat accumulation. This ectopic fat accumulation exacerbates insulin resistance in the skeletal muscle and liver, in addition to potentiating chronic diseases of aging. Another promising experimental drug, Imeglimin, promotes the upregulation of a master metabolic regulator, Nuclear Hormone Receptor family coactivator, peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α) in mitochondria. Imeglimin promotes the biogenesis of mitochondria. This increases bioenergetic capacity and decreases oxidative stress, enhancing insulin sensitivity in skeletal muscle. Imeglimin increases glucose-dependent insulin secretion in beta cells of the pancreas. Another important effect of Imeglimin is inhibition of oxidative phosphorylation in the liver, resulting in reduced gluconeogenesis. Imeglimin may also stimulate the activity of the mitochondrial respiratory chain (electron transport chain, ETC) Complex II (succinate dehydrogenase enzyme; Figure 1.11).

1.6 Key Bioenergetics Concepts (Basic Concept of Metabolism, Introductory Level) The central physiological purpose of metabolic pathways is to provide the bioenergetic needs of the body. Glycolysis, the TCA cycle, the electron transport system, β-oxidation of fatty

FIGURE 1.8  Dichloroacetate promotes the conversion of pyruvate to acetyl-CoA promoting the coupling of glycolysis and mitochondrial oxidative phosphorylation. Adapted from (4). *DCA = dichloroacetate; H+ = hydrogen; NADH = the reduced state of nicotinamide adenine dinucleotide; PDH = pyruvate dehydrogenase; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

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Introduction to Metabolism acids, and ketogenesis from fatty acids are metabolic processes that produce ATP, fueling the body. Proteins are also usually in balance and they contribute 15–20% of energy expenditure, particularly the branched-chain amino acids (BCAA) and glutamine. Glycolysis utilizes glucose to synthesize low levels of ATP (a net production of 2 ATP per molecule of glucose) when oxygen is unavailable. During glycolysis, lactate becomes the end product of this pathway. Lactate can serve as a fuel in some tissues, or it can circulate to the liver to be converted back to glucose via the Cori cycle. Glycolysis also produces 2 NADH molecules, which are transported via the malate-aspartate shuttle into the mitochondria. If the cell has mitochondria, NADH can then feed into the electron transport system to contribute to ATP production. The TCA cycle is the central metabolic hub for producing ATP. In the presence of oxygen, pyruvate translocates into the mitochondria to drive the TCA cycle. The TCA cycle completes combustion of acetyl CoA products into CO2 and ATP. This is an aerobic process known as oxidative phosphorylation. The cycle is a sequence of chemical reactions incorporating acetyl CoA, which is derived from the degradation of fatty acids (via β-oxidation), glucose (via glycolysis and oxidative decarboxylation of pyruvate), amino acids, and ketone bodies (degradation of amino acids and ketone bodies are generically referred to as oxidative catabolism).* The electron transport system is the part of aerobic respiration that uses molecular oxygen as the final electron acceptor from fatty acid and glucose metabolism. The electron transport system consists of 4 protein complexes seated in the inner mitochondrial membrane along with two diffusible electron carriers (Coenzyme Q and Cytochrome C) shuttling electrons between them. Catabolism of glucose and lipids generates high-energy electron donors, such as NADH and FADH 2. This process contributes to the electrochemical gradient used in chemiosmosis to form ATP (see Figure 1.4). β-oxidation of fatty acids is a process of catabolizing longchain fatty acids within the matrix of mitochondria into the 2-carbon unit-sized molecule acetyl CoA, NADH, and FADH2. The acetyl CoA groups are then further oxidized through the TCA cycle, producing additional NADH and FADH2, and ultimately ATP (see Section 1.7.5). Ketogenesis is the formation of ketone bodies in liver mitochondria. It occurs when the production of acetyl CoA exceeds what can be utilized in the TCA cycle. In this situation, excess acetyl CoA is converted into ketone bodies, which are released into the circulation and utilized as an energy source in the * Each turn of the TCA cycle consumes 1 acetyl CoA, and generates 3 NADH and 1 FADH2, for a total production of 6 NADH and 2 FADH2 per acetoacetate molecule. The electron pair donated from each NADH molecule into the electron transport system produces 2.5 molecules of ATP, while the electron pair donated from FADH2 drives 1.5 ATP molecules. The TCA cycle also produces GTP, another energy source. Succinyl CoA reacts with succinyl CoA synthetase, guanosine diphosphate (GDP), and inorganic phosphate to produce succinate, GTP, and coA. CoA is used as a substrate to generate ATP. This is also an example of substrate-level phosphorylation.

brain, skeletal muscle, and cardiac muscle (5). The complete oxidation of the ketone bodies β-hydroxybutyrate and acetoacetate generates ~23 and ~20 ATP molecules, respectively. Figure 1.9 shows the connection between the TCA cycle, fatty acid oxidation, ketogenesis, and ATP production.

SIDEBAR 1.6: METABOLIC EFFICIENCY OF KETONE BODIES Ketone bodies are a super fuel that potentiates the proton electrochemical gradient across the inner mitochondrial membrane. This in turn drives a higher production of ATP per unit of oxygen consumed, which defines a higher metabolic efficiency. A compromise in the ratio of these biochemical parameters is equal to metabolic and chronic disease. Cardinal features of compromised ATP production per unit oxygen consumed include mitochondrial dysfunction and insulin resistance (see Section 1.8). The concepts of metabolism and metabolic pathways are further discussed in Chapter 9.

SIDEBAR 1.7: METABOLIC EFFICIENCY OF GLUCOSE VERSUS FATTY ACIDS The complete combustion of glucose is bioenergetically more efficient than fatty acids in the setting of insulin-stimulated signaling: stimulated PDC activity increases pyruvate-derived mitochondrial acetyl CoA. This decreases the ratio of NAD+: NADH couple due to NAD+ reduction in the TCA cycle*. A subsequent increase in NADH dehydrogenase activity at Complex I of the electron transport chain promotes the electron transfer to coenzyme Q, which drives the proton motive force to produce ATP. This is the coupling of cytosolic glucose metabolism through the glycolysis pathway to the TCA cycle and oxidative phosphorylation. The metabolic efficiency of mitochondrial combustion of glucose (defined by the amount ATP produced per unit quantity of O2 consumed) is greater than fatty acid oxidation. This is because the catabolism of long-chain fatty acids to acetyl CoA groups produces a 1:1 ratio of NADH to FADH2, in contrast to a 3:1 ratio of NADH and FADH2 produced in the TCA cycle. FADH2 donates one pair of electrons to the electron transport chain but does not contribute to the proton pump. *Technical note: It is challenging to directly measure the efficiency of these macronutrients in terms of NAD+/ NADH produced. Total NAD+/NADH is not a valid measurement; only free NAD+/NADH is of value. Further, there are two pools of free NAD+/NADH in the cell: the cytosol (from glycolysis) and mitochondria (from fatty acid oxidation). It is very difficult to measure the content of these different pools.

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FIGURE 1.9  Acetyl CoA is the connection between the TCA cycle and ketone body formation. β-oxidation of fatty acids produces acetyl CoA, which can enter the TCA cycle, undergo oxidative phosphorylation, and produce ATP. Alternatively, acetyl CoA can be used to synthesize ketone bodies, a “super fuel”. Two acetyl CoA fuse to form acetoacetyl CoA. Acetoacetyl CoA combines with acetyl CoA to form HMG-CoA, which is converted into AcAc. AcAc can be converted into 2 molecules of acetone or 1 molecule of BHB. Ketone body oxidation converts BHB to AcAc (producing 1 NADH), and reduction converts AcAc back to BHB. These reactions are catalyzed by β-hydroxybutyrate dehydrogenase. Oxidative metabolism of the 4-carbon AcAc involves conversion to acetoacetyl CoA, followed by catabolism to 2 acetyl CoA molecules. Source: adapted from (6). *AcAc = acetoacetate; ATP = adenosine triphosphate; BHB = β-hydroxybutyrate (also known as 3-hydroxybutyrate); CoA = coenzyme A; HMG CoA = 3-hydroxy3-methylglutaryl coenzyme A; NADH = the reduced state of nicotinamide adenine dinucleotide; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

1.7 Dysfunction in Electron Transport System, Mitochondrial Function, and its Importance in Chronic Disease (Metabolism and Physiology, Translational Medicine, Introductory Level) Hungarian physician and biochemist Professor Albert SzentGyörgyi won the Nobel Prize in Physiology or Medicine in 1937 for his pioneering work in cellular respiration and antioxidant processes. He described the roles of electron transport dysfunction and free radicals in health and disease. His discovery of the potent antioxidant vitamin C marks a new era in antioxidant and metabolic homeostasis research. Later discoveries revealed that alterations in the balance between antioxidants and reactive oxygen species (ROS) in the mitochondrial electron transport chain underlie many metabolic diseases of aging, such as diabetes, obesity, cardiovascular disorders, neurodegenerative disorders, some cancers, and insulin resistance states of cancer. Mitochondria are key regulators of cellular energy metabolism and cellular redox homeostasis. Diet can directly modulate mitochondrial function, explaining why diet has such a huge impact on health (7, 8). For example, a diet chronically

high in fatty acids can promote insulin resistance, and a diet high in glucose can promote diabetes (especially hyperglycemia). Normally, fatty acids and glucose are converted into the high-energy electron transferring compounds NADH and FADH2, which donate their electrons to the mitochondrial electron transport system (ETS), eventually generating energy (ATP). However, high levels of fatty acids and glucose produce too much NADH and FADH2, which overwhelms the mitochondrial energy production system with a flood of electrons. These excess electrons in the ETS cause electron leakage, reverse electron transport, generation of pathogenic reactive oxygen species, oxygen wasting, and uncoupling from ATP production. In the following sections, we discuss the details of how high-energy electron transferring compounds such as NADH and FADH2 are involved in generating ATP in the ETS, and how disease states interfere with this essential process.

KEY POINTS Metabolism of different substrates influences the integrity and function of the mitochondrial electron transport system.

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Oxidative stress-induced mitochondrial dysfunction in the electron transport system is one of the common early features of many chronic age-related diseases. Mitochondrial dysfunction ultimately leads to the onset and progression of metabolic disorders, such as diabetes, obesity, cardiovascular disorders, and certain cancers. Understanding the mechanisms of mitochondrial dysfunction is the first step towards designing therapeutics for mitochondrial-related chronic diseases.

1.7.1 Biochemistry of the Electron Transport System (Biochemistry, Medium Difficulty) Peter Mitchell was awarded the Nobel Prize in Chemistry in 1978 for his 1961 “chemiosmotic” hypothesis. His hypothesis states that electrons flowing from reducing equivalents, such as NADH and FADH2, through the mitochondrial electron transport chain (a set of 5 sequential multiprotein complexes and two electron shuttles located in the inner mitochondrial membrane), generate electrochemical and pH gradients. Generation of these gradients results in changes in free energy, which drives the proton motive force—the ability to efflux protons (H+) across the inner mitochondrial membrane. The proton motive force is used to generate ATP at the final complex of the electron transport chain. Dysfunction of any part of the electron transport system results in reduced efficiency of electron transfer to oxygen, and thus less energy to power the cell. We discuss the details of the electron system components during healthy and pathological states in Chapter 9.

Basics of the Electron Transport Chain The terms “electron transport chain” (ETC) and “electron transport system” (ETS) are used interchangeably in the literature. However, some biochemists are of the opinion that the term ETC is misleading: ETC connotes a linear sequence of reactions in a single pathway, like links in a chain. In reality, electron transport is not always a linear process. It is well known that there are four major complexes in the ETC, starting with Complex I (NADH dehydrogenase). New evidence suggests that electrons from succinate or fatty acid oxidation enter the ETC at additional points: Complex II (succinate dehydrogenase [SDH]) and electron transferring flavoprotein (ETF). See Chapter 8, Section 8.3.2 for a detailed description of the ETS). Given these new insights on electron flow, the “term electron transport system” (ETS) or “branched electrontransport chain” would be better representations of the process. To briefly summarize the reactions that take place in the ETC: 1) Electrons enter at Complex I (or Complex II). 2) The mobile intermediate coenzyme Q (CoQ, or ubiquinone) carries electrons to Complex III

(ubiquinol–cytochrome c reductase). After CoQ unloads its electrons on Complex III, it becomes oxidized into ubiquinol. 3) Electrons from Complex III are transferred to another mobile intermediate, cytochrome c, which ultimately guides the flow of electrons to Complex IV (cytochrome c oxidase). 4) The process of transfer of electrons through these complexes creates a proton motive force that leads to the efflux of electrons from the mitochondrial matrix to the inner mitochondrial membrane space. This causes an electrochemical gradient across the inner mitochondrial membrane. The energy used to pump the protons are used to synthesize ATP via another complex called ATP synthase (F0·F1-ATPase) or Complex V. Complex V consists of a membranebound F0-ATPase and rotatory F1-ATPase. ATP synthase functions to couple proton flow to the conversion of ADP to ATP via a mechanism that is not completely understood. The ETS does not perfectly transfer all electrons down the chain. In fact, Complex II can also contribute to ROS generation during fatty acid metabolism (see Section 1.7.6) and reverse electron transport (see Section 1.7.7). High levels of H2O2 and OH in the mitochondria cause oxidative damage. Superoxide is not directly destructive, but indirectly generates hydroxyl radical when it reacts with copper or iron. Caloric excess can enhance ROS generation in mitochondria, exhausting the antioxidant defense system. ROS can damage mitochondrial components, especially the ETS and mitochondrial DNA. This damage causes mitochondrial dysfunction, leading to disrupted ATP production, among other crucial mitochondrial functions.

1.7.2 Biochemical Characteristics of Electron Transport Chain Dysfunction (Mechanism of ROS Generation Through ETC, Introductory Level) The exact structures and functions of the different complexes in the electron transport chain remain to be uncovered. However, despite these gaps in scientific knowledge, it is clear that any defect in the ETC or intertwined metabolic pathways will impair cellular metabolism. For example, NAD and FAD are required for many reactions in the TCA cycle, glycolysis, and fatty acid oxidation. Defects in the ETC will decrease the availability of NAD and FAD, which prompts pyruvate to convert to lactate, resulting in lactic acidosis. Further, defects in the ETC can lead to high levels of NADH, which interfere with fatty acid oxidation by inhibiting the dehydrogenase reaction that transforms NAD+ to NADH. Other types of ETS defects can produce reactive oxygen species (ROS). If these excess free radicals are not scavenged by antioxidant defense mechanisms, they can cause oxidative damage and mitochondrial dysfunction.

18 Mitochondria continuously metabolize oxygen and generate ROS (Figure 1.11 and Figure 1.12).* At low levels, ROS are important physiological signaling molecules, but at high levels, they are a signature feature of metabolic dysfunction and disease (9). Dysfunctional mitochondria that produce high levels of ROS contribute to the pathology of many chronic agerelated metabolic diseases. For example, hypermetabolism of certain nutrients or defects in the ETC lead to excessive ROS generation. These pathologically high levels of primary ROS interact with other compounds, converting into harmful “secondary” ROS. This overproduction of ROS damages the mitochondrial proteins/enzymes, and membranes. This damage interrupts ATP generation and other essential functions in mitochondria. Further, the interactions of the secondary ROS hydroxyl radical (•OH) with DNA molecules damages the nitrogenous bases (purine, pyrimidine, and deoxyribose backbone of DNA). These examples demonstrate that physiological levels of primary ROS are not necessarily dangerous, but that a careful balance between energy demand and supply is necessary to control excess mitochondrial ROS generation (10).

SIDEBAR 1.8: FORWARD AND REVERSE ELECTRON TRANSFER Principally, there are two modes of generation of mitochondrial ROS: forward electron transfer (FET) and reverse electron transfer (RET). The first mode, FET, such as occurs under hyperglycemic conditions, is mediated by a high ratio of NADH/NAD+, and consequently an overwhelmingly reduced state of flavin mononucleotide (FMN) in Complex I. FET generates ROS when function at Complex I is inhibited; damage to or mutation of Complex I, ischemia, loss of cytochrome c, or a low cellular demand for ATP all inhibit function of Complex I. This inhibition of function raises the NADH/NAD+ ratio, which increases ROS production. In contrast, RET generates ROS when electrons flow backwards from CoQH2 (ubiquinol) to Complex I. This causes NAD+ to be reduced to NADH, raising the NADH/ NAD+ ratio. ROS generation by RET can occur during oxidation of succinate or fatty acids. RET-dependent mROS generation with succinate accumulation is observed during heart ischemia. mROS production during RET can * Electron transfer through the ETC is tightly regulated; however, electron leakage causes 0.4 to 4% of oxygen consumed by mitochondria to be incompletely reduced, producing a small amount of ROS. Generation of primary ROS occurs when a single electron is transferred to molecular oxygen (O2), producing a highly reactive superoxide (•O2−) molecule. Superoxides are continuously produced due to the steady electron leak in the ETC. Physiological levels of these primary ROS are required for signaling and other cellular functions (9). Cells have enzymatic and non-enzymatic mechanisms to counter the effects of physiological levels of free radicals such as ROS. For example, cells can directly inhibit free radical generation or can scavenge the free radicals with antioxidants. At physiological pH, superoxide dismutase in the cytoplasm (SOD1) and mitochondrial matrix (SOD2) rapidly convert •O2− to peroxide (H2O2) before they can cause damage.

Metabolism and Medicine be attenuated by inhibiting Complex II (succinate dehydrogenase), improving cardiac health. A slight depolarization of the mitochondrial membrane potential can also abolish RET. Overall, conditions that lower the NADH/NAD+ ratio tend to suppress ROS production.

1.7.3 Clinical Perspective of Electron Transport System Dysfunction (Mitochondrial Dysfunction, Metabolic Homeostasis, and Onset of Chronic Diseases of Aging, Clinical Level) Clinical evidence suggests that mitochondrial dysfunction could be a fundamental cause of many age-related metabolic disorders. Mitochondria are primary sites for energy generation, transforming food into energy. Excess caloric intake of either carbohydrates or lipids has deleterious impacts on mitochondrial health. For example, hyperglycemia and excess fatty acid metabolism alter the generation of high-energy electron transferring compounds, such as NADH and FADH2. An altered ratio of these compounds often impairs the function of the electron transport chain, causing mitochondrial dysfunction (see Figure 1.10 and Figure 1.13). Excess NADH, generated under hyperglycemic conditions, hampers the function of Complex I in the ETC. Alternatively, high FADH2 generated from fatty acid oxidation can negatively influence the function of Complex II in the ETC. Excess FADH2 promotes ROS generation due to the excess flow of the electrons.

1.7.4 Influence of Glucose and Lipid Metabolism on the Function of the Electron Transport System (Biochemistry, Intermediate Level) The metabolism of different micronutrients have differential impacts on the function and efficiency of the electron transport system. For example, fatty acid oxidation is comparatively less efficient in terms of ATP generation as compared to glucose. The complete oxidation of glucose (through the coupling of cytosolic glycolysis and mitochondrial TCA cycle pathways) produces a higher ratio of NADH to FADH2 (~5:1) than does mitochondrial oxidation of fatty acids (via β-oxidation and TCA cycle pathways, with a NADH to FADH2 ratio of ~2:1). NADH and FADH2 donate high-energy electrons to the ETC. NADH donates electrons to Complex I, while FADH2 donates electrons to Complex II via an electron transferring flavo-protein (ETF). Complex II contributes much less to the proton motive force than Complex I, meaning that less ATP is produced per electron transferred from FADH2 to O2, as compared to the amount of ATP produced per electron transferred from NADH to O2. Understanding these processes explains why oxidative metabolism of glucose has greater metabolic efficiency than oxidative metabolism of fatty acids. However, fatty acid oxidation can compensate for this low-efficiency

Introduction to Metabolism

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FIGURE 1.10  Succinate dehydrogenase and electron transferring flavo-proteins (Acyl-CoA Dehydrogenase) contain FAD as a prosthetic group. FAD as a prosthetic group serves as an alternate way to tunnel electrons from the TCA cycle or from fatty acid oxidation. *ACAD = Acyl CoA dehydrogenase; ETF = electron transferring flavo-protein; ETF-QOR = electron transferring flavo-protein coenzyme Q oxidoreductase; FA-CoA = fatty-acylcoenzyme A; FAD = the oxidized form of flavin adenine dinucleotide; FADH2 = the reduced form of flavin adenine dinucleotide; Fe–S = iron sulfur cluster; Q = the oxidized form of coenzyme Q (also known as ubiquinone); QH2 = the reduced form of coenzyme Q (also known as ubiquinol); SDH (A, B, C, D) = succinate dehydrogenase (complex components A, B, C, D).

process by generating larger total amounts of NADH and FADH2 from each fat molecule than glucose oxidation can produce from each glucose molecule. Therefore, complete oxidation of a fatty acid produces much more ATP cumulatively than glucose. See Sidebar 1.7 and Chapter 9, Section 9.3 Linchpin Concepts Connecting Mitochondrial Dysfunction to Chronic Diseases of Aging for an expanded discussion. In the following sections, we introduce how these high-energy substrates modulate the function of the electron transport system. Complex II: a branching point that connects the TCA cycle and electron transport system. Complex II transfers electrons from succinate (or Fatty Acyl CoA) into the electron transport system. However, Complex II contributes very little to the proton motive force and is unable to pump the proton across the inner mitochondrial membrane. It is unclear from the literature as to why Complex II contributes very little to the proton motive force (see Sidebar 1.13 and 1.14). It is widely reported that electrons are transferred from FADH2 to Complex II. However, it is succinate (or fatty acyl-CoA in case of β oxidation) that donates its electrons to FAD. This event takes place at Complex II (or ETF), generating FADH2. FADH2 is a part of Complex II (see Figure 1.10). Complex II, also known as succinate dehydrogenase (SDH), is a TCA cycle enzyme. Free FADH2 has a negative redox potential, but does not contribute to the proton motive force at Complex II. FAD and FADH2 are prosthetic groups (cofactors that can covalently bind with enzymes such as SDH, Acyl CoA dehydrogenase, or ETF). In contrast, NAD+ and NADH are coenzymes (cofactors necessary for activity of certain oxido-reductases and dehydrogenases, such as Complex I and PDH). These differences in their

occurring forms result in FAD/FADH2 having more redox potential (positive) than NADH or succinate (see Sidebar 1.11). Therefore, NADH is a more efficient electron donor than FADH2 or succinate. It seems counter-intuitive that succinate electrons pass from Complex II then down the chain to oxygen, rather than starting at Complex I. The reason for this is because substrates with more-negative redox potential can easily donate electrons to substrates with positive redox potential. Therefore, succinate donates its electrons to the FAD/FADH2 redox pair (bound with SDH), which has a more-positive redox potential than succinate. The electrons are then transferred from FADH2 to coenzyme Q (CoQ). The redox potential difference for the electron transfer from succinate to coenzyme Q via Complex II is Succinate < FADH2 < FeS< CoQ. The redox potential is strong enough to transfer electrons from succinate to Complex II (FAD), but not strong enough to pump the proton as the net difference in the redox potential between succinate to CoQ is very small (see Sidebar 1.10 and 1.11). Complex II plays a crucial role in controlling glycolysis. Inhibition of Complex II causes succinate to accumulate in mitochondria. Succinate in the cytosol inhibits prolyl hydroxylase (PHD), causing disinhibition of HIF1α (hypoxia inducible factor 1 α). This produces a pseudohypoxic state in the cell that favors the Warburg effect. During the Warburg effect, the cell undergoes metabolic reprogramming, which promotes tumor formation. Inhibition of Complex II can also lead to the generation of superoxides, which can cause genomic instability and tumorigenesis. For these reasons, activation of Complex II is considered tumor suppressing.

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1.7.5 Redox Potential and Its Importance in Biochemical Reactions The redox potential drives the proton motive force. When the difference in redox potential is high, electron slippage is low. Fewer electrons slipping means less generation of mitochondrial reactive oxygen species. The electron transfer potential (oxidation-reduction potential, redox potential, E’0) is the tendency of a compound to either acquire electrons (be reduced, become more negative) or lose electrons (be oxidized, become more positive). Each compound has a specific redox potential. The more positive the reduction potential of a compound, the higher its affinity for electrons, meaning that the compound has a greater tendency to receive electrons from another compound (see Figure 1.6). The reduced forms of the NAD+/ NADH and FAD/FADH2 redox pairs mediate the transfer of 2 electrons from intermediates of fatty acid and glucose catabolism to the electron transport system. Barbara Corkey’s group has extensively explored the concept of redox in the biological system. She proposed that redox might have something to do with information sharing with respect to fuel availability (personal communication). This can be understood in the sense that “information” fundamentally is reduced entropy which, in a biological system, is equatable to organized complexity. Fuel availability is equatable to ATP production, largely derived from mitochondrial bioenergetics. This same process is responsible for generating physiological redox stress. The inextricable relationship of redox physiology and bioenergetics determines the state of health or disease. In the former case, organized complexity, or information, is robust, whereas in the latter case, these parameters are diminished. NADH/NAD+ is the master redox regulator, in addition to reflecting the state of energy of the cell (Sidebar 1.11). The likelihood of these spontaneous reduction-oxidation reactions (redox reactions) depends on the Gibbs free energy of the system (ΔG). Gibbs free energy is partially determined by the relative affinities of the two substrates for electrons. Gibbs free energy can also be indirectly affected by acid/ base dynamics. There is a significant overlap in the principles of redox reactions and acid/base dynamics. A key difference between redox and acid/base dynamics is that redox involves electron transfer, whereas acid/base dynamics involve proton transfer.

SIDEBAR 1.9: MEASURING REDOX INDICATORS DURING DISEASE STATES Poor diet, sugar substitutes, and food additives disturb intracellular redox, leading to the development and progression of acute and chronic diseases. However, it is challenging to directly measure intracellular redox disturbances because redox pairs do not typically permeate outside of cells. Fortunately, redox pairs equilibrate with cellular metabolites, and these metabolites can be measured as a proxy for redox pairs. The ratios of lactate to pyruvate reflect free cytosolic NAD+/NADH in muscle tissue. The ratio of β-hydroxybutyrate to acetoacetate reflects free NAD+/NADH in liver mitochondria. Measuring these metabolites can give insight on redox

Metabolism and Medicine disruption in diseases such as hypoxia, shock, sepsis, hyperinsulinemia/insulin resistance, obesity, and diabetes.

Source: adapted from (8). Energy generated from nutrients in food are stored in highenergy bonds of NADH or FADH2. These bonds are formed by transferring electrons from the substrates (catalysis of glucose/ fatty acid/ketone bodies) to NAD+ or FAD. Energy stored in the high energy bonds of NADH and FADH2 is used in the ETC to synthesize ATP. NADH serves as a strong electron donor because these high-energy bonds create a large change in the free energy, favoring electron transfer. Because NAD+ does not form a high-energy linkage, it is a weak electron acceptor. This explains why NAD+/NADH are often written as their redox pair, rather than individual molecules. High-energy electron transfer and redox potentials are of fundamental importance in mitochondrial oxidative phosphorylation. The electron transfer potential of NADH or FADH2 is ultimately converted into the phosphoryl transfer potential of ATP (i.e., conversion of ADP and inorganic phosphate [Pi] to ATP). The phosphoryl transfer potential (change in free energy) is given by ΔG°’ for the hydrolysis of the high energy phosphate compound (ATP → ADP + Pi). In the context of mitochondrial oxidative phosphorylation, the difference in electron transfer potential is critical for the spontaneous movement of electrons from a redox pair like NAD+/NADH with a low redox potential (a low affinity for electrons) to a redox pair like O2/H2O, which has a high redox potential (a high affinity for electrons). Electrons donated by NADH to Complex I in the ETC will eventually travel to O2. O2 has such a high affinity for electrons that O2 acts as an electron “sink”; therefore, electrons do not readily travel backwards from O2 to the lower-affinity Complex I (see Sidebar 1.8). Under certain conditions, reverse electron transfer can occur (see Section 1.7.8).

SIDEBAR 1.10: REDOX POTENTIAL BASICS Redox potential is a quantitative measure of the change in voltage when an atom or molecule gains an electron. Electrons are donated to molecules with higher redox potential. For example, in order for NADH to donate electrons to Complex I, NADH’s redox potential must be lower than that of Complex I. Similarly, in order for Complex 1

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Introduction to Metabolism to donate its electrons to the electron-carrying molecule coenzyme Q, Complex I must have a lower redox potential than coenzyme Q. Accordingly, the electron transport system is organized with a sequential increase in the redox potential from NADH to O2 (NADH < Complex I < coenzyme Q < Complex III < Complex IV < O2). Alteration in redox potential can alter the flow of electrons in the ETC, leading to slippage and ROS generation. The pair of oxidizing and reducing agents that are involved in a particular reaction is called a redox pair. The oxidizing member of the redox pair has the higher redox potential. The oxidizing member receives electrons from the reducing member of the redox pair, which has the lower redox potential. Here is a list of Standard Redox Potentials E'0 of Redox Pairs. NAD+/NADH FAD/FADH2 Fumarate/Succinate FAD/FADH2 (protein bound) Ubiquinone/Ubiquinol Cytochrome a3(oxidized)/Cytochrome a3 (reduced) ½ O2/H2O

−0.320 V −0.220 V +0.031 V +0.060 V +0.095 V +0.385 V +0.810 V

The balance of redox pairs maintains homeostasis. Redox pairs are correlated with Gibbs free energy, Nernst redox, and Henderson–Hasselbalch acid–base states. The ratio of the redox pair NAD+/NADH defines intracellular redox state, while NADP+/NADPH and GSH/GSSG are the major redox pairs involved in intracellular antioxidant systems.

SIDEBAR 1.11: WHY IS REDOX POTENTIAL MORE NEGATIVE FOR NAD+/NADH THAN FAD/FADH2? NADH, succinate, and coenzyme Q are soluble (free) components of the electron transport system. The standard reduction potential of free NAD+/NADH is –0.32 V. The difference in the redox potential for a 2-electron transfer from NADH (at Complex I) to coenzyme Q is: +0.06 V – (–0.32 V) = +0.38 V. FAD and FADH2 are prosthetic groups (cofactors that can covalently bind with enzymes such as succinate dehydrogenase, Acyl CoA dehydrogenase, or ETF). Free FAD/ FADH2 has a redox potential of –0.22 V, while enzymebound FAD/FADH2 has a redox potential ranging +0.003 to +0.009 V. The difference in the redox potential for a two-electron transfer from succinate (bound FADH2) to coenzyme Q is: +0.06 V – (+0.03 V) = +0.03 V). Both NADH and FADH2 donate two electrons to the ETC, but these calculations show that NADH has more negative redox potential than FADH2. Negative redox potential of NADH represents greater ability to transfer electrons horizontally (downstream, ultimately to oxygen) and greater ability to transfer protons vertically (proton motive force).

1.7.6 Clinical Application and Examples of Redox State to Insulin Resistance and Type 2 Diabetes The notion of the state of redox is critical basic knowledge to understand the health or disease state of any biological system. Importantly, the inextricably parallel processes of redox, free energy (usable for biological purposes), and acid-base are revealed by the fantastically similar Nernst, Gibbs free energy, and Henderson–Hasselbalch equations. It should be noted that inflammation is a stress on a biological system. It follows that there is a fundamental bidirectional and self-amplifying loop between NFκB, the central transcription factor for inflammatory cytokine production, and ROS, a parameter of redox homeostasis. If abnormal (ROS levels too high, redox state too low) redox stress occurs. It is therefore not surprising that in recent years groundbreaking scientific research has linked disturbed redox homeostasis to unrecognized disease-causing exposures, as well as improving redox as the mechanism for the long-sought understanding of the therapeutic effect of drugs. Indeed, biological tissues and organ systems do not function in silos, but rather are orchestrated in a common soil of which redox is a basic and fundamental parameter. This allows the astonishing and beautiful complexity that is time synchronized within and across tissues and organ systems with organizational perfection in states of optimal health. In Volume 1’s Chapter 5 we describe our model of the Physiological Fitness Landscape (PFL). Folded into this model is the late Bruce McEwen’s notion of stress allostasis and allostatic overload. The series of dynamical peaks and troughs along this topological terrain are unstable and metastable phase transitions, respectively. As the altitude of this portrait falls over time, physiological/metabolic “fitness” or “free energy” declines. In this model, it represents a threshold of criticality, one that is not reversible. A phase transition from healthy allostasis to allostatic overload may be in the form of a disease state, or an acceleration of biological aging that represents the vulnerability state for chronic diseases of aging. Disruptions in redox disturb the molecular fidelity of vital organ systems to the extent that compensatory systems become exhausted. The bioenergetic capacity of these cells is inextricably entangled with impaired redox to the point that normal function is not possible. Thus, the “fitness” or “free energy” of the PFL model of an individual in the youthful state of health displays extraordinary organized complexity within narrow physiological ranges of redox, Gibbs free energy, and acid-base that are far from equilibrium. Over the decades and years of a lifespan, declines in altitude of “fitness” or “free energy” parallels the aging process as it approaches and ultimately reaches thermodynamic equilibrium, a phase transition from a biological to an inanimate system. Redox homeostasis can give hints about health and disease. When the redox state is reduced, there is an elevated ratio of NADH/NAD+ and elevated reactive oxygen species (ROS) (11). ROS have several beneficial roles at physiological levels, and cells have built-in compensatory mechanisms (scavenging systems or antioxidant defense) in place that protect against the detrimental effects of ROS. However, when ROS are elevated

22 beyond a certain level (pathological ROS), they promote production of inflammatory cytokines. Inflammatory cytokines and ROS create a bidirectional self-amplifying loop, further unbalancing redox homeostasis. Pathologically elevated ROS levels exhaust the cell’s scavenging capacity, and the cell’s bioenergetic capacity becomes impaired. Similarly, an elevated ratio of NADH/NAD+ can cause redox stress. Redox stress modulates liver functions and bioenergetics. One of the liver’s roles is to produce glucose through the process of gluconeogenesis. Gluconeogenesis is regulated by various mechanisms, such as insulin. Insulin inhibits transcription of key gluconeogenic enzymes and reduces the availability of gluconeogenesis substrate precursors. Redox state is the most fundamental regulator of hepatic gluconeogenesis. In the above situation, redox stress caused by an elevated ratio of NADH/NAD+ is beneficial to individuals with hyperglycemia. However, redox stress can also have detrimental effects in type 2 diabetics. For example, hepatic steatosis (fatty liver disease, common in insulin-resistant individuals) is often accompanied by redox stress. Hepatic steatosis is also associated with impaired mitochondrial function: proton leakage from the electron transport system and reduced electrochemical gradient (12). The altered redox that occurs during hepatic steatosis could theoretically promote pancreatic oversecretion of insulin, independent of glucose consumption (8, 11, 13). The result of redox stress is lower efficiency of energy production and hyperinsulinemia (11, 14). These examples illustrate that redox pair ratios have a very narrow window of therapeutic effects, which can quickly become pathological. Since the 1970s, some 80,000+ processing chemicals have been introduced to food and the environment. In her 2011 Banting Award lecture, Barbara Corkey proposed that food additives disturb redox, promoting metabolic disease. Food additives (artificial colorings and flavorings, emulsifiers, and preservatives), bisphenol A (found in plastic food containers and bottles), and excess iron (commonly taken as a supplement) are absorbed into the portal venous system, where they circulate to the liver. In the liver, these agents promote the generation of ROS, thus altering redox balance. One of the redox ratios that becomes disturbed is BHB/acetoacetate. Acetoacetate metabolites enter the bloodstream, travel throughout the body, and influence the redox states in other tissues. The effects of acetoacetate in skeletal muscle cause lactate/pyruvate metabolites to enter the circulation. The increase of acetoacetate metabolites, lactate, and pyruvate in the circulation creates oxidative stress on tissues throughout the body. While a sugar-free sweetener sounds like a perfect option for someone trying to cut down on sugar intake, the redox stress that artificial sweeteners cause outweighs the benefits. Corkey and colleagues demonstrated that various artificial sweeteners induce redox stress in vitro, including saccharin (Sweet’N Low), sucralose (Splenda), and aspartame (NutraSweet/Equal). Moreover, Corkey also found that when artificial sweeteners are incubated with differentiating adipocytes in vitro, the combination promotes the generation of ROS and more-rapid lipid accumulation within the adipocytes. Antioxidant agents were effective at abrogating the deleterious effects of artificial sweeteners in two cell lines (15).

Metabolism and Medicine

FIGURE 1.11  Mitochondria interact with nucleotides. There is a hierarchy of redox pairs that are central to the redox code (16). These include most fundamentally the “master” redox regulator NADH/NAD+ system followed by the NADPH/NADP+ system, followed by the thiol/disulfide systems. The latter include the reduced and oxidized pairs of glutathione, thioredoxin and peroxiredoxin. Source: adapted from (11). *ATP = adenosine triphosphate; FFA = free fatty acids; GPX = glutathione peroxidase; GR = glutathione reductase; GSH = glutathione; GSSG = oxidized glutathione; H+ = hydrogen proton; H2O2 = peroxide; H2O = water; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; NADP+ = nicotinamide adenine dinucleotide phosphate; NADPH = the reduced form of nicotinamide adenine dinucleotide phosphate; NNT = nicotinamide nucleotide transhydrogenase; O2– = superoxide anion; Prxox = oxidized form of peroxiredoxin; Prxred = reduced form of peroxiredoxin; SOD = superoxide dismutase; Trxox = oxidized form of thioredoxin; Trxred = reduced form of thioredoxin.

In recent years, groundbreaking scientific research has strengthened the connection between disturbed redox homeostasis and disease states (8, 11, 13). Rebalancing the redox state might be the future of medicine. Keeping redox pairs in their optimal therapeutic windows has the potential to control the onset or progression of metabolic diseases (Figure 1.11 and Figure 1.12). Redox stress can be kept in check with specific diets, fasting/calorie restriction, and exercise, in addition to some drugs mimicking fasting/calorie restrictions. Harkening back to Corkey’s work in vitro, it would be interesting to see if antioxidants could buffer redox stress caused by food additives in patients.

SIDEBAR 1.12: PHYSIOLOGICAL ROLES OF REDOX PAIRS The bioenergetic functions of the NAD+ system (and FADH2/FAD) are discussed in neighboring sections of this Chapter. However, Corkey makes the important distinction that all of these central redox pairs are localized to subcellular regions that fit their respective and intertwined physiological roles in bioenergetics and redox homeostasis. Additionally, the NADH/NAD+ and the NADPH/ NADP+ systems have pleiotropic functions, bioenergetic and redox in the former case, and redox and biosynthetic

Introduction to Metabolism

FIGURE 1.12  Liver and muscle redox can be measured indirectly with blood samples. The ratios of metabolites correspond to redox in the target tissues. Source: adapted from (11). *A = acetoacetate; GSH = glutathione; GSSG = oxidized glutathione; L = lactate; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; NADP+ = nicotinamide adenine dinucleotide phosphate; NADPH = the reduced form of nicotinamide adenine dinucleotide phosphate; P = pyruvate; SH = reduced form of thiols; SS = oxidized form of thiols.

(particularly de novo lipid synthesis) in the latter case. While these various redox systems are spatially confined and cannot be directly measured, the balance of the systems equilibrate with ones that are free to move from intracellular to the blood, subsequently equilibrating and potentially altering the redox balance in other tissues. These circulating redox pairs are referred to as “redox indicators”, the major ones being lactate/pyruvate and β-hydroxybutyrate (BHB)/acetoacetate, originating from cell cytoplasm and mitochondria, respectively. Skeletal muscle, due to its sheer mass, is the major site of origin for lactate/pyruvate whereas BHB/acetoacetate is derived largely from hepatocytes, a highly metabolically active site of ketogenesis.

23 nutrient oversupply, reducing equivalents such as NADH and FADH2 are elevated. This promotes an overflow of electrons through the electron transport system, causing hyperpolarization of mitochondrial membrane potential. This increased electrochemical gradient causes uncoupling from ADP phosphorylation, stopping ATP production. This may increase electron pressure at ETC Complex I and III, further increasing electron leak. A high NADH/NAD+ ratio under hyperglycemic conditions exhausts the capacity of electron transfer at Complex I, resulting in leakage of electrons at Complex I and III, producing ROS. Superoxide can also be formed as a result of this high influx of electrons. Complex II contributes less to the redox potential difference (Sidebar 1.13), which makes Complex II less susceptible to ROS generation. However, vigorous oxidation of lipids can lead to excess-FADH2-mediated ROS generation at Complex II. Additionally, high FADH2 generated from fatty acid oxidation can negatively influence the function of Complex II (Figure 1.10). Dietary excess can also initiate an inflammatory cascade. Inflammation is bidirectionally linked to oxidative stress with feedforward self-amplifying behavior. The inflammatory response initiates a cascade of redox stress by generating ROS. Viral and microbial pathogens can provoke inflammatory responses. Hydrogen peroxide (H2O2) can permeate across lipid membranes (Figure 1.13). Oxidative modification of hydrogen peroxide damages mitochondrial function. Similarly, poor quality diets with additives are toxic to redox. Both dietary excess and additives cause cascades of inflammation, which

1.7.7 Contributions of Macronutrients to Redox Potential, Proton Motive Force, and Oxidative Stress Balance of macronutrients in the diet, the timing of eating, as well as circulating levels of nutrients generated from the body’s stores are important for metabolic health. Metabolism of different macronutrients has different impacts on the function and efficiency of the electron transport system. Electron transport through the ETC is directly coupled to proton (H+) translocation across the inner mitochondrial membrane. This process is tightly controlled by the redox potential difference between all the electron transport complexes. The redox potential also affects the magnitude of the proton motive force (PMF). The greater the difference in redox potential, the less frequent electron slippage. Fewer slipped electrons translate to fewer mitochondrial reactive oxygen species generated. Electrons extracted from different nutrients feed into the mitochondrial ETC. This influx of electrons modulates the PMF and the function of the electron transport system. During

FIGURE 1.13  Production of superoxides and ROS in the ETC. Excess energy substrate (hyperglycemia) induces the production of superoxides by the mitochondrial electron transport chain (ETC), leading to redox damage and ultimately mitochondrial dysfunction. In cells with high levels of glucose, a critical threshold in the voltage gradient across the mitochondrial membrane is reached, which blocks the transfer of electrons along the protein complexes of the ETC. These backed up electrons interact with coenzyme Q to form superoxides. Source: adapted from (17). *Cyt c = cytochrome c; e- = electron; H+ = hydrogen proton; H2O = water; Mn-SOD = manganese superoxide dismutase; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; O2 = oxygen; O2˙- = superoxide anion; Q˙ = coenzyme Q semiquinone intermediate.

24 induce redox stress. Inflammation and disturbed redox can both independently interrupt insulin signaling and degrade mitochondrial structure and function. This creates another feedforward self-amplifying loop of insulin resistance and mitochondrial dysfunction.

SIDEBAR 1.13: WHY IS ELECTRON FLOW WEAK AT COMPLEX II? Succinate donates electrons to bound FAD, producing FADH2. The difference in redox potential between bound succinate/FADH2 and coenzyme Q is very small and contributes minimally to the proton motive force. Only ~1.5 molecules of ATP are generated per two electrons transferred from succinate/FADH2 to oxygen. Hypothetically, if electrons were transferred from free FADH2 to coenzyme Q, the difference in redox potential would be greater, producing enough energy to pump the proton. However, succinate has higher redox potential than free FAD, so succinate would not be able to donate its electron to FAD, meaning that FADH2 would not be synthesized. Importantly, unlike NAD+/NADH redox pair, FAD/ FADH2 must always remain in bound form so as to prevent the interaction with oxidizing/reducing agents in the cytosol. This way dioxygen won’t directly react with enzyme bound FAD/FADH2 in the cytoplasm).

1.7.8 Elevated Fatty Acid Metabolism and Its Relevance in Aging and Chronic Diseases Fatty acid oxidation (FAO) tunnels more electrons into the ETC than any other macronutrient even though fatty acid oxidation is less efficient at generating ATP than glucose oxidation or any other macronutrients. However, because of an enormous amount of electrons flow through the electron transport chain, FAO can hamper the electron transport efficiency that leads to excess ROS generation. Fatty acid-induced generation of mitochondrial superoxide and other ROS is pathologically linked to mitochondrial dysfunction and insulin resistance in insulin dependent tissues. Consequently, glucose elevation with compensatory hyperinsulinemia may ensue. It has been proposed that the β-oxidation of fatty acids may result in ROS generation at a different site in the mitochondrial matrix, different from the ROS generation site at Complex III. Alternatively, it has been suggested that ROS production during fatty acid oxidation comes from electron transferring flavoprotein which accepts electrons from dehydrogenases (Acyl CoA dehydrogenase-ACAD) and transfers them to the coenzyme Q which is catalyzed by another enzyme called ETF-ubiquinone oxidoreductase (ETF-QO) present in the matrix side of the inner mitochondrial membrane (Figure 1.10 and Figure 1.13). As shown in Figure 1.10, ETF-QO covalently binds with flavin (FAD) and 4Fe-4S cluster (similar to complex II). ETF-QO functions as a convergence point for electrons coming from 9 flavoprotein acylCoA dehydrogenases.

Metabolism and Medicine One of the main problems with excess fatty acid oxidation is a massive influx of electrons to coenzyme Q. These excess electrons reduce coenzyme Q (ubiquinone) to CoQH2 (ubiquinol). This results in loss of redox potential and reversal of electron flow from ubiquinol to Complex I. Reverse electron transport (RET) collapses the PMF and associated proton electrochemical gradient, impairing downstream biosynthesis of ATP (Sidebar 1.14). Free electrons at Complexes I and II combine with O2 to produce reactive superoxide species with the potential to cause oxidative stress (Figure 1.14) (18).

SIDEBAR 1.14: HOW DOES REVERSE ELECTRON TRANSPORT HAPPEN? Reverse electron flow is the transfer of electrons through the ETC via reverse redox reactions. This usually requires the input of a substantial amount of energy, such as caloric excess. This backflow negates the proton electrochemical gradient, preventing ATP formation at Complex IV. Further, electron backflow leads to electron slippage and ROS generation. Excess fatty acid oxidation renders coenzyme Q (ubiquinone) into a reduced state (ubiquinol, QH2). Ubiquinol has a greater electronegative voltage than ubiquinone, causing electrons carried by ubiquinol to flow backwards to Complex II. When the redox potential at Complex II is decreased (becomes more electronegative than Complex I), electrons flow back to Complex I (Figure 1.10). If reverse electron transport persists, it can exhaust the cell's antioxidant capacity, leading to mitochondrial dysfunction and many age-related diseases (Sidebar 1.15).

SIDEBAR 1.15: ANTIOXIDANT SYSTEM AND CELLULAR REDOX STATE Redox state is the balance of compounds (such as GSH/ GSSG, NAD+/NADH, and NADP+/NADPH) that can donate or accept electrons. Antioxidant systems maintain the balance of redox and fight oxidative stress by providing electrons. Harmful oxidizing agents such hydrogen peroxide (H2O2) and superoxides (O2) can be neutralized by adding electrons. However, when redox disturbance becomes severe enough, it overwhelms antioxidant capacity. This is essentially allostatic overload: the threshold when metabolic stress causes disease.

Oxidative stress and redox homeostasis is maintained by coordinated systems of antioxidants. The embedded figure highlights the major cell antioxidant systems.

Introduction to Metabolism

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FIGURE 1.14  Interrelationship between fatty acid oxidation, mitochondrial dysfunction, and insulin resistance. The balance between uptake and utilization of lipids (fatty acids) is perturbed under the condition of insulin resistance. This causes oxidative stress and mitochondrial dysfunction in skeletal and cardiac myocytes, hepatocytes, and large vessel endothelial cells (coronary arteries). Catabolism of lipids generates intermediates, such as DAG and ceramide, which inhibit insulin signaling. β-oxidation of fatty acids reduces the NADH/FADH2 ratio from 5:1 to 2:1. This causes enhanced electron flow in the electron transport system, mediated by increased electron transferring FADH2 redox equivalents from acyl CoA dehydrogenase to ETF and to CoQ. This causes the CoQ pool to be over-reduced, resulting in a change in membrane redox potential to lower than that of Complex I, hence favoring RET. During RET, electrons leak at either ETF or ETFQO, as well as Complex I and III, generating a significant amount of superoxide. (Solid lines represent greater flux than the dotted lines.) *Akt = protein kinase B; AS160 = Akt substrate of 160 kDa; CoQ = coenzyme Q; CPT 1 = carnitine palmitoyltransferase 1; CPT 2 = carnitine palmitoyltransferase 2; DAG = diacylglycerol; e- = electron; ETC = electron transport chain; ETF = electron transferring flavoprotein, ETFQO = electron transferring flavoprotein coenzyme Q dehydrogenase; FA-CoA = Fatty-acyl-coenzyme A; FAD = the oxidized form of flavin adenine dinucleotide; FADH2 = the reduced form of flavin adenine dinucleotide; FeS = iron sulfur cluster; GLUT4 = glucose transporter type 4; H+ = hydrogen proton; H2O = water; IRS-1 = insulin receptor substrate 1; O2 = oxygen; O2˙ = superoxide anion; O2 = peroxide; NAD = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; Q = the oxidized form of coenzyme Q (also known as ubiquinone); QH0 = semiubiquinone; QH2 = the reduced form of coenzyme Q (also known as ubiquinol); RET = reverse electron transport; ROS = reactive oxygen species; TAG = triglyceride; TCA = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

1.7.9 Targeting the Electron Transport System for the Treatments of Metabolic Disease 1.7.9.1 Improving Mitochondrial Metabolism (Biochemistry, Introductory Level) Degradation of different micronutrients can influence mitochondrial health, affecting ATP generation. For example, NADH is used by the enzyme nicotinamide nucleotide transhydrogenase (NNT) to form NADPH, which is required for maintaining the optimal cellular antioxidant response. This makes the NAD+/NADH redox ratio crucial for healthy mitochondrial function. It is, therefore, recommended to maintain a high intracellular NAD+/NADH ratio, as well as a reduced FADH2/NADH ratio. This can be achieved by diet and exercise (Figure 1.15). Keeping the balance between macronutrients such as carbohydrates, monounsaturated fats, and proteins

(and perhaps ketones bodies via intermittent/prolonged fasting strategies or ketone body supplementation) can keep mitochondria healthy, produce fewer ROS, and slow the progression of age-related disorders. Lifestyle modification, involving exercise and diet, decreases the risk of developing type 2 diabetes. Physical activity improves glucose tolerance by three mechanisms. First, it regenerates the cellular supply of NAD+, which is required for cells to metabolize nutrients and generate NADH. Second, physical activity also activates sirtuin 1 (SIRT1) and PGC1α, which reprograms mitochondrial metabolism and biogenesis (19). Third, physical exercise promotes AMP-activated protein kinase (AMPK)-dependent oxidation of glucose and fatty acids via enhanced oxygen consumption. Oxygen consumption is enhanced due to an increase in the ratio of cellular AMP/ATP (especially during aerobic exercise). Maintaining a

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FIGURE 1.15  Impact of lifestyle on mitochondria. Healthy mitochondria have a high mitochondrial membrane potential, oxygen consumption rate, and ATP production rate. Chronic metabolic diseases such as obesity and diabetes impair mitochondria function and structure, reducing mitochondrial membrane potential, oxygen consumption rate, and ATP production rate. Caloric restriction acts as an energy stress challenge in these dysfunctional mitochondria, reprogramming AMP/ATP ratios. AMP-activated protein kinase (AMPK) responds to these changes in ratios by phosphorylating PGC1α. Exercise also acts as an energy–stress challenge in these dysfunctional mitochondria, reprogramming NAD+/NADH ratios. NAD-dependent deacetylase sirtuin-1 (SIRT1) responds to the changes in NAD+/NADH ratios by deacetylating PGC1α. Together, these modifications of PGC1α stimulate mitochondria remodeling, which ultimately increases efficiency of ATP production. Source: adapted from (20). *AMPK = AMP-activated protein kinase; ATP = adenosine triphosphate; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; PGC1α = peroxisome proliferator-activated receptor gamma coactivator 1α, SIRT1 = NAD-dependent deacetylase sirtuin-1.

healthy balance of complex carbohydrates with micronutrient vitamins and minerals supports the biosynthesis and function of the ETC components. A balance of dietary carbohydrates and fat substrates can also optimize the combustion of macronutrient fuel, producing the greatest efficiency of electron transfer along the respiratory chain, yielding maximal ATP while wasting minimal oxygen (in the form of biologically harmful reactive oxygen species). Recent research suggests that some specialized diets, such as the Mediterranean diet as well as the ketogenic diet, have health benefits. The soluble fiber components of the Mediterranean diet such as legumes, fresh berries, fruits, vegetables, nuts, and seeds have a powerful effect on promoting a healthy diverse symbiotic intestinal microbial composition (see Chapter 6 for discussions on the microbiome). This is undoubtedly at least a major factor in the 75% of all-cause mortality reduction found with this diet. The decreased caloric intake of the Mediterranean diet is also a contributing factor to decreased mortality. Caloric restriction or long-term fasting can also be useful in reducing the FADH2/NADH ratio, helping maintain a high level of NAD+, ultimately improving mitochondrial health. Prolonged fasting (early starvation phase beginning about 28 to 36 hours or longer) or ketogenic diets force rapid fatty acid oxidation in the liver to generate an ample amount of ketone bodies. These ketone bodies (especially β-hydroxybutyrate) serve as spare fuel for glucose (21, 22). Ketone bodies are considered a “super fuel” and are most efficient in terms of ATP production (high phosphate/oxygen ratio [P/O]). This makes the ketogenic diet important in the clinic. The notion of ketone bodies as a “super fuel” will be further discussed in Section 1.8.1.

1.7.9.2 Manipulation of Mitochondrial Redox System for Therapeutic Implications: Pharmacologic Intervention Redox potential in the electron transport system is foundational to human health and disease. Early work uncoupling

mitochondrial function showed potential therapeutic utility. One uncoupling agent from the 1930s, dinitrophenol, was able to reduce obesity, but caused liver failure. Recent studies on uncoupling oxidative phosphorylation suggest that mild to moderate uncoupling can control intramitochondrial ROS levels. Mild uncoupling activity of cationic rhodamine derivatives improved mitochondrial function. Specific redox agents with mild redox potential (−0.1 V to 0.1 V) could theoretically be used to manipulate mitochondrial redox for certain disorders. Mechanistically, these agents can improve mitochondrial function since they can freely donate or accept electrons without altering the redox status of ETS redox centers. These mild redox agents could elevate metabolic activity and reduce ROS production. These redox agents could modify the biochemical activity of certain mitochondrial components, altering the expression of nuclear and mitochondrial genes, promoting mitochondrial biogenesis. Coenzyme Q supplementation might also improve mitochondrial function. The antioxidant properties of coenzyme Q make it a good candidate for the prevention and management of inflammation, oxidative free radical stress, and age-related disorders (neurodegenerative diseases, cancers, cardiovascular disease, inflammatory liver disease, and diabetes). Coenzyme Q is currently used in the prevention and treatment of statin cholesterol therapy-induced myopathy. Pharmacological research on the mitochondrial redox system would lead to valuable medications for the treatment of metabolic disease.

1.7.10 Conclusion Mitochondrial dysfunction is the root cause of the transition to an unhealthy metabolic state, putting the body on a trajectory to premature metabolic and chronic diseases of aging. The self-escalating process of redox stress promotes a progressive deterioration of mitochondrial structure and function. While low levels of reactive species protect against inflammation, high levels induce pro-inflammatory cytokines, such

Introduction to Metabolism as NFkB. Redox and inflammatory stress are bidirectionally self-amplifying. Inflammation causes uncoupling from the proton electrochemical gradient of ATP production, which impairs bioenergetics. Impaired bioenergetics contributes to heat loss, increased entropy, and biological aging. The final stage of bioenergetic decline involves compensation of classical oxidative phosphorylation mode of ATP production by the less energetically efficient glycolytic pathway, which produces less ATP per molecule of glucose. The interwoven relationship of insulin resistance and mitochondrial dysfunction causes disease states including obesity, sarcopenia, hypertension, dyslipidemia, glucose intolerance, type 2 diabetes, cardiovascular disease, and dementias. In particular, advancing deterioration of mitochondrial function is accompanied by increasing inflammation, entropy production rate, and redox stress that promotes mutagenesis and increasing vulnerability to carcinogenesis. A healthy lifestyle that includes physical activity could help improve metabolism, preventing the onset and progression of age-related metabolic disorders such as diabetes, obesity, cognitive decline, Alzheimer’s disease, heart and vascular disease, and cancer. Potential future therapies for age-related metabolic diseases should include restoration of mitochondrial function.

1.8 Ketone Bodies in Metabolism in Health and Disease (Metabolism and Physiology, Ketones, Introductory Level) During prolonged fasting or while following certain diets (ketogenic diet), stored fatty acids (derived from the lipolysis of lipids in white adipose tissue) undergo oxidation in the liver to produce Acetyl CoA. Instead of metabolizing through mitochondria, Acetyl CoA is converted to ketone species such as acetoacetate, β-hydroxybutyrate, and acetone (Figure 1.16). These ketone bodies (especially β-hydroxybutyrate) are used as a spare fuel by the brain, muscle, heart, and other tissues (21, 23). As compared to fatty acid or glucose oxidation, ketone bodies are energetically more efficient: they yield more ATP per pair of electrons transferred to each molecule of oxygen (high phosphate to oxygen ratio) through the ETC, with fewer electrons leaked and less ROS generation.

SIDEBAR 1.16: THE KETOGENIC PATHWAY PARALLELS THE CHOLESTEROL SYNTHETIC PATHWAY The main distinction between the pathways is location. Ketones are produced in mitochondria, while cholesterol biosynthesis occurs in the cytosol. The precursor to ketone body production is acetoacetyl CoA. This can combine with yet another acetyl CoA to produce 3-hydroxy-3-methylglutaryl CoA (HMG CoA), promoted by mitochondrial HMG CoA synthase (the major regulatory step in ketogenesis). An acetyl CoA group may then

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FIGURE 1.16  A ketogenic diet leads to an increased rate of fatty acid oxidation (FAO) in the liver, creating an abundance of acetyl-CoA. Under the conditions of this diet, acetyl-CoA is diverted from being utilized by the TCA cycle and is instead used in the process of ketogenesis to generate ketone bodies. Ketone bodies enter the bloodstream and can be utilized for ATP production in vital tissues such as the brain and heart. *ATP = adenosine triphosphate; CoA = coenzyme A; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

be cleaved off this molecule by mitochondrial CoA lyase, ultimately converting it back to acetoacetate. By comparison, the cholesterol pathway in the cytosol begins with the convergence of two acetyl CoA groups to form acetoacetyl CoA, followed by merging with another acetyl CoA group, catalyzed by cytoplasmic HMG CoA synthase, forming HMG CoA. During cholesterol synthesis, the ratelimiting step is HMG CoA reductase. The primary hormonal regulators of ketogenesis are insulin and glucagon. Insulin inhibits ketogenesis, whereas glucagon promotes ketogenesis. The rate-limiting step for ketogenesis is HMG-CoA synthase. Another key hormone-regulated enzyme is hormone-sensitive lipase (HSL). When insulin levels or activity is low, activated HSL stimulates the release of triglycerides from adipose tissue. Similarly, insulin-stimulated acetyl CoA carboxylase (ACC) is released, mediating lipogenesis. The ratio of reducing equivalents (NADH/FADH2) is a key determinant of the efficiency of energy generation. The NADH/FADH2 ratio is highest for ketone bodies (~4), followed by glucose (~3), then fatty acids (~2). An example of the efficiency of ketone bodies as a fuel source can be observed in the heart: oxidation of ketone bodies increases the hydraulic efficiency of the heart 28% more than glucose. Hepatic amino acid catabolism can be used to synthesize glucose, urea, and ADP. This ADP can then be used to fuel processes to degrade more amino acids. Because hepatic catabolism has high oxygen demands, it prevents adequate oxygen for fatty acid oxidation. Theoretically, if the liver could completely oxidize long chain fatty acids, the oxygen demands of the liver would more than double, and such reactions would produce high amounts of heat. Instead, the liver uses ketogenesis to generate energy.

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1.8.1 Ketone Bodies are “Super Fuels” and Electron Scavengers Ketone bodies are a super fuel that potentiates the proton electrochemical gradient across the inner mitochondrial membrane. This in turn drives a higher production of ATP per unit of oxygen consumed, which defines a higher metabolic efficiency. A compromise in the ratio of these biochemical parameters is equal to metabolic and chronic disease. Cardinal features of compromised ATP production per unit oxygen consumed include mitochondrial dysfunction and insulin resistance. The concepts of metabolism and metabolic pathways are further discussed in Chapter 8. Ketone bodies have antioxidant effects in mitochondria and areas other than mitochondria (23). Ketone body metabolism lowers NADP/NADPH ratios in the cytoplasm. This ketone body effect is driven by the ratio of the redox couple NAD/ NADH in the mitochondria. NADPH maintains redox balance by keeping glutathione in a reduced antioxidant state. The ratios of NADP/NADPH and oxidized glutathione/free glutathione balance antioxidant stress (Sidebar 1.15) (24).

SIDEBAR 1.17: β-HYDROXYBUTYRATE MECHANISM OF ACTION The ketone β-hydroxybutyrate acts as a histone deacetylase class 1 and 2a inhibitor (25). This disinhibits FOXO3 (forkhead box transcription factors class O3) transcription. FOXO3 promotes the transcription of antioxidants, such as catalase, superoxide dismutase 2, and glutathione peroxidase. FOXO3 also orchestrates redox stress resistance programs, including cell and DNA repair, autophagy, apoptosis when cell redox damage is severe, and deacetylase activity of sirtuin1 and sirtuin 3. Sirtuin 1 and sirtuin 3 in turn induce FOXO3-mediated redox cell stress programs. β-hydroxybutyrate can also act as a direct antioxidant scavenger of hydroxyl radicals (OH•), which would be beneficial during reperfusion. However, antioxidant vitamin supplements serve no physiological purpose in the absence of nutritional insufficiency; Linus Pauling’s unverified claims of intravenous vitamin C as a cure-all were faulty. It is incredible that ketones can suppress oxidative stress through direct antioxidant actions, inhibition of mitochondrial formation of ROS, and non-mitochondrial upregulation of programs combating redox cell stress.

1.8.2 Role of Ketone Bodies in Starvation (Molecular Biology, Intermediate Level) Ketone bodies are involved in all three branches of metabolic homeostasis: energy, redox, and acid/base (23). Ketones compensate for low glucose availability and the accompanying relative insulinopenia. Insulin promotes glucose uptake into the cytoplasm of muscle cells and stimulates the enzyme complex pyruvate dehydrogenase (PDC). PDC pairs glycolysis with mitochondrial oxidative metabolism. The oxidative combustion of ketone bodies does not require insulin to gain access to the energy-producing machinery of the mitochondria.

Metabolism and Medicine Additionally, ketone body bioenergetic efficiency is superior to that of glucose (with insulin) because of the antioxidant effects of ketone bodies (23). Depending on the stage of starvation, ketogenesis is most common in the brain, skeletal muscle, and cardiac muscle (Figure 1.16) (22, 26). Insulin secretion is dependent on glucose. When glucose levels are in the lower range of normal (70–90 mg/dL), insulin secretion is suppressed. The initial phase of starvation spans from ~16–48 hours of fasting. Hepatic glycogenolysis (the breakdown of glycogen) occurs during the early phase of starvation. However, glycogenolysis is already on the marked decline even at the onset of this early phase of starvation (26). Tissue-dependent use of these fuels increases when glucose is low, or when the signaling effects of insulin are low. As glycogen stores near depletion, gluconeogenesis becomes the predominant process for the liver to sustain euglycemia, using the body’s muscle and fat stores as a fuel supply. Precursor substrates for gluconeogenesis include lactate, glycerol, and amino acids. Lactate is the glycolytic end-product derived from glucose metabolism in cell types that lack mitochondria and cannot fully combust glucose, such as central nervous system glial cells, and red blood cells. Lactate is also produced in skeletal muscle under anaerobic conditions, and some muscles produce lactate under aerobic conditions. Glycerol accompanies the release of fatty acids during adipose tissue lipolysis. Chylomicrons from dietary fat fuel hepatic gluconeogenesis by providing glycerol as a substrate. Chylomicron-derived adipose lipolysis by the liver promotes mitochondrial β-oxidation, generating acetyl-CoA. During gluconeogenesis, acetyl-CoA is diverted away from TCA cycle metabolism and instead undergoes oxidative phosphorylation, which favors the production of ketone bodies (acetoacetate, β-hydroxybutyrate, and acetone). Ketogenesis is an important glucose-sparing backup fuel for the brain, as the brain is not well-adapted for fatty acid metabolism (5). In addition to the body’s stores of fat, ketones can also be acquired from the diet, in the form of saturated fatty acids, monounsaturated fats, polyunsaturated fats, and ketogenic amino acids. Further, gut microbiota can synthesize ketones. These ketone bodies are utilized for ATP generation, especially by the brain and heart (Figure 1.16). The start of the intermediate phase of starvation is characterized by the total absence of hepatic glycogen; hepatic glucose output is entirely in the form of gluconeogenesis, maintaining glucose at the low euglycemic level of ~70 mg/dL. During the initial phase of starvation and the early part of the intermediate phases of starvation, hepatic and skeletal muscle proteins are a major source of amino acids that fuel gluconeogenesis (22, 26). Gluconeogenesis can produce an adult form of kwashiorkor malnutrition, a critical condition when serum albumin falls below 2.5 mg/dL, the threshold for hydrostatic pressure of circulating blood. Poor circulation causes generalized swelling of the body (anasarca). During this state of high metabolic stress, there are high levels of circulating inflammatory cytokines and counterregulatory hormones, such as cortisol. This proinflammatory state causes gene suppression of reverse phase reactants, such as albumin. High cortisol promotes protein catabolism of skeletal muscle, resulting in muscle wasting (sarcopenia and cachexia; Sidebar 1.18). The immune system becomes compromised in this state.

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SIDEBAR 1.18: PROLONGED FASTING LEADS TO MUSCLE WASTING The daily glucose consumption in the brain is roughly 120 grams (~420 kilocalories). During early starvation (two to seven days), 100 grams of this glucose can be provided by degradation of ~800 grams of protein (~160 grams of amino acids) from skeletal muscle and the liver. Additionally, lipolysis provides 20 g of glycerol that contributes to the glucose production required by the brain. During late starvation, gluconeogenesis produces 20 grams of glucose per day from glycerol, but only 16 grams from amino acids. By this point, the brain has replaced most glucose needs with ketone bodies. The kidney transitions in role to becoming the major site of gluconeogenesis, which is linked with ammonia production, to counterbalance ketoacidosis. Septic and surgical patients are often not fed for many days. Instead, they receive ~450 kilocalories through intravenous dextrose solution. This is sufficient fuel for the brain, but not sufficient energy to prevent muscle and total body protein wasting. Glucose-sparing fatty acids and ketone bodies fuels derived from the body’s fat stores rescue much of the catabolic state in the early periods of starvation. However, if insulin is low and cortisol is high, body protein stores will be used as fuel sources. During the initial few days of fasting, the energy stress is accompanied by both insulinopenia and a robust cortisol response, amplifying catabolism. Excess ketones induce a stress-like response: glucagon, growth hormone, cortisol, and epinephrine (adrenaline) can be released. Epinephrine stimulates adipose tissue lipolysis and hepatic ketogenesis. Together, lipolysis and ketogenesis enhance gluconeogenesis to support euglycemia. While these processes sound like healthy means of bodyweight regulation, prolonged fasting can exhaust stores of fatty acids and fat-derived ketone body fuel. Without sufficient body fat to draw energy from, gluconeogenesis will progress to body protein reserves, causing cachexia (muscle weakness and wasting). The liver can also undergo auto cannibalization. Prolonged absence of energy from dietary sources causes thermodynamic disequilibrium, leading to death. Death occurs when one-third to half of the total body protein is lost.

1.8.3 Benefits and Dangers of Ketosis in Diabetes (Molecular Biology, Intermediate Level) Metabolic failure in type 1 diabetes is characterized by severe insulinopenia with acute metabolic diabetic ketoacidosis (DKA). Type 1 diabetes is an autoimmune disease that can take months to years to develop. Symptoms can start subacutely over the course of weeks, or acutely over the course of hours. Therefore, diabetic ketoacidosis might be the first sign of type 1 diabetes. Before the discovery of insulin by Frederick Banting in the 1920s, a diagnosis of type 1 diabetes from ketoacidosis was lethal. DKA continues to be a serious concern; DKA is the most common endocrinological emergency that

presents in the hospital setting. In a feedforward fashion, insulinopenia (inadequate secretion of insulin) drives hepatic ketogenesis, and ultimately the failure of the body to compensate for the impaired organ damage caused by diabetes. This failure to compensate progresses into ketoacidosis, a state with dangerously high levels of ketones (see Sidebar 1.18 for a case report).

SIDEBAR 1.19: A CASE REPORT OF KETOACIDOSIS First responders received a report of a 14-year-old male with shortness of breath, weakness, generalized abdominal discomfort, nausea, vomiting, and altered mental state. The patient’s breath had a “fruity” scent and he was oriented to people but was slow to respond. His bedside glucose levels were 488, blood pH was 6.68, and heart rate was 156 beats per minute. The patient reported polyuria (increased urination) and polydipsia (increased thirst). Based on signs and symptoms, recent-onset type 1 diabetes, presenting with diabetic ketoacidosis, was suspected. Intravenous saline was administered in transit to the hospital. Upon arrival at the hospital, the patient received insulin treatment. Cardiac arrhythmias were detected, possibly due to insulin-induced drop in potassium levels (hypokalemia) or osmotic diuresis-induced magnesium depletion. Intravenous sodium bicarbonate was administered to raise pH. Fluids and electrolytes— potassium, sodium, chloride, magnesium—were replenished. Blood pH, glucose levels, and electrocardiogram returned to normal. Diabetic ketoacidosis is an example of the detrimental effects of excess ketone body accumulation. In Section 1.8.4 and 1.8.5, we discuss how inducing mild ketosis can have beneficial effects on health, including weight loss, improved cognitive function during low glucose levels and Alzheimer’s disease, improved insulin sensitivity, protection of mitochondrial structure and function, decreased inflammatory stress, anticonvulsant activity, and a variety of benefits on fighting cancer. During pathological insulin resistance in type 2 diabetes mellitus (T2DM), there is continuous, unregulated adipose tissue lipolysis and mitochondrial combustion of fatty acids in cardiac and skeletal muscle. This wastes oxygen in the ETC, transforming oxygen into ROS. The oxidative stress from ROS amplifies direct damage to the molecular integrity of mitochondria, worsening insulin resistance. Wasting oxygen with the generation of ROS prevents maximum efficiency of ATP production. Further, ROS-mediated proinflammatory upregulation interferes with insulin signaling. Inducing mild ketosis has therapeutic potential in the management of type 2 diabetes, prediabetes, and underlying states, if the patient is insulin resistant. Inducing heavy ketosis with prolonged fasting regulates acidosis through the renal excretion of ketone body ammonium salts. Sodium-glucose transport 2 (SGLT-2) inhibitors, which act in the kidney, lower blood glucose by reducing the threshold for the excretion of

30 glucose in the urine from ~200 (in the absence of the drug) to ~140 (in the presence of the drug). SGLT-2 inhibitors cause weight loss (Figure 1.17). Insulin resistance in type 2 diabetes often causes high visceral body fat content. Because SGLT-2 inhibitors reduce blood sugar, insulin is not released. In the absence of insulin, adipose tissue undergoes massive lipolysis. This flood of fatty acids to liver mitochondria undergoes β-oxidation, producing more acetyl CoA than the TCA cycle can burn. The acetyl CoA molecules form ketone bodies that are released from the liver into the general circulation. These excess ketone bodies can be used as an energy source in the brain, skeletal muscle, and cardiac muscle (5). Ketone bodies can also regulate blood glucose by inhibiting hepatic gluconeogenesis (inhibiting blood sugar rise) and suppressing pancreatic insulin secretion (preventing blood sugar drop). However, ketone body metabolism is not a long-term solution for insulin resistance. There are many important physiological effects of insulin not replicable by ketogenic strategies, such as circadian rhythms. Mild ketosis in type 1 and type 2 diabetes can be beneficial during neuroglycopenia (hypoglycemia unawareness characterized by cognitive impairment). Dangerously low glucose levels (20–40 mg/dL) are often associated with seizures, confusion, lethargy (obtundation), and even coma. The goal of glucotherapy during neuroglycopenia is to raise glucose from dangerously low to functional levels, but not high enough to progress to diabetes-related organ disease (retinopathy, nephropathy, and peripheral neuropathy). Ketogenic states preserve normal cognitive function at low levels of blood glucose. Required ketone body levels are in the range of 90–130

Metabolism and Medicine mg/dL (~6–8 mmol/dL). Intravenous or oral ketone body supplementation (as salts or esters) and ketogenic diets may be promising metabolic approaches to help achieve acceptable glucose control in patients with neuroglycopenia.

1.8.4 Potential Benefits of Ketosis in Non-Diabetic Diseases (Biochemistry, Introductory Level) Ketone bodies improve mitochondrial-dependent and mitochondrial-independent redox stress. As an energy fuel, ketone bodies manage to replicate the energy producing effects of insulin-stimulated glucose metabolism by generating the same ratio of NADH/FADH2 reducing equivalents, subsequent physiological redox signaling, and even improve the efficiency of ATP production by oxidative phosphorylation (by generating a higher ratio of ATP per oxygen consumed). Further, the antioxidant effects of ketone bodies make them more efficient than oxidative metabolism of glucose. Additionally, the antioxidant actions of ketone bodies protect the integrity of mitochondrial structure and function, which protects insulin sensitivity and signaling. Several of the beneficial effects of mild ketosis involve improving insulin sensitivity. Chronic insulin resistance and hyperinsulinemia causes: 1) impaired glucose utilization, as may be exemplified in Alzheimer’s disease; 2) overutilization of fatty acids, which reduces the efficiency of the ETC and overwhelms the capacity of the ETC in skeletal and cardiac muscle; 3) dyslipidemia with accompanying atherogenic

FIGURE 1.17  Dietary manipulation or supplementation to induce circulatory β-Hydroxybutyrate. Calorie restriction or ketogenic diets are best known to elevate lipolysis in adipose tissue. Lipolysis in adipose tissue produces free fatty acids, which are taken up by the liver. Liver converts free fatty acids into acetyl CoA and ketone bodies. Ketone bodies can be used as a fuel source by many tissues, but not the liver. Ketone bodies have antioxidant properties and modulate blood glucose levels. SGLT-2 inhibition can also elevate ketone bodies. SGLT-2 inhibition decreases blood sugar levels by promoting excretion of glucose in urine; this indirectly leads to fat loss. During SGLT-2 inhibitor-induced hypoglycemic conditions, ketogenic diet, or caloric restriction, insulin signaling is suppressed. In the absence of the insulin/glucose signaling system, the body’s fat stores are used as an alternative fuel source. Source: adapted from (27). *AcAc = acetoacetate; BDH = β-hydroxybutyrate dehydrogenase; CoA = coenzyme A; FFA = free fatty acids; SGLT-2 = Sodium-glucose transport 2.

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Introduction to Metabolism disease in the vascular subintimal space; 4) impaired insulinmediated endothelial nitrous oxide-induced vasodilation; 5) hyperinsulinemia-mediated activation of mitogen activated protein kinase (MAPK) pathways of cell wall mitogenesis; and 6) pro-coagulant, prothrombotic, and anti-fibrinolytic effects that accompany the pro-inflammatory and oxidant stress effects of insulin resistance. These pathogenic effects on the vasculature limit blood flow, delivery of nutrients, and delivery of oxygen to tissues. Insulin resistance combined with a hyperglycemic state causes an exponentially greater inflammatory and oxidant antagonistic stress response than either condition alone. This helps to explain the greater morbidity and mortality of acute vascular events in diabetics, versus insulin-resistant individuals who are not diabetic. An expanded discussion of these processes are described in the vascular biology section of Chapter 9. One of the beneficial effects of ketones on insulin signaling is in the heart. The ketone β-hydroxybutyrate inhibits fatty acid oxidation in the heart, which decreases redox and inflammatory stress (21). Reduction of fatty acid metabolism in skeletal muscle may decrease redox and inflammatory stress, too. When fatty acid metabolism is replaced by ketone body metabolism, there is upregulation of insulin receptor expression in muscle, improved intracellular signaling, and improved glucose utilization. There may also be an improvement in insulin secretion patterns. Possible systemic responses to insulin could include feelings of satiety (fullness) and cognitive improvement. Another beneficial effect of ketones on insulin signaling is in the brain. Using ketones as a fuel source in the brain of insulin-resistant patients can be a way of postponing cognitive decline. Insulin resistance in the brain prevents uptake of glucose, which ultimately leads to reduced synthesis of acetylcholine in the hippocampus, a brain region for memory. Acetylcholine has many functions, including muscle contraction and cognition. Reduced levels of acetylcholine in the hippocampus lead to poor memory formation and retrieval, a characteristic of Alzheimer’s disease, accelerated cognitive decline, and aging. Other benefits of mild ketosis unrelated to insulin signaling include anticonvulsant (anti-seizure) activity (28). For example, ketone body esters administered as oral supplements and ketogenic diets are effective for the treatment of seizure disorders (29, 30). Seizures are caused by uncontrolled electrical activity in the brain. Ketogenic diets (medium chain and omega-3 polyunsaturated fatty acids as substitutes for saturated fatty acids) reduce excess electrical activity in the brain by limiting excitatory signals and favoring inhibitory signals. This diet increases the transamination of the excitatory neurotransmitter glutamate, decreasing the amount of glutamate available to overstimulate the brain. The diet also increases the conversion of glutamine to ɣ-aminobutyric acid (GABA), an inhibitory neurotransmitter. Further tamping down excess electrical activity in the brain, ketone body metabolism and ATP-dependent ion transport hyperpolarize neurons. Following a ketogenic diet for two years might be sufficient to permanently reprogram glutamate and GABA levels in the brain. Mild ketosis might also starve cancer. Cancer cell proliferation is stimulated by the Warburg effect: reprogramming

and upregulation of the glycolysis pathway, independent of anaerobic conditions. This upregulation of the glycolysis pathway stimulates cancer cell growth by providing the building blocks of cell replication and fueling the bioenergetic demands of the tumor. Preclinical research and clinical trials suggest that ketogenic diets may be able to reduce tumor size and survival. Cancer cells are vulnerable to ketone body metabolic therapy because cancer cells typically have lower mitochondria numbers, mitochondria functional capacity, or mitochondrial ketolytic enzymes. Also, rapidly-growing tumors have poorly-oxygenated areas that are unable to perform oxidative metabolism. In the absence of glucose, tumor cells with dysfunctional mitochondria or inadequate access to oxygen starve on the ketogenic diet. Glioblastoma, malignant astrocytoma, glioma, breast cancers, invasive rectal cancer, and non-small cell lung cancer treatments might all benefit from adding a ketogenic diet as an adjunctive therapy to the standard chemotherapy and radiation plans (31–35). Aside from starving cancer cells, a ketogenic diet can combat the side effects of chemotherapy, while simultaneously sensitizing cancer cells to chemotoxicity. Ketone bodies promote a range of anti-oxidant stress resistance programs that protect non-cancer cells from cancer, chemotherapy, and radiotherapy. The stress resistance program can prevent cancer cell initiation by upregulating DNA repair. Any given tumor exists in its own complex environment, with an optimal balance of ROS to promote tumorigenic growth and replication (36). Metabolic therapy with ketone bodies strategies disturb this delicate tumor environment, preventing tumor cells from thriving. Insulin resistance and hyperinsulinemia stimulate insulin receptor and insulin-like growth factor (IGF-1) receptor-mediated signaling, which promote the growth and proliferation of cancer cells (37). Ketogenic diets and esters of ketone bodies reduce hyperglycemia and hyperinsulinemia. This improvement in insulin sensitivity stunts pro-cancer signaling. These ideas will be discussed in greater detail in Chapter 8. Volume 1 Chapter 5 “Roadmap to the Future of Medicine” provides a model for a precision personalized scale of Medicine. Further, ketones as an energy source have value in circulatory compromise. Moderate circulatory compromise with tissue ischemia (brain, heart, lower extremities, or bowel) could benefit from ketotic state because ketosis requires less oxygen to produce ATP.

1.8.5 Yin-Yang Perspectives on Ketone Body Metabolism (Biochemistry, Intermediate Level) The yin-yang relationship of the fed-fasting states in skeletal and cardiac muscle favors mitochondrial bioenergetic oxidation of glucose in the fed state, and of fatty acids and ketone bodies in the fasting state. During the absorptive phase of the fed state, insulin promotes glycogen synthesis in the liver, skeletal muscle, and cardiac muscle. Insulin inhibits multiple lipases, suppressing lipolysis and the release of fatty acids from adipose tissue. Additionally, insulin suppresses the utilization of fatty acids in muscle as a fuel source. Insulin-stimulated

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FIGURE 1.18  Ketones may be a way to turn back the clock on biological aging. β-hydroxybutyrate is a ketone super fuel with antioxidant properties. Ketones have been demonstrated to prevent, slow the progression of, and even reverse diverse disease pathologies. Source: adapted from (27). *β-HB = β-hydroxybutyrate.

activation of acetyl CoA carboxylase-2 (ACC-2) is the major regulatory step of malonyl CoA synthesis and other fatty acid synthesis.*

1.8.6 Conclusions Ketosis may be a strategy for treating or preventing seizures or chronic diseases of aging related to mitochondrial dysfunction, such as cardiac disease, vascular disease, neurodegenerative diseases (Alzheimer’s disease, accelerated cognitive decline with aging), and cancers (especially brain cancer; Figure 1.18) (39, 40).

1.9 Energy Sensors and Fuel Gauges (Metabolic Physiology and Translational Medicine, Introductory Level) While nutrient excess provokes the fundamental pathological web of insulin resistance and mitochondrial dysfunction, calorie restriction conversely enhances mitochondrial function and insulin sensitivity. Molecular sensors of low energy status, especially AMP activated protein kinase (AMPK) and sirtuin1 (SIRT1) are activated by external control parameters such as fasting, calorie restriction or exercise, due to a high ratio of AMP to ATP. The principal functions of AMPK (and SIRT1) are to stimulate pathways that increase the production of ATP, and to inhibit those pathways that consume ATP, thereby maintaining energy homeostasis. For example, * Malonyl CoA has roles in fatty acid chain synthesis. Malonyl CoA also inhibits the enzyme carnitine-palmitoyltransferase-1 (CPT-1), which mediates transfer of fatty acids from the cytoplasm into the mitochondria for β-oxidation. An enzyme Malonyl CoA decarboxylase (MCD) lowers malonyl CoA levels by converting it to acetyl CoA, allowing unimpeded transfer of fatty acids by CPT-1 into the mitochondria. Conversely, inhibition of MCD leads to excess malonyl CoA, reducing fatty acid transfer, diminishing fatty acid oxidation (38). This leads to a reciprocal increase in glucose utilization. Anaerobic glycolysis and rapid uptake of glucose are staples of the Warburg Effect, which promotes tumor growth. Therefore, switching the cell’s fuel source from glucose to fatty acids starves cancer cells.

Metabolism and Medicine

FIGURE 1.19  External parameters such as calorie restriction or exercise cause an increase in AMP/ATP and NAD+/NADH ratio, which in turn activate AMPK and SIRT1, respectively. AMPK phosphorylates PGC1α, while SIRT1 deacetylates it. Both of these pathways stimulate PGC1α and, thus, promote mitochondrial biogenesis. *AMP = adenosine monophosphate; AMPK = 5’ adenosine monophosphate-activated protein kinase; ATP = adenosine triphosphate; LKB1 = liver kinase B1; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; NAMPT = nicotinamide phosphoribosyltransferase; PGC1α = peroxisome proliferator gamma coactivator 1ɑ; SIRT1 = NAD-dependent deacetylase sirtuin-1.

signaling through peroxisome proliferator gamma coactivator 1ɑ (PGC1α), in concert with various transcriptional activators, serves to promote mitochondrial biogenesis (Figure 1.19) (41). Low nutrient availability provides selective pressure to maximize the efficiency of energy production through mitochondrial oxidative phosphorylation. However, in the setting of excess nutrient intake, mitochondrial function is compromised by the pathological accumulation of reactive oxygen species causing redox modifications of mitochondria and other cellular structures (see Figure 1.20). Redox stress continues to impair mitochondrial function, which further worsens redox stress in a positive feedback loop. With each cycle, there is an acceleration in the entropy production rate, accompanied by a decline in the amount of available free energy. In the natural course of chronic pathophysiology, this acceleration is not linear but rather interrupted by states of relative stability. In contrast to low energy states that promote mitochondrial biogenesis, high-energy states degrade mitochondrial function. There are mediating nuclear hormone receptor control parameters of mitochondrial biogenesis beyond fasting, calorie restriction, and exercise, such as PGC1α, which can act as an important transcription regulator of carbohydrate, lipid, and protein metabolism (42, 43).

1.9.1 Energy Sensors, Circadian Biology, and Metabolic Homeostasis (Metabolic Physiology and Circadian Biology, Translational Medicine, Intermediate Level) Declining mitochondrial function is a hallmark of metabolic disease and the chronic diseases of aging. Examples of this

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Introduction to Metabolism

FIGURE 1.20  Excess nutrient intake creates a state of mitochondrial dysfunction that leads to a self-amplifying positive feedback loop whereby there is an increase in redox stress and ROS, causing an increase in the EPR as well as a decrease in free energy. *EPR = entropy production rate; ROS = reactive oxygen species.

include hyperglycemia-promoting microvascular disease and insulin resistance-induced macrovascular disease. Not only are mitochondria the powerhouse organelle of the cell responsible for ATP production, but the process of performing this function is the major cause of reactive oxygen species. Oxidative stress is the major form of redox stress which is arguably the most basic parameter of the rate of aging and chronic disease in living systems. Sirtuin 1 (SIRT1) is a molecule that functions as an NAD+-dependent deacetylase enzyme of histones and other proteins. It governs repair of redox damage to biological cell structures. Accordingly, the result is wide-ranging effects on preserving physiological health. This critical cell metabolic regulator has been demonstrated to significantly prolong the lifespan of mice, and to promote beneficial effects on the major chronic diseases of aging, cancer, cardiovascular disease, and neurodegenerative disorders. There is a reciprocally negative interdependent relationship between SIRT1, a calorie restriction mimetic, and inflammatory and oxidative stress. Conversely, inflammation and oxidative stress have a reciprocally positive feedforward relationship. Accordingly, the classical metabolic disease states of obesity and insulin resistance are characterized by mitochondrial dysfunction, a proinflammatory and high redox stress state. SIRT1 activity is inhibited by both redox stressmediated molecular damage, as well as by various effects imposed by the central inflammatory cytokine transcription factor NFkB. SIRT1 downregulates redox stress, and like its companion metabolic regulator AMPK, it inhibits energyconsuming metabolic pathways while stimulating bioenergetic metabolism. A reciprocally positive feedforward relationship exists between these two core metabolism governing proteins. There is a rich multidirectional interplay among the cardinal intrinsic control parameters of disease, NFkB and oxidative stress, and the metabolic regulators, AMPK and SIRT1. This is illustrated in Figure 1.21. The balance of these parameters is finely tuned in the healthy state of redox and energy homeostasis. However, in the context of chronic disease, this critical metabolic system of checks and balances goes awry. Due to the intertwined coexisting relationship of SIRT1 with AMPK, and their combined role in energy production, it is not surprising that these two central regulators are most active during the nocturnal fasting phase of the circadian cycle in

humans. In coordination with ATP production, these metabolic regulators are also responsible for cell redox stress resistance programs. While AMPK is the “master metabolic regulator” of ATP production, SIRT1 has the more primary role in governing the repair of cell redox damage (Figure 1.22).* SIRT1 exerts powerful effects on the health of all living systems. Its activity is upregulated by low-energy states, such as those resulting from endurance exercise or calorie restriction. This reduces the accumulation of damaging redox stress, while increasing the capacity for cell resilience to this fundamental mediator of metabolic and chronic disease. Furthermore, the positive regulation of mitochondria, mediated by PGC1α, reciprocally enhances insulin sensitivity generating a feedforward loop. Consistent with the connection of mitochondrial dysfunction and insulin resistance to chronic diseases of aging including cancer, cardiac, vascular and neurodegenerative diseases, SIRT1 provides a mechanistic link for plausibly effective therapeutic strategies to include calorie restriction, intermittent fasting, endurance exercise, and high-dose resveratrol (a plant compound that acts like an antioxidant).

1.9.2 Parameters of Diet and an ETC Mechanistic Model of Human Metabolic Health and Disease (Circadian Biology and Translational Medicine, Introductory Level) Why is the timing of diet a crucial parameter in human health and disease?

Homeostasis of redox and energy parameters of metabolic health is orchestrated by SIRT1 and AMPK, respectively, in an intertwined fashion. These metabolic regulators rely on the circadian organizing principle of time that applies to humans as they do to all biological systems. This has robust and fundamental implications for perspectives of human health and disease. A bidirectional relationship between cell molecular clocks and the metabolic regulators AMPK and SIRT-1 conform with the fasting insulin-resistant nocturnal phase of the daily cycle. An analogous reciprocal relationship exists between cell molecular clocks and both insulin secretion and signaling. However, in the latter case, the interdependence conforms with the feeding phase of the circadian cycle during the daylight hours. In states of human health, glucose uptake into insulinresponsive skeletal muscle and adipose tissue during the fed state is normally mediated by the glucose transporter, GLUT4. Additionally, in the fed state, insulin signaling induces glucose

* Examples of these programs are SIRT1-regulated antioxidant, DNA repair, and autophagy systems. Autophagy of damaged cell organelles is mediated by SIRT1 deacetylation of the AMPK activating kinase liver kinase B 1 (LBK1), and subsequent activation of AMPK. Antioxidant and DNA repair systems are enhanced by mechanisms that include the activating deacetylation of transcriptional regulators, FOXO and PGC1α. For instance, SIRT1 may interact directly with FOXO transcription factors, which in turn bind to the promoter region of genes to induce the production of antioxidant enzymes, such as superoxide dismutase. SIRT1 upregulation of FOXOs may also be indirect, mediated by its interaction with PGC1α (Figure 1.22).

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Metabolism and Medicine

FIGURE 1.21  The intricate interplay of the metabolic sensors and regulators AMPK (energy) and SIRT1 (redox) with mediators of inflammatory stress and ATP producing pathways. *AMP = adenosine monophosphate; AMPK = 5’ adenosine monophosphate-activated protein kinase; ATP = adenosine triphosphate; NFκB = nuclear factor kappa-light-chain-enhancer of activated B cells; PGC1α = peroxisome proliferator gamma coactivator 1ɑ; PPAR = peroxisome proliferator-activated receptor α; ROS = reactive oxygen species; SIRT1 = NAD-dependent deacetylase sirtuin-1.

FIGURE 1.22  The intricate interplay of metabolic sensors and regulators AMPK (energy) and SIRT1 (redox) with mediators of inflammatory and redox stress, and major cell redox stress response programs. *AMP = adenosine monophosphate; AMPK = 5' adenosine monophosphate-activated protein kinase; ATP = adenosine triphosphate; DNA = deoxyribonucleic acid; FOXO = forkhead box transcription factors class O; LBK1 = liver kinase B 1; NFκB = nuclear factor kappa-light-chain-enhancer of activated B cells; PGC1α = peroxisome proliferator gamma coactivator 1ɑ; PPARα = peroxisome proliferator-activated receptor α; ROS = reactive oxygen species; SIRT1 = NAD-dependent deacetylase sirtuin-1.

oxidation by promoting the entry of pyruvate (an end product of glycolysis) into mitochondria via activation of the enzyme pyruvate dehydrogenase (PDH). Alternatively, during the fasted nocturnal phase of the circadian cycle, there is reduced insulin secretion and increased resistance to insulin signaling in these tissues. Accordingly, glucose uptake and metabolism are supplanted during the fasted diurnal phase by fatty acid oxidation from endogenous adipose tissue lipid stores. This metabolic design is maximally efficient from the perspectives of flexibility for fuel source utilization and of non-wasteful oxygen consumption and hence of energy and redox homeostasis, respectively. The loss of the diurnal metabolic rhythm with

alternating insulin sensitivity and resistance during opposing phases of the circadian cycle equates to the loss of metabolic balance and homeostasis. Chronic insulin resistance manifests in a tissue-dependent fashion. In skeletal muscle, for example, there is a continued reliance on fatty acid substrates for ATP production, supplied by adipose tissue lipolysis. The imbalance and oversupply of fatty acids to skeletal muscle results in a quantity of electron transfer to the respiratory chain that exceeds mitochondrial capacity. This, together with the phenomenon of reverse electron transport (see Figure 1.13), is responsible for inefficient oxygen consumption along the respiratory chain and the

Introduction to Metabolism associated generation of redox stress (18, 44). This, in turn, leads to degradation of mitochondrial structure and function and a host of indissoluble consequences, including progressive insulin resistance, deterioration of redox and energy homeostasis, and other parameters of metabolic health. The inseparably entwined properties of chronic insulin resistance and mitochondrial dysfunction are metabolic keystones of the chronic diseases of aging. A sine qua non manifestation of mitochondrial dysfunction per se is an uncoupling of the glycolytic pathway of glucose metabolism from the TCA cycle and oxidative phosphorylation. Another hallmark of mitochondrial dysfunction is chronic insulin resistance. This is the loss of circadian metabolic flexibility that governs the transition of fuel selection from fatty acid to glucose oxidation, occurring at dawn. Both signature metabolic manifestations of mitochondrial dysfunction described in the above paragraph, 1) the decoupling of glucose conversion to pyruvate via the cytosolic glycolytic pathway from mitochondrial oxidative metabolism; and 2) the phenomenon of metabolic inflexibility, are characterized by a compromised oxidative phase of glucose metabolism and an accompanying increase in fatty acid oxidation. These substrate metabolic alterations lead to increased oxidative stress and a feedforward self-amplifying loop of mitochondrial dysfunction. Fundamentally, glucose combustion burns cleaner than the oxidation of fatty acids from the standpoint of providing a higher ratio of ATP produced per molecule of oxygen consumed (P/O ratio). This is the gist of the message depicted in Figure 1.14, showing cell types excessively reliant on fatty acids for ATP production due to chronic insulin resistance. It mechanistically illustrates at the molecular level of the electron transport chain of cell respiration, mediated by the phenomenon of reverse electron transport, the link between chronic insulin resistance, fatty acid oxidation, mitochondrial dysfunction, and ultimately the chronic diseases of aging. Alternatively, distinct cell types, such as small vessel endothelial cells and metabolic environments, such as hyperglycemia, reactive oxygen species generation, and metabolic disease sequelae, are more typically a consequence of electron slippage in the setting of forward electron transport. Thus, on the one hand, continuous insulin resistance and the inextricable concurrence of mitochondrial dysfunction lies at the core of accelerated biological aging and premature onset of the chronic metabolic diseases of aging. This is characterized by exaggerated lipolysis of endogenous adipose tissue fat stores unsuppressed by carbohydrate consumption, and consequently, excessive fatty acid oxidation. Moreover, this is mechanistically mediated by an inefficiency in the ratio of ATP production per oxygen consumption at the level of the electron transport chain process of cell respiration. From a behavioral perspective, the driving force of pathogenic insulin resistance is chronic dietary overconsumption relative to energy expenditure. This results in a direct surplus of exogenous dietary fat in addition to the overfilling of adipose tissue storage capacity and subsequent endogenous delivery of excess fatty acids to skeletal muscle and other tissues. On the other hand, metabolic

35 health in humans equates to the fidelity of diurnal cycling of peripheral insulin sensitivity with insulin resistance. The former is responsible for glucose oxidation in the fed state, while the latter is responsible for fatty acid oxidation in the fasting state. Food is the most dominant external time cue, or zeitgeber, for entraining peripheral biological clocks mediated by insulin signaling. Chronic noncycling insulin resistance is a foundational component parameter of desynchronized circadian biology. This leads to the loss of metabolic homeostasis and the development of chronic disease. A distinguishing behavioral hallmark of human health is the alternating pattern of nocturnal fasting and daytime feeding metabolically synchronized to insulin resistance and sensitivity, respectively. Taken together, time as a cardinal organizing parameter of physiology, food as the most dominant external time cue for entraining endogenous peripheral molecular clocks, and circadian insulin sensitivity and resistance as a critical synchronizing metabolic strategy, help to appreciate the time-restricted implications of diet on human health and disease. Consider the effects of nocturnal dietary consumption of carbohydrate and fat superimposed on the baseline physiology of insulin resistance teleologically designed to maintain metabolic homeostasis during the anticipated nocturnal 12-hour fasting phase. Metabolic pathways of circadian insulin resistance include hepatic glycogenolysis and gluconeogenesis, and adipose tissue lipolysis purposed to provide endogenous resources of glucose and fatty acid energy substrates during periods of fasting. Energy and other parameters of homeostasis become disturbed by “unexpected” eating behavior occurring at night. Crucially, the evolution of a circadian metabolic design is premised on anticipation. Abnormal timing of eating essentially ambushes a system that doesn’t anticipate the challenge. Specifically, this leads to high circulating blood glucose and non-esterified fatty acids. The disruption of metabolic homeostasis as a result of nocturnal eating provides an example of the pathogenesis of insulin resistance from an etiology perspective. As portrayed in the sketches of Figure 1.14, high circulating levels of glucose and fatty acids overload the mitochondrial capacity for forward and reverse electron transport, respectively, in a cell-specific fashion. This, in turn, leads to oxidative stress, mitochondrial dysfunction, and the transition from the healthy circadian states of insulin sensitivity and resistance to a chronic pathological state of insulin resistance (45). In summary, diet is a major control parameter of human health and disease. Poor timing and excess food consumption result in poor metabolic health manifested by mitochondrial dysfunction and chronic insulin resistance, as depicted in Figure 1.23. Hallmarks of chronic insulin resistance include exaggerated daytime adipose tissue lipolysis and hepatic gluconeogenesis. The typical intake of food during the daytime hours not only fails to suppress these processes, which is distinctive of insulin resistance, but also superimposes on them, resulting in excess circulating levels of lipids and glucose.

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Metabolism and Medicine insulin signaling and secretion is an important underlying factor in the genesis of chronic disease. Non-circadian insulin resistance is linked to mitochondrial dysfunction. This creates a feedforward, self-amplifying loop of inflammatory and redox stress as well as acid–base energy imbalances that serve as the foundation for metabolic disease. The energy sensors AMPK and SIRT1 have coexisted throughout evolution: they are critical and fundamental metabolic regulators under strong circadian control. AMPK links energy consuming and producing pathways while SIRT1 plays a pivotal role in the initiation of redox stress resistance programs in order to maintain metabolic homeostasis. These multiple factors are interrelated but is there a driver of change in the complex pathophysiology of metabolic dysfunctions? We address this question below.

SIDEBAR 1.20: THE IMPORTANCE OF CIRCADIAN INSULIN SIGNALING

FIGURE 1.23  Genetics and lifestyle contribute to mitochondrial health. Obesity, overnutrition, and sedentary lifestyle lead to mitochondria dysfunction, resulting in premature aging, diabetes, and certain cancers. Diet, exercise, and mitochondria-targeting medications are strategies to improve mitochondrial health. Source: adapted from (20).

1.10 The Genesis of Accelerated Aging and Chronic Diseases of Aging (Clinical Pathophysiology, Introductory Level) The development of insulin resistance and mitochondrial dysfunction are inextricably interwoven and underpin the evolution of metabolic pathology, senescence, and chronic diseases of aging. Here, we propose a model that posits that all chronic diseases of aging stem from this same fundamental basis. In fact, this model rests on the central thesis of this book, which states that insulin resistance and mitochondrial dysfunction are inextricably related and result in an increase in ROS and inflammation in self-amplifying cascades. We elaborate on this in subsections below where individual aspects of the central thesis are discussed in detail.

Insulin secretion and signaling are each under circadian regulation. Moreover, insulin signaling governs the timing of biological clock activity. This bidirectional relationship highlights the significance of food as the strongest external cue for peripheral clocks. The loss of circadian rhythm of daytime insulin sensitivity and secretion alternating with nocturnal insulin resistance is a primary driver and component in the pace of aging and in the pathogenicity of chronic diseases of aging. Furthermore, non-circadian insulin resistance is integrally linked to mitochondrial dysfunction. Consequently, there is a matrix of feedforward self-amplifying loops of redox and inflammatory stress that are intrinsic to the most basic elements of metabolic disease, which also include imbalances of energy and acid-base. The relationship of redox, energy, and acid–base parameters of metabolic homeostasis is highlighted by a strikingly tandem correlation between the Nernst (redox), Gibbs free energy, and Henderson–Hasselbalch (acid–base) equations. The energy sensors AMPK and SIRT1 are primary metabolic regulators with a strong circadian influence. They connect energy-consuming and -producing pathways (in the case of AMPK) and redox stress-resistance programs (in the case of SIRT1) in an inextricably linked fashion with biological clocks for the maintenance of metabolic homeostasis.

1.10.1 Insulin Resistance, Diet, Peripheral Clocks, and Metabolism

1.10.2 Insulin Resistance and Hyperinsulinemia: The Chicken or the Egg?

(Metabolism, Circadian Biology, Clinical Physiology, and Pathophysiology, Introductory Level)

(Metabolic Physiology, Introductory Level)

Insulin signaling and secretion are regulated by circadian rhythms. Importantly, insulin signaling also dictates the timing of biological clock activity. In light of this, food serves as a vital external cue for peripheral clocks. Disruption in circadian

Traditional views suggest that it is the development of insulin resistance that leads to hyperinsulinemia and related pathology. However, more recent theories argue that hyperinsulinemia derives from redox disturbances in the liver stemming from the ingestion of toxicants in the form of foods containing non-edibles (e.g., emulsifiers, preservatives, stabilizers,

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Introduction to Metabolism artificial colorings and sweeteners, flavorings, etc.). This notion suggests that such disturbances in redox homeostasis is an independent driver of hyperinsulinemia separate from altered redox in the blood, which reaches the pancreas and promotes hyperinsulinemia prior to the onset of insulin resistance. Additionally, hyperinsulinemia induced by environmental agents leads to increased food consumption and, in turn, increased fat mass, which further promotes insulin resistance (and hyperinsulinemia in a positive feedback loop; Figure 1.24). It is the belief of this author that both views bear great merit, are not mutually exclusive, and that these two models themselves become a feedforward self-amplifying loop.

1.10.3 The Protective Role of Visceral Adiposity (Obesity, Translational Medicine) Interestingly, this more contemporary view we expounded above is related to the idea that visceral adipose tissue (VAT) evolved for dual purposes: to protect abdominal organs against immunological challenges arising from the gastrointestinal tract, and to maintain total body redox homeostasis. In fact, there is evidence that VAT derives from myeloid bone marrow progenitor cells, which is of different embryological origin than subcutaneous adipose tissue (SAT) that derives from mesenchymal stem cells (46). The primary role of SAT is for fat storage and maintenance of total body energy homeostasis. An important general perspective in human health and disease, as presented in the Chapter on Nuclear Hormone Receptors, and illustrated in Figure 4.33 (see Chapter 4 in Volume 1) redox and energy homeostasis are intertwined, thus supporting an intuitive value for a combined role of adipose tissue. The omentum (Latin for “apron” or cover) is a layer of fatty tissue that expands from the stomach and liver to the intestines. It consists of the greater omentum, which connects the greater curvature of the stomach to the transverse colon, and the lesser omentum, which connects the lesser curvature of the stomach and the duodenum to the liver. The omentum represents the majority of VAT in the body. More than fat storage, the omentum has immune system functions: it can migrate,

blocking infections from a ruptured appendix or gallbladder from spreading to the rest of the body. Visceral adipocytes contain much of the same biodetoxification machinery as immune cells and hepatocytes. These include: 1) Toll-like receptors (TLRs). 2) Aryl hydrocarbon receptors (AHRs) among other xenobiotic sensing nuclear hormone receptors (NHRs), cytochrome P450 (CYPs) enzyme systems. 3) Antimicrobial peptides. 4) Inflammatory protein messengers (IL-1, IL-6, TNFalpha, MCP-1) in addition to those produced by infiltrating inflammatory M1 phenotype macrophages. Toll-like receptors recognize and bind antigenic challenges such as pathogen-associated molecular patterns (PAMPs) and danger-associated molecular patterns (DAMPs). Prime examples of PAMPs and DAMPs, respectively, are lipopolysaccharide (LPS), or endotoxin, and saturated fatty acids (SFAs). Noninfectious xenobiotic exposures in the diet also contain DAMPs. These are bound by TLRs, which then interact with NFkB, the central transcription factor that drives the production of inflammatory mediators. There are different types of TLRs. For example, TLR-2 binds PAMP’s of commensal microbes from translocated microbiota, eliciting an anti-inflammatory response (47). Aryl hydrocarbon receptor (AHR) is a nuclear hormone receptor. NHRs (as discussed in Chapter 3) are a family of lipid sensing transcription factors that regulate a wide range of metabolic functions. AHR functions as a lipophilic xenobiotic receptor, which upon binding a xenobiotic, translocates to the nucleus and regulates the transcription of cytochrome P450 phase 1 enzymes, as well as other biodetoxification programs (48). AHR binds to more than 400 petrochemical-derived persistent organic pollutants (POPs), which also commonly contaminate fatty foods. ARH activation is associated with the high-fat, low-fiber Western diet. Similarly, the pregnane X receptor (PXR) is another NHR with analogous functions,

FIGURE 1.24  The traditional view of insulin resistance is that it develops as a result of dietary excess and decreased energy expenditure that in turn lead to hyperinsulinemia and ectopic fat accumulation. A more contemporary theory is that insulin resistance results from hyperglycemia induced from dietary toxicants. Further, hyperinsulinemia leads to an increase in food consumption and thus an increase in fat mass, which further potentiates both hyperglycemia and insulin resistance.

38 and like AHR is richly expressed in both the liver and VAT (49). Activated xenobiotic NHRs promote visceral adiposity, which likely relates to a protective dilutional sequestration of the lipophilic toxicant molecules and accompanies the biodetoxification process. VAT shares and limits the vulnerability of hepatic exposure by insulating these toxic molecules. Antimicrobial peptide production by visceral adipocytes highlights the intricate bidirectional coordinate interactions with traditional immune cells. The relationship of adipose tissue with the innate immune system is well known, such as the infiltration of macrophages, and an apparent influence of adipocyte TLRs on the phenotype of macrophages. For example, TLR-2 promotes the M2 anti-inflammatory phenotype (in contrast to the M1 inflammatory phenotype). However, orchestrated and bidirectional interactions of adipocytes extend also to the adaptive immune system. Not only do adipocytes regulate changes in lymphocyte behavior, but the reverse is exemplified by T cell’s capacity to recalibrate the priority of adipocyte gene expression from the biosynthesis of lipids to upregulated transcription of antimicrobial proteins.

SIDEBAR 1.21: CLINICAL CONSIDERATIONS The drug pioglitazone improves insulin sensitivity and glucose homeostasis by changing the topography of body fat: it moves fat out of the liver and other visceral adipose stores in favor of subcutaneous adipose tissues, such as in the buttocks and thighs. This results in small, insulinsensitive adipocytes. While pioglitazone is a very effective agent, its connection with weight gain is a discouraging and undesirable effect for many patients. An important immune system effect of the drug is the upregulation of T-regulatory cells, hence inducing anti-inflammatory actions and an accompanying increase in the adipocyte biosynthesis of lipids (50). Perhaps this type of insight will foster a less negative attitude towards body fat, and the understanding that body fat is not inherently unhealthy. Immune cells and adipocytes show biological and pathobiological transcellular, bidirectional regulation of behavior and gene expression. This theme can be extended to cancer. For example, highly aggressive ovarian cancer often metastasizes to the omentum, and lipid stores from omental adipocytes can be transferred to metastatic ovarian cancer cells. Upregulated fatty acid-binding protein four (FABP4) facilitates hormonesensitive lipase (HSL)-induced lipolysis. The fatty acids are transferred into adjacent tumor cells, in which fatty acid oxidation pathways are also upregulated, hence providing energy for rapid tumor growth (51). Cell surface tyrosine kinase receptors, such as human epidermal growth factor receptor three (HER3), also promote the growth and proliferation of ovarian cancer cells. The endogenous ligand for HER3, neuregulin, is abundantly expressed in omental adipose tissue. Neuregulin robustly contributes to vigorous cancer cell replication. These examples highlight the interplay between cancer and visceral adipocytes. Targeting visceral adipocytes may be a means of inhibiting pathways of metabolic and chronic diseases, such as cancers.

Metabolism and Medicine

1.10.4 Loss of or Lipolysis of VAT and Autonomic Dysfunction: An Unrecognized Parameter of Premature Chronic Disease and Mortality (Obesity, Translational Medicine) The link between VAT and systemic insulin resistance and metabolic disease discussed in the previous subsection spotlights its role as a double-edged sword in human physiology. The adaptive beauty of biological systems can go awry when the challenges exceed the conditions for which they evolved. While the arrival of VAT in human evolution is a relative newcomer, it indeed predated the past four to five decades which ushered in a culture of high stress, breakdown of the diurnal lifestyle, and the entry of processed and fast foods coupled with gluttony and sloth (52). It should also be mentioned that visceral adipogenesis and the associated expansion of fat mass is likely driven by the exposure of infectious and noninfectious lipophilic toxicants and the increased demand for biodetoxification in addition to excess caloric intake. It is important to note the potential dangers that xenobiotic fat-soluble molecules pose in the event that they escape into the circulation. This may occur in the setting of rapid weight loss in the absence of a sufficient dietary program of antioxidants. Alternatively, it is quite plausible that this is an often unrecognized complication of the robust and exaggerated lipolysis characteristic of insulin resistance. Consequently, these neurotoxins may seed the myelin sheaths of neurons peripherally or in the brain. Seeding the autonomic nervous system may promote autonomic dysfunction and may cause sudden cardiac death. Additionally, this is a harbinger for the onset of chronic diseases of aging and of all causes of premature mortality (see Chapter 9) (53). In this writer’s view, this supports the significance of intricately synchronized circadian systems biology, and thus the sharp implications of altering the regulatory function of the autonomic nervous system.

1.10.5 An Anecdote for Current Times: Obesity and SARS-CoV-2 in Pulmonary Fibrosis The severe acute respiratory syndrome coronavirus two (SARS-CoV-2) broke out at the end of 2019 in China. By spring 2020, this coronavirus disease from 2019 (Covid-19) caused a global pandemic, infecting over 80 million people, and killing roughly two million. Scientists and physicians have been working around the clock to try to understand how Covid-19 initiates widespread and detrimental damage in the body. At the time of publication of this book, new information about Covid-19’s mechanisms of action and long-term effects have been published almost daily. It is generally accepted that type 2 diabetes (54) and abdominal obesity (55) are independent predictors of Covid-19 severity. An obese family friend, who is working as a nurse during the pandemic, was concerned that she would be at high risk of death if she contracted Covid-19. I explained that how your fat is distributed through your body can mitigate that risk. Diplomatically, I explained that having a “pear” shape (carrying fat in the lower body) was healthier than having an “apple” shape (carrying fat in the upper abdomen). Here are some

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Introduction to Metabolism preliminary theories as to why abdominal obesity increases mortality rates in people infected with Covid-19: 1) People with type 2 diabetes or abdominal obesity have higher amounts of the angiotensin-converting enzyme 2 (ACE2) in their adipocytes. This coronavirus is able to enter cells by way of the ACE2. In healthy cells, ACE2 stabilizes lipofibroblasts, keeping them frozen in an inactive state. However, when ACE2 is repurposed by Covid-19 as a transporter, ACE2 is no longer able to fulfill its original role of stabilizing lipofibroblasts. Covid-19 forms reservoirs in fat cells, further interfering with the stabilizing actions of ACE2. This means that lipofibroblasts destabilize and transdifferentiate into myofibroblasts. Myofibroblasts in the lung cause pulmonary fibrosis (a similar process happens in patients with scleroderma: adipocytes located at the dermal junction transdifferentiate into myofibroblasts). A fibrotic lung loses elasticity and has interstitial edema, making it harder (or impossible) to breathe. Unfortunately, when obese patients are put on mechanical ventilation with high-peak inspiratory pressure, they are at increased risk of fatal, spontaneous pneumothorax (56). 2) Abdominal obesity and type 2 diabetes cause higher baseline levels of hypoxia and inflammation. Visceral omental adipocytes have relatively little storage capacity for lipids. When visceral adipocytes are full, lipids are typically stored in subcutaneous adipocytes, which have much greater storage capacity. Subcutaneous adipocytes are of mesenchymal embryological origin. They are inherently noninflammatory, and even release adiponectin, which has anti-inflammatory effects. Adiponectin also has insulin-sensitizing effects. Because type 2 diabetes and insulin resistance often coincide with abdominal obesity, there is less subcutaneous fat storage. Instead, visceral omental adipocytes are overfilled with lipids. These hypertrophic adipocytes outgrow their blood supply, causing hypoxia, systemic inflammation, hormonal changes, autonomic stress responses, immune suppression, and adipocyte dysfunction. Hyperglycemia also gylcosylates pulmonary proteins. For these reasons, type 2 diabetics have impaired lung function at baseline (57). Any additional insult to the lungs, such as Covid-19, further decimates lung function in this vulnerable population. 3) Abdominal obesity and type 2 diabetes causes ectopic fat storage in the lung, providing the raw materials for pulmonary fibrosis. Localized inflammation from hypoxic, hypertrophic, dysfunctional adipocytes causes insulin resistance within the adipocyte, producing exaggerated lipolysis—free fatty acids spill out into the bloodstream. Excess lipids dumped into the circulation get packed away as ectopic fat in unhealthy places, such as the skeletal muscle, liver,

heart, pancreas, brain, and lungs. Because there are more ectopic fat cells in the lungs of obese patients and people with type 2 diabetes, ectopic fat provides more raw materials to create lipofibroblasts, which, in turn, provide more raw materials to become myofibroblasts, developing into pulmonary fibrosis. On autopsy of two abdominally obese patients that died from Covid-19, fat embolism of the lungs was present (58), suggesting another possible connection between ectopic pulmonary fat and Covid-19 mortality. For the obese nurse who must interact with Covid-19-infected patients daily, her best protection from Covid-19-related mortality (besides personal protective equipment) would be to exercise and lose weight. Preventing progression to abdominal obesity, insulin resistance, and impaired lung function is crucial. A persuasive opinion article by Kruglikov and Scherer suggests that common type 2 diabetes medications may be novel therapeutic options for the prevention and reversal of Covid19-induced pulmonary fibrosis (59). Thiazolidinediones (peroxisome proliferator-activated receptor-gamma agonists) can prevent transdifferentiation of lipofibroblasts into myofibroblasts, and metformin can induce transdifferentiation of myofibroblasts back into lipofibroblasts. The authors cautiously suggest using these medications as an adjuvant therapy for the treatment of Covid-19. If validated in clinical trials, the antifibrotic properties of these type 2 diabetes medications would have the potential to save the lungs of millions of Covid-19 patients. Another potential treatment option for Covid-19 patients could involve stimulating the adipokine hormone adiponectin, which has antifibrotic effects. Adiponectin is a hormone involved in regulating glucose levels and breaking down fatty acids. Adiponectin signaling promotes rapid differentiation and replication of preadipocytes, creating mature, insulinsensitive, large, lipid-storing adipocytes (60). These adiponectin-induced adipocytes are less likely to outgrow their blood supply, and therefore, the adipocytes do not become hypoxic or induce systemic inflammation, and do not create dysfunction that results in insulin resistance. As a bonus, when adiponectin activates its conjugate receptor, ceramidase is activated. Ceramidase is an enzyme that degrades lipotoxic ceramides. The net effect of adiponectin signaling is anti-inflammatory and insulin-sensitizing. Unfortunately, individuals with insulin resistance, obesity, or type 2 diabetes have lower circulating levels of adiponectin, so they do not receive this protection against hypertrophic adipocyte-mediated hypoxia and inflammation.

1.10.6 Endotoxicosis and Insulin Resistance Bacterial subclinical endotoxicosis is a typically unrecognized hallmark in the triggering and perpetuation of insulin resistance. While it is not an essential component per se of either model described above, it is an important driver of insulinresistant disease. It is the consequence of the disassembly of the tight junctional complexes that support the intestinal barrier. An altered compositional pattern and reduced diversity

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Metabolism and Medicine parameter of one another. This cascade, in addition to the stress response as a primary trigger, may be precipitated by other notable factors. Glucocorticoids or other immunosuppressants lead to immune system dysfunction. Alternatively, a course of antibiotics leads to overgrowth of pathogenic microbes, intestinal inflammation, and microbial translocation to the portal circulation causing inflammatory responses in VAT and in the liver. In the section below, we discuss specific interactions involving SFAs, VAT, inflammation and insulin resistance and its downstream consequences.

FIGURE 1.25  This figure illustrates the relevance of both views of insulin resistance. One is that dietary xenobiotic-induced redox disturbance causes hyperinsulinemia, which secondarily causes insulin resistance (Corkey model). The second is that insulin resistance is the primary disturbance (that now appears to be induced by ectopic fat droplets, sometimes occurring in fit young individuals due to subtle inherited mitochondrial defects) with secondary hyperinsulinemia (Reaven/DeFronzo model). Intestinal dysbiosis promoting enterotoxicosis supports both models. It starts in the gut and causes an inflammatory-induced change in systemic redox in the liver and VAT. This leads to the overproduction of insulin, causing insulin resistance (Corkey model). In turn, an exaggerated lipolysis and ectopic fat in the liver and skeletal muscle occur, inducing insulin resistance and downregulation of insulin receptors that leads to hyperinsulinemia (Reaven/DeFronzo model). Source: adapted from (15).

of the microbiota is the central control parameter leading to a breakdown of the intestinal epithelial lining, with resulting enhanced permeability and translocation of immunogenic microbe components or even intact microbes (Figure 1.25).

SIDEBAR 1.22: PARAMETERS OF ENDOTOXICOSIS In the case of a disturbed microbiota, dysbiosis, or small intestinal bacterial outgrowth, as a control parameter of metabolism, health, and disease, it may be considered both an intrinsic (inside the human host) or extrinsic (outside the human host) control parameter. In this sense, it can be distinguished, taken from Physics nomenclature, as a second order parameter. The microbiota itself is controlled by extrinsic parameters such as unhealthy voluntary circadian, dietary, or stress patterns of behavior. Similar to other pathological responses of the body, the psychogenic stress response is importantly contributed to by the fundamental intrinsic metabolic parameters of inflammatory and redox stress. Pro-inflammatory cytokines, elicited by a pathogenic microbiota, cause prolonged or exaggerated autonomic/hormonal activation. Moreover, proinflammatory cytokines and redox stress may reduce the threshold for the perception of stress by direct actions on the limbic system of the brain. Thus, there is an intertwined and bidirectional self-amplifying relationship of the intestinal microbiota and the stress response, each being a control

1.10.7 Visceral Adiposity at the Intersection of an Inflammatory Diet and Insulin Resistance (Clinical Metabolism, Translational Medicine) SFAs may play an adaptive role by assisting a vital immunogenic response. SFAs as a basic macronutrient component are inflammatory instigators of TLR-4. In the case of both endotoxin and SFA bound TLR-4, the transcription factor NFkB is activated, which drives the expression of proinflammatory cytokines IL-1 beta, IL-6, TNF-alpha and chemokine monocyte chemotactic protein-1 (MCP-1) (47, 61). Consequently, this inflammatory response in VAT and liver antagonizes insulin signaling, which results in lipolysis and gluconeogenesis/hepatic glucose output, respectively. Additionally, VAT lipolysis liberates free SFAs into the portal system, promoting hepatic steatosis, steatohepatitis, and the signature systemic dyslipidemia of insulin resistance, characterized by small dense LDL atherogenic particles, low HDL, and elevated triglycerides (62). Because visceral adipocytes are smaller than subcutaneous adipocytes, their potential for fat storage is commensurately limited. Both dietary SFAs and gut-derived infectious and noninfectious lipophilic toxicants promote inflammation and insulin resistance in depots of visceral adipose tissue. So does adipocyte hypertrophy due to lipid storage exceeding the size capacity of the cells. Thus, while VAT initially protects the liver from these toxic exposures reaching the organ directly, the development of insulin resistance with ensuing exaggerated lipolysis often cascades into a pernicious systemic effect (63, 64). The inability of adipose depots to expand is due in small part to the downregulation of adipose tissue uptake of dietary chylomicron and hepatic VLDL carrying fatty acids. This is an insulin-resistant manifestation of adipose tissue capillary endothelial cell lipoprotein lipase. However, a larger effect of limited adipocyte size is the impaired insulin suppression of adipose tissue lipolysis in the feeding state. This is mediated by the enzymatic activities of hormone-sensitive lipase and adipose triglyceride lipase (ATGL). It is this later effect that appears to be the major driver of intra- and extra-cellular ectopic fat accumulation in systemic tissues (65). The etiologies of insulin resistance, hyperinsulinemia, mitochondrial dysfunction, and metabolic disease are both interwoven and self-amplifying. Excess quantity and poor quality of nutrient consumption lead to subsequent ectopic fat

Introduction to Metabolism storage, chronic disease, and insulin resistance. This results in unregulated lipolysis and ultimately in ectopic fat storage (66). The genesis of insulin resistance (independent of whether insulin resistance or hyperinsulinemia occurs first), is the hallmark of hepatic insulin resistance and subclinical endotoxemia. Subclinical endotoxicosis is the result of translocation into the portal circulatory system (67). Importantly, the loss of diversity in the gut microbiota and the healthy symbiotic compositional pattern is fundamental, as is an exaggerated and prolonged psychogenic stress response with associated immune dysfunction and inflammation. Mitochondrial dysfunction has complex implications on pathophysiology through multiple mechanisms outlined above that account for complex interwoven cellular pathways. However, the role of metabolic dysfunction has a long history dating back almost a hundred years. One of the most important consequences of mitochondrial dysregulation is the so-called Warburg effect, which is almost always found in cancer cells (68). In the next section, we take a look at this old hypothesis using the recently acquired knowledge base.

1.11 Models of Chronic Diseases in Medicine as Metabolic Disorders (Clinical Metabolism/Translational Medicine) 1.11.1 The Warburg Effect: A Modern Perspective of an Old Hypothesis Nobel Prize recipient Otto Warburg hypothesized in the 1920s that cancer arises as a result of enhanced acid production

41 during glycolysis even in the presence of oxygen, a process called aerobic glycolysis. Warburg believed that aerobic glycolysis was a consequence of impaired oxidative phosphorylation. In his seminal paper, ‘On the origin of cancer cells,’ he argued that “the irreversible injury of respiration” was responsible for the origin of cancer cells (69). Nonetheless, recent research supports an essential role of mitochondrial metabolism in tumorigenesis. Mitochondrial respiration promotes intermediates in the tricarboxylic acid (TCA) pathway that supply building blocks for cell replication (Figure 1.26). For example, the intermediate citrate is converted to acetyl CoA which in turn fuels subsequent fatty acid synthesis and the formation of cell membranes. Even before Warburg, Pasteur, another pioneering biochemist, had demonstrated that oxygen suppresses the fermentation of sugars (anaerobic glycolysis), therefore categorizing the conversion from glucose to lactate as an anticipated hypoxic response. Assuming the same logic, tumors may be hypoxic, and this might be the leading cause of lactate secretion in the tumors as high expression of hypoxia-inducible factor (HIF1a) is observed in many tumors. In effect, that is not the Warburg effect. What set tumors apart in Warburg’s analysis was the ability of tumors to uptake glucose at a higher rate and convert it to lactate, even in the presence of sufficient oxygen. Although mitochondrial respiration is suppressed in cancer cells, it is now evident that certain TCA cycle intermediates such as citrate and succinate are elevated and play a crucial role in sustaining glycolysis besides regulating pro-tumorigenic signaling (via activating hypoxia-inducible factor). In contrast to normal cellular metabolism, the TCA cycle in cancer cells functions more anabolically than catabolically.

FIGURE 1.26  The Warburg effect suggests that an increase in glucose and thus an increase in glycolysis potentiates cancer cell proliferation. An increase in glycolysis leads to increases in glycolytic intermediates such as glucose-6-P, which in turn activates the pentose phosphate pathways to increase production of lipid and nucleotide synthesis. Additional increases in 3-phosphoglycerate lead to enhancement in serine levels and ultimately (via one-carbon metabolism in the folic acid and homocysteine/methionine pathways) nucleotide and protein synthesis. The increased rate of synthesis of these molecular building blocks allows for further cancer cell replication. *HK = hexokinase; NADPH = the reduced form of nicotinamide adenine dinucleotide phosphate; P = phosphate; PEP = phosphoenolpyruvate; PFK = Phosphofructokinase; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

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Citrate is diverted for lipogenesis via the enzyme ATP citrate lyase, which is overexpressed in cancer cells.

SIDEBAR 1.23: DEFINING TERMS The Pasteur effect: as the O2 level decreases, the generation of ATP is shifted from oxidative phosphorylation to glycolysis, also known as fermentation or anaerobic glycolysis. The Crabtree effect: generation of alcohol in presence of excess extracellular glucose irrespective of oxygen level. The Warburg effect: tendency of cancer cells, unlike normal cells, to ferment even in the presence of ample amount of oxygen, also known as aerobic glycolysis. In addition to tumors, many physiological processes utilize the Warburg phenomenon. The Warburg effect not only accounts for rapid energy production to meet proliferation demands, but also to generate substrates required for cell proliferation. One fundamental difference between the metabolism of tumors and other normal cells is that tumor cells can adapt to the fluctuating nutrient availability and growth signals. Thus, excess glucose is itself a signal for the induction of the Warburg effect in cancer cells, unlike normal cells which require growth factors. For example, hepatocytes have access to lots of nutrients, including glucose and fats; however, the liver does not grow unless it is stimulated by growth factors, in which case it takes up glucose and stores it at rates far exceeding most cancer cells. Additionally, most cancer cells use glutamine as an intermediate for the TCA cycle and as a biosynthetic substrate. One theory to explain the high dependency of cancer cells on the Warburg effect is that they use it to generate energy as well as the substrates to support rapid growth. For cells to divide at a rapid rate, many cellular components are needed, including building blocks, such as acetyl-CoA. The Warburg effect plays an essential role in maintaining acetyl-CoA production. Oxidative phosphorylation utilizes the majority of acetyl-CoA for energy generation. For example, fatty acid biosynthesis of palmitate requires eight acetyl-CoA molecules (requiring seven glucose molecules) along with seven molecules of ATP. If a cell burns all of the available glucose for ATP, there will be no building blocks remaining for cell proliferation. As mentioned previously, acetyl-CoA is generated by both glucose and fatty acid β-oxidation in the mitochondria. Further, fatty acids combine with select TCA cycle intermediates (such as pyruvate carboxylase or glutamine) to generate other TCA cycle intermediates (the process of anaplerosis). The Warburg effect facilitates both ATP production and generation of substrates that augment rapid cell growth and proliferation. The Warburg hypothesis has opened the curtain to a metabolic perspective of dietary and pharmacologic approaches to cancer prevention and treatment. The best strategy is to starve cancer cells without affecting normal cell metabolism. Therefore, if somehow nutrient sensors can be activated to signal “low energy”, this would impose selective pressure on cells

to maximize ATP production, moving away from the Warburg effect favored by cancer cells. A simple dietary manipulation— fasting—can do this. Ketogenic diets that mimic the fasting state not only lower insulin but also activate the energy sensor AMPK. Ketogenic diets were initially hypothesized to be useful for brain cancers, noting that normal but not malignant brain cells readily use ketone bodies bio-energetically (39, 40). Ketone bodies are metabolized to Acetyl CoA, which feeds into the TCA cycle. Ketogenic diets selectively stave tumors by providing the fatty acids and amino acids that otherwise could not be used by glucose-dependent tumor cells. Competition between cancer and non-cancer cells is such that the metabolic circuitry of the cell best matched to the environmental conditions will prevail. While the enzymatic network turnover frequency relying predominantly on cytoplasmic glycolytic pathway for energy production is rapid, lack of cooperation among cancer cells makes energy production inefficient across the tumor, leading to isometric scaling (see discussion of allometric scaling laws above in Section 1.4.2). The energy-inefficient nature of this pathway typically precludes the likelihood of nutrient oversupply. The opposite is often the case, whereby the rapid replication of cancer cells as well as the voracious nature of their metabolism, leads to an overall undersupply of energy, which is also due to the inefficient mode of glycolytic energy generation, resulting in cachexia. The theory of quantum metabolism provides a molecular basis relating metabolic rate with cell size and body size. It also explains differences in the metabolic rates of normal cells and cancer cells.

1.11.2 An Extension of Brownlee’s Unifying Hypothesis Another, more recent theory of pathology that is rooted in the idea of mitochondrial dysfunction is the unifying hypothesis presented by Michael Brownlee in his 2005 Banting Award Lecture (17). His seminal work proposes that hyperglycemia induces the overproduction of superoxides in the mitochondrial electron transport chain and that this is the single unifying mechanism that underlies numerous pathogenic processes associated with diabetes. Simply, in endothelial cells of diabetics with hyperglycemia, the excess amount of glucose overloads the ETC, causing electron slippage and thus the formation of superoxides (see Figure 1.13 for review). These ROS (such as superoxides) then inhibit glycolytic intermediates, creating a bottleneck in the glycolysis pathway. Consequently, the buildup of upstream intermediates of glycolysis increases, ultimately leading to the activation of non-energy producing pathways (hexosamine, PCK, and AGE pathways) that induce glycosylation and inflammatory-mediated diabetic complications (Figure 1.27). Brownlee hypothesized and identified these unifying mechanisms as the underpinning force in microvascular diseases of diabetes, and later extended this to macrovascular disease. Here, we propose a further extension of the unifying hypothesis that broadens it and suggests that it contributes to all chronic diseases of aging. Moreover, such a broader application of this hypothesis is consistent with the interwoven nature of chronic non-circadian insulin resistance and mitochondrial dysfunction, which are fundamental to the pathogenesis of these disorders.

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FIGURE 1.27  Brownlee’s unifying hypothesis depicts the results of hyperglycemia-induced increases in ROS generation in the mitochondria along the electron transport system that inhibits the activity of glyceraldehyde-3-P dehydrogenase (GAPDH), resulting in the bottlenecking of the glycolysis pathway intermediates leading to the activation of non-energy producing pathways. Increasing glyceraldehyde-3-P activates AGE and PKC pathways, while an increase in fructose-6 phosphate enhances the hexosamine pathway. In addition, there is an increase in pyruvate conversion to lactate, and an impaired conversion of pyruvate to acetyl-CoA in the mitochondria, resulting in an increase in fatty acid oxidation. *AGEs = advanced glycation end products; CoA = coenzyme A; DAG = diacylglycerol; ETC = electron transport chain; FAO = fatty acid oxidation; GAPDH = glyceraldehyde 3-phosphate dehydrogenase; GFAT = glutamine fructose-6-phosphate aminotransferase; GLcNAc = N-Acetylglucosamine; Glu = glutamic acid; Gln = glutamine; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; NFκB = nuclear factor kappa-light-chain-enhancer of activated B cells; PARP = Poly (ADP-ribose) polymerase; PDC = pyruvate dehydrogenase kinase; PFK = phosphofructokinase; PKC = protein kinase C; ROS = reactive oxygen species; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle); Upd = uridine diphosphate glucose.

1.11.3 The Warburg Effect and the Extension of the Unifying Hypothesis: A Broader Unifying Pathobiology Is there a possible confluence of the Warburg effect and Brownlee’s unifying hypothesis and can the two aspects of pathophysiology work in tandem in some cases?

Here, we seek to highlight the important features of a proposed model of the chronic diseases of aging. This composite model posits that chronic diseases are metabolically shaped by the interwoven fabric of both the Warburg effect as well as an extension of Brownlee’s unifying hypothesis to include manifestations of insulin resistance and mitochondrial dysfunction, intrinsically fundamental to each of these contributing models. A central thesis of this book posits that insulin resistance and mitochondrial dysfunction are inextricably related and cardinally result in an increase in ROS and inflammation in self-amplifying cascades. The concepts that comprise both the Warburg effect and the extension of the unifying hypothesis are not mutually exclusive in most cases. While both are rooted in impaired oxidative phosphorylation, the Warburg effect proposes an upregulation of glycolysis and glycolytic enzymes that drive the pathway from the start. Conversely, the unifying hypothesis suggests that bottlenecking of the glycolysis pathway (and

the resulting activation of non-energy producing pathways) is the central pernicious event leading to pathology (Figure 1.28). We propose that both theories contribute to the development of chronic diseases of aging, but perhaps to different degrees depending on the specific disease.

SIDEBAR 1.24: KEY CONCEPTS We posit that the Warburg effect and the unifying hypothesis extension are not mutually exclusive. Both are fundamental to chronic disease, rooted in mitochondrial dysfunction. There may be varying levels of interdependence between these pathways dependent on the particular disease state. The central mechanisms underlying the Warburg effect include an increase in glycolysis that leads to enhanced biosynthesis of molecular building blocks required for cell replication. The central elements of the unifying hypothesis extension include an increase in superoxides that inhibit glycolysis and activate non-energy producing pathways as well as increasing mitochondrial fatty acid oxidation. The metabolic lynchpin for both of these driving phenomena is the uncoupling of the glycolytic metabolism of glucose to pyruvate from the mitochondrial oxidation phase of glucose metabolism.

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FIGURE 1.28  Insulin resistance and mitochondrial dysfunction are inextricably related through a self-amplifying feedback loop. This leads to the development of chronic diseases of aging through the mechanisms of both the Warburg effect and the unifying hypothesis extension. The Warburg effect describes increased glycolysis that results in an increase in the PPP as well as in one-carbon metabolism. Both pathways lead to the biosynthesis of the building blocks required for cell replication. The unifying hypothesis describes an increase in ROS that inhibits glycolysis pathway enzymes, creating a bottleneck resulting in upstream intermediates that activate non-energy producing pathways. In addition, the increase in ROS inhibits the PDC and hence the conversion of pyruvate to acetyl-CoA required for coupling the glycolysis pathway to the TCA Cycle, thus, resulting in an increase in fatty acid oxidation and dysfunctional mitochondria. Collectively, these mechanisms contribute to the development of chronic diseases of aging. *CoA = coenzyme A; FAO = fatty acid oxidation; PDC = pyruvate dehydrogenase kinase; PPP = pentose phosphate pathway; ROS = reactive oxygen species; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

1.12 Concluding Remarks All metabolic diseases are propelled by the inter-convertible processes of inflammation and oxidative stress. Metabolic disease is best understood by looking at the physiological sources of energy in its different forms in the body. The efficiency of how these energy forms are converted (especially electrochemical conversion in the mitochondria) and utilized to create biological structure and function across the networks of systems informs about the health of the organism. Conversely, insufficient or excessive consumption of energy, vitamins, minerals, or phytonutrients, and consumption of dietary or other toxicants, are indicative of metabolicallydriven pathologies. Also, alternative interference of electrochemical conversion within mitochondria can become a source of oxidative stress, disturbed redox, and the inextricable process of inflammation. Maximal entropy reduction and metabolic stability are part of physiological health but become gradually degraded by the natural process of aging. This biological decay is governed by the inevitable accumulation of inseparably intertwined redox and inflammatory stress, which is both a cause and a consequence of inefficient bioenergetic metabolism. Mitochondrial structure and function decline is a hallmark of metabolic instability. It is logical to assume that quantum metabolism, and other less precisely defined integrated and synchronized quantum biological manifestations, are the first to be lost as a

result of the exquisite sensitivity of these phenomena to heat, which is an intrinsic attribute of inflammation. The synchronized orchestration of the circadian rhythm by molecular clocks, albeit not yet demonstrated, is instinctively rooted in the quantum regime of metabolic functioning. Because of the structural similarity, it is a plausible assumption that the core clock component cryptochrome (CRY) has analogous quantum electromagnetic properties as the cryptochrome present in the retina of birds. This allows migratory birds to use the Earth’s weak magnetic field as a compass or GPS device when they fly thousands of miles with mind-bending geographical precision each year. The quantum electromagnetic property of cryptochrome molecules in birds’ eyes relates to “free radical pairs” of electrons with opposite directions of spin. Changing direction in the electron spin of one cryptochrome molecule in response to magnetic cues causes its counterpart electron to spin in another cryptochrome molecule to simultaneously reverse direction. This quantum mechanism followed by electronic and conformational transitions, in turn, guides a physiological response. The result of this veering behavior allows the birds to return to exact locations of a specific community in widely different parts of a country or even across continents. This is analogous to the amazing level of organizational perfection of the human spatio-temporal synchronized physiology orchestrated by molecular clocks. Low intensity magnetic fields, generated by moving charged particles, may induce quantum effects by changing directions of correlated electron spins between different molecules of

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Introduction to Metabolism the human cryptochrome core clock component. Akin to the free radical pairs of electrons in cryptochrome molecules in the retina of migratory birds, it is highly probable that these comparable processes modulate biological signaling. This may ultimately influence a macroscopic scale of physiology and behavior. Mitochondrial dysfunction not only inhibits the effect of quantum metabolism, but also affects other quantum biological processes that may originate outside the mitochondria. It follows that disruption of the central and essential organelle energy transformer lies at the core of both accelerated metabolic instability, senescence, and its associated chronic disease states. Further, the central axis of the biological equivalent to the second law of thermodynamics is the desynchronization and decoupling of this temporal organizing fabric. The uncoupling of bioenergetic pathways of oxidative phosphorylation from glycolysis is a fundamental process in metabolic disease initiation. This uncoupling is the corollary to metabolic inflexibility that is the hallmark of insulin resistance, the precursor to type 2 diabetes as well as, more generally, the metabolic disease sequelae of aging. Fundamentally, in the opinion of this writer, optimal metabolic efficiency of mitochondrial oxidative phosphorylation processes drives the metaphorical biological engine of the human body. This can be elegantly related to quantum metabolism and the associated minimal entropy generation. Insidiously gradual transition from quantum metabolism to classical metabolism parallels, in the most exquisite sense, loss of organism-wide synchronization and the related symptoms of aging. However, synchronization may still possibly occur at the quantum circadian level mediated by core clock component cryptochrome. Quantum biological effects of all types involve the “quantum wave function”, which has minimal tolerance for heat, and thus collapses in the context of even trivial degrees of inflammatory and redox stress. In physics this is called thermal decoherence and to the best of this author's knowledge, has not yet been directly linked to metabolism as a pathological manifestation of the loss of quantum coherence in the human body. Nonetheless, circadian biology may stay synchronized in a classical sense orchestrated by the temporally organizing cell clocks. The continued breakdown of mitochondrial structure with dysfunctional cell respiration is the most significant source of reactive oxygen species and heat generation in cells. It is the root cause of the exponential progression of biological aging and of chronic metabolic diseases. In effect, these sequelae manifest themselves in parallel to the loss of the intricate circadian functionally integrated and “synchronized” physiology within and across tissues. Accordingly, there is feedforward pathogenicity involving redox and inflammatory stress, mitochondrial dysfunction, and insulin resistance, with reverberating pathological effects on extrinsic control parameters of behavior, including circadian rhythms, dietary patterns, and the stress response. These behaviors and intrinsic biological parameters converge inextricably on intestinal and other interfaces of microbiota, which are bidirectional effects. All of these intrinsic and extrinsic parameters of human health are woven into the same metaphorical cloth with self-potentiating effects on one another,

impacting hierarchical scales of behavior, metabolism, and physiology. While the process of aging and pathogenicity cannot be stopped, it can be kept at a maximally slow rate with proper lifestyle adjustments as we outline in detail in this book. While gradual metabolic dysregulation and loss of efficiency is inevitable, a sudden and significant transition from quantum to classical model of energy production may be symptomatic of serious pathologies such as cancer. Hence, it usually requires appropriate therapeutic interventions. Quantum-to-classical transitions that occur at the level of mitochondrial ATP production, possibly involve the loss of coherence of biological clocks. However, this occurs early on in the progression of metabolic dysregulation, marking the loss of the optimal state of health. Further acceleration in the pace of aging conforms to deterioration in the bioenergetic machinery required in the oxidative phosphorylation mode of ATP production. Correct and accurate interpretation of symptoms is a necessary first step in designing a therapeutic regimen. This underscores the importance of understanding the metabolic origins of many diseases. Many of the ideas discussed in this introductory chapter will be explored in more detail in Chapter 9, which focuses on the role of metabolism in health and disease.

SIDEBAR 1.25: FINAL THOUGHTS Mitochondria are the power plants of the cell, producing the vast majority of the cellular currency in the form of ATP. Mitochondrial oxidative phosphorylation largely contributes to the overall metabolic rate and is the most efficient method of energy production. Prolonged loss of energetic efficiency is associated with pathological states. Metabolic diseases are induced by the interwoven processes of inflammation and oxidative stress resulting from mitochondrial dysfunction. The major human extrinsic control parameters of metabolic dysregulation and disease are: quantity, quality, and timing of diet; other circadian behaviors including fasting/ feeding, sleep/wake, rest/active cycles; stress and the autonomic/hormonal branches of the stress response that affect the immune system. Of major significance to human health and disease, as an extrinsic control parameter is the intestinal microbiota, which is intricately entangled within this fabric of other extrinsic control parameters. Together, these parameters act bidirectionally, forming many feedforward self-amplifying loops that underpin the pathogenic acceleration of human aging and accordingly, the chronic diseases of aging. Calorie restriction, fasting, and exercise induce the body’s fuel gauge sensors (AMPK and SIRT1) to stimulate pathways of mitochondrial biogenesis. A hybrid state of quantum and classical metabolism at some optimal ratio underpins maximal physiological health.

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47 54. J. M. Dennis et al., Type 2 diabetes and COVID-19-related mortality in the critical care setting: A national cohort study in England, March-July 2020. Diabetes Care 44(1), 50–57 (2021). 55. A. Petersen et  al., The role of visceral adiposity in the severity of COVID-19: Highlights from a unicenter crosssectional pilot study in Germany. Metabolism: Clinical and Experimental 110, 154317 (2020). 56. M. Zantah, E. Dominguez Castillo, R. Townsend, F. Dikengil, G. J. Criner, Pneumothorax in COVID-19 disease- incidence and clinical characteristics. Respiratory Research 21(1), 236–236 (2020). 57. A. Mendy, R. Gopal, J. F. Alcorn, E. Forno, Reduced mortality from lower respiratory tract disease in adult diabetic patients treated with metformin. Respirology 24(7), 646– 651 (2019). 58. S. Cinti, L. Graciotti, A. Giordano, A. Valerio, E. Nisoli, COVID-19 and fat embolism: A hypothesis to explain the severe clinical outcome in people with obesity. International Journal of Obesity (London) 44(8), 1800– 1802 (2020). 59. I. L. Kruglikov, P. E. Scherer, The role of adipocytes and adipocyte-like cells in the severity of COVID-19 infections. Obesity (Silver Spring, Md) 28(7), 1187–1190 (2020). 60. Y. Fu, N. Luo, R. L. Klein, W. T. Garvey, Adiponectin promotes adipocyte differentiation, insulin sensitivity, and lipid accumulation. Journal of Lipid Research 46(7), 1369– 1379 (2005). 61. J. M. Zha et al., Comparison of gene transcription between subcutaneous and visceral adipose tissue in Chinese adults. Endocrine Journal 56(8), 935–944 (2009). 62. G. Perseghin, Lipids in the wrong place: Visceral fat and nonalcoholic steatohepatitis. Diabetes Care 34 Suppl 2, S367–S370 (2011). 63. C. I. Le Roy et  al., Dissecting the role of the gut microbiota and diet on visceral fat mass accumulation. Scientific Reports 9(1), 9758–9758 (2019). 64. M. J. West-Eberhard, Nutrition, the visceral immune system, and the evolutionary origins of pathogenic obesity. Proceedings of the National Academy of Sciences of the United States of America 116(3), 723–731 (2019). 65. S. E. McQuaid et  al., Downregulation of adipose tissue fatty acid trafficking in obesity: A driver for ectopic fat deposition? Diabetes 60(1), 47–55 (2011). 66. J. O. Ebbert, M. D. Jensen, Fat depots, free fatty acids, and dyslipidemia. Nutrients 5(2), 498–508 (2013). 67. H. Kitabatake et  al., Association between endotoxemia and histological features of nonalcoholic fatty liver disease. World Journal of Gastroenterology 23(4), 712–722 (2017). 68. V. Gogvadze, B. Zhivotovsky, S. Orrenius, The Warburg effect and mitochondrial stability in cancer cells. Molecular Aspects of Medicine 31(1), 60–74 (2010). 69. O. Warburg, On the origin of cancer cells. Science 123(3191), 309–314 (1956).

2 The Stress Response: From Health to Disease

Abbreviations ΔG ΔS aCC ACTH ADH AMPAR Amy Apo-C2 ARC ATP BAT BMAL1 BMI Ca2+, CAD CNS CQ CR CRH CRY1/2 CVD DHA DHEA DMH DMV EPR EPSP GABA GH GLP-1 GLUT4 GR HDF HDL Hipp HPA HPG HPT HTN Hyp IGF (1) lPFC IQ LC LC/NS

Gibbs free energy entropy anterior cingulate cortex adrenocorticotropic hormone antidiuretic hormone; also known as vasopressin α-ami​no-3-​hydro​xy-5-​methy​l-4-i​soxaz​olepr​opion​ ic acid receptor amygdala apolipoprotein C-II arcuate nucleus adenosine triphosphate brown adipose tissue brain and muscle Arnt-like protein-1 body mass index calcium ions coronary artery disease central nervous system consciousness quotient calorie restricted corticotropin-releasing hormone cryptochrome circadian regulator 1/2 cardiovascular disease omega-3-fatty-acid docosahexaenoic acid dehydroepiandrosterone dorsomedial hypothalamus dorsal motor nucleus entropy production rate excitatory postsynaptic potential gamma aminobutyric acid growth hormone glucagon-like peptide-1 glucose transporter type 4 glucocorticoid receptor high-fat diet high-density lipoprotein hippocampus hypothalamic-pituitary-adrenal axis hypothalamic-pituitary-gonadal axis hypothalamic-pituitary-thyroid axis hypertension hypothalamus insulin-like growth factor (1) lateral PFC intelligence quotient locus coeruleus locus coeruleus/nervous system

DOI: 10.1201/9781003149897-2

L/D LHA LPL LTD LTP M Mg2+ MR MRate MS Na+ NAcc NF-κB NMDAR NPY NTS OFC PER1/2/3 PFC PFL PVN ROR ROS s. muscle SCN SNPs SPZ SSRIs T2D TCA Trk VLM VLPO vmPFC VO2 max VTA

light/dark lateral hypothalamus lipoprotein lipase long-term depression long-term potentiation weight/mass magnesium ions mineralocorticoid receptor metabolic rate metabolic syndrome sodium ions nucleus accumbens nuclear factor kappa B N-methyl-D-aspartate receptor neuropeptide Y nucleus tractus solitarius orbitofrontal cortex period circadian regulator 1/2/3 prefrontal cortex Physiological Fitness Landscape paraventricular nucleus retinoid-related orphan receptor reactive oxygen species skeletal muscle suprachiasmatic nucleus single nucleotide polymorphisms subparaventricular zone selective serotonin reuptake inhibitors type 2 diabetes tricarboxylic acid tropomyosin-related kinase ventrolateral medulla ventrolateral preoptic nucleus ventromedial prefrontal cortex maximal volume of oxygen consumption ventral tegmental area

Chapter Overview Colloquially speaking, stress is often used to describe an unpleasant situation (e.g., an overbearing boss), the reaction to the situation (i.e., headache, chest pain, heartburn), or the cumulative response to these reactions (i.e., an ulcer or a heart attack). Historically, stress was often perceived as negative and synonymous with distress—a physical, mental, or emotional strain. However, stress has both positive (health-promoting) and negative (health-damaging) functions. Stress is any 49

50 challenge to the normal balance of biological systems of the body. Stressors may include work or school stress, social conflict and isolation, financial stress, adjustment stress, bereavement stress, competition stress, and health stress. The type, amount, and effect of stress on the body can be quite subjective depending on physical, psychological, and social makeup. However, resilience to stress is required for a healthy state just as debilitating stress is required for a diseased state. Stress, in the context of this volume, is defined as any disruption or a threat of disruption to homeostasis, the body’s dynamic equilibrium. Homeostasis is the maintenance of morphological, physiological, and behavioral daily routines of the life cycle through allostasis. Allostasis is the healthy, adaptive response to maintaining/restoring homeostasis through the hormonal, autonomic, and immune systems. Allostatic load is the cumulative result of an allostatic state and a subthreshold critical point whereby homeostasis of vital organ systems is maintained. Beyond this threshold is allostatic overload, which is tantamount to the onset of chronic disease. This is represented when allostasis can no longer maintain homeostasis of vital organ systems. Disharmony in this exquisite, organizationally complex system can drive the body from health to disease. When the brain senses a stressful situation, it activates the autonomic nervous system or the body’s “fight or flight” response, triggering a metabolically demanding cascade of stress hormones that produce well-orchestrated physiological changes. The brain, particularly the hypothalamus, signals the adrenal glands on the kidneys to release stress hormones such as adrenaline, cortisol, and norepinephrine. As these hormones travel through the bloodstream, they increase heart rate, increase blood pressure, and dilate the air passageways of the lungs to bring in more oxygen with each breath. Extra oxygen delivered to the brain increases alertness and heightens the body’s senses, priming the body for instant action. Following this fast-acting surge of hormones, the secondary stress response system activates what is known as the hypothalamic-pituitary-adrenal axis, continuing to release hormones into the bloodstream if the brain continues to perceive a threat. Acute and short-lived stress promotes enhanced cognition and emotion regulation whereas prolonged and chronic stress deteriorates learning and memory, and accelerates the trajectory to mental illness and biological diseases of aging. There is an amazingly complex network of molecular pathways and receptors dedicated to the handling of stress at the cellular level. This chapter will provide the reader with an up-to-date overview of these networks and the key players at molecular, cellular, and organ levels. Stress may be understood in terms of the binding of cortisol to glucocorticoids and mineralocorticoid receptor neuron cells of particular structures in the brain where objective cognitions occur. Some of the major brain regions involved in the stress response are the amygdala, the emotional seat of salient information in the brain, the hippocampus, where contextual memory consolidation and retrieval mainly occur and, the prefrontal cortex, where stress regulation and higher-order cognitive functioning take place such as decision-making. This should be thought of as shorthand and not an indication of brain regions with completely separate functions in the stress response.

Metabolism and Medicine Anxiety is often related to psychogenic stress. The root cause of anxiety (accumulated prolonged and excessive levels of stress) resides in the failure to achieve a solution to a problem, which leads to a state of uncertainty. When this occurs often and surpasses a critical threshold, a chronic state of anxiety sets in leading to allostatic overload whose consequences can be detrimental to an individual’s state of health. Prolonged stress may result in exaggerated stress responses, chronic anxiety, pathophysiology, and psychopathology. Conversely, one way to reduce anxiety is to lower expectations of the goal state. An adaptive stress response is required of an individual to build resilience to be able to cope with stress and maintain allostasis. Allostasis is mediated by hormonal (endocrine), catecholamine (nervous), and cytokine (immune) system responses. Mediators of allostasis can be both protective, in the case of allostasis (stability through change), and harmful, in the case of allostatic overload. This is known as the stress paradox whereby acute stress can be vitalizing (healthpromoting and lead to resilience) but chronic levels of stress can be devitalizing (health-damaging and lead to psychophysiological ramifications). Psychogenic stress manifests not only as anxiety but also as depression, anger, and aggression, all fundamentally rooted in the fear of the inability to control, and the consequences of, challenges/stressors. The aggressive behavior of an individual with alcohol use disorder, which is often attributed to the drinking itself, the “alcohol makes him/her aggressive or violent”, is rather due to the fear of not being able to control the resistance not to drink, and the fear of its consequences. These are very important concepts discussed in this chapter that need to be emphasized here. The most fundamental concepts of this current chapter are homeostatic-allostatic balance, the stress-driven progression from healthy to diseased states and, the implementation of a stress-centric predictive model to improve clinical practice known as the Physiological Fitness Landscape model (Figure 2.0). The Physiological Fitness Landscape model is a quantitative measure of an individual’s state of health or disease represented by a multi-dimensional topography. Each axis in this model consists of control and order parameters. A control parameter represents a potential stress factor that can be applied to the organism. For example, a control parameter can be nutritional intake, physical exertion or even the disturbances in circadian rhythmicity (see Chapter 4 for more on biological clocks). Equally important, an order parameter is a variable that the living system changes in response to the control parameters and whose value is a measure of health or disease. A classic example would be the maximum heart rate that correlates with the VO2 max (maximal oxygen uptake) in response to vigorous exercise, the latter being measured by speed of running or the maximum velocity attained on a stationary bike. Importantly, the perception of stress underscores its effect on the body. Overall, people who report experiencing high levels of stress increase their risk of death by 43%. However, people who report experiencing high levels of stress but do not perceive the stress as harmful to their health have a considerably low mortality rate, comparable to those who report low levels of stress. So, can the body’s perception of stress

51

The Stress Response

FIGURE 2.0  Stress response summary. Prolonged or chronic stress leads to a variety of downstream physiological outcomes including increased inflammation, immune system dysfunction, emotional and cognitive disturbances, anxiety, depression, disturbed microbial composition, and sleep disruption.

alter life expectancy? New research on the effects of stress on the body, presented in this chapter, suggests that this may be possible. For example, when the brain senses a stressful situation, it signals increases in heart rate, blood pressure, and oxygen intake. These physiological changes are often interpreted as signs of anxiety or the body’s incapability of coping with stress. However, if individuals perceive these physiological changes as the body’s preparation to successfully meet the challenge it is facing, psychological and physiological effects of stress are dampened, and the body is able to return to homeostasis. The intention of this chapter is to give the stress response the recognition it deserves. This chapter hopes to shed light on how the stress response provides a unifying explanation for virtually all chronic diseases of aging, which is often the most underappreciated element in medicine and public health. The perception of stress can alter life expectancy, which is the single greatest challenge to the profession of medicine—predicting death and intervening appropriately to delay it. The notion of stress can be extremely useful in clinical medicine as a model for testing susceptibility states of disease that cannot be assessed reliably in the baseline state, e.g., using a cardiac stress test to assess adrenal sufficiency. Monitoring responses to stressors and adaptability once the stressors are removed on a patient-by-patient basis can provide more valuable insights into disease prediction and progression as well as recommendations for optimal therapeutic interventions.

2.1 What Is Stress? What is stress? What are the major stressors in our lives and how do we respond to stress? What is the difference between homeostasis and allostasis? How do hormones regulate the stress response? What neural circuits regulate the stress response? How can chronic stress lead to disease? How does

diet influence stress? How is insulin resistance involved in disease initiation? Which concepts help us better understand stress response and its consequences for health? Stress is a phenomenon that is broadly and fundamentally responsible for human adaptation and influences human development, health, and disease. Developing resilience to stress is required for a healthy state. The notion of stress has a predominant connotation as something that induces a psychogenic or emotional response; however, stress applies to the molecular scales of biology at its core including autonomic, hormonal, and immune systems. The effects of stress manifest along every hierarchical scale of a system, in an integrated fashion with the macrocosm of psychogenic stress. Examples of cognitive and psychogenic stressors may include work, school, adjustment, and competitive stressors. However, they also include stressors such as social, financial, health, and bereavement, all typically accepted to be categorically detrimental. Who coined the term “stress”?

Historically, the term “stress” as it is currently used from a biological standpoint was first coined by Dr. Hans Selye in 1936, who defined it as “the non-specific response of the body to any demand for change” (1). Selye observed that in all his hospitalized patients, despite their diagnosis, the common denominator was that they were under physical stress, which resulted in the release of stress hormones such as adrenaline, increased adrenal weight, reduced thymus weight, and increased vulnerability to the occurrence of ulcers by suppressing immune reactions. He called this “The General Adaptation Principle” comprised of three stages—the alarm reaction (“fight or flight”), the resistance (short-term stress reaction) and the exhaustion (long-term stress reaction) (2). However, the term stress had been used for centuries in the physics field to describe an external force. For example, Hooke’s Law of 1658 states that “the magnitude of an external force, or stress, produces a proportional amount of deformation, or strain, in a malleable metal”. Colloquially, stress is often used to describe an unpleasant situation (e.g. an overbearing boss), the reaction to the situation (i.e. headache, chest pain, heartburn) or the cumulative response to these reactions (i.e. an ulcer or a heart attack). This confusion in the definition led to Selye’s coining of the term “stressor” to distinguish stimulus from response. Another source of confusion was that stress was often perceived as negative and synonymous with distress, which is defined as “physical, mental, or emotional strain and tension”. However, stress has both positive (health-promoting; eustress) and negative (health-damaging; toxic) functions (3). For example, winning a race or election can be just as stressful as losing, or more. Further, the type, amount, and effect of stress on the body can be quite subjective. Thus, after years of controversy and struggling to reason through animal and human research to define stress, Selye more accurately redefined and was the first to coin the term stress as “the rate of wear and tear on the body” (4). Prior to Hans Selye, several scientific giants contributed to the study of stress including Charles Darwin in his monumental

52 book “On the Origin of Species” in 1859. Darwin wrote that only organisms that adapt to changing environments can survive—in other words, the ability to adapt to change or stress promotes survival (5). Also, in the late 1800s, Claude Bernard theorized that adaptation to a changing environment is possible if the organism can keep the internal environment stable and constant (milieu intérieur, or internal medium). In 1932, Walter B. Cannon formulated the concept of the stress response and possible biological mechanisms of stress hormones such as adrenaline. He was the first to introduce the “fight or flight” model of the stress response based on numerous physiological experiments. Cannon also coined the term “homeostasis” as being disrupted by stress and as a potential mechanism for maintaining a stable and constant internal environment, based on Claude Bernard’s work (1). The concepts of “fight or flight” and homeostasis are the foundation of stress research as we know it today. Stress, in the context of this volume, is defined as any disruption to homeostasis, both real and imagined, caused by a stressor. A stressor is any stimulus that (threatens to or) disrupts homeostasis. The stress response is the spectrum of physiological and behavioral adaptations coordinated by the endocrine, autonomic, and immune mediators. At some severity and duration, a given stress can be either vitalizing and healthpromoting or devitalizing and toxic. Homeostasis, the body’s dynamic equilibrium, is the maintenance of physiological and behavioral daily routines of the life cycle through allostasis. Allostasis is the healthy, adaptive response to maintaining homeostasis through the hormonal, autonomic, and immune systems. Allostasis refers to the process to re-establish homeostasis while the stress response refers to the communication systems needed to do so. Allostatic load is the cumulative result of an allostatic state and a subthreshold point of criticality whereby homeostasis of vital organ systems is maintained. Beyond that threshold is allostatic overload, which increases the vulnerability to chronic disease. This is represented when allostasis takes much more energy to maintain homeostasis of vital organ system parameters. Consequently, our biological systems become insidiously destabilized in a self-amplifying positive feedforward fashion. This moves us away from the maximally healthy state and far from the exquisite, organizationally complex state of equilibrium. Disharmony in the exquisite organizational complexity of this system can drive the body from health to vulnerability to disease (6). This disease itself is a state of accelerated aging carrying any biological system, a human being for example, gradually over a lifetime towards greater vulnerability to disease (disruption in thermodynamic equilibrium) and, ultimately, death. Allostasis is defined as re-establishing stability (homeostasis) through change of physiological parameters induced by a stressor. Allostatic mediators include hormones, autonomic neurotransmitters, and neuromodulator monoamines (catecholamines), and immune cell cytokines. On the other hand, homeostasis represents resistance of vital organ system parameters to change. Allostasis maintains homeostasis. Allostatic load is the cost of allostasis or the chronic exposure to a stressor, on the body. When the body is no longer able to maintain homeostasis, a point of allostatic overload is reached. At this point the body responds to stress via

Metabolism and Medicine hormonal, autonomic, and immune systems, which further disturbs dietary, circadian, or emotional stressors, and becomes ineffective in maintaining homeostatic parameters of redox and Gibbs free energy (thermodynamic potential) These disturbances themselves become the soil that exacerbates the disturbance of all the upstream control parameter behaviors. All dietary components typically worsen; as do other circadian behaviors such as the perception of (and hence, response to) psychogenic stressors. The prolonged and pathogenic detachment of homeostatic parameters’ ability to maintain allostatic regulatory control becomes exponentially self-amplifying, marshalling the conversion of allostatic load to allostatic overload as markers of chronic disease sequel. When allostatic mediators do not efficiently transition back to the baseline state, then the activated state of stress is prolonged and metabolic inefficiency ensues, which is the cost of allostasis. This cost is a function of allostatic load, a concept coined by Sterling and Eyer in 1988 (7) and further developed and popularized by a pioneer in this field, Bruce McEwen, and further elaborated on with his collaborators (8). Allostatic load, in everyday terms, is the wear and tear of major life events (defined as stress by Selye). Prolonged allostatic load commonly precedes disease states. But how can stress be both protective and harmful? Pharmacologist and pioneer in the science of stress and the brain, Ron de Kloet, was the first to discover that the switch from a stressor producing resilience to vulnerability depends on the balance between activation and suppression of stress reactions, which is under control of one stress hormone— cortisol (9). Stress hormones, such as cortisol, are critical for life, but their actions in the brain can lead to protective or harmful outcomes, such as reducing or enhancing vulnerability to stress-related disorders. de Kloet demonstrated that cortisol is mediated by two types of nuclear receptors that have complementary yet opposing functions in processing of stressful information: one receptor (mineralocorticoid; MR) is involved in appraisal of novel salient information and the onset of the stress reaction, while the other receptor (glucocorticoid; GR) terminates stress reactions and promotes behavioral adaptation. This is referred to as the MR:GR balance. This discovery has led to major breakthroughs in the field of depression biomarkers and the development of novel treatment strategies for stress-related disorders aimed to promote a mechanism of resilience instead of vulnerability to disease. How can a better understanding of stress improve clinical practice?

The single greatest challenge to the profession of medicine is the predictability of death, the onset and trajectory of disease, and the response to interventions. The notion of stress can be extremely useful in clinical medicine as a model for testing susceptibility states of disease that cannot be assessed reliably in the baseline state. For example, a patient with a familial genetic mutation (e.g. Lipoprotein lipase [LPL] or Apolipoprotein C-II [apo-C2]) for severe hypertriglyceridemia has only a modestly abnormal lipid profile in the non-stressed baseline state. However, under the setting of hypothyroidism,

The Stress Response a new onset of or uncontrolled diabetes represents a metabolic stressor that expresses this genetic defect, often driving triglycerides to exceedingly abnormal levels. This can cause acute pancreatitis, a life- threatening condition. Thus, rather than a compartmentalized approach to healthcare, a model that focuses on a system of parameters has a unique capacity for a high-precision personalized scale of medicine. Every specialty or specialty physician in medicine is a single dimension (parameter), in the context of many other dimensions or parameters in the overall physiology or disease of an individual. Integrating critical parameters into one system enables a better understanding of and prediction of the trajectory of human health and disease, particularly concerning the choice of appropriate interventions. We propose a model framework that includes a system of three proximal major intrinsic control parameters: 1) psychological stressors (the stress response), 2) gut Microbiota (the quantity, quality, and timing of dietary intake), and 3) circadian metabolism and physiology, and four major extrinsic control parameters: 1) stressors, 2) support systems, 3) diet, and 4) circadian behaviors, for modeling medicine’s approach to health and disease. The fabric of these parameters is inextricably linked, and while each of them are on the periphery of the traditional establishment of medicine, a healthy versus maladaptive stress response is the most powerful and least appreciated parameter. Each axis in this model consists of control and order parameters. A control parameter represents a potential stress factor that can be applied to the organism. For example, a control parameter can be nutritional intake (including non-food items and xenobiotics), or physical exertion and or even the disturbances in circadian rhythmicity. Equally important, an order parameter is a variable that the living system changes in response to the control parameters and whose value is a measure of health or disease.

53 Intrinsic control parameters, also known as secondary order parameters, represent responses to the external control parameter behaviors. For example, downstream intrinsic control parameters to the psychogenic stress response include the endocrine and autonomic branches of the stress response, which couple to the immune system and inflammatory responses. Moreover, peripheral inflammatory stress activates the emotional stress response in the sense of reducing the threshold to the perception of stress. Most fundamentally, those parameters are redox, free energy and acid base that are required to maintain healthy organ system function, including vital signs: blood pressure, heart rate, respiratory rate, and temperature. The psychogenic or emotional stress response is vital to the self-amplifying cascade of disease pathogenesis (10). In this chapter and throughout this volume, we present homeostasis, allostasis, and allostatic overload through the lens of a Physiological Fitness Landscape (PFL), which is a quantitative measure of the state of health or disease for each individual represented by a multi-dimensional topography (Figure 2.1). The authors hope to convey that the neuroendocrine system in conjunction with the brain as the principal organ of allostasis and these systems’ interactions with the primary (cortisol, dehydroepiandrosterone (DHEA), inflammatory and anti-inflammatory cytokines, catecholamines and acetylcholine) and secondary (i.e. insulin resistance and mitochondrial dysfunction) mediators of allostasis deserve center stage attention for the implementation of the model of Physiological Fitness Landscape in medicine. The intention of this chapter is to give the stress response the recognition it deserves. Often the most underappreciated element in medicine and public health, this chapter hopes to shed light on how the stress response provides a unifying model for virtually all chronic diseases of aging. It is important to note that there are gender disparities in the prevalence of stress and stress-related chronic diseases. For example, men are more susceptible to the influence of stress on the body’s adiposity, blood pressure, and cardiovascular mortality whereas women are more susceptible to behavioral risk factors of cardiovascular disease such as the impact of stress on diet quality and quantity. These disparities

FIGURE 2.1  Allostasis from health to disease. Each axis in this space of control parameters represents a potential stress factor that can be applied to the organism under health-promoting stress (a), allostatic load (b), and allostatic overload (c). F stands for fitness function. Health-promoting stress and subsequent regulation via allostasis encouraged the return to an equilibrium state following a stressed state. Allostatic load drives the system away from a healthy equilibrium and towards disease. When the cost of allostasis is so high that another metastable state results, the point of criticality is surpassed, allostatic load becomes allostatic overload and the system is driven towards greater vulnerability to a diseased state of equilibrium.

54 highlight the criticality of targeted interventions for vulnerable populations (See Section 2.5.3 for more on gender differences in response to stress). Finally, in this Chapter the authors begin to weave in the notion of quantum metabolism, a new concept with important implications for our understanding of the living state since all life forms require energy input for survival. This theory highlights that our metabolism is truly a quantum mechanical phenomenon that derives allometric rules relating cellular metabolic rate and cell size. This implies correlated bioenergetics across scales from mitochondria to cell to tissues and it makes possible the extraordinary complexity and efficiency of human physiology. Thus, we argue that quantum metabolism is intimately connected to our Physiological Fitness Landscapes. In this framework of understanding human health, neural regulation works to attenuate allostatic overload and associated processes, like insulin resistance and mitochondrial dysfunction. Ultimately, this slows the degradation of the biological fabric of space-time through the efficiencies enabled by quantum metabolism.

2.1.1 The Interdisciplinary Nature of Stress The domains of scientific study, from clinical medicine to basic biological research to theoretical physics, have become more compartmentalized as a function of becoming more specialized. While great advances in medicine have been achieved under this framework, researchers and clinicians are slowly coming to the consensus that further advances require more collaboration amongst the different disciplines. The authors argue that much insight can be gleaned by adopting and translating concepts from across scientific fields. A compelling example of this objective is the study of neuroendocrinology. In the late 1980s researchers and clinicians started to weave together concepts from neuroendocrinology and immunology to reveal how these systems interact with the brain and what this means for understanding chronic disease. Continued research on these topics brought to light mechanisms by which chronic immune system activation becomes pathogenic as a function of increased circulating proinflammatory factors that contribute to a shift towards allostatic overload and manifestations of disease (11). Nearly three decades on, we believe that the physics of complex systems can provide a unique and fruitful platform to the study of the human body, one of the most complex systems known to us. Both theoretical and applied research rooted in physics and chemistry can be used to bridge this gap in our understanding of human health. Illustrative of this transference of ideas is that the most fundamental parameters of homeostasis can be viewed in terms of free energy changes, redox fluxes, and acid–base status. For example, activation of the canonical inflammatory pathway (known as the NF-kB pathway) and the resulting disturbed redox homeostatic concentrations impair both free energy flows and acid-base chemistry. This sequence of events alters the structure and function of protein, lipid, and nucleic acid components of cells leading to tissue injury (12). This is an example of a molecular basis for chronic disease development that can be further explored through the lens of physics and chemistry (Figure 2.2).

Metabolism and Medicine

FIGURE 2.2  Endocrine, immune, and nervous systems. Factors such as early life adversity, or social stress activate the HPA axis which activates the NF-κB inflammatory pathway. Chronic stress increases NF-κB signaling resulting in disturbed redox homeostasis and a prolonged and heightened stress response driving endocrine, immune and nervous systems further from homeostasis. *ACTH = adrenocorticotropic hormone; CRH = corticotropin-releasing hormone; NF-κB = nuclear factor kappa B.

2.2 The Stress Response The origin of neuroendocrinology as a modern area of medicine can be traced to the 1940’s when the major hypothalamic pituitary adrenal axis (HPA), the canonical stress response system, began to be uncovered. This axis encompass essential hormonal regulating systems of metabolism, growth, and reproduction, which are fundamental to healthy communication between the brain and the body. These systems highlight the complexity and significance of integrating interactions between the brain and the body. Thus, neuroendocrinology describes the intersection of the two major physiological systems––the central nervous system (CNS; electrical) and the endocrine system (chemical)––whose roles focus on the signals and responses the body receives and generates. The clinical importance of the interactions between these two systems becomes apparent in our understanding of the stress response: allostasis, or how our body responds to insult to regain homeostasis, or stability, is adaptive (7), but these same mechanisms can quickly become pathophysiological under chronic and compounding stress, or allostatic overload (13).

2.2.1 Homeostasis, Allostatic Load, and Allostatic Overload Homeostasis, or stability, cannot be defined without allostasis. Much of our understanding of the interface between homeostasis and allostasis comes from the neuroscientist Bruce McEwen, who reconceptualized the definition of homeostasis as a function of allostasis by means of the stress response. Stress is defined as a disruption or a threat of disruption of homeostasis, both real and imagined. Homeostasis is the maintenance of morphological, physiological, and behavioral daily routines of the life cycle through allostasis. A cardinal feature of allostasis is the wide-ranging adaptability of allostatic mediators (primarily hormonal, catecholamine, and immune responses) that not only maintain life but also help adapt to new situations/challenges (Figure 2.3).

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FIGURE 2.3  Stress and allostasis. Homeostasis here represents a tendency toward a stable equilibrium. The system can be perturbed during circumstances of acute stress; however, it will return to the same previous stable state once the stressor is removed. This flexibility and responsiveness help maintain resilience. *s. muscle = skeletal muscle

We now understand that the mediators of allostasis can be paradoxically both protective and health-promoting, in the case of allostasis, or harmful and health-damaging, in the case of allostatic overload. The purpose of physiological allostasis is to maintain homeostasis of vital organ system function and is embodied in a mechanism of adaptive resilience (coping; the ability to adapt in the face of adversity) that involves orchestration of the endocrine, nervous, and immune systems. Allostatic load is the cumulative result of an allostatic state and a subthreshold point of criticality whereby homeostasis of vital organ systems is maintained. A point of criticality is the threshold for the irreversible phase transition from a metastable or unstable point to a new stable state representing greater allostatic load (Figure 2.4). By irreversible, it is meant that the metaphorical energy barrier back to normal and optimally healthy parameters is too great. Conversely, the new “stable steady-state” (or attractor) is actually only a “metastable state” such that the distance and slope to overcome the next energy barrier is reduced, which carries the system to an even lower amplitude on the Physiological Fitness Landscape. Chronic stress provokes allostatic responses that chronically activate biological pathways, consequentially crossing this threshold. Beyond this threshold, when allostasis can no longer maintain homeostasis, is allostatic overload, resulting in increased vulnerability to and manifestations of chronic disease, including psychiatric disorders (Figure 2.5). While homeostasis means resistance to change, and allostasis means the process of stability through change, allostatic overload means energy instability through change (14). If acute stressors are managed through allostasis, then how does the body handle chronic stress?

How does chronic stress affect our future ability to respond to an acute stressor?

Allostatic overload is a concept first coined by Bruce McEwen to redefine the relationship between stress and disease (16). The concept of allostatic overload draws attention to the need to confront chronic stress. Stress on the body comes in many forms: emotional stressors from an unhealthy relationship, dietary stressors that shift the body towards a state of

FIGURE 2.4  Allostatic load to overload. Fitness function across control parameters is depicted. As allostatic load increases, irreversible phase transition occurs from a metastable (or unstable; sometimes referred to as labile state (15)) to a new stable state (an attractor) representing allostatic overload. This phase transition occurs at points of criticality, the threshold for the irreversible phase transition to a lower state on the fitness landscape further from the healthy state and closer to a diseased state.

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FIGURE 2.5  Stress and prolonged allostasis. Under conditions of prolonged stress, a suprathreshold (“point of no return”) is reached whereby the system’s stability limits are exceeded. Here, allostasis can no longer maintain homeostasis resulting in unstable states which lead to disease states.

high blood pressure, and even physiological stressors, such as chronically low levels of insulin in type 1 diabetes. Allostatic overload occurs as a result of chronically elevated hormonal, catecholamine, and inflammatory mediators of allostasis detached from regulatory control. It is often accompanied by cortisol and catecholamine resistance, which engenders a compensatory rise in the proinflammatory responses not counter-regulated by glucocorticoids. Biological phenomena in which resistance is achieved, such as to cortisol or insulin, are contextual and depend on the cell and tissue type. For example, while immune cells show resistance to cortisol fluctuations, cells in the hippocampus, a brain region critical for memory and emotional regulation, atrophy in response to chronic elevations in cortisol levels. When cumulative and recurring, these processes can lead to chronic metabolic diseases that are further aggravated by secondary mediators of allostasis (Figure 2.6). For example, markers of insulin resistance, which include low HDL (high-density lipoprotein), high triglycerides, and endogenous hyperinsulinemia are often coinciding and can exacerbate a diseased state. Furthermore, protracted CNS stress responses, including neuroendocrine and autonomic signaling that are mediated by endogenous cortisol, have been reported to contribute to vulnerability to pathological states of obesity, hypertension, dyslipidemia, diabetes, and osteoporosis. The pace of the decline in the amplitude of the attractor state on the Physiological Fitness Landscape is equatable to the pace of biological aging and the advancement of the chronic diseases of aging including cardiovascular disease, cancers, and dementias (Figure 2.7) (17). This attractor trajectory on the Physiological Fitness Landscape accompanies a fundamental property at all hierarchical scales, the loss of complexity or connections between component parts. These include the span from intracellular, to intercellular, and tissue level, to the trans-tissue and

FIGURE 2.6  Declining health. As allostatic load increases, irreversible phase transition occurs from a metastable (or unstable) state (peaks) to a new stable state (troughs). This phase transition occurs at points of criticality, the threshold for the irreversible phase transition to a lower state of poorer health on the fitness landscape further from the healthy state and closer to a diseased state. The Physiological Fitness Landscape models these downhill connected metastable states to predict fitness function.

total organismic plane, as well as the inter-individual social scale. Understanding the dynamic balance of homeostasis and allostasis and how this delicate balance can plunge towards a state of allostatic overload is critical for preventing, monitoring, and treating disease. The neuroendocrine (hormonal) and autonomic (catecholamine) components of the stress response and the inflammatory response to the microbiota represent primary allostatic parameters and chronic allostatic load that can lead to allostatic overload. Consequently, mitochondrial dysfunction and insulin resistance occur independently but also are mutually interactive (18). This manifests itself as an intricate interdependence within an interwoven inextricable process of reciprocal

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FIGURE 2.7  Physiological fitness function cascade. The stress response is vital to the self-amplifying cascade of disease pathogenesis. The pace of the decline in amplitude of the attractor state on the Physiological Fitness Landscape is equatable to the pace of biological aging and the advancement of the chronic diseases of aging including, cardiovascular disease, cancers, and dementias.

self-amplification. Redox stress and loss of free energy compromise molecular fidelity of the components of circadian clocks. This in turn contributes to the primary systemic parameters of allostatic load, which deteriorates the amplitude of circadian metabolic pathways in physiology. It follows that circadian behaviors become more vulnerable to fundamental spatio-temporal breakdown in synchronized cyclicity. This worsens oxidative/ inflammatory stress and further causes a decline in free energy. The inflammatory stress worsens the central psychological stress response in the sense of amplification and prolongation. Feedforward exacerbation of mutually interacting control and order parameters ensues. The intrinsic control parameter of insulin resistance, that is, the stress response, can be defined by VO2 max (volume of oxygen in milliliters per kilogram body weight per minute) which is a common measure of the level of fitness in athletes but should be used in a more general context of physical fitness. VO2 can be a useful measurement defining an order parameter of a susceptibility state to chronic disease in the fitness landscape (19). In this connection, oxidative stress can be measured by the rate of oxygen consumption via oxidative phosphorylation only since it does not account for the glycolytic mode of ATP production. Allostatic load and overload result in disturbed redox homeostasis and impaired free energy load. Redox stress and inflammatory stress parameters of allostatic load are no longer able to maintain the healthy state of redox homeostasis and free energy homeostasis. The transition to allostatic overload accompanies an attractor state of primary allostatic parameters that evolve to greater adrenergic and proinflammatory (i.e., blood markers of disturbed microbiota composition, and the breach in intestinal mucosal integrity such as endotoxicosis and high

levels of zonulin) dominant states. Subsequently, markers and manifestations of non-cyclical insulin resistance manifest including hyperinsulinemia, hypoglycemia, impaired fasting glucose and glucose intolerance, dyslipidemia, hypertension, and visceral adiposity. These exemplify secondary markers of allostasis. This leads to feedforward exacerbation of deregulated extrinsic control parameters, such as diet, social vigor, and circadian behaviors such as sleep, work, exercise, and other activities. This self-amplifying detachment from healthy homeostatic parameters is mediated by detrimental effects i.e., proinflammatory cytokinemia, cortisol, and hyperinsulinemia that together compromise cognitive function while potentiating uncontrollable, non-goal-oriented emotions. This lowers the threshold for the perception of stress, in effect further exaggerating the prolonged stress response. In consequence, this instability promotes both pathophysiology and psychopathology, forcing the attractor state of disease on the Physiological Fitness Landscape to further loss of amplitude. Furthermore, we can make a case for connecting the reciprocally related insulin resistance and mitochondrial dysfunction with impaired VO2 max, which is premised on the loss of metabolic efficiency correlated with aging and chronic disease, with metabolism being the distinguishing feature of living systems and also metabolic efficiency being a measure of physical fitness (20). Consequently, it makes eminent sense to use VO2 max as an order parameter in diseases such as cancer for both diagnostic and therapeutic purposes. Improving aerobic oxygen consumption is expected to lead or correlate with mitochondrial health. Currently, very little if anything is available in terms of pharmacological interventions aimed at this process in cancer therapy, except for a few investigational drugs such as dichloroacetate (21) and 3-bromopyruvate (22), which have not lived up to their expectations so far (23). Nonpharmacological approaches such as ketogenic diet (24) or breathing exercises through yoga (23) do show some benefit but may not be sufficiently powerful enough to stop or reverse cancer progression in most cases. The final metabolic tendril of life support is the lowest mountaintop on the Physiological Fitness Landscape, below which there is no further organized complexity, no stability or metastable zone protecting the living system from total chaos, and a total loss of reduced entropy, or thermodynamic equilibrium, all synonymous terms for death. This solidifies the notion that resilience to stress is required for a healthy state. The lower the resilience of any tissue or physiological system to a given stress the less steep the attractor state is of that system on the Physiological Fitness Landscape, and the lower its amplitude. This concept is already invoked by the standard cardiac stress test to assess myocardial supply to demand. It is, however, necessary for all disease states to be assessed by an analogous standard. The Physiological Fitness Landscape thus provides a standard model for diagnostic, in addition to therapeutic medicine (discussed in Chapter 9). How can stress be both health-promoting and health-damaging? Does the age of exposure to stressors play a role in our ability to adapt to stress?

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2.2.2 The Stress Paradox A fundamental theme of this book is the stress response state of arousal due to external factors, real and imagined, psychological and physical. These factors, depending on the individual, can either lead to positive or negative responses by the human body. They can vitalize psychophysiology and even optimally influence epigenetic potential, or conversely, they can lead to psychological and physiological pathology. Early life experiences play a powerful role in determining mental and physical health as they can lead to epigenetic modifications in development that set lifelong patterns of physiological reactivity and behavior. Adverse, early life stress such as poor quality and intensity of maternal care increases emotional and stress hormone reactivity, exacerbates allostatic overload, and determines methylation patterns on gene promoter regions that affect the expression of the glucocorticoid receptors (GRs) in the brain (25). Conversely, strong maternal behavior lessens emotional reactivity, dampens the stress response, and improves brain function and cognition (26). External stressors represent a critical and woefully underrecognized dimension of public health. Such stressors come in many forms, including work or school stress; social conflict and isolation, a particularly important and potentially debilitating form of stress; financial stress; adjustment stress; bereavement stress; competition stress; and health stress. Stress has overarching connotations that are enfeebling, broadly negative, and deleterious to physical health. In fact, this is not unfounded as underscored by the fact that a major stressful event, such as a family, social or financial crisis, carries a 30% increased risk of dying. However, it is crucial to recognize the following–this depends on the quality and dose of a stressor and its perception (27). It is essential to believe that stress is not inherently destructive and unhealthy. The notion of hormesis, whereby too little or too much is injurious, is a crucial concept that concerns the dose of a stressor, but some optimal amount builds resilience to the system receiving the stress (28).

Metabolism and Medicine The stressor, for example, may be a dietary one—such as a phytonutrient from organic plant- derived foods—that induces antioxidant response elements of genes to promote an overall salutary effect. This exemplifies the concept of hormesis whereby a high dose of toxicants present in many species of organic greens are harmful to humans. For example, individuals with the single nucleotide polymorphisms (SNPs) of cytochrome P450 biodetoxification enzymes may be highly sensitive, due to the impaired ability to detoxify specific contaminants (29). Analogously, it may be a superoxide reactive oxygen species that promotes cell signaling. Moreover, on a more macroscopic scale, it may be a vitalizing work, school, or competitive task or a physical exercise with a rewarding outcome, which is controllable. In the context of the latter, in addition to the dose of stress, its qualitative properties must be aligned to an individual’s skill set, values, and interests (30) (Figure 2.8). The notion of stress has a predominant connotation as a factor that induces a psychogenic response. However, acute, or vitalizing stress can have beneficial, or health-promoting effects on cognition, emotion, and behavior, by strengthening of neural circuits (via synaptic plasticity) mediating these processes, such as the prefrontal cortex and hippocampus (see the section about neural circuitry of stress that follows). Alternatively, chronic, excessive, and uncontrollable stress responses perturb the system, and can have health-damaging effects on cognition, emotion and behavior, by weakening some neural connections while strengthening others. Examples of these effects include decreased parasympathetic vagal tone, increased sympathetic activity with reduced heart rate variability, a chronically activated hypothalamicpituitary-adrenal axis, a proinflammatory cytokine dominance, insulin resistance with impaired glucose tolerance and chronic hyperinsulinemia (31). Additional susceptibility states for chronic metabolic diseases include neurodegenerative and cardiovascular diseases (CVD) and even cancers making this a very serious health risk (Figure 2.9).

FIGURE 2.8  Vitalizing stress. Examples of physical and psychosocial stressors that can challenge homeostasis and when overcome, lead to building stress resilience. This is known as vitalizing stress. *VO2 capacity = maximal volume of oxygen consumption.

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FIGURE 2.9  Metabolic disease states. Stress leads to insulin resistance and hyperinsulinemia which lead to the pathogenesis of chronic diseases such as obesity, cardiovascular disease (CVD), type 2 diabetes (T2D), Alzheimer’s disease, cancer, and accelerated cognitive decline (32). *CVD = cardiovascular disease; T2D = type 2 diabetes.

The exaggerated and prolonged stress response is a fundamental component, and often the origin, of virtually all chronic diseases. Importantly in this connection, structural plasticity of the brain, predominantly between the prefrontal cortex and hippocampus, is thought to be critical for high-level consciousness and cognitive functions underlying goal-directed behaviors. Consciousness is quantifiable as a consciousness quotient (CQ) (33) which is analogous to the intelligence quotient (IQ). By effectively controlling the emotional and reward centers of the brain, like the amygdala and nucleus accumbens, subconscious chronic feelings of fear and anger as well as emotionally driven motivational behavior for food and other hedonic rewards, are maintained (34). Healthy neural functioning works to constrain and control the effects of pro-inflammatory processes or chronic fear and anxiety that accelerate biological aging.

2.2.2.1 The Impact of Social Networks on the Stress Paradox The notion of heterogeneity in physics is analogous to the differences in strengths and weaknesses in personality traits of people and variations in their potential to regulate results in the spectrum of life’s challenges. This can be likened to a puzzle with the heterogeneity of personality traits fitting together to produce a whole, which is greater than the simple sum of its parts, a sine qua non of the complexity of biological systems. Thus, complexity in systems biology extends beyond a single independent living system. This becomes inherently relevant to a discussion of the vitalizing versus devitalizing nature of stress, its perception, and accordingly the building of resilience of the stress response strengthened by social networking. Thus, the complexity of a social network is analogous and complementary to the exquisite organizational beauty of a human individual in the sense of nonlinearity and a bottom-up

self-organizing system representing the composite of many integrated parts that evolved as a coordinated system to the challenges of evolutionary pressures. The interacting parts are intimately integrated across hierarchical scales whereby a network of individuals is yet another hierarchical scale. While this comparison may seem exaggerated, it is actually more literal than it at first appears if one considers the power of interpersonal relationships and social networking in terms of enriching resources and confidence or diminishing fear necessary to overcome everyday challenges. This engages the vitalizing nature of the stress response that welcomes challenges to succeeding, such as opening a business, or at least accepts stressors such as a diagnosis of diabetes. The critical intersection of this comparison is strengthening the stress response. In nonhuman species this applies to acute stress, whereas in human modern life, the stress, or the perceived stress, in a pathological sense, is chronic. Furthermore, considering the psycho-pathophysiology of chronic devitalizing stress and its relationship to chronic disease mediated by autonomic and hormonal manifestations, interpersonal relationships and social networking is indeed a survival strategy. It invokes the power of hormesis to promote both health span and lifespan. This strategy involves bottom-up processes for which there is no blueprint, but rather, are defined by the nonlinear interactions between elements of a system to generate a greater whole. The individual component interactions, in terms of how they contribute to the trajectory of the outcome, cannot be defined by an equation. This discussion returns to the concept of hormesis from an overlapping perspective of physiology below.

2.2.2.2 A Clinical Example of the Stress Paradox In the paragraphs that follow, I will relate an anonymous hospital patient from my clinical Endocrinology practice to illustrate the roots of the stress response and its dual potential for protective, as well as pernicious effects on physical health. However, I will first state some relevant premises as well as attempt to intermix comments throughout the discussion of the patient. If one inadvertently poses a threat by walking nearby the nested eggs or goslings of Canadian geese, the geese are known to become aggressive and even attack humans. This aggression is rooted in fear due to the threat of their offspring’s wellbeing. Similarly, human aggressive behavior is typically rooted in anger, which in turn is based in fear. Fear is a sense of dread or helplessness to adversity or challenge. It is the foundation of the human emotional stress response. The lifeline to alleviating fear and accepting or overcoming adversity requires help or perceived help from people. That is, the lifeline consists of the relationships and networks with other people. Anger and aggression are rooted in fear.

In fact, in addition to the classical autonomic and hormonal HPA axis branches, the posterior pituitary gland’s release of the hormone oxytocin is a recently recognized component of the stress response (35). Oxytocin promotes balancing

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anti-inflammatory and other salutary systemic effects in addition to enhancing goal-directed behavior. Furthermore, oxytocin acts on the limbic system prefrontal cortex to stimulate empathy and compassion (36, 37). This endocrine-mediated nurturing of interpersonal connection is a protective stress response resilience mechanism designed to strengthen courage to face and overcome difficult circumstances. Importantly, human connections and bonding stimulate oxytocin, and furthermore the stress response-stimulated oxytocin release promotes human connection (38). It follows that social bonding teleologically enhances the self-confidence to tackle or adapt to confronting adversity and challenges. Healthy enlivening stressors must match personality traits, experiences, and abilities, capable of stimulating the perception of oneself being able to rise to the challenge with confidence of controlling its outcome (39, 40). Social networking in modern day life may be metaphorically equated to Darwinian survival of species whereby members of a species form a herd, a school, or a flock to protect one another from predation and other survival purposes. The hospital patient I was consulted to see was a 16-yearold young woman with type 1 diabetes, anorexia nervosa, and poor glucose control. The young woman was mature, open and sincere. She was very sweet and friendly but appeared anguished. During my initial interview with her she outright stated that she was “terrified” of being overweight, and so was intentionally noncompliant to insulin as a means of staying thin. Insulin is a growth-promoting hormone that uses glucose to drive anabolism. By not taking insulin, glucose, rather than being taken up into metabolic tissues, acts as a diuretic and the calories are instead lost from the body in the urine. The shortterm effects of weight loss, however, carry the life-threatening risk of electrolyte abnormalities, volume depletion and metabolic acid-base decomposition with diabetic ketoacidosis as well as the pro-inflammatory and redox stress induced by severe hyperglycemia. In effect, this sweet and friendly adolescent woman displayed no overt signs of expressed anger or aggressive behavior towards others, but instead the anger and aggression were implicit and self-directed, analogous to the self-mutilating behavior of children on the autism spectrum. The natural question to ask is, why does this nice young woman perceive the thought of becoming overweight so terrifying? The purpose of this discussion is not to describe the psychopathology of anorexia nervosa, but more generically to explore the genesis of fear manifesting in a chronic exaggerated stress response that is self-destructive by exploiting physical disease. Stress tethered to meaning and purpose, in the absence of fear and anger, and with innate confidence to handle life’s challenges can be powerfully strengthening and invigorating. Further, people who do not perceive stress as bad or negative have significantly lower mortality than agematched controls (27). Thus, stress in the form of life’s challenges is a doubleedged sword—one side has the capacity to galvanize the fulfilling potential to handle the stress, rooted in

the engagement of human connection and the other side chronically elicits the emotional responses of fear and anger, mediated largely by cortisol actions on the amygdala overriding the modulating effects of oxytocin.

While this underscores the basis for fear, it’s the prolongation of the fear-induced stress response that in modern human life is mentally, emotionally, and physically destructive. Literature in the field increasingly suggests that the autoimmune and auto-inflammatory nature of type 1 diabetes originated from a disturbed composition of the gut microbiota (41, 42), such that it is potentially triggered by a herpes simplex viral etiology (43). This in turn contributes to impaired gut motility and an immunocompromised state mediated by the autonomic and hormonal branches of the stress response, respectively. This relationship, as a central control parameter to the chronic diseases of aging, is presented elsewhere in this book (see Chapter 7). Therefore, there should be a contextual appreciation for the wide-spanning antagonistic impact of a pathologically perceived stress on physical disease states, ranging from triggering the onset of, to poor coping strategies for, unintentional, and even intentional self-destructive behaviors. My experience of 25 years in private clinical practice has revealed a common theme of self-infliction that is striking among women with type 1 diabetes, all of whom have poor social support systems. I now turn back to the clinical vignette. By all accounts this young patient was friendly, cooperative, and kind with others including staff members involved in her care. The problem is her covert self-inflicting aggression and anger, which as stated above is fundamentally rooted in fear. Broadly speaking, the object of fear is anything that is perceived to be an uncontrollable barrier to the achievement of personal expectations for happiness. Humans are genetically hardwired with the correct intuition that interpersonal connectedness builds opportunity for meeting these expectations. However, chronic fear, mediated by cortisol effects on the amygdala, drives the emotional manifestation of the stress response. This degrades the capacity for goal-directed behavior as well as qualities of empathy, compassion, social awareness, intuition, love, and appreciation, all fundamentally necessary for building interpersonal bonds (44). Human connection enhances a successful and adaptive stress response facilitated by promoting the release of oxytocin from the posterior pituitary that in turn strengthens these human qualities to self-amplify human connection (45). This enhances the courage and reduces the fear to successfully overcome barriers to achieving personal expectations. It should be highlighted that people who do not perceive stress as bad have a significantly lower risk of dying than those who do. The lack of connection with people significantly contributes to a chronic fear-mediated stress state. Accordingly, a healthy adaptive stress response characterized by top-down cognition over emotion is supplanted by topdown emotion over cognition. In this patient example, anorexia nervosa, an irrational fear of being overweight is an emotionally distorted view as are all irrationally perceived stressors. However, it is deductively reasoned that the object of fear most

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The Stress Response fundamentally is the inability to form healthy relationships. This in turn is generalized to a fear of all life’s challenges, and consequently a learned helplessness. Moreover, it underpins the exaggerated and chronic emotional perception of stress, which is relatively detached from rational cognitive thought and intuition. Social connections may serve to overcome barriers by opening doors to opportunities. The powerful connectedness of members of a team sport, a musical band, or any network of interacting people in society gives a nonlinear product of the system whole that is greater than the sum of its parts, enhancing the likelihood of success. The distress of bereavement grief is also dissipated by human connection. Not surprisingly, the shared stress helps the non-griever by dissipating their own stress, analogous to the heterogeneity of complementary parts to a puzzle. However, in contrast to an analogy of dissipating heat (and increasing entropy), which leaves a system weaker due to the loss of energy in the interconnections of the system, sharing stress builds connections that produce a greater whole. Furthermore, by helping a distressed person successfully achieve personal expectations by coming to peace with a new reality, replacing the old connections with new human and even spiritual ones, it strengthens resilience (46). Additionally, helping others find solutions to their stressors powerfully elevates the human psyche in a sense of broadening opportunities that otherwise would not exist. This, along with creating and bolstering human connections reciprocally promotes resilience. Like other “chicken or the egg” scenarios addressing the question of what comes first, we may ask: Is it the chronic stress state impairing the potential to form powerful relationships and social networks, or is the lack of the latter causing the chronic stress response? In either event, this pernicious cascade becomes circuitous and self-amplifying. Although an unambiguous origin of the psychopathology and exaggerated stress response cannot be certain, some clarity did evolve along the course of my conversation with this young patient. She explained that her parents are divorced. Although she expressly stated her wish to see her mom, her father told her it was unhealthy for her to see her mother who also had an eating disorder. The story, however, is further complicated by the fact that her dad is an alcoholic who reportedly has “anger issues”. The young patient stated that she was fearful of telling her dad she wanted to see her mom. The upshot here is a sad and unfortunate circumstance where the daughter appears to have become a ping-pong inside the contentious imbroglio between the parents. The daughter likely has an unhealthy and unformed relationship with both parents and hence no precedent for future healthy relationships. It is likely relevant that this attractive 16-year-old was inappropriately flirtatious. It struck me as sad and ominous, that her self-esteem and ability to relate to people was constrained by her sexuality. This certainly connects to her terrifying fear of becoming overweight and willingness to exploit her disease at any cost to prevent this from occurring. On one visit she appeared visibly more somber. She described that she had met and “become close” with another patient on the floor who had been discharged home and didn’t live close by. He was a young boy about her age. She commented that she did not have many friends.

Anger and aggression are anchored in fear of failing expectations of an outcome, which in turn are made easier or even possible with human connection and networks. Hence, the act of helping others in times of need is both noble and self-fulfilling, underscoring the privilege of the life service of a physician. Taken together, the commonly observed self-destructive behavioral profiles of females with type 1 diabetes who use their disease as a means of controlling their weight may be similarly rooted in a variety of potential causes. These may include epigenetically inherited from a stressful intrauterine environment as a result of the mother’s psychopathology, or poor psychosocial family support systems with the lack of human connection. Both scenarios appear likely in the vignette presented here as important contributors to this patient’s chronic exaggerated perceived stress. This clinical presentation at such a young age may, as stated above, be responsible for the onset of juvenile diabetes. Moreover, it is typical that the prolonged stress response inextricably promotes the other behavioral control parameters of metabolic and chronic diseases discussed above, including poor quantity, in this case inadequate, quality and timing of dietary consumption, and of other circadian behaviors. Because of the vicious and selfamplifying nature of this process, and the young age of this patient, it is particularly crucial that behavioral and cognitive therapy be immediately and aggressively pursued. Fortunately, despite the unfavorable circumstances at such a dependent and vulnerable early phase of life, the limbic system demonstrates neuroplasticity. This allows the capacity for cognitive behavioral therapy to effectively reverse the framework of neural functioning and synaptic connections of an emotionally overactive, cognitively underactive brain. The potential exists for rewiring the brain by exercising neural circuitry responsible for empathy, compassion and other qualities required for building social connections, in addition to cognitive skills. Together, this enhances the enjoyment of the passage of time and the opportunities for fulfilling personal expectations that achieve happiness while reducing the stress responseperceived fear and consequently anger. An under-recognized contributing factor to the chronic emotional stress response in patients such as these is the chronicity and severity of volume depletion. This is further described in Chapter 9. In short, the response to intravascular volume depletion includes the co-secretion of antidiuretic hormone (ADH; also known as vasopressin) and corticotropin releasing hormone (CRH) from the magnocellular and parvocellular neuronal subgroups, respectively, in the paraventricular nucleus (PVN) of the hypothalamus and project to the pituitary. These hormones are co-localized in the parvocellular neurons and released in response to stress. ADH amplifies the CRH effect on other circulating hormones. While ADH inhibits excretion of free water by the kidney, CRH initiates the HPA axis arm

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of the stress response, and hence cortisol secretion from the adrenal gland. Cortisol allostasis, when chronic, mediated by immune dysfunction and systemic pro-inflammatory cytokines, in turn may promote allostatic overload states including cancers and cardiovascular disease. Another pattern I have seen recently in patients, several of them females with type 1 diabetes with poor social support systems and passive personalities, is narcotic substance abuse. In contrast to the patient described above, whose behavior is a form of aggression turned inward, in response to fear, the narcotic abuse seems to be an escape mechanism. Thus, in one case the stress “fight or flight” response manifests as “fight” whereas in the other it manifests as “flight”. The classical stress response is a “fight or flight” (or freeze) behavior in response to acute life-threatening contexts, particularly predatory.

The conceptual framework for the healthy physical and mental adaptive changes induced by low levels of stress is the notion of hormesis, introduced above. It is a low level of a stressor that is sufficient for inducing the adaptive capacity to cope with it. However, a dose of the same stressor, which is too high will be toxic to the system, while the absence of or too low of a dose will fail to build adaptive resilience. The oxytocin component of the stress response imparts systemic anti-inflammatory effects, and it has receptors in the heart that promote cell repair and antioxidant systems (47). Oxytocin neurons release oxytocin in the brain as a neuropeptide whereas ADH neurons in the brain release this neuropeptide under conditions of aggression. These effects and the actions mentioned above involving brain regions including the prefrontal cortex, hippocampus, and amygdala that promote the cognitive qualities to enhance human connection, are an integral component of the psychogenic stress response when it is in the favorable hormetic zone. The application of hormesis to phytonutrients, as stated above to induce antioxidant response elements on genes, highlights the ability of a human biological system to resist the pro-inflammatory and pro-oxidant toxicity. Most significant is the advantage of generating a predominant healthy anti-inflammatory effect on physiology. However, analogous to what is a healthy type and dose of psychogenic stressor for one human being compared to another, a given type of phytonutrient that is physiologically healthy for humans may be toxic to other species of organisms that feed on plants. In fact, it also may be toxic to some humans with impaired specific detoxification enzyme capacity. Hence, phytonutrient chemicals are an evolutionary natural pesticide (48).

2.2.3 Stress through the Physiological Fitness Landscape Homeostasis, allostasis, and allostatic overload are presented through the lens of a Physiological Fitness Landscape, which is a quantitative measure of the state of health or disease for each individual represented by a multi-dimensional topography (Figure 2.1). Each axis in this space of control parameters

represents a potential stress factor that can be applied to the organism. For example, one such parameter can be nutritional intake, another physical exertion and yet another the concentration of a xenobiotic in the bloodstream. Creating a detailed map of the Physiological Fitness Landscape for each person is still a distant goal but it could be achieved in the coming decades. Navigating this map could lead to a rationally designed choice of a promising target for personalized clinical intervention or indeed a time-dependent therapeutic plan (Figure 2.10). What factors contribute to the transition from health to disease?

The concept of a Physiological Fitness Landscape is borrowed from physics, a comparatively far more natural scientific discipline than biology, in order to better understand biological systems. This way of conceptualizing the human body, on the spectrum of healthy and diseased states, could be especially useful in the context of medicine, where these insights may have the greatest impact on human life. I believe that the implications of this conceptual framework and its already demonstrated applicability to physiology will have Nobel Prize-winning potential. The compartmentalization of scientific disciplines, particularly clinical medicine, from the branches of physics, should be recognized and answered with collaborative endeavors. The deeply embedded separation of scientific disciplines is extraordinary, and we believe it is a tragic oversight that this model has not yet been invoked and implemented into the standards of clinical medicine. For example, by homing in on various aspects of the stress response in the context of the metaphorical Physiological Fitness Landscape, metabolic susceptibility states for disease can be identified as the control and order parameters for phase transitions from a healthy to a diseased state. Further, the trajectory to chronic disease may be predicted based on sophisticated mathematical models of these parameters and their attractors. This has profound implications for both diagnostic and therapeutic purposes. Critical points whereby homeostasis is maintained may represent the threshold for phase transition from a normal to a diseased state and predictions can be made regarding this transition's reversibility or irreversibility, which would be of enormous clinical value. Thus, the model of Physiological Fitness Landscape can serve as a critical tool and strategy to the development of therapeutic interventions capable of targeting control parameters and changing the trajectory of order parameters from susceptibility states or reversible stages of disease to healthy states. Which control and order parameters play a key role in the transition from healthy and diseased states? What are the mediators of these parameters?

2.2.4 The Effects of Stress on Synchronized Physiology and Metabolism Human health is bolstered and undermined by three key intrinsic (the psychogenic stress response, microbiota, circadian

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FIGURE 2.10  Neuroendocrine and autonomic stress response. Both healthy and unhealthy stressors engage the neuroendocrine and autonomic stress response. If stressors are vitalizing and expectations match attainable goals, the prolonged and exaggerated stress response is inhibited, stress coping occurs, and resilience to future stressors increases. On the other hand, if stressors are devitalizing and expectations exceed attainable goals, the prolonged and exaggerated stress response is enhanced, stress coping strategies fail, and resilience to future stressors decreases. Microbiota, inflammation, and circadian cycles mediate these responses which can lead to allostatic load, allostatic overload and acceleration from healthy to disease states.

metabolism/physiology) and extrinsic (stressors, social support systems, diet, and circadian patterns) control parameters. As will be discussed in Chapter 4, circadian patterns such as feeding/fasting, sleep/wake and light/dark cycles represent a fundamental pillar of intrinsic and extrinsic control parameters to human health and disease. Fasting/feeding, sleep/wake cycles and even cycles of social support systems have evolved to be in sync with the external light/dark cycles. This resonates with Darwinian survival of the fittest, the notion of fitness function and of the proposed Physiological Fitness Landscape as an overarching model of healthcare. Diet and the gut microbiota represent a second pillar of extrinsic and intrinsic control parameters, respectively, and will be discussed in more detail in Chapter 7. Finally, possibly one of the most underappreciated major control parameters of human health is the psychogenic stress response, the physiological response to psychological stressors that lead to physical illnesses. It is of powerful clinical importance as the psychogenic stress response is intimately tied to the body’s stress response to allostasis and ability to cope with stress. Optimal types and levels of stress can be a vitalizing or health-promoting force and lead to

resilience, but this is a delicate balance that can shift towards devitalizing or health-damaging stress with psychophysiological ramifications. The growing recognition of the importance of stress response to human health is in no small measure attributable to the seminal work of such giants in the field as Bruce McEwen (49) and Robert Sapolsky (50), whose work has demonstrated that activation of the stress response system leads to behavioral changes that can enable an organism to return to a state of homeostasis and thus increase its chances for survival. Their research helped to reveal the intricacies of the stress response system and its interactions with neural circuits involved in emotion regulation, cognitive function, and behavior, as well as with the axes responsible for reproduction, growth, and immunity. Furthermore, stress system dysfunction, characterized by sustained hyperactivity and/or hypoactivity, has been correlated with various pathophysiologic states that include psychiatric, endocrine, and inflammatory disorders and susceptibility to such disorders. Free energy, associated bioenergetics, metabolism, and redox homeostasis are processes in physics and chemistry that unify

64 all three major intrinsic and extrinsic control parameters and underpin an individual’s state of health or disease. It follows that the most upstream order parameters of physiology, intrinsic control parameters referred to as secondary order parameters, or the interpretation of the living experience, which may represent the stress response, the gastrointestinal microbiota and the endogenous circadian molecular clocks of metabolism and physiology that exist in virtually every cell of the body. The beautiful and exquisite organizational complexity of a living system, and certainly of the human being, invokes power of non-classical physics that explains our metabolism as the quantum manifestation of energy production. This in turn is responsible for synchronization and coherence across spatial and temporal scales of biological and physiological function. For example, allometric scaling laws of metabolism scale the metabolic rate (MRate) with weight/mass (M) according to the equation MRate = ɑMβ, with the coefficient α depending on the mode of energy production and exponent β for humans having a value of 3/4 uniformly across mitochondria in the cells in the setting of optimal health (51). This equation with the scaling exponent of 3/4 describes the body energetically working in the regimen of quantum metabolism (52). However, like the allostatic threshold, there is a “takeover” threshold at which the β scaling exponent changes and the metabolic rate efficiency slows down. This threshold pertains to the energetic overload of mitochondria from excess caloric intake. The disturbed composition of microbiota disrupting hormonal, autonomic nervous system balance and other parameters of allostasis amplifies and exaggerates the neuroendocrine and autonomic stress response. The consequences extend to disrupted sleep and dietary patterns and can even affect sociability. Together, there is a feedforward and pernicious perturbation of redox homeostasis impairing mitochondrial function alongside increased inflammation that deteriorates the quantum metabolic mode of energy production driving it toward isometry. This process changes the β exponent of the allometric scaling law of metabolism from 3/4 to 1, which causes the reduction in metabolic rate efficiency and metabolic health. In other words, for a given mass unit of the body, more energy is required to maintain its metabolic activity to achieve the goal state of homeostasis. To conclude this section, time and metabolism are interdependently interwoven in biological systems because the efficiency of the metabolic cycle of ATP (adenosine triphosphate) production is the fundamental unit of time in a living system. A decline in the coherence of energy production is tantamount to the reduced synchronicity of circadian oscillations in the body as well as the shorter and longer cycle processes, ultradian (less than 24 hours) and infradian (greater than 24 hours), respectively, to which they are coupled across temporal and spatial hierarchical scales of biology and physiology. Hormone receptors are regulators of both metabolic genes as well as clock genes and lie at the intersection of metabolism and physiology. Thus, in the presence of emotional or physical stressors that disrupt hormone receptor signaling, energy transfer is further thrown into disarray (see Chapter 3 for more detail). Thus, both time and stress can be interpreted as a reduced efficiency in the hierarchical organization of the biological system. Furthermore, a compounding effect arises as the stress

Metabolism and Medicine response system accelerates the process of senescence as well as the associated chronic diseases of aging. This is important because it highlights an intrinsic control parameter–– the psychogenic stress response––in a Physiological Fitness Landscape that can be therapeutically targeted for the purpose of promoting prolonged and successful aging fueled by a quantum metabolism regime of energy production.

2.3 A Modern-Day Stress Response Model 2.3.1 The Metabolic Demand of Stress How much of the total body energy does the brain consume when under stress?

Energy balance is maintained by rich interconnections to and within the hypothalamic region of the brain. The hypothalamus is the central regulator of neuroendocrine, autonomic, and metabolic physiology. All living systems, including human beings, routinely endure stress. The response to stress is metabolically demanding, and as a result, it must carefully calibrate the pathways of energy expenditure. In fact, the evolution of biological systems is purposed to optimize the stress response for a given ecological niche. In humans, the metabolic demand in the brain approximates 25% of the total energy intake despite representing less than 5% of total body mass (53). This is not surprising, however, given the cognitive demands of decision making in modern life. It may be that a nimble, vitalizing capacity to adaptively respond to stress and build resilience is a powerful basis for human post-reproductive longevity. Even in the hunter/gatherer period, humans were never the strongest or the fastest animal in the jungle, but they were the smartest, which explains the success of humans in achieving ascendancy on planet Earth. However, when acute stressors are not successfully resolved, serious physical consequences ensue. The brain is the top-down commander of total body health. The more (physical or mental) energy put into life, the greater the energy production by the body and the greater energy expenditure required by the brain (54). When the brain is energetically challenged, several metabolic processes occur, including 1) more ATP is produced, 2) ~30% of the energy is lost as heat, accompanying a higher redox state, and, 3) the higher ATP production leads to a largely proportional higher ROS (reactive oxygen species) formation produced by mitochondria (Figure 2.11). The higher the ROS formations, the higher the entropy production rate (EPR), which is synonymous with the rate of premature aging. Thus, we can deduce that the more energy put into life, the faster the body ages (55) (Figure 2.12). However, when too little energy is put into life, the levels of physiological challenge are too low, mitochondrial function in muscle and brain tissue is reduced leading to increased redox stress. Stress builds resilience in all living systems and at every hierarchical scale. Cognitive and psychogenetic stress is no different. The key is the notion of hormesis regarding the dose and duration of any type of stressor. For example, a small and

The Stress Response

FIGURE 2.11  Energetically challenged brain. Consequences of energetically challenging the brain include increases in ATP production, redox state, and ROS formation. *ATP = adenosine triphosphate; ROS = reactive oxygen species.

FIGURE 2.12  Advancing allostatic overload. Pathway from stress to allostasis to allostatic overload via feedforward self-amplifying loops accelerating the pace of aging. *EPR = entropy production rate.

acute oxidative stress dose might provide a sense of control, promoting vitalizing energy and resilience against a high EPR, whereas a large and prolonged oxidative stress dose might elicit a sense of helplessness, promoting toxic energy and a high EPR (Figure 2.13) (56). The predictability of a stressor is essential for coping and creating a sense of control that dictates the duration, severity, and context of the stress response. The nature of stressors has changed considerably over time for humans. Although unlike an existence of being constantly stalked by predators whereby one unsuccessful challenge results in death, human’s modern-day stressors can still lead to morbidity and shorter lifespans. Whether primarily cognitive, physical, or even an immune system auto-inflammatory process, a pathogenic psychophysiology emerges as a result of a pernicious cascade of inflammatory and redox stress. This alters chemical signaling and consequently impedes the flow of free energy through the dynamic interactions of metabolic pathways. This is the fundamental basis of most chronic diseases.

2.3.2 The Uncertainty Reduction Model What is an example of a strategy the brain uses to predict the likelihood that it will achieve homeostasis following a stressor?

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FIGURE 2.13  Stress dose and duration. The duration, severity and context of the stressor dictates a sense of control/helplessness and resilience mediated by EPR. *EPR = entropy production rate.

Much of our understanding of the stress response is due to the pioneering work of Bruce McEwen who introduced the term “allostatic overload”, discussed in previous paragraphs. One novel perspective on the state of stress places emphasis on uncertainty and lack of control, whereby stress arises when people are unable to predict an uncertain answer (57, 58). Unpredictable and uncontrollable stress contribute to the behavioral phenomenon known as learned helplessness. Learned helplessness is the maladaptive passivity following experience with uncontrollable events which can lead to anxiety, depression, and post-traumatic stress disorder (59). Learned helplessness is a default mode of survival and one learns to escape from helplessness by critical amygdala-frontal brain circuits via noradrenergic and serotonergic neurons. There is significant uncertainty to how an acute stress is best resolved in terms of our alternative options for controlling the stress, thus increasing cognitive load. Our ability to control an acute stress would shift the current state to some attainable state, which equals the goal state––homeostasis. Thus, the strain on our cognitive capacity is reduced, which equates to an adaptive or successful resolution of the stress. This perspective for defining and resolving stress is not only appropriate and relevant to the conditions of modern living, but it is rooted fundamentally in physics because it deals with mathematical probabilities. The brain integrates information to assess, in probabilistic terms, the risk versus reward of each of many alternative actions, to predict the likelihood of attaining a goal state, or homeostasis, that reduces the uncertainty of the strategy to the present challenge at hand. Importantly, this notion of uncertainty reduction is similar to entropy reduction of information. Biological systems are a product of entropy reduction, which requires work against the headwind of the second law of thermodynamics, that states that entropy in the universe is unidirectional, always increasing over time. In the quantum biology chapter of this book (Volume 1, Chapter 3), entropy reduction is discussed in terms of applying thought to information to create solutions. This is essentially equivalent to the notion of uncertainty reduction. One distinction is that the concept of uncertainty reduction per se does not seem to invoke quantum algorithms. However, the brain does indeed appear to take advantage of quantum phenomena at several levels, which include quantum metabolism, describing the quantum nature of energy production, as well as conscious cognition. The notion of consciousness or conscious cognition derives from the direction of dipolar oscillations of

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the constituent tubulin dimers of the microtubules within the neurons of the brain's cortex. By definition a quantum oscillation is originally a non-biased underscoring of the purity of the cognition per se. In the process of uncertainty reduction to resolve a state of stress, it is energetically demanding to reduce the information stored from prior experiences into an adaptive response that returns the individual to the goal state––homeostasis (57). This general understanding of information reduction as entropy reduction is conceptually abstract; however, it is nothing more than the entropy that comprises the exquisite and beautiful complexity of biological systems at all organizational scales. What neural connections, neuroendocrine signaling pathways and neurotransmitter systems are involved in the stress response?

2.4 The Neural Circuitry of Stress 2.4.1 Interconnections When cognitive uncertainty cannot be resolved and thus the adaptive return to the goal state is hindered, anxiety supervenes. Although a complex biological response, the state of anxiety may be understood in terms of binding of cortisol to GRs and mineralocorticoid receptor (MRs) neuron cells of particular structures in the brain including the prefrontal cortex (PFC), amygdala, and hippocampus, where executive function, emotion regulation, and memory predominantly reside, respectively. In a healthy state, cortisol levels cross the blood brain barrier where they gain access to receptors in the brain. If cortisol levels are only moderately elevated, cortisol has a higher binding affinity to MRs relative to GRs (Figure 2.14). When this occurs, it leads to the growth of synaptic dendrites, that is, synaptic plasticity (60) in the PFC, hippocampus, and amygdala (see the section on synaptic plasticity that follows). Intrinsic excitability of the neurons, or neuronal plasticity, also occurs in the PFC and hippocampus, however, in the amygdala, contrasting patterns of excitatory and inhibitory responses occur. Conversely, when cortisol levels are wildly

FIGURE 2.14  Stress paradox. The hippocampus shows an inverted U shape dose–time response to stress. Acute stress can enhance synaptic transmission, promote learning and memory, and build resilience while chronic stress (prolonged exposure to stress and activation of the stress response) can have the opposite effect suppressing synaptic transmission and impairing adaptation to stress.

elevated, as in a state of stress, cortisol binding to the low affinity GRs prevails and opposes the function of the MRs. Consequently, over time there is atrophy of the dendritic branches of both the hippocampus and PFC but a hypertrophy of dendritic branching in the amygdala (61–64). After a reduction in elevated stress hormone levels these detrimental synaptic changes observed in the hippocampus and PFC may be reversed. However, even following a period of low levels of stress, the hypertrophy initiated in the amygdala persists (65, 66). These morphological changes disrupt the adaptive regulation of cognition, emotion regulation, and memory and impair the networks capacity to respond to subsequent stressors and challenges by promoting cognitive and emotional adjustments for adaptation (Figure 2.14). Thus, a deeper understanding of the function and interconnections of these brain structures is necessary for understanding this modern-day stress response model proposed by McEwen and colleagues. For example, these three critical brain regions connect with and influence the activity of brain regions implicated in reward, motivation, and neuroendocrine signaling.

Psychogenic stressors build emotional resilience by inducing neurotrophic effects of neurons involved in cognition and memory including the PFC and hippocampus, respectively, which put the brakes on the emotional centers of the brain, especially the amygdala.

2.4.2 Neuroendocrine Response to Stress and Insulin Resistance Cortisol is the allostatic regulator of the stress response designed to maintain homeostasis. Stress-induced cortisol activation of GRs and MRs leads to several downstream effects (Figure 2.15; adapted from (67]). Mechanistically, the differential effects of GRs and MRs activation and resultant gene expression reflect opposing actions on the transcription of proteins such as brain-derived neurotrophic factor (BDNF), which enhances neuronal plasticity. These effects are neuron cell type dependent whereby the low affinity GRs genomic effects antagonize neuronal plasticity in the hippocampus and PFC, while enhancing it in the amygdala. Conversely, the opposite occurs in the case of predominantly high affinity MR activation. Accordingly, this allows the principle of hormesis whereby at some relatively low dose of exposure to glucocorticoids, for example a dose to that which maximally activates the MRs, has an optimal effect. Conversely, when glucocorticoid levels are too low, memory consolidation and retrieval is suboptimal. This is referred to as the MRs:GRs balance (68). In particular, the membrane actions by MRs on glutamate release (69), GR on endocannabinoid release (70), and classical gene-mediated action of MRs and GRs (Chapter 3) are critical for the control of neuronal excitability and endocrine control. On the other hand, at high doses of exposure, such that which maximally activates GRs, toxicity occurs in terms of promoting an exaggerated chronic stress response and chronic disease risk as well as acutely to the rate of learning with impaired memory consolidation and memory retrieval (60).

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FIGURE 2.15  Stress effect on hippocampal neurons. Glucocorticoids bind to both glucocorticoid and mineralocorticoid receptors and can have immediate and delayed downstream effects on neurotransmission involved in memory consolidation and retrieval. Source: adapted from (67). *AMPAR = α-ami​no-3-​hydro​xy-5-​methy​l-4-i​soxaz​olepr​opion​ic acid receptor; GR = glucocorticoid receptor; MR = mineralocorticoid receptor; NMDAR = N-methyl-D-aspartate receptor.

Glucocorticoid signaling during acute stress and uncertainty must be robust enough to reduce insulin secretion from pancreatic islet cells and to promote insulin resistance at the insulin receptor level. Peripheral insulin resistance is induced in skeletal muscle and adipose tissue, which impairs insulinregulated glucose transporter type four (GLUT4)-mediated glucose uptake thus promoting greater noninsulin dependent GLUT1 glucose transport across the blood brain barrier (71, 72). This provides the impetus for energy resources like glucose and to a lesser extent, ketones, and lactate, to fulfill the high metabolic demands presented during a state of acute stress, namely the release of neurotransmitters and catecholamines, throughout the brain. (53) founded the concept of the “Selfish Brain” whereby the neurophysiological stress response generates energy production in the periphery, but the brain is able to outcompete peripheral tissues for these resources.

2.4.3 Stress and Norepinephrine The catecholamine norepinephrine is primarily produced in the locus coeruleus (LC), a nucleus in the brainstem involved in the physiological response to stress. Presynaptic release of norepinephrine from neurons in the LC, if co-occurring alongside increased excitatory glutamatergic activity, binds to both

the high affinity presynaptic adrenergic alpha-2 receptors as well as low affinity alpha-1 and beta presynaptic receptors. Analogous to the GRs and MRs, the low affinity and high affinity adrenergic receptors have opposing actions. While the high affinity adrenergic receptors reduce the probability of glutamate release, low affinity adrenergic receptors, which prevail during a state of acute stress when norepinephrine release is robust, increase the probability of glutamate release. There is also evidence that glutamate amplifies noradrenergic effects and enhances post-synaptic plasticity (73) (see the section on synaptic plasticity that follows). A similar relationship exists with presynaptic norepinephrine release onto inhibitory GABAergic (gamma-Aminobutyric acid) neurons in the LC. During a state of stress, norepinephrine release is robust and low affinity alpha and beta presynaptic receptors are preferentially activated, which increases the release of GABA, the primary inhibitory neurotransmitter. Conversely, during a normal state, norepinephrine preferentially binds to high affinity alpha-2 presynaptic receptors, which does not promote further GABA release. In both cases of norepinephrine binding to low affinity alpha-1 and beta-3 receptors on highly activated GABAergic and glutamatergic neurons, the overflow of GABA and glutamate, respectively, causes positive feedback loops on norepinephrine release (74).

68 Both the autonomic and the hormonal branches interact interdependently with the immune system. Increased adrenal cortisol release promotes the upregulation of beta-2 adrenergic receptors on immune cells. Furthermore, beta-2 adrenergic receptors signal the increased GR-induced gene expression. This coupled autonomic sympathetic nervous system and cortisol activity in general moderate inflammatory responses (75, 76). In the setting of the prolonged stress response, immune cell resistance to cortisol suppression develops. This is responsible for much of the pro-inflammatory cascading that occurs in the studying of allostatic load in the setting of pathogenic prolonged stress, i.e., allostatic overload (Figure 2.16). Stress-induced prolonged activation of this catecholamine circuit can be detrimental. Prolonged release of catecholamines can reduce the effects of glutamate and GABA on mood, creating a negative feedback loop between emotions and physiology leading to chronic inflammation of organs and the failure to adapt. Several drugs target or interact with norepinephrine to mitigate the physiological effects of acute stress, such as beta-blockers (block beta adrenergic receptors), however the off-target effects of these drugs often cause uncomfortable and even life-threatening side effects (77).

2.4.4 The Neural Circuitry of Uncertainty Information is uncertainty reduction, defined by mathematician and engineer Claude Shannon (78). The brain infers probable cause from an effect using the sensory information it receives. However, information such as that derived from our senses, has no inherent meaning in the absence of context and active thought. This requires the input of energy. In the setting of uncertainty, cerebral function requires a high metabolic demand to link organized sensory input with all available information. This dictates necessary vigilance and

FIGURE 2.16  Autonomic and hormonal response to stress. Stress activates both autonomic and hormonal systems that can immediately activate or inhibit the immune system response.

Metabolism and Medicine focus with rapid learning assimilated into decision-making solutions. The regions of the brain that appear fundamentally responsible for carrying out this uncertainty model of the stress response initially appears to involve the anterior cingulate cortex (aCC), the lateral PFC, and ventromedial PFC (vmPFC); including orbitofrontal cortex (OFC) and presupplementary motor area (79). Connectivity between which emotion-generating and which emotion-regulating brains regions is critical for decision-making under stress?

The aCC is a cortical region that forms a network with prefrontal cortical structures that activates when we are presented with a new situation and the brain must prepare to act immediately. Together, the amygdala and the OFC guide decisionmaking in an uncertain environment, using past experiences. The aCC is connected to the “cognitive” PFC and “emotional” subcortical limbic regions such as the amygdala and hippocampus. The aCC receives dopaminergic inputs from ventral tegmental area (VTA) neurons involved in reward motivation pathways and projects directly to the spinal cord and is thus able to integrate risks and rewards of a given behavioral response (80). When uncertainty arises about what the choice of action should be, activity in the amygdala correlates with that in the aCC. Correlated activity in the amygdala and the aCC regions project to core mediators of the stress response, the LC, the ventral medial nucleus (VMN) and the paraventricular nucleus (PVN) of the hypothalamus, which in turn activate the sympathetic nervous system and the HPA neuroendocrine axis. The activation of these systems and of the PVN is regulated by the suprachiasmatic nucleus (SCN) of the hypothalamus. The SCN also activates the dopaminergic system and controls the daily sleep-wake rhythm via connections to other hypothalamic nuclei (subparaventricular zone [SPZ], dorsomedial hypothalamus (DMH), and ventrolateral preoptic nucleus [VLPO]). Direct neuroanatomical connections between SCN and the arcuate nucleus (ARC) regulate food intake and play a role in the rewarding aspects of food (Figure 2.17; Figure adapted from (81, 82). The SCN is a masterclock that orchestrates several daily rhythms and peripheral clocks that affect multiple processes including glucose metabolism, food intake, sleep-wake behavior, insulin sensitivity, and energy expenditure (83) (See Section 2.7.1.1). SCN directly inputs to orexin neuropeptides found in lateral hypothalamic regions to regulate food intake (84). Orexin neurons are dense neurons that send projections throughout the brain and spinal cord. Orexin neuropeptides are released into synapses from neurons projecting from the PVN into the VTA located in the pons and into the medulla, both located in the brain stem. The VTA sends dopaminergic inputs into the limbic system encoding pleasure and reward. The medullary nuclei such as the nucleus tractus solitarius project dense neurons in the serotonergic dorsal raphe nucleus and the noradrenergic LC. These nuclei are involved in promoting arousal, attention, and vigilance (85). The regions of the PFC (including lateral and ventromedial portions) interconnect and exert executive control on behavior

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FIGURE 2.17  SCN and other hypothalamic nuclei. The SCN is the central clock that orchestrates the parasympathetic nervous system, sympathetic nervous system, pituitary glands, the dopamine system, and other hypothalamic nuclei (PVN, SPZ, DMH, VLPO, ARC) that coordinate the stress response, sleep-wake cycles and food intake. Source: adapted from (81). *ARC = arcuate nucleus; DMH = dorsomedial hypothalamus; HPA = hypothalamic-pituitary-adrenal axis; PVN = paraventricular nucleus; SCN = suprachiasmatic nucleus; SPZ = subparaventricular zone, VLPO = ventrolateral preoptic nucleus.

through complex cognitive processes (86). Connectivity between the emotion-regulating PFC and emotion-generating limbic regions such as the amygdala is critical for decision-making under stress. These regions communicate with the aCC and are involved in abstract thinking and concept formation as well as perceptive thinking, error-monitoring, intuitiveness, and memory (Figure 2.18). Additionally, they are concerned with goal-directed behavior and internal drive under the influence of the limbic system. Executive thinking integrates subconscious cognitive dimensions, such as empathy and compassion, into conscious awareness, such as planning an intended movement, but also entails deep realizations of societal interactions and many aspects of social behavior.

2.4.5 Uncertainty and Chronic Anxiety How does the brain make predictions of future outcomes under conditions of uncertainty?

The neural circuitry of uncertainty and resulting behavioral output has the potential to put the brakes on emotional, and hence visceral, autonomic, and neuroendocrine output. These brakes are applied when uncertainty is resolved through cognitive processing in the PFC, an energy expensive operation through the LC. A primary function of the LC is to generate an adaptive state of arousal via norepinephrine release throughout the brain and brainstem. The LC projects to the PFC where it secretes norepinephrine (Figure 2.2). In a healthy state, these neural connections can transmit information and orchestrate cellular activity to integrate past and present experiences into a solution. This eliminates uncertainty and prevents a shift towards uncontrollable stress.

This is the theoretical construct of the Bayesian Brain (87). The brain's ability to master uncertainty is required to prevent allostatic overload of activated neuroendocrine and autonomic responses purposed to supply the high metabolic cost of cortical neurotransmission. The lateral and frontal orbital PFC allows uncertainty reduction to occur that has predictive capacity due to the integration of past and present sensory input and experiences. How can uncertainty lead to chronic anxiety?

If information transferred and integrated across the cortical circuitry of the regions of the PFC is not capable of reducing the uncertainty that resolves the decision-making process and discrepancy between the current and goal states, emotional distress supervenes. Under conditions of high or chronic stress, increased release of norepinephrine in the PFC impairs cognitive functioning. Subsequently, a positive feedback loop occurs between the frontal cortical regions and the LC. Consequently, failure to achieve a solution (certainty) to a problem, a state of uncertainty can shift towards a chronic state of anxiety and the organism moves away from homeostasis (79). Chronic psychophysiological stress becomes the driver in vital organ systems such as the brain, causing cognitive decline. An alternative way to eliminate uncertainty, and thus reduce anxiety, could be to lower expectations of the desired goal state and instead choose other currently available alternatives. By lowering expectations, a solution to the problem, a state of certainty often becomes possible. How is resilience and susceptibility to stress mediated by neuronal plasticity?

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FIGURE 2.18  Neuroanatomy of stress response. The stress response involves complex coordination and communication between several brain regions mostly in the prefrontal cortex (PFC, lPFC, vmPFC, OFC), subcortical/limbic areas (aCC, NAcc, Hyp, Amy, Hipp) and the brainstem (VTA, LC) regions. *aCC = anterior cingulate cortex; Amy = amygdala; Hipp = hippocampus, Hyp = hypothalamus, LC = locus coeruleus; lPFC = lateral PFC; NAcc = nucleus accumbens; OFC = orbitofrontal cortex; PFC = prefrontal cortex; vmPFC = ventromedial prefrontal cortex; VTA = ventral tegmental area.

Chronic stressors to which certainty states, or solutions, have been habitually achieved, is required to build resilience. This resilience is mediated by neuronal plasticity of the PFC and hippocampus. Alternatively, chronic stressors to which certainty remains unresolved results in chronic anxiety, exaggerated stress responses, psychopathology, and pathophysiology. These disturbances are rooted in atrophy and the loss of neuronal plasticity in the PFC and hippocampus accompanying increased neuronal plasticity in the amygdala (88).

2.4.6 The Neural Circuitry of Energy Expenditure under Stress There is a rich network of redundancy or “fail safe” physiologic mechanisms for providing a continuous supply of energy to accommodate the high metabolic demands of the brain, particularly during acute stress that requires active problem solving. This is a paragon example of the capacity of the body to invoke allostatic mechanisms to maintain homeostasis. The

brain, which is the principal organ of allostasis, hence deserves the title “Selfish Brain” since the allostatic changes it produces are self-serving to maintain its own homeostasis (53). Synaptic transmission, the main energy-consuming process in the brain, is highly energetically demanding (89). The necessary ATP is provided by the mitochondria. In fact, the highest density of mitochondria within the brain are found in synaptic dendrites. BDNF plays a critical role in the regulation of mitochondrial transport and distribution. The expression of BDNF in response to stress is context-dependent and neuronal cell type dependent. BDNF is optimally expressed following limited duration moderate stress (Figure 2.19). BDNF mediates phosphorylation of GRs and cortisol liganded GRs regulate mitochondrial function. GRs induce the gene expression of mitochondrial respiratory oxidative phosphorylation machinery encoded by nuclear and mitochondrial DNA. In the context of prolonged or severe cortisol elevation (i.e. uncontrollable perceived stress), BDNF is not expressed and thus, GR signaling does not occur (90). This underpins the phenomenon of cortisol resistance (91, 92). Cortisol resistance explains the concept of burnout (Figure 2.20) (93). The

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FIGURE 2.19  Mitochondria and GR signaling. Mitochondria provide the required energy for GR-induced synaptic transmission mediated by BDNF under moderate stress conditions. *BDNF = brain-derived neurotrophic factor; GR = glucocorticoid receptor.

upregulation of corticotropin-releasing hormone (CRH) (96). Like the CRH and the HPA axis, the LC mediates hypothalamic and pituitary release of growth hormone releasing hormone (GHRH) and growth hormone, respectively. Growth hormone release is triggered by reduced circulating glucose to replenish the high demand required for metabolic processes. Both cortisol and growth hormone contribute to insulin resistance, fatty acid oxidation, gluconeogenesis, and ketogenesis. Furthermore, neurons of the hypothalamus nucleus project to the brain stem mediating the upregulation of the sympathetic nervous system (97). The sympathetic nervous system also maintains energy availability to promote the release of another catecholamine, epinephrine, from the adrenal medulla, which amplifies the sympathetic nervous system action. It does so by acting on adipose tissue to promote lipolysis. This results in release of free fatty acids for use in peripheral tissues such as the heart and skeletal muscle sparing glucose to be consumed by the brain that cannot utilize free fatty acids for bioenergetic needs. The glycerol from lipolysis is garnered in the liver to produce glucose by gluconeogenesis (Figure 2.21) (98). How does the brain generate energy for transmitting signals?

2.5 Motivation and Reward

FIGURE 2.20  GR signaling and cortisol resistance. Under prolonged or severe stress conditions, BDNF is not expressed, thus, GR signaling does not occur leading to cortisol resistance and burnout. *BDNF = brainderived neurotrophic factor; GR = glucocorticoid receptor.

relationship of cortisol regulation of mitochondrial function also explains the endocrine energy that occurs in the setting of adrenal insufficiency. The sympathetic nervous system is the major driver for generating energy to maintain information transmission across synapses in the brain underpinning cognitions including the most energy-consuming branch of the stress response––the LC norepinephrine response (94). The sympathetic nervous system generates energy in a number of ways including inhibiting insulin release (beta cells of the pancreas), enhancing glucagon release (alpha cells) and, promoting glycogen (glycogenolysis) and glucose (gluconeogenesis) production in the liver driving hepatic glucose output (95). Increased sympathetic tone acts on skeletal muscle to downregulate GLUT4 mediated glucose transport, a hallmark of peripheral insulin resistance. Cortisol and growth hormone are part of a slower acting counterregulatory system shipping glucose utilization away from peripheral tissues to support the metabolic demands of the brain. Moreover, norepinephrine from LC neurons mediates these processes. For example, norepinephrine contributes substantially to the HPA axis generation of cortisol and the

One of the main themes of this book is to use physics as inspiration to better understand biology. In this vein, force is a fundamental physical quantity that accelerates the motion of massive objects comparable to how motivation is a psychological trait that drives human behavior. While force can be described by its magnitude, direction, and duration, motivation can be similarly characterized by intensity, focus and persistence. Motivation drives behavior and these behaviors can be rewarded. While rewards that are intrinsically motivating are inherently pleasurable (hedonic) and intrinsically rewarding, extrinsic rewards, for example money, being unlearned provide no innate joy or lasting value. Intrinsic rewards such as food, water, and sexual gratification are naturally motivating and serve as tangible stimuli that reinforce the experience because their recollection is learned to be associated with pleasure. Unfortunately, much the same can be said for an addictive drug such as a narcotic, cocaine, amphetamine, tobacco, and alcohol. How does the reinforcement of a reward drive a particular behavior?

The emotional memory of the reinforcement of reward is the motivation responsible for the attribute of “wanting”. Thus, behavior is driven by the desire or “wanting” of the reinforcement of the reward, especially when the reward is salient. Reward salience (also known as incentive salience) is a quality of the reward standing out among the totality of sensory information. This is an adaptive evolutionary mechanism

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FIGURE 2.21  Short-term and prolonged stress. The effects of short-term and prolonged stress on the adrenal glands and their downstream effects on metabolic and bioenergetic functions. *ACTH = adrenocorticotropic hormone; CRH = corticotropin-releasing hormone

developed in animals with limited perceptual and cognitive capacity that allows honing attention in on the intrinsic rewards necessary for survival and promoting goal-directed behavior (99). In contrast to motivation that equates to “wanting”, reward equates to “liking”. However, there are circumstances whereby “wanting” does not equate to “liking”, such as in addictive behavior seeking to avoid the discomfort of withdrawal and negative emotions and promote negative reinforcement neural mechanisms. In this case, motivations shift from goal-directed to hedonic (100).

2.5.1 The Neural Circuitry of Reward The brain’s reward circuit mediates reinforcement of a reward, such as food, sex, or a drug, specifically through direct neural connections between the ventral tegmental area (VTA) and the nucleus accumbens (NAcc). The neurotransmitter dopamine is primarily produced in the VTA, a cluster of nuclei in the midbrain. Dopamine neurons project directly from the VTA of the midbrain into the NAcc where they synapse. The NAcc, or “reward center” of the brain, located in the ventral striatum, receives the dopaminergic signal from the VTA and mediates the effects of the reward through other

neurotransmitter systems and brain regions. For example, the amygdala and hippocampus are critical for learning and remembering if an experience is rewarding. The amygdala is crucial for the mnemonic associations pertaining to the emotionally salient aspects of the reward, while the hippocampus is more involved in the contextual aspects of such memories (i.e., the environment in which the rewarding experience occurred in) (101–104). The hypothalamus coordinates the physiological need for the reward. The LC, the PFC, as well as the VTA itself act as regulatory regions modulating mood associated with the reward, the decision to seek the reward, and the self-regulation of dopamine release through a negative feedback loop, respectively (105). While stated very simply here, the functions of these regions are extremely sophisticated, highly interrelated, and critical for an individual’s response to a rewarding stimulus. The reward circuitry is also sensitive to novelty and expectation of rewards (106, 107). When rewards exceed expectation, pulses of dopamine from the VTA neurons surge into synapses within the NAcc. Subsequent expectations for reward are sufficient to induce a dopaminergic response and the driving motivational force for the reward becomes stronger (108). This controls the central survival behavior such as the desire to eat, drink, and have sex. The good feeling associated with

The Stress Response dopamine related to the expectation is the motivating chemical flux, which is distinct from the sensation of the reward that is anticipated. What brain regions are involved in reward and reinforcement? What brain regions are involved in detecting a threat or stressor? How do these brain regions interact to motivate behaviors?

The NAcc appears to be the most prominent site in conveying the sensations of reward and reinforcement as it is the principal target of dopaminergic neurons. The NAcc directly connects with the amygdala and is considered a component of the extended amygdala. While both structures play a role in conferring the sensation of pleasure, emotional processing, motivation, and learning, the amygdala also has a predominant role in fear and negative emotion (109–112). Thus, the amygdala is critical for the evaluation of a threat or stressor and learning whether a particular experience was rewarding or aversive. The bed nucleus of the stria terminalis and olfactory tubercle are also part of the extended amygdala due to their functional overlap emotional processing of rewarding and aversive stimuli. The NAcc is not only strategically situated in the brain to receive limbic information from the amygdala, hippocampus, and PFC and but also to convert this

73 information to motivational action through connections with the motor system (see [113] for review). Neurons of the amygdala synapse with hippocampal neurons, which attach emotion to memories of significant experiences. Such emotion-charged memories of an initial experience of a pleasurable consumptive or other reward serve as a powerful motivator with dopamine neurotransmission from VTA neurons synapsing with NAcc, which in turn synapses with the “emotion association area” of the brain, the amygdala (114). The memory from these emotionally charged experiences such as food, sex, and drug-taking are rooted in these synaptic connections that continues to release dopamine from neurons of the VTA. However, this forms the basis for the enduring vulnerability to maladaptive and unhealthy behavior such as addictions if regulatory areas such as the PFC and VTA are compromised. Another main target of the dopaminergic neurons in the VTA is the PFC. The PFC in turn projects back to the VTA as well as to the NAcc via noradrenergic/serotonergic projections modulating activity that weighs the cost against the reward of activating a particular behavior (Figure 2.22). The PFC calibrates cost in terms of availability of the reward, energy expenditure required to attain reward and the associated risk of obtaining the reward. That is, the PFC determines if it's worth the effort. Such decision-making analysis is an important part of executive function, a hallmark of the PFC (115).

FIGURE 2.22  Neural circuitry of reward. The most notable brain reward pathway involves the mesolimbic dopamine system by which the ventral tegmental area (VTA) projects to the nucleus accumbens (NAcc), which is part of the ventral striatum, as well as the prefrontal cortex (PFC). Noradrenergic, serotonergic, glutamatergic, and GABAergic projections regulate the brain’s reward response, which further impacts reward-related behaviors. *GABA = gamma aminobutyric acid; NAcc = nucleus accumbens; PFC = prefrontal cortex; VTA = ventral tegmental area.

74 However, when PFC function is impaired by a salient reward, its capacity to govern executive function over reward motivation behavior is compromised. Chronic and persistent elevated motivation to obtain a reward, decreases dopamine inputs to the PFC which impairs executive function. This is manifested as atrophy of dendritic branches and is largely mediated by the effects of cortisol and insulin. This represents a susceptibility state for addictions as hedonic rather than goal-oriented motivations prevail. The motivated behavior to harmful addictive substances is analogous to that of food, water, or sexual activity, all of which have limited governing cognitive regulation by the PFC. Instead, they primarily represent subservient subconscious motivated behavior. Teleologically, such motivation enhances survival and is persistent not only when the expectation is met with disappointment but even if the expected stimulus is aversive (116). Appetitive behavior of food consumption is fundamentally rooted in the same chemistry that drives other reward salience driven pathological addictive motivational patterns of behavior. Furthermore, food addiction and associated morbid obesity is an inherent vulnerability for individuals with a Physiological Fitness Landscape of control and order parameters of the chronic exaggerated stress response. The engaging pursuit to accomplish the goal-oriented challenges that synchronize with one’s inspired core values and strengths is arguably fundamental to fulfilling the joy of the living experience. Such goal-oriented motivations are cognitive top-down processes that regulate emotion from becoming chronically exaggerated. Alternatively, the stress response often becomes a central devitalizing control parameter of human disease. This is mediated by the disseminated subclinical allostatic burden of inflammatory and redox stress. Accompanying this process is the deterioration of free energy into dissipated heat lost from the body’s cells. In turn, proinflammatory cytokine signals and cortisol access the emotional regions of the limbic system in the brain upregulating their neural activity. Conversely, cortisol and pro-inflammatory cytokines down-regulate the activity of the hippocampus, where memory formation and consolidation occur, as well as the higher cognitive center, the PFC (117). The PFC is important for a wide range of functions including complex cognitions, personality expression, executive function, rational thought and decision-making, social intuition, empathy and compassion. These contrasting effects are mediated by differentially promoting synaptic plasticity and neuroplasticity in cognitive versus emotional components of the limbic system. In the presence of cortisol, hippocampal neurons are damaged, and their function becomes compromised. Further, hippocampal neurogenesis and proliferation and migration of new neurons is suppressed by chronic stress and high cortisol. In the case of cortisol absence, apoptosis of hippocampal neurons is promoted (118) (Figure 2.23). Furthermore, the activated pathological stress response disturbs all branches of the diet as a control parameter of health and disease (Figure 2.24).

2.5.2 The Reward Circuitry, Stress, and the Uncertainty Model The previously described strategy of reducing the goal state to an attainable state lessens the burden of uncertainty and

Metabolism and Medicine

FIGURE 2.23  Stress and cognitive decline. Prolonged allostasis and elevated levels of cortisol result in GR-mediated hippocampal damage (and apoptosis in the absence of cortisol) that perpetuate a feedforward loop further prolonging allostasis. *GR = glucocorticoid receptor.

FIGURE 2.24  Stress and anxiety and depression. Prolonged allostasis disturbs gut microbiota, decreasing neurotransmission and resulting in the development of neuropsychiatric disorders such as anxiety and depression further prolonging allostasis (see Chapter 7). *GABA = gamma aminobutyric acid.

anxiety. This is consistent with an interesting phenomenon known as “hedonic treadmill”. This means that material rewards such as wealth serve only to increase future expectations such that the level of happiness per se remains constant (119, 120). Conversely, conditions of relative poverty reduce expectations serving to avoid the loss of happiness. This latter condition invokes the notion of habituation, the diminishing of a response. Social connectedness and networks of family and friends are critical as support systems as well as to provide a more robust resource availability for problem solving, enhancing the potential to resolve problems. It is also the latter that seems to primarily confer an effect on reducing motivating addictive behavior much the same way that the former promotes primarily satiety in the obese insulin resistant state. What happens when the brain is compromised by stress?

The Stress Response In the event of repetitive mild stressors, the repetitious recruitment of neuronal circuitries of the stress response mechanism drives toward an attainable goal state and away from a state of uncertainty. These processes mainly involve synapses from the PFC sending signals to and from the hippocampus and mediating the successful coping and adapting to the stressor. This mechanism builds resilience and the sense of purpose fundamentally strengthening synaptic connections as a result of structural plasticity (121) (Figure 2.25). However, under conditions of chronic stress, the brain’s ability to resolve problems is compromised primarily due to atrophy of dendritic branches mediated by the effects of cortisol and insulin (122). The excess of the circulating cortisol entering the brain causes synaptic atrophy of dendrites in hippocampal and prefrontal cortical neurons and conversely, an increase of synaptic plasticity in the amygdala. This also occurs in persons with hyperinsulinemia and consequent neuronal insulin resistance independent of the presence of diabetes. Accordingly, cognitive decline ensues and is accompanied by diminished cerebral glucose metabolism. The effects of hyperinsulinemia and insulin resistance are correlated with a reciprocal relationship involving inflammatory cytokine effects provoking the HPA stress response. The resulting increased cortisol levels in turn stimulate insulin resistance, perpetuating the crosstalk in a positive feedback loop. Alternatively, hypercortisolemia may result from a primary chronic emotional stress or some peripheral inflammatory stress that instigates peripheral insulin resistance/hyperinsulinemia that in turn drives further the

FIGURE 2.25  Goal-oriented behavior. Following the successful resolution of a stressor, synaptic connections are strengthened and a sense of purpose results.

75 HPA axis (123). Together these systems exert their pernicious effects in the brain Additionally, cortisol may promote adipose expansion by enhancing insulin action in brain tissue, which promotes whole body insulin resistance. This is largely due to an increase of circulating free fatty acids inducing skeletal muscle insulin resistance, hepatic steatosis, and dyslipidemia. Cortisol (or glucocorticoid) also amplifies hypothalamic neuropeptide Y (NPY) neurons that impair satiety, a signature state of central insulin resistance, hyperphagia, and obesity (72). Consequently, the PFC is compromised in its ability to put the brakes on the more subconscious motivational behavior rooted in the emotional component of the limbic system, the amygdala, and the dopaminergic neurons connecting the VTA to the NAcc, which is followed in turn by its sending projections to the amygdala. This disrupted PFC to amygdala connection and heightened amygdala response results in impaired learning of stimulus-outcome associations shifting towards a state of uncertainty resulting in maladaptive responses and pathology (72).

2.5.3 Gender Differences in Response to Stressors Stress-related neuropsychiatric diseases such as anxiety, depression, panic disorder, and post-traumatic stress disorder affect many individuals worldwide, however, they disproportionately affect women more than men. This gender bias in prevalence rates is observed across cultures and thus, sociocultural differences cannot fully explain the increase in women’s vulnerability to stress and stress-related pathology. Men and women tend to react differently to stress—both psychologically and biologically. These gender-specific differences in disease pattern may be attributed to individual differences in the subjective feelings of stress, known as stress reactivity, the cognitive, emotional, and behavioral coping, known as stress regulation, and the effects of sex steroid hormones on the stress response (124–127). Following an acute stressor, women report higher levels of stress whereas men have stronger physiological stress reactivity and higher levels of glucocorticoid hormones (128). Men and women also engage in different coping strategies whereby males express a more active “fight or flight” response and women express a more passive “tend and befriend” response to stress that involves verbal expression of emotions (129). Women have higher amygdala responses to stress whereas men have higher prefrontal cortex region response to stress. Prefrontal cortex region response to stress is associated with higher subjective anxiety for women, but lower subjective anxiety for men. Stress reactivity, stress regulation, and sex steroid hormones all contribute to adaptation to stress and stress resilience. HPA axis responses to stress are markedly different between men and women. Men show a two-fold higher cortisol response to acute stress such as public speaking or arithmetic tests. Female sex hormones attenuate the sympathoadrenal and HPA response to stress. Estradiol attenuates cortisol stress reactivity. Estradiol stimulates the production of cortisol-binding globulin, which removes free cortisol from circulation resulting in lower net concentrations of active cortisol. Women with high levels of estradiol, such as those on oral contraceptives, have a low HPA stress response whereas

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women with endogenous low levels of estradiol have a heightened HPA stress response comparable to men. Similarly, variability in testosterone accounts for individual differences in HPA responses to stress (130). HPA axis stress reactivity also increases with age thus postmenopausal women show a threefold higher cortisol response then older men. Repeated or chronic activation of the HPA axis has an inhibitory effect on estrogen and testosterone secretion (131). Sexual dimorphisms in HPA axis function may explain differences in stress-related diseases (132).

2.5.4 Possible Interventions for Addictions There is a world-wide pandemic of addictions, especially in the US, including alcohol and tobacco as well as escalating epidemics of pharmaceutical methamphetamine stimulants used for attention deficit disorder as well as prescribed and street narcotics including heroin. The latter largely accounts for tragic and shockingly commonplace overdose-related mortality. Because of the associated pathological structural plasticity of neurons, the enduring vulnerability of addictive behavior makes successful therapeutic approaches uniquely challenging (133). Programs such as Alcoholics Anonymous or Narcotics Anonymous have limited success as do nicotine replacement strategies and existing pharmaceutical interventions for tobacco cessation. Methadone and similar approaches for narcotics transfer one addiction to another instead of drug use cessation and recovery. Fundamentally, interventions must focus on the maladaptive chronic stress response capable of inducing a phase transition that takes the dynamical physiological system from the basin of attraction of the addictive state to the area around a healthy stress response attractor. This requires encouraging stressors that are manageable and are specific to the individual's personality traits and skill sets making a “one size fits all” formula for therapy invalid. While the prefrontal cortex is clearly an important target for intervention regarding multiple devastating brain disorders in humans, individual differences as well as gender/sex differences and the influence of sex steroid hormones on the stress response should be considered. How can we use our knowledge of the maladaptive stress response to inform addiction interventions?

Intriguingly, novel hormonal and neuromodulator strategies may represent an unexpected pharmaceutical application. As discussed ahead in the microbiota and enteroendocrine system chapters in relation to the stress response, GLP-1 (glucagonlike peptide-1), a satiety hormone produced by the L cells of the gut, appears to have promising potential in reducing addictive behavior to tobacco, alcohol, cocaine, and amphetamines (134–136). It appears that there are two systems of GLP-1, one as a circulating hormone and the other as a neuromodulator. It is the latter that seems to confer an effect on reducing motivating addictive behavior much the same way that it promotes satiety in the obese insulin resistant state. Although these types of interventions are attractive and potentially quite valuable, they should not be relied upon as

the primary strategy but rather adjunctive to the cognitive exercising discussed above which is the most fundamental therapeutic approach. However, additional core favorable extrinsic control parameters include physical exercise, calorie restriction, intermittent fasting, and a socially- and cognitivelystimulating environment. The omega-3-fatty-acid docosahexaenoic acid (DHA) as well as flavonoids have also been shown to be beneficial in promoting synaptic plasticity and cognition. Moreover, dietary DHA and flavonoids enhance the effects of exercise on the associated order parameters. Of these parameters, calorie restriction, intermittent fasting, exercise, repeated mild adaptive stress exposures, and DHA all appear to share the common mechanism of synaptic plasticity (137). These extrinsic control parameters critically have the potential to change the attractor trajectory on path for the genesis of not only cognitive decline, neurodegenerative disorders, anxiety, and depression, but as a result of improved psychophysiology, virtually all chronic disease states of aging, and possibly to induce a phase transition back to the normal state.

2.6 Synaptic Plasticity It should be recognized that the conventional antidepressant drugs such as selective serotonin reuptake inhibitors (SSRIs), for example Paxil or Zoloft, and tricyclic antidepressants, for example Elavil, were developed as a result of the monoamine hypothesis of neurotransmission (138). Antidepressant agents that increase neurotransmitters serotonin, norepinephrine, or dopamine in synaptic clefts of the hippocampus and cortex including the PFC modulate glutamate release from presynaptic terminals with subsequent neurotransmission. Thus, while the monoamine neurotransmitters have a primary role in neurotransmission, mediating functions such as emotion and cognition in the brain, synaptic level interactions of neurotransmitters are complex, and their elucidation is evolving. Nonetheless glutamate, the primary excitatory neurotransmitter accounts for the overwhelming majority of neurotransmitter systems in the brain, while a derivative, GABA, an inhibitory neurotransmitter, is the second most prevalent neurotransmitter in the brain. Many systems have co-transmitters working in concert, often with one having a 1:1 relationship between the pre- and postsynaptic neurons as in the case of glutamate or GABA whereas the monoamine may be less discriminatory, spreading out over a number, or volume, of synaptic clefts

2.6.1 Long-Term Potentiation (LTP) More recently the neuroplasticity hypothesis of depression has evolved with the understanding that repetitive glutamate release from presynaptic neurons into synaptic clefts activates N-methyl-D-aspartate (NMDA) receptors that then stimulates another glutamate receptor, α-ami​no-3-​hydro​xy-5-​methy​l-4i​soxaz​olepr​opion​ic acid, (AMPA) receptor (139). When NMDA receptors are repetitively stimulated enough, sodium cations (Na+) entering through the ion channels of the AMPA receptors eventually depolarize the neuron causing the

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The Stress Response voltage-dependent release of the Mg2+ ion blocking the Ca2+ from entering through NMDA receptors. The influx of Ca2+ into the neuron causes an upregulation of AMPA receptors that reduces the threshold of stimulation causing subsequent postsynaptic firing. Frequent depolarizations of the postsynaptic membrane allow sodium ions (Na+) to enter the ion channels of the AMPA receptors, the removal of the magnesium ions (Mg2+) and the entering of calcium ions (Ca2+) into the postsynaptic neuron. Ca2+ bonds calmodulin forming a complex. This complex determines the phosphorylation of various substrates, including that of AMPA receptors. This stimulation causes subsequent postsynaptic firing (Figure 2.26). How do positive and negative experiences change and shape the brain?

This is the early phase of long-term potentiation (LTP), the late phase being structural increase in the density and arborization of synaptic dendrites. Essentially, the idea is that brain synapses get stronger with experiences. The prototypical regions of the brain studied are the cognitive areas of the hippocampus and PFC, and the more evolutionarily ancient region, the amygdala. Accordingly, the nature of the experience determines where the neuronal plasticity occurs. Importantly, cognitive processing that occurs in, for example, the hippocampus and prefrontal regions are not distinct from the emotional processing that occurs in, for example, the amygdala. Rather, there is an inextricable intertwining of neuronal circuitry across these regions. Consistent with this message, cognitive processes associated with the functional and structural changes of neuronal plasticity in glutamate neurotransmission exert a top-down control over emotional processing of sensory neural information when the stress experiences are repetitively positive. Synaptic-related changes are largely mediated by brainderived neurotrophic factor (BDNF), an important regulator of synaptogenesis and synaptic plasticity mechanisms in the CNS (140, 141). BDNF present in the dopaminergic neurons

of the VTA is promoted to trophic support of neural plasticity. Glutamate-induced postsynaptic depolarization, calcium influx and signaling, leads to the nuclear transcription of BDNF (142). BDNF is secreted into the synaptic cleft where it acts on its receptor, tropomyosin-related kinase (Trk) (a member of the family of receptor tyrosine kinases) presynaptically to promote glutamate release and post-synaptically to modulate expression of the glutamate NMDA expression. BDNF acts through several pathways that underpin the proliferation and neurogenesis of neural plasticity and synaptogenesis. BDNF has actions that promote growth on a variety of neurons, including ganglionic dorsal root cells, and hippocampal and cortical neurons. BDNF has also been found to enhance neurogenesis through signaling mechanisms that involve TrkB activation, followed by activation of the kinase pathways and downstream modification of transcription factors. BDNF also upregulates a protein that sustains substrates for synaptic dendritic branches, therefore, strengthening glutamatergic synapses and weakening GABAergic neuronal inhibition.

2.6.2 Long-Term Depression (LTD) However, in the setting of chronic negative stressful experiences, a learned helplessness and anxiety result coincident with a shrinkage of dendritic extensions and a weakening of synaptic processing in the PFC and hippocampus. Conversely, there is an increase in neural plasticity in the amygdala, such that emotion exerts a top-down control over cognition. The process of shrinking dendrites and weakening synapses is known as long-term depression (LTD), the opposite of LTP, and is also mediated by BDNF (143). Furthermore, chronic stress is a risk factor or susceptibility state that augments vulnerability to cocaine, amphetamines, and other chemicals of abuse, which hijack the natural experience dependent neural plasticity. This is known as “stressinduced cross sensitization” (144).

FIGURE 2.26  Synaptic plasticity and LTP. AMPA-type (dark gray) and NMDA-type (light gray) glutamate receptors (AMPARs and NMDARs, respectively) allow the passage of sodium and potassium (and calcium for NMDARs) through their channels to depolarize the membrane, producing an excitatory postsynaptic potential (EPSP). This can initiate synaptic plasticity. A long-lasting increase in synaptic strength is referred to as LTP. LTP leads to the addition of new synaptic AMPARs and an increase in the size of the postsynaptic spine head and branching of the actin cytoskeleton. Long-term depression (LTD) is a long-lasting decrease in synaptic strength that involves a decrease in the number of AMPARs, and a shrinkage of the spine head. * AMPAR = α-ami​no-3-​hydro​xy-5-​methy​l-4-i​soxaz​olepr​opion​ic acid receptor; EPSP = excitatory postsynaptic potential; LTD = long-term depression; LTP = long-term potentiation; NMDAR = N-methyl-D-aspartate receptor.

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2.6.3 Synaptic Plasticity, Will Power, and Consciousness The vitalizing nature of problem solving due to repeated mild stressors itself becomes an inherent motivating reinforcement and should become incorporated into goal-oriented motivations consistent with core values, individuality, and skill sets. However, this requires hard mental work and will power. This is essentially no different from an athlete training to become competitive and eventually win the competition. Weight training hypertrophies muscles just like mental training builds synaptic connections. Arnold Schwarzenegger said in the 1970s when he was a champion body builder that he would regularly look in the mirror to see what muscles needed to be developed and this regimen felt like painting a picture. He would work the muscles that needed it most until he achieved the desired result. Shaun O’Hara was a captain of the 2007 Super Bowl winning team, the NY Giants, who defeated the (until then) undefeated, 18-0, and arguably, the best team in NFL history, the New England Patriots. He famously stated: “hard work beats talent when talent doesn't work hard”. How do consciousness and will power provide a sense of control (and loss of control) for the attainment of goals?

Developing structural plasticity and synaptic connections of the PFC and hippocampus that build the strength of conscious cognitions, free will (the ability to act at one’s own discretion) and will power, supplants the need for current strategies of, for example, heroin addiction to an ostensibly preferable methadone addiction. In the latter case, so-called therapy (treatment using an alternative drug) is just further entrenching maladaptive addictive behavior. It enhances reward motivational circuitry of the extended amygdala while promoting atrophy of the synaptic connections from the PFC and hippocampus. Indeed, goal-oriented reinforcement is crucial to harnessing the stress response in such a way that it empowers a sense of certainty and of control for the attainment of those goals. At the level of conscious cognitions this represents the strength of free will. This must be distinguished from the reward motivation type behavior, which is driven by neuronal circuitry in regions of the brain that are detached from conscious regulation. That is, these reward motivation pathways are subconscious. This loss of conscious regulation is a loss of self-control that is helpless. Moreover, a learned helplessness leaves an individual essentially unarmed and vulnerable to frequent even daily stressors of life. From a philosophical perspective, vitalizing stressors may define the meaning and purpose of life and the notion of free will.

These insights can be appreciated from the perspectives of psychophysiology and the deleterious effects of the stress response on promoting chronic disease states. The joy and success of the living experience is only truly fulfilled when under the control of willful cognitions. This defines the richness of the conscious experience.

In this context it is also worth considering more abstract concepts such as biological quantum behavior, especially quantum metabolism and quantum consciousness (145). The delicate nature of such non-classical, almost magical, bio-physiological phenomena that made life possible in the first place, should be appreciated as necessary for achieving full human potential. This is true not only for healthy physiology and longevity but also for experiencing the joy of life, which should be one of the ultimate goals of healthy living. The focus of this chapter on the fundamental significance of the stress response brings these two perspectives together as inseparably linked. When solutions cannot be found by effective decision-making, the next best thing is to reduce one's expectations leading to habituation. This can catalyze a transition from a state of uncertainty to an attainable state, which is also the goal state. Its consequence is a reduced chronic psychopathology of anxiety and depression and diminished associated toxic effects on the quality of life in terms of joy. Beneficial changes can also then be seen in psychophysiology.

2.6.4 Quantum Consciousness through the Lens of the Prefrontal Cortex Signature characteristics of the PFC in addition to executive function include social and self-awareness that are the barometers of the depth and strength of conscious cognition. These parameters form the basis for the consciousness quotient (CQ), which is an analog of the intelligence quotient (IQ). Roger Penrose, renowned mathematical physicist with expertise in bridging the gap between physics and human consciousness, defines consciousness as awareness of awareness, which essentially boils down to understanding both the perception of oneself and events and experiences from the perspective of others. This can also be viewed as a type of coherence in the sense of being in resonance with or even being in an entangled superposition with others. Consciousness in this context is intrinsically a quantum phenomenon since classical physics cannot involve entanglement because all physical objects are distinguishable and separate from each other according to classical paradigms. Information patterns in the brain are multiscale iterations of both temporal and spatial fractals. For example, there are six layers of the cerebral cortex, each representing a different spatial scale. When we superimpose a higher-frequency temporal scale of vibrations appropriate for many smaller subunits, a larger scale pattern emerges with lower frequencies. Accordingly, with each higher (larger) spatial scale represented by the different cortical layers, there is an associated lower vibrational frequency. However, the resonance across the temporal scales for waves that oscillate in unison occurs because there is a greater number of waves of higher frequency, which are superimposed in the spatially smaller cortical layers. Due to constructive interference these waves form a resultant wave with a vibrational frequency that is matched with that of the largest cortical layer. This is not synchronous (100% constructive interference) or coherent (in phase oscillations) (Figure 2.27) across all scales or across all

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FIGURE 2.27  Constructive and destructive interference. Top: Two waveforms with the same frequency and starting at the same point in the cycle (synchronous) superimpose to give a waveform with double the amplitude (100% constructive interference) Middle: Two waveforms with the same frequency but starting half a cycle apart superimpose to give a waveform with zero amplitude (100% destructive interference).

vibrational structures of the same scale, acting in the classical electromagnetic regime. However, Stuart Hameroff (anesthesiologist) along with Penrose, proposed that in the cortical layer 5 giant pyramidal cells, which give rise to the EEG scan, quantum coherence (when wave sources are perfectly coherent with a constant phase difference, the same frequency and the same waveform) occurs. This is exactly where the richness of the conscious experience is postulated to arise. It is in the microtubule networks within the apical dendrites that this magic of quantum coherence analogous to laser action is expected to take place, giving rise to quantum consciousness. These coherent quantum excitations in the microtubule structures of the apical dendrites of cortical layer 5 pyramidal cells have been identified to lie in the larger terahertz frequency range (1012 cycles per second). The mechanism of these excitations involves pi electron clouds of tryptophan amino acids found in the tubulin building blocks of microtubules. In contrast to quantum electromagnetic coherence of a laser pointer and biological phenomena such as higher-level consciousness and quantum metabolism, in classical electromagnetism the rainbow of colors together forms white light due to the superposition of the many different frequencies and phases that cancel one another out through destructive interference (Figure 2.28). The different patterns of the fractal orchestra of coherence of microtubules across sensory and prefrontal cortical neurons of the brain represent patterns of information transfer, perceptions, cognitions, and neural pathways of the conscious experience manifesting in layer 5 of the PFC (146). This can lead to both positive consequences when quantum coherence is maintained and negative when it is lost. How can we use quantum phenomena to understand consciousness in the brain?

The loss of executive function can be considered in the context of the loss of the quantum nature of the neuronal microtubules. Inflammatory processes in the brain, such as those stemming from proinflammatory cytokines deriving from the periphery are due to, for example, peripheral insulin resistance, obesity, or altered microbiota composition. This activates the innate CNS’s immune system neuroglia. The heat from the inflammatory process can be implicated in causing decoherence of quantum waves that under normal conditions are correlated due to coherent production of energy via quantum metabolism. This provides a connection between quantum metabolism and another major quantum biological phenomenon discussed here, consciousness (145). High cerebral glucose exposures in diabetes as well as insulin resistance with prediabetes, even in the range of hemoglobin A1c 5.4% to 5.8 %, result in the response in the form of hippocampal atrophy. The mechanistic basis of this effect may be glucose overloading mitochondrial electron transport chains causing superoxide free radical formation and loss of mitochondrial function. The impaired bioenergetics fails to support the high-level cognitions of a quantum regime of consciousness. The loss of mitochondrial structure and function amplifies the lack of capacity to accommodate sufficiently high glucose entry into cells, worsening the inflammatory cascades. The associated heat release causes collapse of the coherent quantum wave function of the microtubules with subsequent detrimental effects on consciousness following suit. Finally, insulin resistance in the CNS impairs insulin signaling mTOR pathway of anabolism. Notably, Alzheimer's disease is associated with hyperphosphorylation of tau, a microtubule associated protein, hence invoking the role of microtubules and by extension the quantum nature of cognitions (147). As mentioned above, it is from these microtubules that fundamentally abstract and conceptual cognition arises. Conversely, lack of quantum coherence may lead to cognitive

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FIGURE 2.28  In-phase oscillations. In-phase (coherent) oscillations, when superposed, combine to produce an oscillation with larger amplitude.

FIGURE 2.29  Visible light wavelengths. The different wavelengths of visible light show that the individual light waves are not in phase. Superposition of these waves gives rise to destructive interference, yielding a continuous, white-light spectrum.

impairment (Figure 2.29). High-level conscious cognition may be equated to free will that defines the essence of our perception of ourselves and who we are in terms of core values and individuality. It is the motivating force or will power required for the execution of personal success.

2.7 Toward Integration of Physical Concepts into Medical Practice A common vernacular of stress refers to an emotional distress. It can be the stress of labor-intensive work, of financial or other hardships, even tragedies. Psychosocial isolation and discord are a societal pandemic, which is the most underappreciated extrinsic control parameter that adversely affects public health. Moreover, emotional forms of stress are inextricably tied in a bidirectional fashion to chronic immune system responses to microbial pathogens typically gut-derived or to other chronic

inflammatory or disease states. This is a feedforward relationship with a primary psychogenic basis of the stress response when chronic stress leads to physical manifestations of disease, which in turn amplify the initial psychogenic stress response. Alternatively, prolonged peripheral activation of pro-inflammatory cytokines upregulates the stress response (148, 149). In either case, this is a bidirectional self-perpetuating phenomenon. Furthermore, there are hemodynamic and metabolic control parameters of the stress response including volume depletion, hyperglycemia, hypernatremia, hypoglycemia, and hypoxemia (150–152). While stress can be devitalizing when it breaks down resilience, it is also underappreciated that it is theologically designed to be vitalizing in an absolute sense in terms of building resilience. This is the case in terms of motivational forms of stress which can be more primal, such as the search for food, water, shelter, or sex, or can be goal oriented. This is well illustrated by the adage “what doesn't kill you makes you stronger”, implying that stress should not be understood as something inherently “bad” that can break one down or bring one to tears. Stress should not be understood as something inherently “bad”. When is stress good and when is stress bad?

Indeed, “tears of joy” are manifestations of the stress response. Further, the good mood that accompanies socializing and the energizing effect of an engaging good conversation underscores the positive impact of those interactions. While these experiences are vigorous and animate expressions of our personality, they are stressful although they may not be recognized as such. After all, they require input of effort or work and a considerable amount of attention and mental involvement. As a result of chronic devitalizing stress accumulated over many years some people are challenged not only in a physical sense but also in an emotionally energetic sense. This can create a motivational barrier that is hard to overcome. Moreover,

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The Stress Response these people tend to suffer from chronic pain, fatigue, and depression. They have a hardening or loss of their core values including empathy, compassion, social awareness, and intuitions. They are cognitively and physically debilitated and at high risk of addictive behaviors, lawlessness, and suicide as well as virtually all forms of chronic disease. The intent of this final section of the chapter is to describe the relationships of control and order parameters to chronic disease states in the framework of the stress response using the Physiological Fitness Landscape as a model that hopefully will have value in advancing the execution of clinical medicine beyond managing signs and symptoms of disease. Ultimately, we wish to provide a relatively simple model and to elaborate on its applications that will have practical use in the field of medicine.

2.7.1 Stress and the Control Parameters As a reminder, the intrinsic control parameters include psychogenic stress, circadian clocks, the microbiota, and the external behavior control parameters are the perceived stress response, diet, support systems, and circadian behaviors. The immune system and the quantity, quality, and timing of the diet shape the intestinal microbiota, and vice versa, the intestinal microbiota shapes the immune system development (153). Additionally, an undisciplined and disturbed timing of the feeding/fasting, sleep/wake, and other cycled behaviors

are intimately and inseparably coupled to the stress response forming a triumvirate of external control parameters regulating human disease (Figure 2.30).

2.7.1.1 The Entanglement of the Stress Response and Biology of Time All living systems, humans of course included, are comprised of systems of cycles within cycles across many hierarchical scales. The fidelity of the cycle, that is the returning to the proximity of its starting point, is the ultimate parameter of the state of health as well as the rate of aging. The cycle is what defines biological time, as the cycle of a mechanical clock. Deviation from this cycle is tantamount to the aging process, and exaggerated deviation is a manifestation of premature aging and disease. Analogously, as was described in this chapter, stress is a determinant of the state of health and the rate of aging. Prolonged or exaggerated stress chronically activates biological pathways, consequentially crossing a threshold by which allostasis can no longer maintain homeostasis resulting in chronic disease. This ineluctable direction from order, information, and complexity to randomness and entropy represents the spectrum from health to disease. Although we cannot stop the cycle of time or the stress response, the goal is to moderate the rate of deterioration for both parameters. The time organizing framework of all living systems centers around a 24-hour cycle dictated by the earth’s rotation,

FIGURE 2.30  Quantum consciousness. The impact of the lack of quantum consciousness, quantum metabolism, synchronized chronophysiology, and physiological fitness in the context of the stress response on declining health and ultimately thermodynamic death. *ΔG = Gibbs free energy; ΔS = entropy.

82 resulting in circadian (~24-hour) rhythms. In the animal kingdom including human beings, the diurnal phases of the fastingfeeding and sleep-wake cycles are tightly linked and adapted to the light-dark cycle. In mammals, the autonomously cyclical master molecular clock is made up of about 18,000 cells in the hypothalamus known as the suprachiasmatic nucleus (SCN). This “master clock”, or master circadian pacemaker, determines the circadian rhythms of the organism without external cues (see Section 4.6.1). It can also be entrained by external light that is transmitted through the eyes to the retinal hypothalamic tract. Signals from the master clock are, in turn, coupled to extra-suprachiasmatic cell clocks in the brain, particularly of the paraventricular (PVN), arcuate, posterior, ventral medial, and other nuclei within the hypothalamus. These intricately interrelated pacemakers, in turn, regulate temporally organized circadian behavioral states of sleepwakefulness, rest-active, and fasting-feeding. Together, these cycles synchronously orchestrate maximal efficiency of total body metabolism and physiology. The stress response lies at the functional intersection of these orchestrated central and peripheral circadian behaviors (154). The entanglement of the stress response and biology of time is essential to the survival of humans from cognitive, physical, and metabolic perspectives. Following stress, the PVN of the hypothalamus sends signals through autonomic and hormonal neuroendocrine pathways that in turn, entrain peripheral clocks in tissues such as the adrenal cortex and medulla to secrete cortisol and catecholamines, respectively. The secretion of these hormones coupled to neural autonomic activity act on the liver and skeletal muscle to promote gluconeogenesis and insulin signaling, thus, enhancing glucose production and uptake, respectively. Nutrient signals (e.g., amino acids, fatty acids, glucose) along with hormonal satiety signals (e.g., insulin, leptin, GLP-1) and hunger (ghrelin) signal both negatively or positively govern food-seeking behavior (See Section 4.6). This results in a fasting-feeding cycle that is coordinately linked in a circadian integrated fashion with restactive and sleep-wake cycles.

2.7.1.1.1 The Importance of Circadian Behavior Synchronization Our understanding of the neurobiological pathways that link stress and circadian biology has accumulated over more than 40 years and continues to grow. The hormonal neurotransmitters, orexins A and B, are exemplary in demonstrating the interactions between circadian and stress systems. Orexins A and B are produced by the lateral hypothalamic neurons and promote wakefulness and energy expenditure in the context of orexigenic behavior (155). Orexins and leptin have reciprocal effects on the hunger promoting neuropeptide-Y neurons. This underscores the inextricable relationship of hunger to the wakeful state. Furthermore, this link extends to the circadian energy expenditure of basal metabolism that is coupled to spontaneous physical activity and to autonomic sympathoexcitatory actions integral to the arousal state of wakefulness. Moreover, orexins encourage the high energy demanding reproductive process by stimulating the endocrine gonadotropin-releasing hormone and the hypothalamic-pituitary-gonadal axis (156). Orexin deficiency leads to a severe

Metabolism and Medicine disturbance in the circadian sleep-wake cycle characterized by narcolepsy, obesity, insulin resistance, and type 2 diabetes. How is it possible to eat and to be physically active while sleeping?

A commonly prescribed pharmaceutical sleeping aid, Ambien, may paradoxically uncouple the state of wakefulness from behaviors of food consumption, particularly binge eating, and energy expending physical activity such as “sleepwalking”. Rather, these behaviors may be intriguingly coupled to the hypnotic state of sleep. Ambien induces sleep by a mechanism independent of blocking orexins. However, a characteristic of adaptive biological systems is the complexity and robustness of intricately balanced interdependent networks and pathways that carry out physiological functions. This highlights the sometimes unpredictable nature of the effects of therapeutic interventions in Medicine that target specific pathways. That is, Ambien’s effectiveness as a sleep hypnotic agent is attributable to preferentially targeting one pathway that more than offsets the anti-hypnotic effect of the elevated activity of orexins. In this case, there appears to be compensatory unregulated actions of orexins that lead to the orexigenic food-seeking behavior and spontaneous movement of sleepwalking, two behaviors often observed under the influence of this drug. Circadian physiology protecting against obesity and metabolic chronic disease?

A glowing example that underscores the significance of the synchronized integration of circadian behaviors are controlled experiments that feed rodents isocaloric (having the same number of calories) diets but only during the natural fasting (and sleep) phase of the daily cycle. The result was significant weight gain, which returns to normal body weight when the feeding timing is restored to the natural phase (157). Conversely, restricting calorie intake to the active phase (time-restricted feeding), even with a high-fat diet, prevents weight gain and associated diseases, such as fatty liver (158). It follows, as Chapter 4 highlights, that shift workers experience a higher incidence of obesity, insulin resistance, type 2 diabetes, and associated chronic disease sequelae (159). Taken together, the hypothalamus thus represents a critical intersection that links nutrient and energy signals to temporally organizing circadian behaviors teleologically connected to the light-dark solar cycle as a fundamental adaptation to survive through the reproductive years to ensure the survival of species (160).

2.7.1.1.2 The Impact of Stress on Circadian Functions An optimal dose and quality of stress exists whereby it builds resilience and the capacity to withstand toxic effects that deteriorate interactions of biological chemistry protects the beautiful and exquisite synchronized nature of the dynamic organizational perfection of optimal complexity (see Section 2.2.4). Devitalizing stress, stress that promotes chronic disease, is inextricably and reciprocally linked to impairment of chronophysiology in a self-amplifying fashion (see Section 2.3.1). In the context of chronic devitalizing stress,

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The Stress Response as opposed to episodic or motivating stress, it becomes virtually impossible to effectively maintain healthy circadian voluntary behaviors, such as sleep/wake, fasting/feeding, social behaviors, and exercise. Stress must be coupled with cognitively motivated goal-oriented behavior and energy expenditure. When emotion dominates and becomes detached from cognitive moderation, the prolonged stress response is maladaptive. Accordingly, it becomes dyssynchronous with and destructive of other circadian voluntary behaviors, and hence self-damaging to physical and to further cognitive health. For maximum efficiency, these autonomic, visceral, and voluntary behaviors must be synchronously timed with energy substrate availability. This timing is the meaning of the biology of time, manifestations of cycles, and cycles within cycles across many hierarchical temporal scales. The metabolic cycle of bioenergetic production of ATP is most fundamental. When this is in the mode of quantum metabolism (see Volume 1, Chapter 4), ATP production is correlated. This means its output is coherent across spatial planes of cells and tissues of the organism, allowing it to be synchronously timed to circadian clock activity and hence, clock-controlled metabolic physiology. The hypothalamus is a small region within the brain that governs astonishingly complex processes simultaneously with exquisite sensitivity. One of its most important roles is to connect endocrine systems with the nervous system, underscoring the interdependence of energy homeostasis and the stress response for survival. While much of our behavior is voluntary, nervous system-mediated activity, it is intricately interwoven

within a fabric of autonomic functions. These visceral actions such as hormone secretory patterns and neural firing are not under conscious regulation. They are largely underpinned by intrinsic circadian clock physiology and the entrainment by the extrinsic diurnal light-dark solar cycle. The intrinsic master SCN and extra-SCN circadian clocks, in turn, stably synchronize with peripheral clock rhythm as the composer of a systemic orchestra of physiology. Importantly, it is crucial that voluntary behavioral patterns align with the rhythm of circadian functions to avoid the loss of bioenergetic efficiency and metabolic homeostasis (Figure 2.31).

2.7.1.1.3 Downstream Effects of Uncoordinated Stress and Circadian Systems The stress response and the biology of time (Chapter 4) are the foundational elements of all living systems and are also the basic parameters that define human health and disease. It’s all about the transformation of energy from one form to another, whereby in conditions of optimal health the transfer of energy orchestrates physiological processes of energy expenditure with a minimum of energy lost to heat that cannot be used for useful purposes. Such optimal metabolism and physiology maintain the fidelity of the cycle which is the central basis of time. The slower the biology of time the more correlated it is to chronologically physical time. The basic theme to the connection between these two Chapters is that stress is essential to all oncogenic and phylogenic evolution that strengthens resilience by building connections and complexity physically, mentally, and socially. However, when it becomes uncoupled

FIGURE 2.31  Circadian control of energy metabolism. The master clock in the SCN sends signals to the extra-SCN regions, which in turn entrain peripheral tissues via the hormonal, autonomic nervous system, and behavioral pathways. These pathways regulate peripheral clock control of fuel utilization, energy harvesting, and energy homeostasis. A balance between energy intake and energy expenditure is maintained through food intake, physical activity, and metabolic processes whereby too much energy intake results in stored energy mostly into adipose tissue, leading to obesity, and too little energy intake results in leanness. Source: adapted from (161). *SCN = suprachiasmatic nucleus.

84 to goal-oriented motivations, this represents a powerful control parameter to human chronic disease and the underlying accelerated pace of aging (Figure 2.32). Analogous to stress, circadian biology is a powerful control parameter to human chronic disease and the page of aging. Metabolic pathways downstream of nutrient and energy sensors interact with the molecular clock in different cell types within and between tissues to guide phase-dependent circadian physiology. When synchronized and coherent, redox, and usable energy are optimal. In this case, biological and chronological aging are more closely approximate. However, when the timing of energy storage or expenditure becomes desynchronized to the natural circadian rhythms among the different pathways within and across tissues, increased biological redox (and in parallel, inflammation and the physical analog entropy), and loss of free energy (information, or organized complexity) result. This leads to the process of accelerated aging and premature chronic disease states of aging. For example, unhealthy or out-of-sync circadian behaviors of fasting/feeding, rest/active, or sleep/wake promote a mismatch of energy availability relative to the bioenergetic demands of intrinsic clock determined by natural physiology. Fasting during periods of high energy expenditure impairs the efficiency of energy homeostasis relative to its storage and mobilization, required such as the bioenergetic demands of anabolism and stress resistance programs (building antioxidant systems, cell, and DNA repair, autophagy, and apoptosis) that are most robust during the period of nocturnal slow-wave sleep. This leads to downstream effects such as inactivating mutations of tumor suppressor genes and cancers. It also leads to inflammation and disturbed redox due, for example, to hypoglycemia and endoplasmic reticulum stress, mediated by the unfolded protein response due to the lack of bioenergetic substrates of energy-requiring processes during the active phase of the daily cycle. It is worth pointing out that physiologic redox appears to be the most basic intrinsic regulator of endogenous clock timing. However, dyssynchronous physiology leads to the uncoupling of metabolic supply and demands. This results in disturbed redox, which alters biological structures, breaks down organized complexity, increases mitochondrial dysfunction, insulin resistance, inflammation, and loss of free energy in an inextricable and self-amplifying fashion (see Section 4.7). Conversely, nighttime eating is teleologically not anticipated and accordingly has pathological consequences. When the body is at rest or should be sleeping, the circadian metabolic design is in the insulin-resistant phase of the daily cycle. During the active phase of the day, food is acquired as fuel and used to provide the high bioenergetic demands of physical and cognitive activity. What energy is not used is stored as glycogen and fat. During the fasting phase, the processes of glycogenolysis and gluconeogenesis in the liver provide glucose as an energy source for the brain, free fatty acids are released from lipolytically active adipose tissue as fuel for the heart and other tissues of the body. Melatonin at night is released in circadian fashion to promote anabolic functions essential for stress resistance programs for example antioxidant enzyme systems, mediated in part by the release of growth hormone.

Metabolism and Medicine Eating during these times promotes a state of circulating energy excess and abnormal energy deposits as ectopic fat. This is pathogenically linked to chronic non-circadian insulin resistance such as occurs classically in skeletal muscle. Ectopic lipid droplets also occur in the brain, and likely contribute to insulin resistance in this organ, manifesting as, for example, impaired satiety that promotes obesity and perpetuates insulin resistance. Fat also deposits in the pancreas and other tissues impairing structure and function, activating inflammatory pathways, and altering homeostasis of redox (see Sections 5.6 and 5.9). In this process, ineluctably endogenous core clock components undergo redox modification which must be part of a feedforward self-amplifying process that further destructs circadian physiology as a central control parameter to accelerating the pace of biological aging.

2.7.1.2 The Influence of Stress on the Microbiota The role of microbiota in human health with regards to stress is important for human health despite being overlooked in the past. Both the numbers of microbiota cells and their gene pool vastly outnumber those of the host organism. We now know that a healthy microbiota can be a protective element in our coping with stress. Conversely, high stress levels or pharmacological agents may exert detrimental effects on the microbiota and hence negatively affect our ability to maintain allostasis. Recent attention given to healthy diet and the use of probiotics is a step in the right direction vis a vis the role and function of microbiota in our health. However, the vast complexity and hence unpredictability of using these agents promiscuously may be another dangerous game. In many ways they appear to be a horizon of promise analogous to antibiotics; they may also pose analogous dangers and pitfalls. Rather, dietary prebiotics such as resistant starches and non-digestible (by human DNA coded digestive enzymes) polysaccharides represent a stronger benefit to risk profile. The Mediterranean diet is an excellent source for this. Probiotics will no doubt have an increasing therapeutic role in disease management and prevention selectively applied based on microbiota analysis (see Chapter 7 for more on Microbiota). Chronic emotional stress is often the initiator of downstream prolonged allostatic parameters such as cortisol and pro-inflammatory cytokines. DHEA-S, an endogenous steroid hormone, and testosterone are elevated in females while decreased in males. The gut microbiota plays a central role in eliciting the pro-inflammatory response (153). A disturbance in the microbiota composition may be rooted primarily in the quantity, quality, and timing components of the diet or primarily from the stress response. In the latter case, chronically up-regulated cortisol immune suppression followed by innate immune cell resistance to cortisol, e.g. of macrophages and dendritic cells, may disrupt the integrated synchronized relationship between the natural healthy microbiota and the intestinal barrier (see Chapter 7, Section 7.3.4). As described elsewhere in this book (see Chapter 7), the intestinal microbiota functions as a virtual organ with interactions between component elements that highlight a singularity. Furthermore, there is a deeply entangled and symbiotic

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FIGURE 2.32  Stress and metabolic rhythms. The interplay between stress and metabolic clocks. These processes are responsible for regulating the autonomic stress response in healthy and diseased states. *ATP = adenosine triphosphate; BAT = brown adipose tissue; BMAL1 = brain and muscle Arnt-like protein-1; CAD = coronary artery disease; CVD = cardiovascular disease; CRY1/2= cryptochrome circadian regulator 1/2; DHEA = dehydroepiandrosterone; DMV = dorsal motor nucleus; GH = growth hormone; HDF = high-fat diet; HPA = hypothalamic-pituitary-adrenal axis; HPG = hypothalamic-pituitary-gonadal axis; HPT = hypothalamic-pituitary-thyroid axis; HTN = hypertension; IGF(1) = insulin-like growth factor(1); LC/ NS = locus coeruleus/nervous system; L/D = light/dark; LHA = lateral hypothalamus; MS = metabolic syndrome; NTS = nucleus tractus solitarius; PER1/2/3 = period circadian regulator 1/2/3; PFC = prefrontal cortex; PVN = paraventricular nucleus; ROR = retinoid-related orphan receptor; SCN = suprachiasmatic nucleus; T2D = type 2 diabetes; VLM = ventrolateral medulla; VTA = ventral tegmental area.

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unity of the microbiota with the intestinal barrier, immune system, and other components of the gut wall, and ultimately the entirety of the human host (162, 163). However, when this relationship becomes desynchronized it allows noncommensal microbial pathogens, and pathogenic components such as their cell walls, to traffic across the mucosal barrier of the gut. Immune system compromise, which is contributed from both the adrenergic and cortisol branches of the stress response, enables the pathogen invasive process to escape the local immune system guards (Figure 2.33) (164). This, in turn, leads to the systemic effects, for example, subclinical endotoxicosis, a signature state mediating the development of insulin resistance (165). One way it likely does this, analogous to the situation with components of food processing, as described above, is via endotoxins reaching the liver and provoking inflammatory responses from the Kupffer cells (macrophages) that in turn disturb the redox state locally and systemically. In any event, the development of innate immune cell resistance, while teleologically intended to modulate unmitigated immune suppression by the prolonged stress response, potentiates the chronic pro-inflammatory systemic milieu. Consequently, this leads to the allostatic overload of insulin resistance and associated metabolic and downstream chronic diseases of aging (Figure 2.34). Independent of whether the primary origin of provocation that desynchronizes and alters the composition of the intestinal microbiota, whether rooted in the diet or the stress response control parameters, a self-amplifying reverberation of redox stress and inflammatory stress ensues. Circadian clocks lie at the intersection of metabolism. Hence, circadian clock and metabolic pathways are coupled and accordingly disruption in clock synchrony is linked to metabolic dysregulation (166–169) (Figure 2.35). Fomenting redox stress and inflammatory stress accompanies each level of molecular pathophysiology with its origin linked to intrinsic control parameters whether it be desynchronized molecular clocks, disturbed intestinal microbiota, or mitochondrial dysfunction (such as when dietary glucose overwhelms mitochondrial electron transport chain capacity) (Figure 2.36). The most fundamental disturbance parameter, integral to the processes of inflammation and redox homeostatic imbalance, is the loss of Gibbs free energy. Consequently, free energy cannot be used to do the work of maintaining the homeostasis of the extraordinary organizational complexity of the healthy state. We will return to a discussion of various modes of bioenergetic metabolism relative to efficiency of free energy generation and their relationship to health and disease. But first, the next paragraph pivots back to the concept of hormesis in the context of calorie restriction and other important examples. These intrinsic control parameters include the psychogenic stress response, the microbiota, and the circadian clocks. This injurious process evolves into an interwoven fabric that unites the four arms of dysfunctional external behavior control parameters: 1) perceived stress response; 2) diet; 3) circadian behaviors; and 4) support systems.

A calorie restricted (CR) diet (40% reduced daily calorie intake from baseline) and exercise are also examples of strategies that invoke the power of hormesis to promote physiology (170). Fundamentally, the adaptive nature of low to moderate stress is teleologically-rooted in survival to promote the evolutionary process. This process activates the energetically demanding hormonal and autonomic branches of the stress response. The quantity of food consumption is inadequate in roughly 50% of cases and excessive in the other 50%. Moreover, the quality of food is compromised in virtually 100% of cases.

While potentially lifesaving, it often requires calibrating energy expensive resources away from physiological processes unrelated to the fight or flight response, for example reproduction. This is analogous, but with different adaptive properties in terms of duration and intensity, to the more acute and more fulminant circumstance of a cheetah chasing a gazelle in the grasslands of East Africa. Both regular moderate exercise and CR diet prolong human health span, and possibly lifespan. CR has been shown in nonhuman mammals to unequivocally prolong lifespan. The average lifespan for males and females in the US in 2017 was 79 years and 81 years, respectively. The World Health Organization 2017 statistic for average healthspan, that is the age up to which there is an absence of a major disease composite for males and females was 63 years.

Regular exercise and long-term CR as chronic low-dose stressors prolong human health span and likely lifespan by improving stress tolerance. CR induces stress response pathways to execute resistance at the cell and ultimately organism level to future higher doses of the same potentially harmful agent or circumstance. CR also turns a metabolic switch from glycolysis to mitochondrial oxidative phosphorylation, not only a more efficient mode of ATP production, but also the central basis for oxidative redox stress, that initiates a mild degree of cell damage and hence stress resistance programs (see Chapter 5 for more detail). Similarly, long-term regular consumption of phytonutrients and vitalizing cognitive and psychogenic stress experiences catalyze biological hormesis that likely improve human health and lifespan. Nonetheless, in these cases too, the perceived stress may be sufficiently mild to build resilience mediated by self-reliance, as well as facilitated by the vivifying nature and opportunities of social networking and integration. Every evolving species learns from experience, improving its competitive qualities. The ontogeny of an individual is also strengthened by its history of competitive experiences. The most fundamental example of a hormetic stress may be competition, an inherent process of evolution. When there is too much competition, the species doesn’t survive, yet too little competition and the species doesn’t evolve. Competitive stress promotes natural selection.

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FIGURE 2.33  Organizing principle of the Physiological Fitness Landscape (PFL). The symbiotic relationship between circadian physiology and microbiota is altered by the stress response. If the stressor is successfully removed, homeostasis is maintained. If the stressor persists, imbalance in the autonomic, hormonal, and immune responses prevails resulting in a self-amplifying loop of disturbed intrinsic control parameters and thus, poor physiological fitness. *HPA = hypothalamic-pituitary-adrenal axis.

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FIGURE 2.34  Stress and microbiota. Stress impacts immune function and intestinal motility, both of which disturb microbiota composition.

Metabolism and Medicine

FIGURE 2.36  Stress and circadian physiology. Altered microbiota due to stress interrupts the synchronously interdependent symbiotic relationship between microbial circadian physiology and human host circadian physiology.

control parameters to these disease states. Based on a mapping out of the control and order parameters into computer (mathematical) models of the Physiological Fitness Landscape, predictive attractor trajectories can be used therapeutically proactively.

2.7.3 Improving Clinical Practice by Integrating Physical and Chemical Concepts with Biology

FIGURE 2.35  Stress and hypoglycemia. Disruption in circadian clock synchrony due to stress is linked to metabolic dysregulation (see Chapter 4).

2.7.2 The Physiological Fitness Landscape as a Clinically Useful Model The benefits stemming from clinicians applying the Physiological Fitness Landscape model are two-fold. First is to show a landscape of interactions that lead to chronic disease, illustrating how diet and stress, the two major extrinsic control parameters, engage the stress response which fundamentally impairs metabolic function, leading to chronic disease states we all confront (171). From the perspective of metabolic disease, the paragon one being insulin resistance and diabetes, we see mechanisms of metabolic dysfunction in metabolic diseases and chronic diseases of aging such as cancers, cardiovascular disease, cognitive decline, and Alzheimer's. Autoimmune diseases will not be mentioned here as they are not metabolic diseases or chronic diseases of aging. The second benefit of the Physiological Fitness Landscape as a clinically useful model is to apply an understanding and quantification of extrinsic and different scales of intrinsic

With a major thrust toward precision medicine in recent years, defining disease states using sophisticated concepts borrowed from physics goes a long way toward accomplishing the goal of precision diagnostics and rational therapy design. Predictions to thresholds of reversibility are also part of the model and are of great significance in diagnostic and therapeutic applications. While cancer is a complex multifactorial disease, it appears that in most cancers, the glycolytic switch seems to be one of the primary events in tumorigenesis (172, 173). Therefore, it stands to reason that a reduction of the glycolytic mode of energy production by the tumor may be one of the properties that can signal that the disease is retreating. We can improve how we understand biological systems and problem-solve in medical practice. This includes thinking about systems as parts and wholes whereby the whole becomes a part of a greater whole. It often requires understanding distinctions involving closely-related concepts, how they are different, and how they are the same. Critically, it involves recognizing the relationships of parameters to one another in a system as being casual or causal. That is, in the latter case identifying control parameters in the multidimensional Physiological Fitness Landscape and the role they play in affecting the biological system's response, that is a change in the order parameter. Importantly, since this landscape is dynamic, relationships may change over time, for example habituation of an intervention. Finally, multi- and interdisciplinary perspectives are crucial to a rich and powerful potential for insights and their therapeutic impact.

The Stress Response A clinical physician or a researcher searching for solutions to clinical problems must be able to appreciate many different viewpoints of the same challenge. That is, we should see a situation that varies depending on the specific perspective taken. This perspective would be different for a clinical physician, including a nephrologist versus an endocrinologist. Even greater difference would be the view seen by a biologist, molecular biologist, a biochemist, or a biophysicist. The integration of such widely different perspectives will be increasingly made possible given the emerging role of computers and advances in “Big Data” Analytics. Specific improvements in our ability to see the “forest for the trees” of biological complexity are being made thanks to bioinformatics as an emerging field of computer science that integrates data provided by genomics, proteomics, transcriptomics, metabolomics, microbiomics, etc. The applied scientist, that is, the clinical physician, should speak the same language as the basic scientist whose research uncovers the underlying molecular mechanisms of clinical manifestations of a physiological dysregulation. Conversely, basic scientists should understand the language of everyday clinical application. Elitist attitudes of publishing to an intellectual and narrow scope of abstract theories that are mathematically sound and scientifically valid are powerful only within a very small audience of those who can understand it. However, in the real world focused on applying only knowledge and information directly relevant to the mission of helping people, basic science is unfortunately useless until we widen our perspectives to the challenges of healthcare. Computers can be fundamental to this type of transitioning. In addition to understanding the language of other scientists, we continue to argue that much insight in clinical practice can be gleaned by adopting and translating concepts that originated in the physics of complex systems since the human body is one of the most complex systems known to us. Both conceptual and quantitative terms can be used in this connection whose origins can be found in physics and chemistry. The framework of the dynamic Physiological Fitness Landscape has the potential to be a groundbreaking tool that is both simple and general enough to become readily applicable to healthcare solutions.

89 acid base disturbances increasingly prevail accompanying free energy that is lost to heat. The generation of damaging oxidative free radical molecules alters the structure and function of protein, lipid, and nucleic acid components of cells leading to tissue injury (174). This is the molecular basis of chronic disease development (175, 176). Peripheral secretions of proinflammatory cytokines or “hormones of the immune system” also interact with the brain manifesting disease state and altering the beautiful and exquisitely organized complexity of any living system of which the human being is the consummate example (Figure 2.37). Another example of the criticality of interdisciplinary perspectives on therapeutic impact is in the “gut-brain-microbiota axis”. A recent development in this area of medicine involves an appreciation of the relationship between the neuroendocrine system and the immune and gastrointestinal systems. This is proving to be critical in the overall construct of the body's systems biology and has led to the explosion of interest in the microbiota-gut-brain axis (or gut-brain-microbiota axis) (177, 178). The neuroendocrine, immune, and gastrointestinal systems form a framework for understanding the rich tapestry of complex interactions between the body and the brain. An interesting and important interdisciplinary metaphor is the notion that biological inflammation represents excess heat, and the incineration of information contained in the amazing and beautiful complexity of the human body at all scales of organization, which is lost to entropy. Entropy is a physical property that is a measure of disorder and it grows over time in physical systems as expressed by the second law of thermodynamics. Biological systems, in contrast to physical systems, reduce entropy due to metabolic energy conversion. Loss of ability to reduce entropy represents an acceleration of biological aging subject to the unavoidable force of the second law of thermodynamics that drives all systems toward a maximum entropy state (179). In the case of living systems, this is overcome by the metabolic energy

The Physiological Fitness Landscape has the potential to be a groundbreaking tool in healthcare. How can we use interdisciplinary perspectives to accomplish the goal of precision diagnostics and rational therapy design?

The physiological fitness model can be used to explain the most fundamental parameters of homeostasis in terms of free energy changes, redox fluxes, and acid base status. It also allows targeting the foundational basis of disease, that is, disturbances in bioenergetic metabolic machinery that is inextricably interwoven with the most elemental parameters of homeostasis rooted in the parallel equations of Gibbs free energy (ΔG), Nernst and Henderson-Hasselbalch. Indeed, the allostasis of the neuroendocrine, autonomic, and immune systems evolved for the very purpose of maintaining these homeostatic measures within tight ranges. When this fails, immune system function goes awry as inflammatory, redox homeostasis, and

FIGURE 2.37  Metabolism and clinical medicine. An interwoven and self-amplifying web of parameters that are affected by stress that results in insulin resistance, mitochondria dysfunction, and disturbed circadian rhythms.

90 input and its conversion into biological structure formation, its maintenance and functional organization. However, with the passage of time these processes become less and less efficient and more and more error-prone leading to biological aging and eventually death. The processes involved in biological energy production, utilization, and efficiency are also closely related to the analogous properties of physical systems, hence it is important to appreciate the fact that physics can inform biology and medicine by being a more mature branch of science dealing with simple systems that lend themselves to precise analysis. Admittedly, biology deals with complex systems that are enormously hard to analyze by reductionist approaches as we have argued throughout this book. For this reason, the use of metaphors borrowed from physics such as entropy, energy balance, thermodynamic equilibrium, quantum coherence, or biostability can offer intuitive insights that are otherwise notoriously difficult to extract from massive amounts of data.

2.7.4 Mediators of the Shift from Health to Disease A transition from a healthy state to a disease state can be described as a symmetry-breaking phenomenon. This is a moniker that has elucidated numerous complex transitions in such physical systems as elementary particles and condensed phases of matter. We believe a similarly profound understanding can be achieved in the field of medicine. A fundamental theme of this book is the stress response state of arousal due to external factors, both real and imagined. These factors, depending on the personal characteristics, can either lead to positive or negative responses by the human body. They can vitalize psychophysiology and even optimally shape genetic potential, or conversely, they can cause psychological and physiological pathology. The former scenario is achieved largely by top-down regulation of thought, emotion, and behavior mediated by the strengthening of neural and synaptic plasticity of the PFC, hippocampus, and limbic brain regions. Synaptogenesis and strengthening of existing synaptic connections within cognitive centers including the PFC results in healthy patterns stimulated by positive experiences, perceptions, and resilience, and largely governed by the capacity and confidence to control the outcome of important life challenges. Conversely, synaptic growth in the amygdala is associated with unhealthy patterns of exaggerated prolonged emotional responses stimulated by negative experiences and/or learned helplessness (see the previous section on synaptic plasticity) These adverse responses in turn perpetuate the chronic stress response. Structural plasticity of the PFC, hippocampus, and limbic brain regions is critical for high-level consciousness and cognitive functions responsible for goal-directed behavior of free will. By effectively controlling the emotional centers of the brain, specifically the amygdala, subconscious chronic feelings of fear and anger as well as emotionally driven motivational behavior for food and other hedonic rewards are prevented (Figure 2.38). This blocks the driving force of systemic pro-inflammatory and out-of-control bottom-up processes that accelerate biological aging and promotes cognition over emotion top-down control (Figure 2.39).

Metabolism and Medicine Alternatively, chronic excessive and uncontrollable stress responses dictate bottom-up processes characterized by the overload of allostatic systems (180). The many consequences include decreased parasympathetic vagal tone, increased sympathetic activity with reduced heart rate variability, a chronically activated HPA axis, a pro-inflammatory cytokine dominance, insulin resistance with impaired glucose tolerance, and chronic hyperinsulinemia (Figure 2.40). Additional susceptibility states for chronic metabolic diseases include neurodegenerative and cardiovascular diseases and even cancers making this a very serious health risk (Figure 2.41). The exaggerated and prolonged stress response is a fundamental component and often the origin of virtually all chronic diseases. How can we modify clinical practice to account for stress vulnerability?

The notion of stress should be used in medicine to recognize disease susceptibility states. For example, type 2 diabetes is more fundamentally a lipocentric disorder than it is a glucocentric one. However, standard medical practice calls for a fasting lipid profile when postprandial conditions are by far more sensitive for discerning underlying insulin resistance. This becomes problematic when combined with a preexisting condition. For example, a patient with a familial genetic mutation (e.g. LPL or apo-C2) for severe hypertriglyceridemia has only a modestly abnormal lipid profile in the non-stressed baseline state. However, under the setting of hypothyroidism, new onset or uncontrolled diabetes represent metabolic stressors that express the genetic defect, often driving triglycerides to well above 1,000 mg/dL (abnormal levels). This can cause acute pancreatitis, a lifethreatening condition. Too often we focus solely on treating the thyroid or the diabetes because when these conditions are controlled, the lipid levels become tame, however only until the next metabolic stressor. Because it is the underlying dyslipidemia, mediated by acute pancreatitis, that may be more life threatening than the hypothyroidism or diabetes per se, it is often overlooked but crucial to treat the lipid disturbance (with fibrates as a first line of treatment). The conventional stress test in cardiology should be considered the original prototype for many forms of stress testing applied across specialties of clinical medicine. Furthermore, chronic physical stress provokes pro-inflammatory immune system allostatic responses of cytokines that activate the autonomic and hormonal branches of the stress response and reduce the threshold for the perception of stress causing a positive feedback destabilizing and reverberating loop of mind–body pernicious effects of stress (Figure 2.42). The notion of using stress-related information for the diagnosis of all chronic disease states is analogous to the prototypical treadmill cardiac stress test. In the heart, it’s about myocardial ischemia after reaching a threshold of metabolic demand that exceeds the mitochondrial capacity. Fundamentally, any disease state can be provoked by increasing the metabolic demand on the tissues that express the diseased state (181). This is manifested by an uncoupling of the glycolytic conversion of glucose (to pyruvate) with the completion of glucose oxidation in the mitochondria, in the oxidative phosphorylation process.

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FIGURE 2.38  Physiological fitness and feedback loops. An overview of the Physiological Fitness Landscape and associated feedback and feedforward loops. *GABA = gamma aminobutyric acid; ΔG = Gibbs free energy.

FIGURE 2.39  Cognition over emotion top-down control. Vitalizing energy leads to cognition overriding emotion. *PFC = prefrontal cortex.

In the case of ischemia of the myocardium, vessel occlusion prevents sufficient O2 uptake relative to the metabolic demand when “stressed”, thus creating an energy crisis. The physical diagnosis of ischemic disease is based on electrocardiographic changes in specific regions of the heart that are being fed by the occluded vessel branches. In the case of “global ischemia”, it is interpreted to be the result of occlusion of the main coronary trunk. This may be the case; however, typically it is not, reflecting a non-ischemic disease state per se. Rather, it is

FIGURE 2.40  Emotion over cognition top-down control. Devitalizing energy leads to emotion overriding cognition.

more likely the result of too much O2 supply relative to the mitochondrial capacity to use it. Stress in the form of physical exertion and emotional strain may be considered natural stress tests in present day human society for the precipitation of disease. As in the prototypical but artificially diagnostic condition of a cardiac stress test, quantifiable measures of physical exertion or emotional strain on various scales may be diagnostically applicable to susceptibility to viral disease or cancer, for example. Metabolically, these cases relate to tissue-specific measures of stress-induced

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FIGURE 2.41  Stress and accelerated disease. An overview of how prolonged devitalizing stress leads to destabilizing feedforward loops and ultimately emotion overriding cognition.

Metabolism and Medicine In the case of cancer, side pathways emanating from the central glycolysis pathway intermediates largely provide the building blocks of cell replication (see Warburg effect and Brownlee hypothesis in Chapters 1 and 8). The goal for medicine should be to invoke these concepts into experimental protocols capable of becoming useful for discovering susceptibility states of the branches of immune suppression (and hence viral infections or cancers), or of epithelial cell transformation (and hence cancers). The challenge is to develop a quantifiable measure of the lowest stress dose capable of uncovering a diagnosis at the subclinical stage that is readily treatable. Furthermore, these experimental developments should coincide with advances in reversing susceptibility states, which should be highly achievable using a Physiologic (or Metabolic) Fitness Landscape (see Chapter 9). The following insert is an example of how physiological stress, in this case exercise, can onset and exacerbate immune suppression thereby uncovering a diagnosis, in this case, the coronavirus disease 2019 (COVID-19). COVID-19 is caused by infection by the coronavirus (SARS-CoV-2). This coronavirus directly targets the renin-angiotensin-aldosterone-MRs system involved in electrolyte homeostasis.

SIDEBAR 2.1 EXERCISE-INDUCED ONSET OF COVID-19

FIGURE 2.42  Stress and chronic diseases of aging. An example of how stress as part of a self-amplifying circuit can lead to chronic disease of aging. *CVD = cardiovascular disease.

challenges on oxidative metabolism. When tissues such as immune or epithelial tissue cells are deprived of sufficient oxygen, they become energetically compromised. This is due to the provocation of metabolic demands and consumption of available oxygen by muscle (in the case of physical exertion) and/or the limbic, autonomic, and hormonal systems originating in the brain (in the case of emotional strain). Immune cell activation, in particular, is the most energy expensive process of the body. Under stress conditions, both immune and epithelial cell types and tissues are forced to rely on the less productive glycolysis pathway to meet their energetic needs rather than oxidative metabolic pathways of the TCA (tricarboxylic acid) Krebs Cycle and the respiratory chain of electron transport.

A 55-year-old male patient reported the onset of flu-like symptoms less than an hour after he completed a highintensity exercise on the elliptical in his home following a full day’s work on a Friday evening. He had not done such high-intensity exercise within the prior three months. Within one hour of the exercise, he reported feeling cold and developing chills, despite a normal room temperature. Later that evening, he developed a headache. He did not report any of the common COVID-19 symptoms such as fever, sweats, cough, or shortness of breath. The next day, he continued to feel chills and Tylenol did not abate his headache. Moreover, malaise set in, further debilitating him. He reported having difficulty reading and writing emails followed by an onset of fatigue and weakness. This mental and physical exhaustion persisted, along with the chills, headaches, and malaise. Unsure if his symptom could be due to the flu or COVID-19, he stayed home for one week and quarantined himself in the basement of his home. During his quarantine, the patient developed a low-grade fever of about 100.4° F—one of the most common symptoms of COVID-19. By the end of the following week, the patient’s symptoms had not improved so he decided to call his primary physician who sent him for COVID-19 testing. Two days later, the test came back negative. The patient decided to rejoin his family upstairs and end his quarantine, but keep his distance in case his illness was contagious. He slept in the basement as a precaution. The next day, the patient spiked a temperature of 101° F, developed a cough and shortness of breath, all of which are the most common symptoms of COVID-19. He drove himself to the emergency room. Chest X-ray and chest CT

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The Stress Response scans confirmed bilateral pneumonia consistent with the pattern of COVID-19. Later that day, while still in the ER awaiting transfer to a hospital bed, the COVID-19 test that was negative the day prior, was now positive. In the “Pearls, Hallmarks and Linchpin Concepts Connecting Mitochondrial Dysfunction to Chronic Diseases of Aging” section in Chapter 8, I apply the metabolic, often intertwined, concepts of the Warburg effect and the unifying pathobiology of Diabetes as the molecular explanation for all chronic disease. For example, when you stress (impose a demand on) the myocardium that has chronically been exposed to inflammatory and oxidative stress, e.g. insulin resistance promoting ectopic fat deposits into the myocardium, the organelle most sensitive to becoming dysfunctional (and becoming part of the self-amplifying loop of potentiating oxidative stress and destruction of bioenergetic capacity) is the mitochondria. Consequently, when the energy demands on a tissue increase beyond the mitochondrial potential to physiologically cope with the energy stress, the result is impaired performance. In the case of nonischemic cardiomyopathy, a positive stress test with global hypokinesis and electrocardiographic changes are largely the result of various oxidative and glycosylated states. This involves the hexosamine modifications of intracellular proteins, such as the contractile myocellular filaments, regulating kinases of calcium and other ion channels. Notably, glycosylation of these proteins can be physiologically transient and protective in the setting of ischemia and ischemiareperfusion injury in an otherwise healthy myocardium (the so-called “stunned myocardium”) (182). However, with an underlying pre-existing cardiomyopathy, prolonged and exaggerated hexosamine pathway mediated glycosylations (along with mitochondrial dysfunction mediated redox stress) drive a feedforward and self-amplifying destructive progression of the underlying disease. Furthermore, other non-energy-producing pathways that originate from the intermediates of the central glycolysis energy-producing pathway, such as AGE/RAGE, NFkB, and DAG/PKC pathways (see Chapter 9). Analogous processes explain the manifestations of Alzheimer’s disease, accelerated cognitive decline, and the clinical expression of cancer. This metabolic perspective can prove to have enormous value in clinical diagnostic medicine by applying disease-specific protocols. In addition to stress, we argue that metabolism is the fundamental basis for health and disease as it is the distinguishing characteristic of any living system. The notion of quantum metabolism is not a concept that is traditionally part of the endocrinologist's lexicon, however, it is scientifically deserving of it. The state of coherent production of biological currency of energy across spatial and temporal scales of organizational complexity occurs only in the spectrum of optimal health, opposite to the state of disease. Perturbation of the inextricably interwoven homeostatic parameters of redox, acid–base, and Gibbs free energy, the latter being free energy available for doing the work of biological and histological processes, can have detrimental consequences. The concept of quantum metabolism is itself an abstraction not applicable in

a tangible and commercially testable context to patient care. Nonetheless, the concept has merit in the sense of appreciating how metabolic pathways and metabolism are the most fundamental perspectives for understanding the trajectory from healthy to disease states. Moreover, this is applicable to virtually all chronic disease states as well as to the process itself. Metabolism is an essential property for life and is core to the concept of fitness function and accordingly is tangibly applicable to research and clinical medicine in the framework of a Physiological Fitness Landscape model. The notion of quantum metabolism is a new concept with important implications for our understanding of the living state since all life forms require an energy input for survival. It highlights that our metabolism is truly a quantum mechanical phenomenon. This implies correlated bioenergetics across scales from mitochondria to cell to tissues and it makes possible the extraordinary complexity and efficiency of human physiology. Importantly, top-down regulation of psychophysiology attenuates allostatic overload and associated processes of insulin resistance and mitochondrial dysfunction. This slows the degradation of the biological fabric of space-time through the efficiencies enabled by quantum metabolism. This is comparable to what the various allostatic mediators achieve on different levels of biological organization and within defined but overlapping time domains either by regulating gene expression or by informing the membrane for rapid non-genomic actions. Below the takeover threshold of nutrient balance or energy oversupply, the metabolic cycle is in the quantum regime. Above it, it switches to the classical regime with allometric scaling becoming isometric. In this latter case, energy lost as heat is not used for thermogenesis but rather as inflammation accompanying electron leakage along with superoxide formation, etc. This leads to mitochondrial dysfunction, which is inextricably linked to insulin resistance, which impairs satiety and leads to inefficient bioenergetics associated with adiposity. This is key since it applies not just to cancer but to other chronic disease states and aging with or without metabolic disease of insulin resistance. This is in addition to the molecular mechanisms that distinguish oxidative phosphorylation from glycolysis. In my opinion, this is a major concept with major consequences for understanding the origin of chronic diseases. Insulin resistance and mitochondrial dysfunction are reciprocally related, and hence loss of metabolic efficiency is fundamental to senescence and chronic disease.

Genetic and extrinsic control parameters can modify the pace of aging. By regulating extrinsic control parameters, that is the environment with which it interfaces, as well as our perception of personal well-being, accompanying goal-oriented motivations, we can optimize the vitalizing nature of the stress response. The neuroendocrine and autonomic axes of the stress response represent the parameters of allostasis, the purpose of which is to maintain homeostasis of vital organ system function. When this is perturbed, the immune system goes awry, and so do parameters of redox homeostasis and free energy that are necessary for preserving the deeply entangled

94 hierarchical scales of biological systems as well as the correlated nature of energy production rooted in metabolic cycles. The slowing of this most fundamental and highest frequency of all intrinsic cycles of the living state of an individual disturbs the fractal nature and integrated timing with each successive more macroscopic scale of biology. Accordingly, the electromagnetic quantum properties that intercede the most efficient operating function of an organismic whole collapse. However, the potential for coherence of organizational complexity at the organism level is metaphorically analogous to the various wavelengths of light of a laser pointer coherently aligning into a single wavelength. This is the basis for the intriguing notion of special relativity in biology and the potential for the dilation of biological time and age and hence the deviation from chronological age.

2.7.5 Implementation of the Physiological Fitness Landscape Model in Clinical Practice We introduced the concept of the Physiological Fitness Landscape model, which is a quantitative measure of an individual’s state of health or disease represented by a multidimensional topography. Each axis in this model consists of control and order parameters. A control parameter represents a potential stress factor that can be applied to the organism (Figure 2.43). For example, a control parameter can be nutritional intake (including non-food items and xenobiotics), or physical exertion and or even the disturbances in circadian rhythmicity. Equally important, an order parameter is a variable that the living system changes in response to the control parameters and whose value is a measure of health or disease. A classic example would be the maximum heart rate that correlates with the VO2 max in response to vigorous exercise, the latter being measured by speed of running or the maximum velocity attained on a stationary bike. The rate of response of the order parameter, or its change, as a function of the control parameter is defined as generalized susceptibility. In measuring a healthy state, its response

FIGURE 2.43  Loss of physiological fitness. An overview of how loss of physiological fitness leads to chronic diseases of aging.

Metabolism and Medicine to stressors should be limited when the state is stable or robust. This is the premise for the proposition that the prototypical cardiac stress test be a model for analogous stress testing that assesses susceptibility states of other chronic disease. On the other hand, lack of susceptibility to therapeutic agents in the disease state is indicative of the therapy’s failure or the resistance to therapy by the disease, such as in the case of drug resistance in cancer. Conversely, normalizing the vital parameters (order parameters) in a dose-response manner with respect to an intervention is a manifestation of moving the disease state toward the state of health and hence a successful outcome of the therapy. Creating a detailed map of the Physiological Fitness Landscape for each person is still a distant goal but it should be achieved in the coming decades. Navigating this map could lead to rationally designed choices of a promising target for clinical intervention or indeed a timedependent therapeutic plan, which is dynamically redesigned as therapy encounters resistance (low susceptibility) of the disease state to change. Healthcare providers will play a vital role in their patient’s capacity to navigate the Physiological Fitness Landscape by evaluating both psychogenic and physiologic factors that contribute to an individual’s state of “fitness” and how they will respond to stress during states of both health and disease. Psychogenic stress is foundational to physiological stress, at all hierarchical scales, from molecular to macroscopic manifestations of health and disease. The prototypical cardiac stress test proposed above can be invoked and tailored for diagnostic purposes to all specialties of medicine. While this may seem like a basic conceptual premise, more specifically, this relates to tissue-specific measures of stress-induced challenges of oxidative metabolism. In order to integrate this concept into medicine, it will require an evolution of organ and/or tissuespecific protocols capable of distinguishing health versus disease. In turn, this will require interdisciplinary integration of smart minds, and creative scientific thinking across multiple scientific fields. By incorporating a Physiological Fitness Landscape model of control and order parameters, both qualitative and quantitative assessments can be employed, the former for the immediate future; however, the latter requires a more scientifically integrated cultural shift in medicine, thus dictating a longer-term horizon. Adaptability and flexibility are paramount in navigating this topographic landscape of mountains and valleys to maintain a state of homeostasis and ultimately increase chances of survival. The evolution of allostasis from protective to harmful in terms of human pathophysiology and psychopathology is depicted in (Figure 2.44), whereby an individual may toggle between stressed and equilibrium states. Allostatic mediators such as healthy initial and primary allostatic parameters including cortisol, DHEA (dehydroepiandrosterone), inflammatory and anti-inflammatory cytokines, catecholamines, and acetylcholine, allow the body to toggle between these two states. In this scenario, a valley represents the stable state of the system as it requires a minimal amount of free energy and is metabolically most efficient. The onset of a stressor would move the system out of equilibrium and metaphorically drive one to a metastable (unstable) state, here represented as a mountain, that requires an increase in free energy as it is more

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FIGURE 2.44  The effects of stress on fitness function. The evolution of allostasis under ideal non-stress conditions a), a period of negative stress followed by vitalizing stress b), and a period of negative stress followed by chronic stress c). Under no stress conditions, biological aging and chronological aging occur at the same rate. As toxic stress levels rise, allostasis drives the maintenance of homeostasis leading to protective/health-promoting stress and a slight disharmony between biological aging and chronological aging. When toxic stress is followed by chronic stress, the threshold of allostatic load is surpassed and the body can no longer maintain homeostasis leading to harmful/health-damaging, driving the system towards accelerated aging and human pathophysiology and psychopathology.

metabolically demanding. Due to the unstable nature of the mountaintop, we will inevitably fall from it. If the stressor is removed, we may fall back into the original valley we came from, thus regaining stability and allostasis. However, if we have been pushed to the very peak, we may slide down into an alternate valley on the other side of the mountain, which represents a different physiological state resulting from allostatic overload (or a progressively more pathological state from more severe levels of perturbations in the parameters of allostatic overload, as the altitude of the valley diminishes within the topographic terrain). The fear of falling into such unknown valleys supports the development of psychogenic disturbances such as anxiety and depression (Figure 2.45). However, change is inescapable and a hallmark of the Physiological Fitness Landscape itself. Our exquisite ability to adapt and respond flexibly to change is a strategy we must utilize to maintain allostasis and develop resilience. Similar to these psychological factors in the way we navigate the Physiological Fitness Landscape is our innate physiological reaction to the stress response, which recruits the action of hormones, triggers autonomic arousal, and engages immune

system function to protect the body and retain a position of equilibrium in the form of homeostasis. This is the biological underpinning of allostasis. However, in order to maintain these homeostatic mediators, we must exercise our capabilities to be flexible in response to stress in order to foster resilience to future psychological or physiological hardships. In other words, we need to experience both the lows of the valleys and the highs of the mountaintops in order to develop protection from future shifts in this metabolic landscape. Uncharted valleys represent challenges to which we might lack the robustness to withstand. However, they are psychologically motivating to have a fuller and richer life by searching for ways to adapt, that is building resilience via flexibility. Flexibility is achieved by finding resources, in the form of lifestyle habits, kinder personalities, and larger personal networks that nurture the progression towards heterogeneity. That is, our current traits can adapt within ourselves and as a group with others to become part of a larger and greater system whole. This allows us to rise above challenges via flexibility when initial robustness is unsuccessful and is penetrated. Inviting challenges to enrich the heterogeneity of life is the crucial

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FIGURE 2.45  Extrinsic control parameters. The self-amplifying feedforward loop of extrinsic control parameters on accelerated aging and chronic diseases.

ingredient to vitalizing stress that motivates finding new paths to fulfilling joy or resilience to toxic stress. The Physiological Fitness Landscape is a dynamic and powerful system, which stress ultimately has the unique ability to disrupt and fracture. It requires delicate orchestration of psychological and biological factors that intersect to provide us with the skills necessary to maneuver through this continually changing environment of peaks and valleys in efforts to increase chances of survival. The concept of Physiological Fitness Landscape is borrowed from physics, a comparatively far more mature scientific discipline than biology, in order to better understand biological systems. This is especially useful in the context of medicine, where these insights may have the greatest impact on human life. Implications of this concept for medicine have a Nobel Prize worthy potential and its applicability to physiology has already been demonstrated. The compartmentalization of

Metabolism and Medicine scientific disciplines, particularly clinical medicine from the branches of physics, should be recognized as a pathological isolation. Moreover, it should be described as an extraordinary and even tragic oversight that this model has not yet been invoked into the standards of clinical medicine. By homing in on various aspects of the stress response in the context of the metaphorical Physiological Fitness Landscape, metabolic susceptibility states for disease can be identified as the control and order parameters for phase transitions from a healthy to a disease state. Further, the trajectory to chronic disease may be predicted based on mathematical models of these parameters and their attractors. This has profound implications for both diagnostic and therapeutic purposes. Points of criticality may represent the threshold for phase transition from normal to the disease state and predictions can be made regarding this transition's reversibility or irreversibility, which would be of enormous clinical value (Figure 2.46). Thus, the model of Physiological Fitness Landscape can serve as a critical tool and strategy to the development of therapeutic interventions capable of targeting control parameters and changing the trajectory of order parameters from reversible stages of disease or susceptibility states to normal states (Figure 2.47). Additionally, the neuroendocrine system, and the brain as the principal organ of allostasis along with the primary and secondary mediators of allostasis deserve center stage attention for the implementation of the model of Physiological Fitness Landscape in medicine (Figure 2.48). This chapter addressed several pertinent questions, including: What is stress? What is the effect of stress on the human body, or stress response? When is the response healthy and when is it pathological? How do our bodies try to maintain metabolic and physiological equilibrium and when do they fail to do so? Finally, how can we best achieve a prolonged state of optimal health facing both modern day's stresses and our

FIGURE 2.46  Healthy and stressed Physiological Fitness Landscape. Metabolic susceptibility states for disease can be identified as the control and order parameters for phase transitions from a healthy a), to a diseased b) state. The trajectory to chronic disease may be predicted based on mathematical models of these parameters and their attractors known as the Physiological Fitness Landscape, which is a quantitative measure of the state of health or disease for each individual represented by a multi-dimensional topography. This has profound implications for both diagnostic and therapeutic purposes. Susceptibility states for chronic metabolic diseases include neurodegenerative and cardiovascular diseases and even cancers making this a very serious health risk. *BMI = body mass index.

97

The Stress Response

these forces, which can be in general referred to as stress, can lead to responses that include maintaining robustness of the biological systems, and sometimes even improving the state of health, but unfortunately in many cases the opposite is true. Chronic stress that is not properly handled may lead to addictions, mental disorders, psychopathologies, and an untimely demise.

2.8 Take-Home Messages

FIGURE 2.47  Human health and disease. Prolonged or chronic stress leads to a variety of downstream physiological outcomes including increased inflammation, immune system dysfunction, emotional and cognitive disturbances, anxiety, depression, disturbed microbial composition, and sleep disruption.

own inevitable aging processes? We also discussed a set of important concepts that is related to maintaining equilibrium under external perturbations and adapting to such perturbing forces that are always associated with being alive. However,

• Homeostasis means resistance to change (such as body temperature, pH, electrolyte concentration) and is a concept closely related to thermodynamic stability of physical systems. Homeostasis is a stable equilibrium. • Allostasis means stability through change and is a hallmark of healthy adaptation to environmental conditions that are typically processed in the brain. The mediators of allostasis (primarily hormonal, catecholamine, and immune responses) are both protective, in the case of allostasis, and harmful, in the case of allostatic overload. Allostasis is the process of stabilizing the change and allostatic load is the cost of the process on the body.

FIGURE 2.48  Physiological Fitness Landscape. The Physiological Fitness Landscape for human progression from health to disease. Optimal health depends on a variety of parameters including exercise level and nutrition level.

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Metabolism and Medicine • The purpose of allostasis is to maintain homeostasis of vital organ system function. This is embodied in a mechanism of adaptive resilience (coping) of the living system, which is regulated by the endocrine, nervous and immune systems through coordination of cell, tissue, and organ function. The integration of these systems over time promotes memory storage to prepare for the future. • Allostatic overload occurs as a result of chronically elevated hormonal, catecholamine, and inflammatory mediators of allostasis outside of regulatory control. Consequently, cortisol and catecholamine resistance present, which represents a compensatory rise in the pro-inflammatory responses not counterregulated by glucocorticoids. • At some dose and duration, a given stressor can be either vitalizing and health-promoting or devitalizing and toxic. This depends on how the individual copes with the stressor based on previous experiences and innate properties. • The brain integrates information to assess the risk/ danger versus reward of many actions, to predict the likelihood of attaining a goal state, or homeostasis, that reduces the uncertainty of the strategy to the present challenge at hand. • Under stress, the brain’s ability to resolve problems is compromised due to atrophy of dendritic branches and synapses in neuronal networks underlying executive cognitive functions. • The exaggerated and prolonged stress response is often the origin of increased vulnerability to chronic diseases. • The Physiological Fitness Landscape can serve as a critical tool and strategy to the development of therapeutic interventions capable of targeting control parameters and changing the trajectory of order parameters from reversible stages of disease or susceptibility states to normal states.























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3 Nuclear Hormone Receptors: Mediators of Dynamic (Patho)physiological Responses

Abbreviations ABC(A1/G1/G5/G8) ACC ACOX AF-1 AgRP Akt ALA AMP AMPK ANS ANG2 ANGPTL3 Apo(A-1/E/2/3/4/5) apoCII AR ATP BARE BAT BSEP CA cAMP CAR CBP CDCA CETP ChREBP

ATP binding cassette A1/G1/G5/G8 acetyl-CoA carboxylase acyl-CoA oxidase activation function 1 agouti-related protein protein kinase B (PKB) alpha-linolenic acid adenosine monophosphate AMP-activated protein kinase autonomic nervous system angiopoietin 2 angiopoietin-like 3 apolipoprotein A-1/E/2/3/4/5 apolipoprotein C-II androgen receptor adenosine triphosphate bile acid response element brown adipose tissue bile salt export pump cholic acid cyclic adenosine monophosphate constitutive androstane receptor CREB-binding protein chenodeoxycholic acid cholesteryl ester transfer protein carbohydrate response element binding protein CoA co-activator COUP-TF(I/II) chicken ovalbumin upstream promoter transcription factor I/II CPT1/2 carnitine palmitoyltransferase 1/2 CREB cyclic AMP response element binding protein CYP(3A4/8B1/27A1) cytochrome P450 3A4/8B1/27A1 CYP7A1 cholesterol 7α hydroxylase CYP7B1 25-hydroxycholesterol 7α hydroxylase DAX dosage-sensitive sex reversal adrenal hypoplasia congenita critical region on the X chromosome gene DBD DNA binding domain DCA deoxycholic acid DHA docosahexaenoic acid DNA deoxyribonucleic acid DNL de novo lipogenesis DOI: 10.1201/9781003149897-3

DSS EcR EGF EPA ER ERR(α/β/γ) FA FAO FAS FBP1 FFA FGF15/19/21 FGFR4/β-klotho FXR G6P G6Pase G6PC GC GC Gcg GCNF GLP-1 GLUT(1/4) GPCR GPK GR GRE GS GSIS GSK3 H2O2 HCA HDCA HDL HGO HMGCR HNF Hr HSP(70/90) IDOL IGF-1 IL(-1/6) IR LBD LCA

dextran sulfate sodium Ecdysone receptor epidermal growth factor eicosapentaenoic acid estrogen receptor estrogen related receptor α/β/γ fatty acid fatty acid oxidation fatty acid synthase fructose-bisphosphatase 1 free fatty acid fibroblast growth factor 15/19/21 fibroblast growth factor receptor 4/β-klotho complex farnesoid X receptor glucose-6-phosphate glucose-6-phosphatase glucose-6-phosphatase catalytic subunit glucocorticoid proglucagon gene germ cell nuclear factor glucagon-like peptide-1 glucose transporter 1/4 G protein-coupled receptor glycogen phosphorylase kinase glucocorticoid receptor glucocorticoid response elements glycogen synthase glucose-stimulated insulin secretion glycogen synthase kinase 3 hydrogen peroxide hyocholic acid hyodeoxycholic acid high-density lipoprotein hepatic glucose output hydroxy-methyl-glutaryl-CoA reductase hepatic nuclear factor hinge region heat shock protein 70/90 inducible degrader of the low-density lipoprotein receptor insulin-like growth factor 1 interleukin-1/6 insulin receptor ligand binding domain lithocholic acid 105

106 LDL LPCAT3 LPL LRH LXR LXRE MAP kinase MR NAD NADPH

low-density lipoprotein lysophosphatidylcholine acyltransferase 3 lipoprotein lipase liver receptor homolog liver X receptor LXR response element mitogen-activated protein kinase mineralocorticoid receptor nicotinamide dinucleotide nicotinamide adenine dinucleotide phosphate NASH non-alcoholic steatohepatitis NCoR nuclear receptor corepressor NF-κB nuclear factor kappa-light-chain-enhancer of activated B cells NGFI-B nerve growth factor-induced-B NHR nuclear hormone receptor NO° nitric oxide NOR1 nuclear orphan receptor 1 NTD N-terminal domain NPC1L1 Niemann-Pick C1-like protein 1 NPY neuropeptide Y NR (I/II) nuclear receptor I/II NRRE nuclear receptor response element Nurr(1/77) nuclear receptor related protein 1/77 OR orphan receptor PCK1 phosphoenolpyruvate carboxykinase 1 PCSK9 proprotein convertase subtilisin/kexin type 9 PEPCK phosphoenolpyruvate carboxykinase PFKBP1 phosphofructokinase-bisphosphatase 1 PGC1α(1/2/3/4) peroxisome proliferator-activated receptor gamma coactivator 1α1/2/3/4 PI3K phosphatidylinositol 3-kinase PKA protein kinase A PKC protein kinase C PLTP phospholipid transfer protein PNR photoreceptor-specific nuclear receptor POMC pro-opiomelanocortin PON1 paraoxonase-1 PPAR(α/β/γ/δ) peroxisome proliferator-activated receptor α/β/γ/δ PPRE PPAR response element PR progesterone receptor PUFA polyunsaturated fatty acid PXR pregnane X receptor PYY peptide YY RA retinoic acid RAR retinoic acid receptor RCT reverse cholesterol transport RIP140 receptor-interacting protein 140 RNS reactive nitrogen species ROR(α/β/γ) retinoid-related orphan receptor α/β/γ ROS reactive oxygen species RXR(α/β/γ) retinoid X receptor α/β/γ S1P sphingosine-1-phosphate S1PK sphingosine-1-phosphate kinase S1PR2 sphingosine-1-phosphate receptor 2 SARM selective androgen receptor modulator

Metabolism and Medicine SCFA SERM SF-1 SFA SGLT-1 SHP SIRT1 SLiM SMRT

short-chain fatty acid selective estrogen receptor modulator steroidogenic factor 1 saturated fatty acid sodium glucose cotransporter 1 small heterodimer partner sirtuin 1 selective LXR modulator silencing mediator of retinoic acid and thyroid hormone receptor SphK1 sphingosine kinase 1 SPPARM selective PPAR modulator SREBP(1c/2) sterol regulatory-element binding protein 1c/2 SUMO small ubiquitin-like modifier SXR steroid and xenobiotic sensing nuclear receptor T3 triiodothyronine T4 thyroxine TCA taurocholic acid TG triglyceride TGR5 Takeda G protein-coupled receptor 5 TLCA taurolithocholic acid TLX “tailless” human orphan nuclear receptor TNF-1 tumor necrosis factor-1 TR(α/β) thyroid hormone receptor α/β TZD thiazolidinedione T2DM type 2 diabetes mellitus UCP1 uncoupling protein 1 UDCA ursodeoxycholic acid VDR vitamin D3 receptor VLDL very low-density lipoprotein WAT white adipose tissue

Chapter Overview In humans, the regulation of growth, metabolic homeostasis, and development processes involve extensive intercellular communication. This is achieved by various endocrine signals that often communicate with intracellular receptors that regulate gene expression. In this latter process, transcription factors, specifically nuclear hormone receptors (NHRs), participate in the up- or down-regulation of gene expression. Nuclear hormone receptors are ligand-inducible transcription factors that mediate changes to whole-body metabolic pathways (Figure 3.0). Nuclear receptors include steroid ligand nuclear receptors such as androgen receptors (AR), estrogen receptors (ER), progesterone receptors (PR), glucocorticoid receptors (GR), and mineralocorticoid receptors (MR). These classical nuclear hormone receptors induce transcription by binding to DNA as homodimers. They have evolved to regulate carbohydrate and lipid metabolism, development, reproduction, and electrolyte balance. The regulation of ligands that bind to these hormone receptors takes place via the classical negative feedback mechanisms of the hypothalamic-pituitary axis. The extended family of steroid nuclear hormone receptors such as GR and peroxisome proliferator-activated receptors (PPARs) are involved in

Nuclear Hormone Receptors

FIGURE 3.0  Nuclear hormone receptor summary. NHRs are involved in numerous physiological processes, including metabolism, reproduction, cell growth and differentiation, immune function, and CNS functions. Source: adapted from Yang X. “A wheel of time: the circadian clock, nuclear receptors, and physiology”. Genes & Development 24(8), 741–747 (2010).

the sensation and utilization of energy. For example, the hormone glucocorticoid binds to the GR, regulating hepatic and systemic glucose metabolism. PPARs regulate whole-body glucose and lipid metabolism. Thus, under normal physiological conditions, GR and PPARs maintain systemic energy homeostasis. Additionally, recent studies have suggested that NHRs are tractable targets for cardiovascular disease and diabetes therapy. This is particularly the case for Farnesoid X receptors (FXRs) and liver X receptors (LXRs), which are known to control multiple metabolic pathways. Upon activation by bile acids, FXR regulates numerous aspects of lipid and glucose metabolism. LXRs play a crucial role in regulating the reverse cholesterol transport pathway in lipogenesis and the maintenance of whole-body glucose homeostasis. Current studies have indicated that both LXR and FXR are associated with the development of metabolic diseases. Therefore, FXR and LXR might have therapeutic implications for the treatment of metabolic diseases such as type 2 diabetes and cardiovascular disease. In addition, ~25% of adipose tissue genes are regulated by the circadian clock to maintain lipid energy metabolism. Thus, the nuclear receptor family plays a pivotal role in mediating communication between circadian rhythms and metabolic functions to maintain whole-body energy homeostasis.

3.1 Historical Context Nuclear receptors (NRs) are a class of proteins found within cells that play diverse roles in physiology, metabolism,

107 immune response, enzyme activity, cell differentiation/development, as well as pathological processes. The NR research sector is traditionally a subfield of molecular biology and has a rich history. To describe the seminal contributions of numerous scientists to this field would comprise an entire book in its own right. The purpose of this synopsis is not to describe at length all the merit-worthy contributors in this field going back to the 1960s but rather to extend a general recognition to the many pioneers who have shaped insights to nuclear hormone receptor circadian biology, metabolism, and physiology. The NR field emerged in the 1960s when scientists, such as Elwood Jensen, Jan-Ake Gustafsson, and Keith Yamamoto, first identified the hormone receptors using classical biochemical techniques (1). Thereafter, in the mid-1980s, the genes (complementary DNA; cDNA) encoding the steroidal glucocorticoid receptors (GRs) were first fully identified using novel molecular cloning technology by Ronald Evans and colleagues (2) (Figure 3.1). These structures were found to be very similar to the steroidal estrogen receptors (ERs) and related to the non-steroidal thyroid hormone receptors (TRs) (3), thus, establishing the concept of a highly related family of nuclear hormone receptors (NHRs). The cloning of these receptors was one of the most revolutionary and surprising findings in the field. It launched an era of discoveries in the NR field demonstrating the conserved features of these receptor molecules. Soon after, dozens of other evolutionarily related proteins were discovered, including “orphan receptors”, (ORs), given the namesake for their unknown associated small-molecule ligands (5–8). The concept of the NR superfamily was born, including several subfamilies such as the steroid receptors and orphan receptors. The identification of this superfamily revolutionized the field in the 1990s, leading to several very rapid and radical developments identifying the structural features and functional mechanisms of hormone activity and transcription regulation. Equipped with the identified cDNA encoding orphan receptors and the powerful co-transfection assay, several pioneers, including David Mangelsdorf, identified the first endogenous ligand for an orphan nuclear receptor, called retinoid X receptor (RXR), establishing it as the founding member of the “adopted” orphan class (9–11). Later, peroxisome proliferator-activated receptor (PPAR), one of a family of fatty acid receptors (12, 13), was discovered to be the first class of orphan receptors shown to heterodimerize with RXR (14). This finding led to an explosive wave of discoveries identifying entirely new physiological signaling pathways, referred to as the “RXR Big Bang”. Since the 1990s, the NR field has moved towards identifying the normal and pathophysiological roles of the 48 known human NRs. For example, PPARs have been physiologically linked to fatty acid metabolism, liver X receptors (LXRs) to sterol homeostasis, farnesoid X receptors (FXRs) to bile acid homeostasis, and pregnane X receptors and constitutive androstane receptors (PXRs and CARs) to endobiotic/xenobiotic metabolism (15). Pioneer Peter Tontonoz and colleagues delineated the role of PPAR and LXR in adipogenesis and cholesterol homeostasis. His work showed that LXR activation in mouse liver both promotes cholesterol efflux and inhibits cholesterol biosynthesis (16), and highlighted a regulatory role for a non-coding RNA in lipid metabolism (17). Another

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Metabolism and Medicine

FIGURE 3.1  Timeline of nuclear receptor discovery. Schematic highlighting groundbreaking discoveries in the nuclear receptor field. Notably, the discovery of the retinoid X receptor (RXR) led to an explosive wave, referred to as the “Big Bang”, in discoveries and publications. Source: adapted from (4). *CAR = constitutive androstane receptor; CoR = corepressor; DBD = DNA binding domain; ERR = estrogen related receptor, FXR = farnesoid X receptor; GR = glucocorticoid receptor; HDAC = histone deacetylase; LBD = ligand binding domain; LXR = liver X receptor; N-CoR = nuclear receptor corepressor; NR = nuclear receptor ; PPAR = peroxisome proliferator-activated receptor; PXR = pregnane X receptor; RA = retinoic acid; RAR = retinoic acid receptor; RXR = retinoid X receptor; SMRT = silencing mediator of retinoic acid and thyroid hormone receptor; TR = thyroid receptor; VDR = vitamin D3 receptor.

noteworthy contributor, Mitchell Lazar, not only discovered several NRs but also elucidated the mechanisms by which they interact with the genome and epigenome. He has made key findings related to the PPARγ, a subtype of PPAR, including the discovery of one of its previously unidentified targets (18). Lazar and colleagues also investigated the NRs that link circadian rhythms and metabolism, called Rev-erbα/β, and uncovered mechanisms by which the environment interacts with the genome to impact obesity and diabetes (19) (See Chapter 4, Section 4.8 for more on chronobiology and NRs). Bart Staels, another seminal contributor to the NR field, was among the first to identify a crucial role for PPARα in the control of lipid and glucose metabolism and cardiovascular function in humans (20). His work identified PPAR transcription factors as potential pharmaceutical targets for the treatment of diabetes, dyslipidemia, cardiovascular disease and non-alcoholic fatty liver disease (21). This discovery contributed to the development of several novel therapeutic compounds, two of which are currently in clinical development. Today, several hormones and drugs that target NRs are in widespread therapeutic use (4, 22). Currently, bexarotene and alitretinoin (RXRs), fibrates (PPARα), and thiazolidinediones (PPARγ) are approved drugs for treating cancer, hyperlipidemia, and type 2 diabetes, respectively (23). Other well-known examples include tamoxifen (ERα) used in breast cancer, dexamethasone (GR) used in inflammatory disease,

and retinoic acid used in acute promyelocytic leukemia. FXR and LXR agonists are in development for treating nonalcoholic steatohepatitis and preventing atherosclerosis. Notably, PXR is used to screen new drug candidates for potentially dangerous drug-drug interactions. NRs have already emerged as powerful molecular targets for therapeutic interventions and hold promise for the prevention and treatment of human disease.

3.2 Introduction Living systems adapt to cycles of environmental change and function through metabolically interconnected cycles of response. At the level of the individual, health is preserved by their fidelity and synchrony within and between cells, tissues, and organs. Importantly, this concept of interconnected cycles extends to ecological levels beyond the individual, such as species, domains, and ecosystems. Proper cycle regulation is, therefore, crucial for the maintenance of health at each of these stages. This is particularly true for the metabolic cycle. NHRs are involved in the control of virtually all facets of the metabolic cycle. Moreover, disturbances in NHR signaling can result in a wide span of disease states including diabetes, hypertension, dyslipidemia, myocardial infarctions, strokes, and cancers.

Nuclear Hormone Receptors

3.2.1 Nuclear Hormone Receptor Structure The cloning and sequencing of the first NHRs in the mid-1980s allowed investigators to identify related family members and quickly gain insight into the structure and function of these transcription factors. NHRs are classified in a superfamily of transcription factors with the theoretical ability to function as receptors for specific (often liposoluble) ligands. These common characteristics of NHRs are the result of their conserved structural organization in functional domains (see Figure 3.2). All NHR family members share a common structure with a ligand-independent activation domain at the amino-terminal, followed by a well-conserved DNA binding domain (DBD), a hinge region (Hr), and a ligand binding domain (LBD) located at the carboxy-terminal. The DBD allows the specific recruitment of NHRs, as monomers, homodimers, or heterodimers, to their DNA response elements located in their target genes. The DBD also allows, together with the Hr and LBD, dimerization of NHRs with their NHR partners. On the contrary, the LBD is a particularity of NHRs through which specific ligands bind and promote NHR interactions with transcriptional cofactors functioning as transcription coactivators (e.g. p300/ CREB-binding protein, CBP) or co-repressors (nuclear receptor corepressor, NCoR, and silencing mediator of retinoic acid

FIGURE 3.2  Structure and function of the nuclear hormone receptor (NHR) superfamily. A) (top): NHRs share the same functional domain structure with a ligand-independent activation domain (AF1) at the amino terminal, a DNA binding domain (DBD) involved in dimerization, a hinge region (Hr) involved in dimerization as well, and a ligand binding domain with co-factor recruitment activities. B) (bottom): NHRs, except those from class I, can be recruited to the promoter of their target genes in the absence of a ligand and are then bound to co-repressors, such as NCoR or SMRT. In presence of a ligand, for either NHR in the complex (NR I or NR II), the corepressor complex is replaced by a coactivator complex, which opens the chromatin in a histone acetyl transferase-dependent manner, and allows the recruitment of proteins from the general transcription machinery. Source: adapted from (24). *AF-1 = activation function 1; Cter = C-terminal; DBD = DNA binding domain; Hr = hinge region; LBD = ligand binding domain; N-CoR = nuclear receptor corepressor; NR = nuclear receptor; Nter = N-terminal; SMRT = silencing mediator of retinoic acid and thyroid hormone receptor; X = one to four nucleotides.

109 and thyroid hormone receptor, SMRT). These interactions are controlled, at the molecular level, by ligand-dependent conformational modifications of the LBD, unmasking a binding platform on the NHR for co-activators (agonists) or co-repressors (antagonists). When an agonistic ligand is trapped in the ligand-binding pocket of the LBD, co-repressors are released and co-activators are recruited, activating the transcription machinery that drives expression of the target gene. The ability of NHRs to be activated by specific ligands, both natural and synthetic, has aroused considerable interest among pharmacologists who have identified them as potential therapeutic targets. The pharmacological interest of these transcription factors will be discussed in the last part of this chapter.

3.2.2 Nuclear Hormone Receptor Classifications The NHR superfamily can be subdivided into different classes based on either their biological properties (Figure 3.3) or their phylogenetic evolution (Figure 3.5). In the first classification (Figure 3.3), the NHR superfamily is subdivided into four subclasses based on their ligand- and DNA-binding properties as well as the nature of their partners. NHRs usually function as mono-, homo-, or heterodimers, which are recruited in the regulatory sequences of their target genes to a specific DNA sequence called response element. This sequence is composed of two AGGTCA-like half-sites separated by one to four nucleotides and organized either as a palindromic sequence or a direct repeat.

FIGURE 3.3  NHR classification by biological properties. The four classes of nuclear receptors. *AR = androgen receptor; CAR = constitutive androstane receptor; COUP-TF = chicken ovalbumin upstream promoter transcription factor; ER = estrogen receptor; FXR = farnesoid X receptor; GR = glucocorticoid receptor; HNF-4 = hepatic nuclear factor 4; LXR = liver X receptor; MR = mineralocorticoid receptor; PR = progesterone receptor; PPAR = peroxisome proliferator-activated receptor; ROR = retinoid-related orphan receptor; RXR = retinoid X receptor; SF-1 = steroidogenic factor 1; TR = thyroid hormone receptor; VDR = vitamin D3 receptor.

110 The first class (Figure 3.3) is primarily composed of the steroid hormone receptors, which function as homodimers and are recruited to palindromic response elements. This class includes the androgen receptor (AR), the glucocorticoid receptor (GR), the estrogen receptors (ERs: ERα and ERβ), the mineralocorticoid receptor (MR), and the progesterone receptor (PR). The GR is a NHR that binds glucocorticoids (GC), steroid hormones produced by the cortex of the adrenal gland. The GR is widely expressed in almost all cells and regulates the expression of thousands of genes to govern various aspects of development, stress responses, metabolic function, inflammation, and other critical physiological processes (25). In addition to endogenous GCs, the GR can also be activated by exogenous drugs, such as the synthetic glucocorticoid dexamethasone, a drug widely used for the treatment of inflammatory disorders. In the absence of ligands, GRs are monomeric and primarily found in the cytoplasm. Ligand-free monomeric GRs interact with chaperone complexes that contain heat shock proteins (HSP90 and HSP70), which prevent their nuclear translocation and DNA binding. Once a GC binds to the GR, a conformational change occurs, triggering translocation of GR into the nucleus. There, the GR will bind to specific genomic glucocorticoid response elements (GREs) and activate or repress the transcription of glucocorticoid-responsive target genes (Figure 3.4) (26). The second class (Figure 3.3) consists of several so-called “adopted” receptors. Initially identified by homology screening approaches as orphan receptors (i.e. without known ligands), subsequent molecule library-screening studies identified naturally occurring ligands. NHRs from this class act as heterodimers with one of the retinoid X receptors (RXRs: RXRα, RXRβ or RXRγ) and are recruited to response elements organized in two hexameric half sites in tandem repeat. This second class includes eicosanoid and fatty acid activated receptors of the peroxisome proliferator-activated receptor

FIGURE 3.4  Glucocorticoid mechanism of action. Glucocorticoids activate the GR, releasing the GR from the HSP90 complex. As a result, GR translocates to the nucleus and binds DNA where it interacts with co-activators (CoA) and the transcription initiation machinery to activate or repress target gene expression. Source: adapted from (27). *CoA = coactivator; GR = glucocorticoid receptor.

Metabolism and Medicine subfamily (PPARs: PPARα, PPARβ/δ, PPARγ), the oxysterol receptors liver X receptors (LXRs: LXRα and LXRβ), and the xenobiotic receptor pregnane X receptor (PXR). This class also includes the thyroid hormone receptors (TRs: TRα, TRβ), the retinoic acid receptors (RARs: RARα, RARβ, RARγ), and the vitamin D3 receptor (VDR). The third class (Figure 3.3) is composed of adopted receptors, such as the RXRs, the heme Rev-erb receptors (Rev-erbα and Rev-erbβ), the hepatic nuclear factor 4 (HNF4α, HNF4γ), and orphan receptors, such as the chicken ovalbumin upstream promoter transcription factors (COUP-TFI, COUP-TFII). These NHRs interact with DNA as mono- or homodimers on direct repeat response elements. Finally, the fourth class (Figure 3.3) is essentially composed of orphan receptors, such as estrogen related receptors (ERRα, ERRβ, ERRγ), retinoid-related orphan receptors (RORα, RORβ, RORγ), nuclear receptor related protein 1 (Nurr1), nuclear orphan receptor 1 (NOR1), Nurr77, and the steroidogenic factor 1 (SF-1). In the second classification (Figure 3.5), NHRs are classified based on the nature of their ligands, as endocrine receptors (high affinity lipophilic ligands, often hormones) or orphan receptors (ligands unknown). Through the application of molecular screening technologies in the 1990s, several of these orphan receptors have adopted ligands, often lipids with lower binding affinity.

FIGURE 3.5  NHR classification by phylogenetic evolution and ligand characteristics. NHR classifications, based on the nature of their ligands, as endocrine receptors (high affinity lipophilic ligands, often hormones) or orphan receptors (ligand unknown). *AR = androgen receptor; CAR = constitutive androstane receptor; COUP-TF = chicken ovalbumin upstream promoter transcription factor; DAX = dosage-sensitive sex reversal adrenal hypoplasia congenita critical region on the X chromosome gene; EcR = Ecdysone receptor; ER = estrogen receptor; ERR = estrogen related receptor; FXR = farnesoid X receptor; GCNF = germ cell nuclear factor; GR = glucocorticoid receptor; LRH = liver receptor homolog; LXR = liver X receptor; MR = mineralocorticoid receptor; NOR1 = nuclear orphan receptor 1; Nurr1/77 = nuclear receptor related protein 1/77; NGFI-B = nerve growth factor-induced-B; PNR = photoreceptor-specific nuclear receptor; PR = progesterone receptor; PPAR = peroxisome proliferator-activated receptor; PXR = pregnane X receptor; RAR = retinoic acid receptor; ROR = retinoid-related orphan receptor; RXR = retinoid X receptor; SF-1 = steroidogenic factor 1; SHP = small heterodimer partner; SXR = steroid and xenobiotic sensing nuclear receptor; TLX = “tailless” human orphan nuclear receptor; TR = thyroid hormone receptor; VDR = vitamin D3 receptor.

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Nuclear Hormone Receptors Finally, because different groups of scientists almost simultaneously identified the same NHR, but gave them different names, such as PPARβ and PPARδ, another phylogenetic nomenclature based on the comparative evolution of the well-conserved DBD and LBD NHR domains was developed (Committee, 1999). This classification yielded six subfamilies with the namesake “NR” (nuclear receptor) followed by letter/ number specifiers. For example, TRβ (NR1A2) is a nuclear receptor of the first subfamily, group A, and number two (Committee, 1999). The most interesting feature of NHRs rests in the diverse nature of their ligands, many of which are either hormones, metabolites, or derivatives thereof. Ligands for the VDR and TRs are derived from a combination of nutritive substrates, cholesterol, and iodine, respectively, whose synthesis is regulated by classical endocrine control mechanisms. Ligands of the FXRs (e.g. bile acids), LXRs (oxysterols), and all the steroid hormone receptors are derived from cholesterol. PPARs are activated by fatty acids and derivatives. RARs bind retinoids, lipids derived from vitamin A, acting as regulators of growth and development. More enigmatic is the role of the heme group that colors the Rev-erbs. Heme is more commonly associated with hemoglobin and oddly does not serve as an energy source when associated with Rev-erbs. Since the synthesis of heme requires the use of succinyl-CoA from the Krebs cycle, its cellular concentration indirectly reflects Reverb activation status and may also indicate the metabolic status of the organism. This group of NRs therefore represents an evolutionary intermediate between endocrine receptors and lipid sensing adopted orphan receptors (ORs). Ligands to this intermediate class of NRs, except for thyroid hormone, cannot be regulated by simple negative feedback. Further complicating the picture, NHR activity is also regulated by a series of arranged post-translational modifications that finely tune their transcriptional activity (Figure 3.6). For instance, PPARα SUMOylation results in the selective recruitment of the corepressor NCoR, to the detriment of SMRT, resulting in the inhibition of a subset of PPARα target genes

involved in the control of lipid metabolism (28). SUMOlyation is a post-translational modification process that involves the addition of small ubiquitin-like modifier (SUMO) proteins. In addition to SUMOylation, many other post-translational modifications, including phosphorylation, ubiquitination, and glycosylation, control NHR transcriptional activity and stability (29–32). Several NHRs are activated in response to a growth factor, such as IGF-1 (insulin-like growth factor 1) or insulin. This occurs via mitogen-activated protein (MAP) kinase phosphorylation, activation of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (PKB, Akt) pathway, or by lipid-controlled pathways (e.g. protein kinase C; PKC) whose activity is induced by inositol-3-phosphate (IP3) and diacylglycerol (DAG) (31). From these findings and further research, it soon became clear that NHRs respond to cyclical metabolic changes and, at the same time, integrate these changes by controlling the expression of metabolic genes.

3.3 NHRs Sense and Modulate Use of Energy The basic metabolic cycle yields adenosine triphosphate (ATP). NHRs control this cycle by modulating the expression of enzymes that provide the intermediary substrates which are bioenergetically converted into ATP. It is noteworthy that NHR ligands are mainly lipid derivatives and can accumulate at some point in the tissue. For instance, oxysterols are oxidized cholesterol derivatives that accumulate in peripheral tissue when cholesterol is in excess (33). Oxysterols then activate LXRs which stimulate the expression of ATP Binding Cassettes (ABCs). ABCA1 and ABCG1 are involved in reverse cholesterol transport, recycling cholesterol from the periphery to the liver for metabolism and excretion (33). In this example, NHRs such as LXRs sense unused substrates and promote their recycling. NHRs thus sense metabolites or energy intermediates in order to manage their recycling, degradation, use, or synthesis (i.e. their total availability). Many NHRs are thus involved in the control of energy homeostasis (Figure 3.7), but their impact is restricted by time and space, as it depends on their spatio-temporal expression pattern and on their target genes (34–38). Indeed, not all NHRs are expressed in every tissue, and their presence may depend on the time of day (i.e. display a circadian rhythmicity; see Chapter 4).

3.3.1 Nuclear Hormone Receptors in Lipid Homeostasis

FIGURE 3.6  Ligand-dependent control of NHR activity. NHR activity is regulated by a series of arranged post-translational modifications that finely tune their transcriptional activity. *NR = nuclear receptor; NRRE = nuclear receptor response element.

Many NHRs are involved in the metabolism of fatty acids, major energy substrates. The prototypal subfamily herein is the PPAR (Figure 3.8). There are three different PPAR subtypes: PPARα, PPARδ (also denoted as PPARβ), and PPARγ, each encoded by different genes and with their own temporal and spatial expression pattern and ligand selectivity (39). PPARα regulates genes involved in lipid and lipoprotein metabolism and fatty acid oxidation (40). It is highly expressed in the liver, muscles, heart, kidney, and brown adipose tissue (41). PPARδ is more equally and ubiquitously expressed throughout the body (42). It is also an important regulator of

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FIGURE 3.7  Function of NHRs in lipid and glucose metabolism. NHRs function in several organ systems to regulate metabolism. *ER = estrogen receptor; ERR = estrogen related receptor; FA = fatty acid; FAO = fatty acid oxidation; FGF15= fibroblast growth factor 15; FXR = farnesoid X receptor; GR = glucocorticoid receptor; LXR = liver X receptor; PPAR = peroxisome proliferator-activated receptor; RCT = reverse cholesterol transport; VDR = vitamin D3 receptor; UCP1 = uncoupling protein=1.

FIGURE 3.8  PPARs in hepatic and lipid metabolism and non-alcoholic fatty liver diseases. The function of the different PPARs in fatty acid metabolism, inflammation, and fibrogenesis in different hepatic cell types and adipose tissues is shown. Factors and genes that are central to the functions are indicated in dark gray boxes and those that are regulated by PPARs are indicated below. Source: adapted from (38). *ACOX1 = acyl-CoA oxidase 1; ANG2 = angiopoietin; Apo(A1/2/3/4/5) = apolipoprotein A-1/2/3/4/5; COL1α1 = collagen type 1α1; BAT = brown adipose tissue; CPT1/2 = carnitine palmitoyltransferase 1/2; EHHADH = enoyl-CoA hydratase and 3-hydroxyacyl CoA dehydrogenase; FFA = free fatty acid; FGF21 = fibroblast growth factor 21; HMGCOAS = hydroxymethylglutaryl CoA synthase; IL(1β/6), interleukin-1β/6; PDGF = platelet-derived growth factor; PPAR(α/β/γ/δ) = peroxisome proliferator-activated receptor α/β/γ/δ; ROS = reactive oxygen species; αSMA = α smooth muscle actin; TIMP1 = TIMP metallopeptidase inhibitor 1; TG = triglycerides; TGFβ = transforming growth factor β; TNFα = tumor necrosis factor α; T2DM = type 2 diabetes mellitus; WAT = white adipose tissue.

Nuclear Hormone Receptors

FIGURE 3.9  Daily oscillation of PPARs expression. Hepatic Pparα and Pparβ/δ gene expression exhibits circadian profiles, whereas the Pparγ gene displays a more constant expression along the day. Source: adapted from (35). *Ppard/g/a = peroxisome proliferator-activated receptors d/g/a genes.

energy balance, including lipid and glucose metabolism (43). The third isotype, PPARγ, has two isoforms due to differential promoter usage and alternative splicing. PPARγ1 is widely expressed (white and brown adipose tissue, the liver and cardiac muscle), while PPARγ2 is exclusively expressed in adipose tissue (both white and brown). The PPARγ isoforms control genes involved in carbohydrate, lipid, and energy metabolism and act as master regulators of adipogenesis (adipocyte differentiation) (44). Importantly, PPAR expression patterns display a circadian rhythmicity, which allows the organism to adapt its metabolism in time according to the circadian fasting/feeding cycles (36, 39) (Figure 3.9).

113 PPARs are activated by fatty acids (natural ligands) and lipid metabolites, such as prostaglandins and leukotrienes (36, 39) (Figure 3.10). Hence, PPARs are lipid sensors, which redirect metabolism following gene transcriptome modifications. These receptors thus allow the organism to respond and adapt to changes in availability of energy sources (fats). Screening for PPAR ligands has identified a plethora of synthetic agonists acting on individual or several PPAR subtypes (36, 39). Amongst the synthetic ligands are fibrates, such as gemfibrozil and fenofibrate, which are PPARα agonists that enhance whole body lipid oxidation (45, 46) (Figure 3.10). Treatment of dyslipidemic patients with these fibrates reduces plasma triglycerides (36, 39). Other examples are the glitazones (or thiazolidinediones, TZD) which activate PPARγ (pioglitazone and rosiglitazone) (39) (Figure 3.10). TZDs are insulin sensitizers that work by promoting adipogenesis of insulin-sensitive adipocytes, thus, redirecting fatty acids to adipose tissue away from liver and skeletal muscle and improving whole body insulin signaling. In addition, PPARs lower the chronic inflammation occurring in metabolic diseases such as obesity, diabetes, and cardiovascular diseases (38). Treatment with TZDs, however, also produces undesirable side effects. As such, by promoting adipogenesis from mesenchymal stem cells, which are also osteoblast precursors, they increase the risk for osteoporosis. Additionally, PPARγ activation may result in fluid retention and edema, which may precipitate heart failure in patients at risk. By contrast, TZD treatment decreases cardiovascular risk due to atherosclerosis (39). The NHRs, LXRα and LXRβ, are expressed in hepatocytes and other cell types including intestinal epithelial cells,

FIGURE 3.10  PPAR activation. PPARα forms a heterodimer with RXR, binds PPAR response element (PPRE), and initiates transcription to respond and adapt to changes in availability of energy sources (fats). PPARα ligands (shown in dark gray), PPARγ (shown in light gray). *HETE: Hydroxyeicosatetraenoic acid, HODE = Hydroxyoctodecadienoic acid; oxLDL = oxidized low-density lipoprotein; LTB4 = Leukotriene B4; PPAR = peroxisome proliferator-activated receptors; PPRE = PPAR response element; RXR = retinoid X receptor; 15-dPG-J2 = 15-deoxy-delta12,14-prostaglandin J2.

114 immune-inflammatory cells (e.g. macrophages), neuronal cells, adipocytes, and renal cells (47). LXRs mediate numerous adaptive physiological processes and thereby represent a powerful class of molecular targets for therapeutic interventions. However, agonists of these NHRs are still not used in clinical medicine, likely because side effects of synthetic agonists have hampered clinical development. LXRs are cellular sensors of cholesterol, being bound and activated by the endogenous intermediates and metabolites of cholesterol synthesis, such as desmosterol (an intermediate in the cholesterol biosynthesis pathway) and oxysterols, such as 22R-hydroxycholesterol and 24S-hydroxycholesterol (48). Upon activation, LXR regulates genes involved in lipogenesis, such as the transcription factors sterol regulatory-element binding protein 1c (SREBP1c), carbohydrate response element binding protein (ChREBP), and fatty acid synthase (FAS) (Figure 3.11) (49). Consequently, LXR agonist therapy has been associated with increased hepatic steatosis, a risk factor for type 2 diabetes, and hypertriglyceridemia, a condition where circulating triglyceride levels are too high. In contrast to this lipid anabolic action, LXRs protect the body from cholesterol overload by modulating genes involved in cholesterol absorption, transport, efflux, and biosynthesis (Figure 3.12) (47). LXRs promote reverse cholesterol transport (RCT), a process by which excess cholesterol from peripheral tissues (macrophages) is transported in high-density lipoprotein (HDL) particles to the liver for excretion in bile (51) (Figure 3.12). LXRs also inhibit cholesterol biosynthesis

Metabolism and Medicine in the liver by complex mechanisms involving the induction of non-coding RNAs and the E3 ubiquitin-protein ligases. Furthermore, induction of the expression of IDOL (inducible degrader of the low-density lipoprotein receptor), a negative regulator of the low-density lipoprotein (LDL)-receptor, LXRs reduce the clearance of circulating LDL-cholesterol by the liver (52). LXR activation in the gut reduces cholesterol absorption through the induction of ABCG5 and ABCG8 (ATP-binding cassette sub-family G member five and eight; mediators of cholesterol efflux in the intestine) and the downregulation of NPC1L1 (Niemann-Pick C1-like protein 1; a mediator of dietary cholesterol absorption in the gut and target of ezetimibe). LXRs enhance lipoprotein formation and secretion in liver and intestine by regulating phospholipid remodeling enzymes, such as lysophosphatidylcholine acyltransferase 3 (LPCAT3). Thus, LXRs have a crucial role in maintaining whole-body cholesterol homeostasis through the regulation of biosynthesis, absorption, excretion, and reverse transport of cholesterol in multiple tissues and cell types. The farnesoid X receptor (FXR) is an NHR that is also highly involved in the regulation of lipid metabolism (54). FXR is highly expressed in the liver and gut where bile acids act as an endogenous ligand (54). Bile acids are biosynthesized from cholesterol in the liver as primary bile acids (cholic acid, chenodeoxycholic acid) that may be converted to secondary bile acids (deoxycholic acid, lithocholic acid) by intestinal bacteria. Bile acids are soaps that promote the emulsification and absorption of dietary triglycerides, cholesterol and fat-soluble

FIGURE 3.11  LXRs regulate liver lipogenesis. LXRs regulate liver lipogenesis by induction of fatty acid and triglyceride biosynthesis by direct regulation of key lipogenic factors including the sterol responsive element binding protein 1c (SREBP1c), fatty acid synthase (FAS) and stearoyl-COA desaturase 1 (SCD1). Source: adapted from (50). *ACC = acetyl-CoA carboxylase; FAS = fatty acid synthase; FBP1 = fructose-bisphosphatase 1; G6P = glucose-6-phosphate; GLUT1/4 = glucose transporter 1/4; LXR = liver X receptor; PEPCK = phosphoenolpyruvate carboxykinase; SREBP1c = sterol regulatory-element binding protein 1c.

Nuclear Hormone Receptors

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FIGURE 3.12  LXRs regulate cholesterol metabolism. The capture of lipoproteins containing cholesterol by macrophages increases transcription of LXR. This leads to increased efflux of cholesterol to HDL by ABCA1 and ABCG1. Induction of CETP expression transfers lipids between HDL and LDL in humans (CETP is not expressed in mice). Subsequent uptake of cholesterol transported in HDL/LDL occurs in the liver where LXR promotes cholesterol excretion in bile. In the gut, the ABCG5 and ABCG8 transporters reduce cholesterol absorption via cholesterol efflux to the intestinal lumen. Source: adapted from (53). *ABC(A1/G1/G5/G8) = ATP binding cassette A1/G5/G8; Apo(A-1/E) = apolipoprotein A-1/E; CETP = cholesteryl ester transfer protein; CYP7A1 = cholesterol 7α hydroxylase; HDL = high-density lipoprotein; LDL = low-density lipoprotein; LXR = liver X receptor; LXRE = LXR response element; RXR = retinoid X receptor; SREBP1c = sterol regulatory-element binding protein 1c; VLDL = very low-density lipoprotein.

vitamins from the intestinal tract. In addition, they act as hormones in endocrine metabolic homeostasis through specific receptors, such as FXR and the Takeda G protein-coupled receptor 5 (TGR5) (54) (Figure 3.13). However, when hydrophobic bile acids are present in excessive amounts (cholestasis), they become cytotoxic. This toxicity of hydrophobic (mainly secondary) bile acids underscores the necessity for a negative feedback mechanism to regulate their synthesis, which is mediated by FXR. Mechanistically, bile acids activate FXR in the intestine and liver. In the intestine, activated FXR induces fibroblast growth factor 19 (FGF19), which inhibits hepatic bile acid signaling by binding to specific membrane receptors in the liver (54). In the liver, activated FXR transcriptionally upregulates the small heterodimer partner (SHP), an atypical nuclear receptor that lacks a DNA-binding domain. Instead of modulating transcription through DNA binding, SHP inhibits two orphan NHRs—hepatic nuclear factor 4α (HNF4α) and liver receptor homolog-1 (LRH-1)—which are positive regulators of the cholesterol 7α hydroxylase gene (Cyp7A1), the rate limiting enzyme of bile acid synthesis. The outcome is repression of bile acid synthesis. Bile acid sequestrants retain bile acids in the intestine, resulting in the upregulation of hepatic bile acid synthesis. As a consequence, sequestrants promote the catabolism of available cholesterol and induce hepatic LDL-receptor levels. These compounds are used clinically to lower serum cholesterol. Bile acid-activated FXR also contributes to the regulation of lipid and glucose homeostasis (54). It reduces plasma

triglycerides by suppressing hepatic lipogenesis and enhancing the clearance of triglyceride-containing lipoproteins. FXR represses SREBP1c, a transcription factor which controls the expression of acetyl CoA carboxylase, fatty acid synthase, and other lipogenic genes. SREBP1c suppression reduces de novo lipogenesis, hepatic fat content, and output of TG-rich very low-density lipoprotein (VLDL) particles, hence lowering circulating triglycerides. Overall, several NHRs are involved in lipid utilization and energy production. Extensive spatial and temporal communication exists among the different NHR signaling pathways, sometimes with antagonistic outcomes. Indeed, NHRs such as the PPARs, ERRs, and Rev-erbs are involved in mitochondrial biogenesis in heart and skeletal muscle, lipid use, and ATP synthesis (55–58). In addition, several NHRs control energy storage by inducing adipogenesis in white adipose tissue. Examples are the GR, PPARγ, and Rev-erbα, which promote adipocyte differentiation, while RORα, ERβ and VDR prevent adipogenesis (55–58). Finally, several NHRs are also involved in energy wasting by modulating thermogenesis in brown adipose tissue. Thermogenesis is a catabolic process yielding heat through the uncoupling of the oxidative phosphorylation chain from ATP production. Although glucose may be used, lipid droplets serve as the main fuel for such oxidative pathways. PPARs induce the expression of the uncoupling protein 1 (UCP1), while Rev-erbα exerts opposition effects by inhibiting UCP1 expression (59–61).

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FIGURE 3.13  Bile acid metabolism. Bile acids activate both the FXR and TGR5 receptor pathways to regulate bile acid metabolism and energy homeostasis. *CA = cholic acid; CDCA = chenodeoxycholic acid; CREB = cyclic AMP response element binding protein; DCA = deoxycholic acid; FXR = farnesoid X receptor; LCA = lithocholic acid; RXR = retinoid X receptor; TGR5 = Takeda G protein-coupled receptor 5.

3.3.2 NHRs in Glucose Metabolism The processes that control lipid and glucose metabolism are closely linked such that disorders of lipid metabolism can lead to the impairment of peripheral glucose utilization and the development of insulin resistance and type 2 diabetes. Hence, it comes as no surprise that many of the above discussed NHRs are also involved in the control of glucose homeostasis (Figure 3.6).

Directional shuttling of glucose in the liver is highly dependent on the balance of glycolysis (glucose utilization) and gluconeogenesis (glucose production) pathways. This is highly regulated by NHRs in a manner dependent on the nutritional status of the organism (fed versus fasted). Gluconeogenesis, which takes place in the liver (as well as the kidney and intestine) in response to glucagon, is a biochemical pathway generating glucose de novo from non-carbohydrate substrates such as pyruvate, lactate, some amino acids, and glycerol. In the post-prandial state, insulin inhibits gluconeogenesis, switching the hepatocyte to glucose utilization and storage in healthy patients. In type 2 diabetic patients, insulin resistance develops due to inappropriate ectopic lipid accumulation in liver and skeletal muscle, and insulin resistant hepatocytes continue to produce glucose thus contributing to hyperglycemia. Gluconeogenesis is a critical pathway in diabetic patients. NHRs, such as PPARβ, LXR, Rev-erbα and ERα, inhibit gluconeogenesis especially during feeding, while GR and PPARα enhance gluconeogenesis during fasting (36, 39, 54–56, 62– 64). While FXR inhibits glycolytic flux in the post-prandial state, it is required for an optimal response to glucagon in the fasted state (54, 65). This energy status-dependent switch in FXR function occurs through post-translational protein kinase

A (PKA)-mediated phosphorylation (54, 65). The NHRs LXRα and LXRβ also play a role in the coordinated regulation of lipid and glucose metabolism (33, 47, 63). For instance, LXR activation leads to the suppression of genes involved in gluconeogenesis and induction of hepatic expression of glucokinase, the first enzyme in the glycolytic cascade, through upregulating SREBP1c and, in adipose tissue, the insulin-sensitive glucose transporter GLUT4 (33, 47, 63). Thus, targeting NHRs may prove to be a viable strategy in managing hepatic glucose homeostasis. NHRs further regulate glucose utilization by modulating glucose uptake in white adipose tissue and skeletal muscle. PPARγ, LXR, and ERα have been shown to upregulate glucose uptake in white adipose tissue (WAT) and muscle by inducing the expression and translocation of GLUT4 at the plasma membrane (36, 39, 62, 63). On the other hand, ERβ and GR decrease glucose uptake in muscle (58, 62). Glucocorticoids are stress hormones that regulate whole body glucose homeostasis during physiological conditions (58, 66). As mentioned, glucocorticoids increase gluconeogenesis and reduce glucose uptake in peripheral tissues (58, 66). These two processes are critical for metabolic adaptation during starvation or fasting conditions when blood glucose needs to be preserved for the brain, which uses glucose as a primary energy source. Glucocorticoids promote gluconeogenesis by activating the transcription of genes such as phosphoenolpyruvate carboxykinase 1 (PCK1), phosphofructokinase-biphosphatase 1 (PFKBP1), fructose-bisphosphatase 1 (FBP1), glucose-6-phosphatase catalytic subunit (G6PC), and G6P transporter, which encode key enzymes in gluconeogenesis that increase blood glucose levels (67). Furthermore, glucocorticoids induce lipolysis in white adipose tissue, increasing ceramide levels in the liver. They produce an overall increase in whole body insulin resistance, leading to elevated circulating glucose levels (68).

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Nuclear Hormone Receptors Insulin is an endocrine hormone produced by β-cells of the endocrine pancreas that binds to the insulin receptor present on the cell membrane to enhance glucose uptake and utilization. NHRs are important regulators of pancreatic homeostasis such as insulin synthesis/secretion and β-cell mass. LXRs, Rev-erbα, PPARs, FXR, and ERα induce insulin production and secretion (36, 39, 54–56, 62–64), while the GR inhibits insulin secretion (58). PPARγ and ERs have been shown to protect β-cells from glucolipotoxicity and maintain β-cell mass (36, 39, 56, 62). However, it is noteworthy that for some NHRs, such as Rev-erbα, the insulin secretory regulatory actions on β-cells have only been assessed in vitro (64). Whether such effects also exist in vivo still needs confirmation. The regulation of blood glucose by bile acids is complex and involves multiple mechanisms that depend on the nutritional state of the organism (see above). One mechanism involves the release of glucagon-like peptide-1 (GLP-1) from intestinal L cells (69). Another involves activation of the G protein-coupled receptor (GPCR) Takeda G protein-coupled receptor 5 (TGR5) through the adenylate cyclase/cyclic adenosine monophosphate (cAMP)/protein kinase A (PKA) signaling pathway to enhance GLP-1 secretion. Further, bile acid-activated FXR down-regulates the expression of the proglucagon gene encoding for GLP-1 (54). Since regulation of GPCR signaling is more rapid than modulation of gene expression, these findings indicate that bile acids impact glucose metabolism in a timedependent manner (Figure 3.14) (54).

FIGURE 3.14  Bile acids and glucose metabolism. TGR5 promotes GLP1 release from the L cells of the intestine, mediated by the signaling pathway: adenylate cyclase (AC) → cyclic AMP (cAMP) → protein kinase A (PKA). By contrast, FXR inhibits the production of GLP1 by down-regulating proglucagon (Gcg) expression. Moreover, their expression differs between small intestinal and colonic L cells. L cells in the small intestine and colon are exposed to different microbes and metabolites derived from diet and diet-microbe metabolism. As such, they induce specific signaling pathways leading to different physiologic outputs. Source: adapted from (70). *DCA = deoxycholic acid; FXR = farnesoid X receptor; Gcg = proglucagon gene; GLP1 = glucagon-like peptide 1; GPR43 = G protein-coupled receptor 43; INSL5 = insulin-like peptide-5; LCA = lithocholic acid; PYY = peptide YY; SCFA = short-chain fatty acids; SGLT-1 = sodium glucose cotransporter 1.

In addition, FXR regulates glucose metabolism by actions on the regulation of β-cell insulin production, intestinal glucose uptake, hepatic glycolysis regulation as well as actions on peripheral tissues, such as white and brown adipose tissue (54). Several synthetic FXR agonists are currently in clinical development for the treatment of non-alcoholic fatty liver disease. While they appear to lower hepatic steatosis and fibrosis, they also increase plasma LDL-cholesterol (see above). Their effects on glucose metabolism remain to be firmly established. By contrast, FXR “de-activation” using bile acid sequestrants improves glucose metabolism and is an FDA-approved treatment for type 2 diabetes. Thus, the metabolic actions of this NHR are again complex. Future studies will demonstrate whether its pharmacological modulation is metabolically beneficial.

SIDEBAR 3.1: THE ROLE OF FXRS IN IMPROVING OUTCOMES OF BARIATRIC SURGERY Roux-en-Y gastric bypass and vertical sleeve gastrectomy have become frequently performed bariatric procedures to treat obesity and its complications such as type 2 diabetes. Intriguingly, increases of bile acid concentrations in peripheral blood are consistently observed after surgery. FXR-mediated effects have been proposed to contribute to reductions of blood glucose and maintenance of weight loss in this setting. Ryan and colleagues showed that these effects are mediated by changes in the microbiota (71). The specific mechanisms involved here remain unclear, but may include changes in microbiota, enteroendocrine hormones, and bile acid metabolism. Like the vitamin D receptor, FXR also plays a role in maintaining epithelial barrier integrity of the gut through a variety of mechanisms, including the promotion of anti-microbial peptides as well as the suppression of inflammatory cytokine tumor necrosis factor-1 (TNF-1), interleukin (IL)-1, IL-6, and cyclooxygenase expression (54, 72). FXR induction of antimicrobial peptides combined with its suppression of inflammatory factors is important for the regulation of a healthy intestinal mucosa and microbiota composition, making it a strategic target for prevention and treatment of chronic disease states like inflammatory bowel disease, ulcerative colitis, and Crohn’s disease (Figure 3.15).

Further study of the gut microbiota as a modulator of chronic diseases may improve the fundamental understanding of the link between western-style high-fat diets and ailments such as type 2 diabetes mellitus, inflammatory bowel disease, or colorectal cancer. For instance, one under-recognized aspect in the pathogenesis of type 2 diabetes is endotoxicosis (poisoning from endogenous toxins), which arises from the gut and passes into the portal circulation. This alone is a tremendous indicator of the critical role gut microbiota composition can

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FIGURE 3.15  Microbial bile acid conversion. Mechanism of diet-induced enforcement of the colonic adaptive immune response through microbial bile acid conversion. Bile acids exert activity on membrane-bound receptor TGR5 and nuclear receptors, farnesoid X receptor (FXR) and vitamin D receptor (VDR), to shape the innate immune responses. Bile acids and VDR play an important role in the adaptive immune system by modulating a specific population of FOXP3+ regulatory T (Treg) cells expressing the transcription factor RORγ in the colonic lamina propria. Source: adapted from (73). *DSS = dextran sulfate sodium; ROR = retinoid-related orphan receptor; Tregs = FOXP3+ (forkhead box P3) regulatory T cells; VDR = vitamin D3 receptor.

play in the control of metabolic disease states. Therapeutic intervention in these systems is tricky due to their complexity and unpredictable non-linear dose-response characteristics. For example, microbiota produce secondary bile acids, deoxycholic acid (DCA) and lithocholic acid (LCA), which may induce colonic carcinomas. Recent studies have identified novel microbiome-produced bile acids (e.g. LCA metabolites) as modulators of immune cell function that act via NHRs (e.g. VDR), further underscoring the importance of microbiomebile acid interactions in the regulation of adaptive immunity that lowers the vulnerability for colitis (Figure 3.16) (73–75). Therefore, through binding and modulating the activities of these different NHRs, microbiome-produced bile acids may protect or promote the onset of diseases, such as colon cancer or inflammatory bowel disease (76–78). It is important to remember that interpreting physiological and pathophysiological outcomes while studying the interface of gut microbiota and human biology is a daunting task. This is the case when studying biological systems in general, but nowhere is it more true than for the human gut microbiota—estimated to involve more than three million genes.

3.3.3 NHRs and Redox Homeostasis Redox homeostasis is the physiological balance between oxidative and reductive reactions occurring in all cells. For proper physiological function, these reactions need to be tightly controlled through time and space. Often, it is measured as the balance between reactive oxygen species (ROS) production

FIGURE 3.16  FXR and gut microbiota. Major events linking FXR, gut microbiota, bile acids and cancer are shown. FXR acts as a central sensor of bile acids in the liver and intestine. Together with the VDR, FXR may modulate excessive inflammation. Several pieces of evidence further point to a role for BA-FXR in tumorigenesis. The intestinal microbiota and epigenetic factors regulating gene expression interface with environmental factors (e.g. diet, lifestyle) and the molecular events promoting cancer onset and progression. For example, a high-fat diet increases the fecal concentration of secondary BAs and is a risk factor for the development of colorectal cancer. *BA = bile acid; DCA = deoxycholic acid; DNA = deoxyribonucleic acid; FXR = farnesoid X receptor; LCA = lithocholic acid.

during metabolic processes and ROS neutralization by cellular antioxidant defense systems. Free radicals, including reactive oxygen and nitrogen species (RNS), display important activities in the cardiovascular, respiratory, and immune systems. Nitric oxide (NO°) and hydrogen peroxide (H2O2) are indeed

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Nuclear Hormone Receptors involved in the control of cellular metabolism, secretion, proliferation, and signaling (79). Their production is regulated by enzymes, including nitric oxide synthases and nicotinamide adenine dinucleotide phosphate (NADPH) oxidase in the cytoplasm (79). ROS are mainly generated in mitochondria as by-products of mitochondrial oxidative phosphorylation in the form of superoxide. Excessive production may result in oxidative stress-induced damage (79). Indeed, excessive production or inefficient removal of ROS and RNS trigger oxidation of DNA, proteins, and lipids, limiting the ability of these biomolecules to promote healthy cellular function and structure (79). Detoxification of ROS is a function of the antioxidant defense system composed of antioxidant enzymes, such as superoxide dismutases, catalase, glutathione peroxidase, and free radical acceptors, including peroxiredoxins, glutathione, and thioredoxin (79). This antioxidant system must be tightly controlled. Interestingly, NHR transcriptional activity and redox homeostasis reciprocally regulate one another to sense and modulate cellular and energy substrate metabolites. Many NHRs are modulated by redox changes (80). NHRs, such as the ERs, GR, RAR, AR, PR, VDR, and REV-ERBβ, are sensitive to changes in cellular redox homeostasis that affects their ability to bind DNA and regulate gene expression in a receptor-specific manner (81). The effect of redox imbalance on ligand binding generally depends on the existence of thiols near the ligand-binding pocket that can reversibly convert to disulfides. In the case of the GR, an increase in ROS levels oxidizes thiols and inhibits GR translocation to the nucleus, thereby preventing it from regulating gene expression (81). It has also been suggested that redox poise may play a role in the dimerization of AR (81). In a comparable manner, oxidative stress, induced in mice by depletion of glutathione levels, reduces the ligand binding capacity of the MR. Interestingly, oxidative stress may also enhance MR activity in a Rac1-dependent manner (Ras-related C3 botulinum toxin substrate 1) (8181). Thus, not only oxidative stress per se, but also the nature of reactive species, may determine the directionality of the effect. Indeed, while NO° suppresses MR-dependent transcription by modifying DBD thiols, peroxynitrite facilitates MR nuclear translocation and target gene transcription (81). Interestingly, H2O2 accumulation in the liver inhibits PPARα expression, as well as its target genes, such as carnitine palmitoyl transferase 1 (CPT1) and acyl-CoA oxidase (ACOX), which are involved in lipid β-oxidation (82). It is noteworthy that H2O2, which is produced during peroxisomal β-oxidation, inhibits, in a negative feedback loop, its own accumulation by indirectly decreasing the expression of enzymes involved in its generation (82). On the other hand, PPARα also regulates the hepatic expression of superoxide dismutase and catalase, both involved in ROS/RNS detoxification (82). In addition, the PPARβ increases the expression of glutathione S transferase, thus playing a role in ROS detoxification. As mentioned above, the main LXR ligands are oxysterols, which are oxygenated forms of cholesterol and are formed in the first steps of cholesterol metabolism or directly from cholesterol by ROS (82). Thus, one can consider LXRs as cellular sensors of oxidative stress. As the PPARs, the redox status modulates the activation of LXRs, with LXR expression being

impaired by strong peroxidation activity induced by iron ascorbate in macrophages (82). Interestingly, one specific oxysterol, 22-hydroxycholesterol, activates FXR, which then induces the expression of the bile–acid–salt export pump, making FXR a redox status sensor as well. Finally, orphan receptors, such as neuron-derived orphan receptor 1 (NOR1), have been demonstrated to control redox homeostasis in different cellular contexts. NOR1 strongly increases the expression of the NADPH oxidase, Nox1 in vascular smooth cells, inducing ROS production and vascular smooth muscle cell (VSMC) migration (83). In addition, NOR1 upregulates the superoxide dismutases 1 and 3 (SOD1 and SOD3). Altogether, NOR1 finely tunes the complex gene networks regulating oxidative stress and redox homeostasis in the vasculature (83). Cellular redox systems display circadian rhythmicity, alternating periods of oxidative and reductive metabolism. As such, the NHRs involved in circadian clock function (see Chapter 4) impact redox homeostasis. Because both NHRs and the biological clock are connected, disruption of circadian rhythms plays a key role in the pathophysiology of disorders involving oxidative stress and downstream inflammation such as obesity, diabetes, neurodegenerative diseases, and sleep disorders (84–86). Oxidative stress is also coupled to inflammation and immune cell function (e.g. neutrophils produce ROS bursts upon infection). NHRs can act herein as interference. For example, glucocorticoid synthesis keeps a check on inflammation by downregulating the expression of pro-inflammatory systems. Since GR is sensitive to perturbations by redox homeostasis, its anti-inflammatory activity may be impacted through the modulation of ligand binding due to thiol-disulfide interconversion. Thus, NHRs may act as redox sensors to regulate gene expression and protein function according to the stage of cell growth, nutrient state, inflammation, and circadian time.

SIDEBAR 3.2: TARGETING RORS TO ENHANCE METABOLIC FITNESS The NHRs RORα and RORγ are core components of the molecular clock that can be targeted therapeutically to improve obesity, diabetes, hypertension, dyslipidemia, and immune responses. The natural phytonutrient Nobiletin is a small molecule polyphenol flavonoid found in citrus fruits that modulates clock-controlled circadian rhythms by acting on RORα and RORγ. Recent reports have shown that Nobiletin enhances metabolic fitness in mice fed either a normal or high-fat diet (87). In skeletal muscle, Nobiletin-induced ROR activation led to an increase in the transcription of genes of the mitochondrial respiratory chain complexes, thereby enhancing ATP production and reducing oxidative stress (87). Intriguingly, Nobiletin has also been associated with anti-inflammatory actions and protective effects against carcinogenicity and atherogenicity (88–90). This again links the molecular clock to NHRs in the control of essential metabolic pathways. The dysregulation of these processes tilt the balance between health and chronic disease.

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3.3.4 NHRs in the Response to Exercise Skeletal muscle is the largest organ in our body, accounting for 40% of our body mass. It contains approximately 60% of all body proteins and 85% of insulin-stimulated glucose uptake (91). Skeletal muscle contributes to 30% of energy expenditure at rest and 90% during physical activity (91). It is therefore one of the primary sites of glucose, lactate, lipid, and ketone body metabolism (91). Beyond its role in contraction, breathing, and posture maintenance, skeletal muscle is also involved in body temperature maintenance, storage of glucose, lipids, and amino acids, and endocrine activities (91). To manage such myriad functions, skeletal muscle must demonstrate resilience and dynamic faculties. It must adapt its biochemical, metabolic and contractile properties to a plethora of stimuli. This is particularly demanding during and after a bout of exertion, in which the myocyte must integrate and respond to a deluge of internal and environmental stimuli. This includes the activation of an intricate transcriptional program to differentially promote endurance or resistance. Although the benefits of exercise on chronic diseases have been extensively documented, these interventions are often underutilized or fail due to a lack of adherence or intolerance. One may speculate that exercise mimetics (i.e. pharmacological compounds that elicit exercise-like effects) could promote

Metabolism and Medicine similar benefits; however, better knowledge of the underlying molecular mechanisms is necessary to identify putative targets. Routine physical exercise modulates many molecular pathways involving NHRs. Muscle-specific overexpression of several NHRs, including PPARβ, PPARγ, Rev-erbα, RORα, ERRγ, Nurr1, and NOR1, favors an oxidative fiber phenotype and improves endurance capacity of the muscles (Figure 3.17) (91). Accordingly, their muscle-specific deficiencies result in a switch to glycolytic fibers, reduced exercise performance, glucose intolerance, and insulin resistance (91). Interestingly, sex hormone–activated NHRs, such as ERα and AR, induce muscular hypertrophy, while their deficiency in muscle results in weakness and shifts the fiber profile from slow to fast twitch fibers (91). In addition to ERα and AR, deletion of other NHRs, such as Nur77, RORα, and RORγ, in skeletal muscle also promotes muscle atrophy (91). By contrast, pharmacological GR activation weakens muscle strength, whereas GR deficiency prevents muscle atrophy and promotes protein metabolism (91). LXRα and LXRβ indirectly modulate muscle performance by improving glycogenesis and lipogenesis (91). Finally, ERRs are products of clock-controlled output genes produced in several tissues, including skeletal and cardiac muscle, where they enhance mitochondrial function.

FIGURE 3.17  NHRs regulate endurance and resistance exercise adaptations in skeletal muscle. Exercise activates PGC1α, a co-activator of several transcription factors, including PPARs, ERRs, which increases fatty acid oxidation, glucose transport, and GLUT4 gene transcription. Source: adapted from (91). *AR = androgen receptor; ER(α/β) = estrogen receptor α/β; ERR(α/γ) = estrogen related receptor α/γ; GR = glucocorticoid receptor; NCoR1 = nuclear receptor corepressor 1; NOR1 = nuclear orphan receptor 1; Nurr77 = nuclear receptor related protein 77; PGC1α(1/2/3/4) = peroxisome proliferator-activated receptor gamma coactivator 1α1/2/3/4; PPAR(α/β/γ/δ) = peroxisome proliferator-activated receptor α/β/γ/δ; RIP140 = receptor-interacting protein 140; ROR(α/γ) = retinoid-related orphan receptor α/γ; TRα = thyroid hormone receptor α; VDR = vitamin D3 receptor.

Nuclear Hormone Receptors NHR activity is thus extensively involved in exerciseinduced muscle adaptation and targeting such transcription factors would constitute an interesting therapeutic strategy. Agonists for certain NHRs, such as REV-ERBα and the estrogen-related receptors (ERRs), could be administered pharmacologically as exercise mimetics—“pills” with the potential of preventing or even treating chronic metabolic disease states in individuals unable to engage in routine physical exercise. Each potential exercise mimetic agent has a specific spectrum of molecular targets that replicate a subset of the molecular pathways regulated by physical exercise. Such targets include NO°, AMP-activated protein kinase (AMPK), sirtuin 1 (SIRT1), peroxisome proliferator-activated receptor gamma coactivator 1α (PGC1α), PPARδ, ERRs, and REV-ERBα. Adenosine monophosphate (AMP) activated protein kinase (AMPK) is an important energy sensor that serves a central role in cellular energy metabolism and bioenergetics. AMPK is activated by AMP, which is present in high concentrations during energy deficient states. At rest, activated AMPK promotes the catabolism of dietary and stored energy. This energy sensor also regulates many metabolic processes such as GLUT4 translocation and glucose uptake, β−oxidation of fatty acids, and mitochondrial biogenesis. (Figure 3.18). AMPK activity can be modulated by REV-ERBα. Thus, REV-ERBα agonists may enhance skeletal muscle function by pharmacologically enhancing AMPK activities, such as mitochondrial biogenesis and activity, fatty acid oxidation, and exercise tolerance (92–95). ERR and PPARβ co-activation in skeletal muscle is another plausible method of pharmacologically mimicking exercise. Acting in concert with the co-activator PGC1α, these NHRs impart benefits similar to physical exercise, including the enhancement of mitochondrial biogenesis, angiogenesis, oxidative metabolism (particularly fatty acid oxidation), skeletal muscle anabolism, and slow twitch muscle function.

FIGURE 3.18  Exercise and energy. Exercise activates PGC1α, a coactivator of several transcription factors, including PPARs and ERRs, which increases fatty acid oxidation, glucose transport, and GLUT4 gene transcription. *AMP = adenosine monophosphate; ATP = adenosine triphosphate; GLUT4 = glucose transporter 4; PGC1α = peroxisome proliferator-activated receptor gamma coactivator 1α.

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3.4 Nuclear Hormone Receptors Integrate Environmental Signals in a Timely Manner The activity of NHRs depends on the time of day and the metabolic state of the organism. NHRs can cooperate in a given organ to allow an efficient activation or repression of a specific pathway. For instance, PPARα promotes fatty acid synthesis during fasting, but inhibits this pathway (together with Rev-erbα) in the fed state. FXR also inhibits hepatic fatty acid synthesis, while Rev-erbα promotes intra-vascular triglyceride (TG)-rich lipoprotein metabolism by inhibiting the expression of apolipoprotein-CIII (apo-CIII). Such impacts would appear to drive metabolism toward glucose utilization during feeding. Interestingly, LXR expression is induced by PPARγ in macrophages, resulting in a cooperative cascade of gene transcription responses. With regard to Rev-erbα, both PPARα and LXRα have been noted to modulate expression in a manner that is highly context-specific (96, 97). Still other NHRs appear to have entirely opposing effects on energy mobilization; while PPARγ decreases lipolysis in white adipose tissue, GR is seen to enhance the degradation of triglycerides. NHR activity may also cooperatively regulate the availability of specific metabolites in various organs. For instance, Rev-erbα enhances bile acid synthesis from cholesterol in the liver, while LXRs promote intestinal cholesterol secretion and reverse cholesterol transport from peripheral tissues to the liver where it serves as a bile acid synthesis substrate. By controlling cholesterol transport and metabolism, these NHRs contribute to cholesterol excess and toxicity. On the other hand, FXR inhibits hepatic synthesis and intestinal reabsorption of bile acids, preventing overload and toxicity. Cholesterol homeostasis is maintained by two separate transcription factor pathways; one involving LXR-mediated elimination of cholesterol in response to excess cellular levels and another involving sterol regulatory element-binding protein 2 (SREBP2)-mediated cholesterol biosynthesis in response to depleted cellular levels (Figures 3.11 and 3.12). Under physiological conditions, SREBP2 drives the expression of the rate-limiting cholesterol biosynthesis enzyme hydroxy-methyl glutaryl-CoA reductase (HMGCR). The activity of HMGCR peaks at midnight when dietary cholesterol provisions and cellular cholesterol content are low. Activation of this enzyme serves to increase cholesterol levels through a normal course of homeostatic regulation. Statins, drugs used to reduce LDLcholesterol by inhibiting HMGCR, are therefore more effective when taken in the evening. During daylight hours, when cellular cholesterol levels are typically higher, the LXR pathway takes over to lower cholesterol levels. Analogous to HMGCR inhibitor therapy, management of adrenal insufficiency is also a classical example of chronotropic therapy. This parallels the natural physiological timing of adrenal glucocorticoid production, which troughs in the late night when the generalized inflammatory burden is at its peak. The most appropriate timing of hydrocortisone replacement is to give two-thirds of the total daily dose in the early morning and one-third of the dose between 2 p.m. and 4 p.m. This is consistent with the circadian rhythmicity of GR binding to the targeted metabolic genes. Similarly, PPARα agonist treatment

122 is most efficient at the peak of its expression (late in the resting phase).

3.5 Nuclear Hormone Receptors Are Important Pharmacological Targets with Clinical Applications Since the development of synthetic ligands for NHRs, they have constituted an attractive pharmacological target, particularly for disease states in which gene transcription has a well-documented role. As a consequence, targeting NHR family members has yielded a large number of therapeutics (glucocorticoids, estrogen and androgen mimetics and antagonists, fibrates, and glitazones, among others). The transcriptional activity of NHRs may be either induced by an agonist or inhibited by an antagonist. Their natural, endogenous transcriptional activity may even be reversed by an inverse agonist (e.g. Rev-erb inverse agonist GSK1362) (98). The best known examples of NHR therapeutics include tamoxifen, a selective estrogen receptor modulator (SERM) used in breast cancer; dexamethasone, a GR agonist used in inflammatory diseases; and retinoic acid used in acute promyelocytic leukemia and skin conditions, such as acne vulgaris. Other examples are agonists of PPARα (e.g. fibrates), which control the expression of genes involved in fatty acid uptake, activation of mitochondrial and peroxisomal β-oxidation (including CPT1, the mitochondrial FA transporter), and TG delivery to peripheral tissues through lipoprotein lipasemediated lipolysis of TG-rich lipoproteins in blood. Fibrateinduced PPARα activation thus produces triglyceride lowering effects (99, 100) and has great utility in patients with hypertriglyceridemia. Additionally, the glitazones (rosiglitazone, pioglitazone) are PPARγ ligands. They exert insulin-sensitizing effects via activation of adipose tissue PPARγ, inducing adipocyte differentiation and fatty acid handling. As a consequence, glitazones also preserve insulin secretion and pancreatic β-cell loss (39). However, a plethora of failed drug development programs has raised awareness regarding the difficulty of developing efficacious and safe NHR-activating compounds. For example, many currently used PPAR agonists are either weakly potent (PPARα agonists) or associated with critical side effects (PPARγ). Nevertheless, optimization of therapeutic strategies may be achieved through the development of selective NHR modulators—so-called selective nuclear receptor modulators (SNRMs). Indeed, selective modulators have been developed for several NHRs, including estrogen receptors (SERMs) (101, 102), LXRs (selective liver X modulators; SLiMs) (103, 104), androgen receptors (selective androgen receptor modulators; SARMs) (105), and PPARs (selective PPAR modulators; SPPARMs) (39). SPPARγM compounds ideally allow the activation of a subset of PPARγ target genes involved in glucose homeostasis without affecting the expression of genes involved in adipose tissue expansion or side effects such as fluid retention. For instance, the SPPARM gamma INT131 produces a bioequivalent reduction in hemoglobin A1c (HbA1c) levels when compared to the full PPARγ agonist pioglitazone in

Metabolism and Medicine patients with type 2 diabetes mellitus; however, its selective modulator design results in less fluid accumulation and weight gain (106). In addition, the selective PPARα agonist pemafibrate displays greater lipid oxidation activity compared to the standard fenofibrate with little or no effect on serum creatinine and homocysteine levels. Furthermore, NHR compounds with dual or pan-activating properties may actually produce cumulative effects. Examples include dual PPAR agonists with the capacity to bind and activate two PPAR isotypes simultaneously. Interestingly, the pan-PPAR agonists lanifibranor and chiglitazar, which activate three isotypes, improve lipid profiles and insulin sensitivity without increasing body weight in preclinical models of obesity. Lanifibranor recently entered the last stage of clinical development (phase 3) for the treatment of non-alcoholic steatohepatitis (NASH), a metabolic liver disease with increasing global prevalence.

3.6 Summary Healthy dietary practices can help optimize energy extraction from the environment when properly timed during the light (active)/dark (inactive) cycle. The quality, quantity, and timing of dietary intake are major extrinsic control parameters for bioenergetic and redox homeostasis. They act as external “zeitgebers”, keeping the body in phase with circadian cycles by synchronizing endogenous clocks. Defining the role of NHRs in this spatial and temporal orchestration of metabolism may prove to be of critical importance for future pharmaceutical developments. Many NHRs bind to nutrients, including metabolites and derivative hormones related to fatty acids or cholesterol, and couple these signals to intrinsic core molecular clocks. Thus, in connection with feeding/fasting cycles, NHRs and core clocks co-regulate the oscillatory transcription for an exceedingly complex network of metabolic processes. This includes glucose versus fatty acid oxidation, mitochondrial biogenesis and function, lipolysis versus lipogenesis, and gluconeogenesis/ glycogenolysis versus glycolysis/glycogenesis.

It should be emphasized that the significance of the intersection between oscillating NHRs, circadian clocks, and metabolic processes extends beyond the coordinated input of energy substrates into bioenergetic pathways. It is additionally representative of a bidirectional relationship and coherence between ATP production and the notion of quantum metabolism. Energy availability provides an essential groundwork for the basic clockwork functionality of the human body. particularly with regard to metabolically demanding processes such as reproduction, immune function, and cell replication. As such, disease states involving these processes may be underpinned by disturbances in biological clocks as demonstrated in preclinical models. This can be seen as the dissonance of lifestyle in humans with disease from the natural light–dark cycle as well as redox disturbances that accompany impaired free energy.

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Nuclear Hormone Receptors As predicted by the close correlation of the Nernst and Gibbs free energy equations, the compromise and destabilization of regulatory processes in biological systems often disrupts circadian rhythms. This manifests in hormonal systems as a disturbance of typical diurnal variation patterns (e.g. an infradian, or greater than 24 hour, menstrual cycle impairing fertility). Similarly, pathologies such as epithelial cell malignancies of the reproductive and gastrointestinal systems, chronic inflammation, immune dysfunction, infectious diseases, and chronic metabolic diseases (e.g. obesity-associated diabetes and cardiovascular disease) exemplify the inextricably interdependent nature of NHRs, metabolism, and endogenous circadian clocks in human disease. Therefore, NHRs mediate two-way communication between circadian rhythm and metabolic processes to maintain whole-body homeostasis (Figure 3.19).

3.7 Bile Acid Metabolism—A Pivotal Crossroad between Nutrient Signaling and Circadian Networking The farnesoid X receptor (FXR), also known as the bile acid receptor (BAR) or NR1H4 (nuclear receptor subfamily one, group H, member four), is a nuclear receptor with high expression in the gut and liver that plays a key modulatory role in bile acid production. Bile acids are amphipathic (“soap-like”) molecules that act as physiological detergents and can be toxic to host tissues at high concentrations. For this reason, their production is closely regulated by mediators like FXR. When bound by bile acids (predominantly chenodeoxycholic acid, CDCA), FXR translocates to the cell nucleus and heterodimerizes to suppress transcription of the rate-limiting enzyme for bile acid synthesis, cholesterol 7α hydroxylase (CYP7A1). FXR does not bind the CYP7A1 promoter directly, but rather induces the expression of small heterodimer partner (SHP) proteins that in turn mitigate CYP7A1 gene expression. This negative feedback loop serves as the classical mechanism for the autoregulation of bile acid synthesis in vivo and is continuously modulated by the circadian system (e.g. regulation of CYP7A1 by clock gene Rev-erbα). Bile acids therefore occupy a pivotal crossroad between nutrient signaling and circadian networking. In addition to its classical role, FXR is also an important mediator of glucose and lipid metabolism. In the liver, FXR has been shown to inhibit both hepatic gluconeogenesis and glucose secretion. In enterocytes, bile acid-bound FXR activates fibroblast growth factor 19 (FGF19), which travels through the portal circulation to bind FGF receptor 4 (FGFR4)/β-klotho in the liver. The latter reduces the inhibition of glycogen synthase (GS) by glycogen synthase kinase 3 (GSK3), increasing glycogenesis. FGF19 in the liver also reduces gluconeogenesis by inhibiting cyclic AMP response element binding protein (CREB). Bile acids, particularly lithocholic acid (LCA) and its conjugates (e.g. taurolithocholic acid, TLCA), also regulate homeostasis and inflammatory processes via the Takeda G protein-coupled receptor 5 (TGR5). TGR5 has prominent effects in both enterocytes and hepatocytes, inhibiting

inflammatory cytokine production via suppression of NFκB (nuclear factor kappa-light-chain-enhancer of activated B cells). In enteroendocrine L cells of the gut, TGR5 activates glucagon-like peptide-1 (GLP-1), which acts on islet cells of the endocrine pancreas to 1) enhance insulin biosynthesis and glucose-stimulated insulin secretion (GSIS), 2) inhibit glucagon secretion, and 3) induce β-cell proliferation. While most prominently expressed in the ileum, GLP-1 may also enter the circulation to exert effects on remote targets. In the brain, it acts on neurons in the arcuate nucleus of the hypothalamus to reduce the threshold of satiety. Both insulin and GLP-1 independently act as satiety factors in the arcuate nucleus, stimulating and repressing pro-opiomelanocortin (POMC) and neuropeptide Y (NPY)/agouti-related protein (AgRP) neurons, respectively. This effect is compounded by GLP-1 activity in the stomach, which slows gastric emptying. In the hippocampus, GLP-1 promotes synaptic plasticity, improving cognition and possibly reducing the risk of Alzheimer’s disease. GLP-1 agonism additionally protects from cardiovascular diseases related to large-vessel atherosclerosis. Activation of TGR5 in white and brown adipose tissue impacts basal metabolic rate and thermogenesis. By promoting TGR5 activation of type 2 deiodinase, bile acids increase the conversion of prohormone thyroxine (T4) into active triiodothyronine (T3). T3 upregulates uncoupling protein-1 (UCP1), which uncouples substrate energy combustion in the mitochondria from ATP production to support thermogenesis. Finally, TGR5 also has prominent effects in cells of the immune system, inhibiting inflammatory cytokine production in macrophages via suppression of NFκB.

SIDEBAR 3.3: DRAWING CONNECTIONS Secondary bile acids, conjugated from primary bile acids by the gut microbiota, have also been observed to activate TGR5. This is one of several sites in which the gut microbiota exerts an influence on mammalian biochemistry. The extent of this interaction is so robust that organisms reared in germ-free environments demonstrate profound developmental immaturity in multiple organ systems. Indeed, human life itself is inextricably dependent on microbiota for survival (see Chapter 6). One pathway that connects bile acids to energy metabolism involves the sphingosine-1-phosphate receptor 2 (SIPR2). SIPR2 is activated when conjugated bile acids (e.g. taurocholic acid, TCA) co-localize at the receptor with sphingosine-1-phosphate (S1P). This activates Src (proto-oncogene tyrosine-protein kinase) and epidermal growth factor (EGF) to induce insulin receptor signaling via the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (PKB, Akt) pathway. Akt inhibits GSK3β, leading to upregulation of GS and induction of glycogenesis. Akt also inhibits the transcription factor FOXO, repressing the action of gluconeogenic enzymes like phosphoenolpyruvate carboxykinase (PEPCK) and glucose6-phosphatase (G6Pase). This, in turn, reduces gluconeogenesis and lowers circulating glucose levels. In hepatocytes, FXR (via SHP) inhibits sterol regulatoryelement binding protein 1c (SREBP1c), reducing de novo

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FIGURE 3.19  NHRs, metabolism, and circadian clocks. NHRs, metabolism, and endogenous circadian clocks are inextricably linked to the maintenance of whole-body homeostasis. Pathologies arise when the synchrony between these systems is compromised. *AMPK = AMP-activated protein kinase; ANS = autonomic nervous system ; CYP7A1, cholesterol 7α hydroxylase; ERR(α/β/γ), estrogen related receptor α/β/γ; FXR, farnesoid X receptor; GLP-1 = glucagon-like peptide-1; GR, glucocorticoid receptor; GS, glycogen synthase; GSK3, glycogen synthase kinase 3; GPK = glycogen phosphorylase kinase; LXR, liver X receptor; NHR, nuclear hormone receptor; PPAR(α/β/γ/δ), peroxisome proliferator-activated receptor α/β/γ/δ; PYY, peptide YY; ROR(α/β/γ), retinoid-related orphan receptor α/β/γ; RXR(α/β/γ), retinoid X receptor α/β/γ; SIRT1 = Sirtuin 1.

lipogenesis. FXR also enhances intravascular lipolysis of triglyceride-rich lipoproteins by inducing apolipoprotein C-II (apoCII) and reducing angiopoietin-like protein 3 (ANGPTL3). These structural components of VLDL (very low-density lipoprotein) and chylomicron particles act together

to enhance lipoprotein lipase (LPL) and hepatic lipase activity. By this means, FXR lowers plasma TG concentrations and enhances hepatic uptake of TG-poor remnant lipoproteins. FXR has additional catabolic effects on lipoprotein and cholesterol metabolism by promoting the expression of

Nuclear Hormone Receptors phospholipid transfer protein (PLTP) and the VLDL receptor. PLTP transfers phospholipids and cholesterol from low-density lipoproteins (LDL) to high-density lipoproteins (HDL). This is consistent with the activation of PPARα (peroxisome proliferator-activated receptor-α) by FXR, which promotes fatty acid oxidation and reduces liver triglyceride accumulation. This reduces the secondary overflow of lipids into the circulation that causes hyperlipidemia. However, FXR also enhances hepatic cholesterol accumulation through its inhibitory activity on bile acid synthesis. As a consequence, hepatic LDL-receptor activity is inhibited and plasma LDL levels increase (an established cardiovascular risk factor). The pharmacodynamic effects of NHRs such as FXR are thus context-specific and difficult to interpret in isolation. An exceptional level of temporal organization occurs between these NHRs to maintain the circadian rhythms and diurnal synchrony that exists among tissues and organ systems. The purpose of these interactions is to maintain metabolic homeostasis and optimize physiological efficiency. Accordingly, the metabolic effects of FXR are specifically tailored to complement the diurnal phase of the circadian cycle. Interacting with the insulin and glucagon signaling pathways in a reciprocal manner, FXR and PPARα adapt their influences on lipid and glucose metabolism to preserve metabolic flexibility, promote insulin sensitivity, and reduce hepatic lipogenesis. Diurnal variation is critical to this dynamic relationship. For example, the fasting-feeding cycle can act as a “zeitgeber”, an extrinsic circadian cue that modulates metabolic activity. During the feeding phase, NHRs—such as ROR, PPAR, FXR, and LXR—are upregulated in a fashion similar to that of hormones like insulin. This same variation occurs in concert with circadian rhythms, allowing the body to optimize metabolic efficiency by coordinating energy utilization with resource availability (see Chapter 4). NHRs are thus at a point of intersection between nutrient signaling and circadian rhythms. For example, polyunsaturated fatty acids (PUFAs) such as alpha-linolenic acid (ALA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) in the diet lower circulating triglycerides. Dietary PUFAs stored in fat cells are more readily mobilized during fasting states than are saturated fatty acids (SFAs). PUFAs signal through NHRs both directly (e.g. RXR, PPARs, and FXR) and indirectly (e.g. FXR downstream effects). Dietary fat promotes bile acid secretion into the stomach before returning to the liver where it activates FXR and, in turn, PPARα. Despite this, PPARα is classically activated during fasting states by FAs released from adipocytes, stimulating mitochondrial fatty acid oxidation. These seemingly contradictory actions underscore the molecular crosstalk that must occur between these two NHRs to coordinate fasting/feeding and diurnal phases of the circadian cycle. Regarding lipogenesis, FXR and LXR have opposing effects on transcription factor SREBP1c and associated target genes. The anti-lipogenic effect of PPARα and FXR coordinate an interplay with LXR during the fed state that facilitates the insulin-sensitizing effects that are characteristic of the fasted state. As the natural ligands for PPARα, PUFAs also act as ligands for FXR and share some of the same antilipogenic properties via this mechanism. PUFAs act as LXR

125 antagonists, preventing it from binding its response element in the SREBP1c gene. This reduces the expression of transcription factor SREBP1c and its downstream lipogenic gene program, including enzymes acetyl-CoA carboxylase (ACC) and fatty acid synthase (FAS). Further, PUFAs impose selective regulation on FXR target genes. They have been shown to promote vasodilation and anticoagulation by inhibiting the FXR target gene kimogen. By contrast, PUFAs actually enhance FXR-induced gene expression of the bile salt export pump (BSEP), promoting bile salt movement into the biliary canaliculi and GI tract. Interestingly, the vasodilating and anticoagulative effects appear to be insulin-sensitizing, while the FXR stimulatory effects on BSEP gene expression are protective against hepatic steatosis, the anatomical hallmark of insulin resistance. To summarize, PUFAs are natural ligands for multiple nutrient-sensing NHRs, including PPARα, increasing fatty acid oxidation during fasting and enhancing lipogenesis during the fed state; FXR, promoting an anti-lipogenic effect during the fed state; LXR, stimulating lipogenesis during the fed state; and PPARγ, exerting pro-adipogenic effects and triglyceride-storing activity that enhances insulin-sensitivity in the fed state. These actions collectively amplify the dynamics of insulin signaling over the diurnal period and have protective effects on healthy metabolic physiology. The general function of these NHRs is to transmit the information from nutrient molecules (e.g. lipids and cholesterol) to metabolically adaptive systems for energy transformation. Insulin is a signal of energy abundance and promotes multiple biosynthetic activities, including the storage of glycogen and fat, anabolic protein synthesis, and glycogenesis. Insulin sensitivity and mitochondrial function are fundamentally and bidirectionally linked to health, as are insulin resistance and mitochondrial dysfunction in disease. The latter is accompanied by ectopic fat deposits in metabolically active tissues such as the liver, skeletal muscle, myocardium, islet cells of the endocrine pancreas, and even the brain. The result of this deposition is a cascade of inflammatory and redox disturbances that degrade mitochondrial structure and function. In the brain, this manifests as microscopic lipid droplets in neurons of the hippocampus and may reasonably occur in energy sensing neurons of the hypothalamus such as the arcuate nucleus. Taken together, this widespread pathological fat deposition could have major implications in obesity, type 2 diabetes, vascular function, cardiomyopathy, and even dementia. In a world with increasing prevalence of obesity and insulin resistance, the implications of bile acid metabolism on chronic disease may be utilized to fundamentally enhance quality of life and prolong lifespan. The triumvirate of bile acid metabolism, microbiota composition, and hormone regulation in the gut deserves center stage in the future of medicine. Humans evolved from conditions of nutrient scarcity and high energy expenditure, and now face a modern society with few physical demands and a constant supply of calorie-dense foods. Although our lifespan has extended in recent decades, health spans have declined due to the morbidities caused by insulin resistance, type 2 diabetes mellitus, cardiovascular disease, cancer, and neurodegenerative diseases such as Alzheimer’s.

126 The chronic exaggerated stress response, as it relates to excess adiposity, contributes substantially to a declining quality of life. The pervasive proinflammatory state perpetuates a spectrum of diseases. It is propitious that the body has the potential, through dietary choices, to upregulate the same metabolic pathways and yield the same healthy physiological states achieved by intermittent fasting. With NHRs at the crossroad of nutrient signaling, circadian metabolism, and metabolic physiology, they provide a promising gamete of therapeutic targets for the treatment and prevention of metabolic diseases. This diagram illustrates the time-coordinated metabolic signaling that occurs in the healthy state. While this system is optimized for precision and accuracy, perturbations of circadian-controlled gene expression can disrupt the temporal synchrony of the system and produce dissonance among interacting components. For example, there appears to be a reciprocal relationship between redox disturbance and clock entrainment. Redox disturbance in the pancreas may provoke fasting insulin secretion in a glucose-independent manner. This subsequently promotes hypoglycemia by suppressing gluconeogenesis and glycogenolysis in the liver. In patients, this typically manifests as nocturnal diaphoresis and headaches between 2 a.m. and 4 a.m. when blood glucose levels trough in the absence of counter-regulatory hormones and neurotransmitters. Circadian bile acid production and downstream activation of FXR may also demonstrate dysregulation in the setting of hepatic redox disturbance. FXR, which is most robustly activated by bile acids in the fed state, may demonstrate augmented activity in the fasted state, resulting in aberrant regulation of insulin signaling and hepatic gluconeogenesis. Accordingly, redox disturbance in the liver creates a vicious cycle of circadian uncoupling that impairs clockcontrolled gene output and further disrupts redox homeostasis. Accelerated cognitive decline with aging may also be linked to insulin resistance in the hippocampus along with co-occurring cortisol-induced apoptosis. Not only does FXR promote suppression of gluconeogenesis and glycogenolysis by enhancing insulin signaling in the fed state, but insulin and glucose reciprocally upregulate FXR as well. Uncoupling from the fasting/feeding cycle may also be a result of circadian cue disturbances, such as aberrant light/dark cycling, core clock gene mutations, or redox dysregulation. It should also be noted that bile acid abundance and composition are modulated by numerous physiological states, including fasting/feeding, hyperglycemia/euglycemia, insulin resistance/sensitivity, and obese/ lean body habitus. Elucidating the role of bile acid metabolism as an intrinsic control parameter of health and disease will likely unveil future targets for therapeutic intervention. At the very least, it must be recognized for its important contribution to the fitness landscape model proposed in this book. Through this understanding, we can ultimately advance the practice of clinical medicine to induce phase transitions from susceptibility and disease to resilience and longevity.

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4 The Biology of Time: How Molecular Clocks Make Living Cells Tick

Abbreviations ΔG ΔS AC ACC ACTH AD AICAR

Gibbs free energy entropy adenylate cyclase acetyl-CoA carboxylase adrenocorticotropic hormone Alzheimer’s disease 5-ami​noimi​dazol​e-4-c​arbox​amide​-1-β-​D-rib​ ofura​nosid​e Akt protein kinase B (PKB) ALS amyotrophic lateral sclerosis AMP adenosine monophosphate AMPK AMP-activated protein kinase ANS autonomic nervous system Apo-C2/3 apolipoprotein C-II/III Apo B apolipoprotein B AR androgen receptor Arc arcuate nucleus ATP adenosine triphosphate AVP vasopressin BAT brown adipose tissue bHLH PAS basic-helix-loop-helix domain PER-ARNT-SIM Bmal1 brain and muscle Arnt-like protein-1 gene BMAL1 brain and muscle Arnt-like protein-1 BP blood pressure BTRCP1/2 beta-transducin repeat containing 1/2 cAMP cyclic adenosine monophosphate CAR constitutive androstane receptor CCK cholecystokinin CGRP calcitonin gene-related peptide CHO carbohydrate CIART circadian-associated transcriptional repressor Clock circadian locomotor output cycles kaput gene CLOCK circadian locomotor output cycles kaput CNS central nervous system CoA Coenzyme A COX-1 cyclooxygenase 1 CR calorie restricted CREB cAMP response element binding protein CRH corticotropin-releasing hormone CPT1 carnitine palmitoyl transferase 1 CSNK1e/d casein kinase 1ε/δ CT circadian time Cry cryptochrome circadian regulator gene DOI: 10.1201/9781003149897-4

CRY1/2 CV CVD CYP7A1 DAGs DBP DEC2 DSPS DYRK1a

cryptochrome circadian regulator 1/2 cardiovascular cardiovascular disease cholesterol 7α hydroxylase diacylglycerides D-site albumin promoter binding protein differentiated embryonic chondrocyte gene 2 delayed sleep phase disorder dual-specificity tyrosine-phosphorylated and regulated kinase 1A D-box destruction box eNOS endothelial nitric oxide synthase EPR entropy production rate ER estrogen receptor ER stress endoplasmic reticulum stress ERR(α/β/γ) estrogen related receptor α/β/γ E-box enhancer box FA fatty acid FAD+ flavin adenine dinucleotide FADH2 dihydroflavin adenine dinucleotide FAO fatty acid oxidation FAS fatty acid synthase FASPS familial advanced sleep phase syndrome FAT fatty acid translocase FATP fatty acid transport protein FBP1 fructose-bisphosphatase 1 FBXL3/21 F-Box and leucine rich repeat protein 3/21 Fe+2/+3 iron (II/III) ion FFA free fatty acid FOXO Forkhead Box O FXR farnesoid X receptor ΔF free energy GC glucocorticoid GCK glucokinase GGH growth hormone GI gastrointestinal GLP-1 glucagon-like peptide-1 GLUT(1/4) glucose transporter 1/4 GPCR G protein coupled receptor GPAT glycerol-3-phosphate 1-O-acyltransferase GR glucocorticoid receptor GREs glucocorticoid response elements GSH glutathione GSK3B glycogen synthase kinase 3β GSSG glutathione disulfide GTP guanosine triphosphate 131

132 G6P HAT HDAC HDL HIF1α/β HLF HMGCR HNF4α HO HPA HREs HSD1/2 HSL HSV H2O H 2 O 2 IF IGF-1 IL(-1β/6) IMCL ipRGCs IR KPNB1 K+ LDL LKB1 LPL LPO LRH-1 LXR L/D MAPK MBH MC2R MR mRGCs Mt mTOR M1/2 NA Na+ NAD+ NADH NADP+ NADPH

glucose-6-phosphate histone acetyltransferase histone deacetylase high density lipoprotein hypoxia inducible factor 1 α/β hepatic leukemia factor hydroxy-methyl-glutaryl-CoA reductase hepatocyte nuclear factor 4 α hydroxide hypothalamic-pituitary-adrenal axis hypoxia response elements 11-β-hydroxysteroid dehydrogenase type 1/2 hormone-sensitive lipase herpes simplex virus water hydrogen peroxide intermittent fasting insulin growth factor 1 interleukin-1β/6 intramyocellular lipid intrinsically photoreceptive RGCs insulin resistance karyopherin subunit beta 1 potassium ions low-density lipoprotein liver kinase B1 lipoprotein lipase lactoperoxidase liver receptor homolog 1 liver X receptor light/dark mitogen-activated protein kinase medial basal hypothalamus melanocortin receptor mineralocorticoid receptor melanopsin retinal ganglion cells mitochondria mechanistic target of rapamycin melatonin receptor 1/2 nicotinic acid sodium ions nicotinamide dinucleotide nicotinamide dinucleotide (reduced form) nicotinamide adenine dinucleotide phosphate nicotinamide adenine dinucleotide phosphate (reduced form) NAM nicotinamide NaMN nicotinate mononucleotide NAMPT nicotinamide phosphoribosyltransferase (visfatin) NCoR nuclear receptor corepressor NFIL3 nuclear factor, interleukin 3 NF-κB nuclear factor kappa B NMN nicotinamide mononucleotide NR nuclear receptor NRE nuclear receptor response element NHR nuclear hormone receptor NPAS2 neuronal PER-ARNT-SIM domain protein 2 NPY/AgRP neuropeptide Y/ agouti-related protein

Metabolism and Medicine NSCLC OB OSA O 2 O -2 p53 P450 PAI-1 PARbZIP

non-small cell lung cancer olfactory bulb obstructive sleep apnea oxygen oxide tumor protein 53 cytochrome 450 plasminogen activator inhibitor-1 proline- and acid-rich subfamily of basic region leucine-zipper PEPCK phosphoenolpyruvate carboxykinase Per period circadian regulator gene PER1/2/3 period circadian regulator 1/2/3 PEG polyethylene glycol PFK2 phosphofructokinase-2 PGC1α/β(1/2/3/4) peroxisome proliferator-activated receptor gamma coactivator 1α/β/1/2/3/4 PHS prostaglandin H synthase PI3/AKt/PKB pathway phosphoinositide 3-kinase protein kinase B pathway PK pyruvate kinase PKA/C protein kinase A/C POMC/CART proopiomelanocortin/cocaine and amphetamine regulated transcript PPAR(α/β/γ/δ) peroxisome proliferator-activated receptor α/β/γ/δ PR progesterone receptor PRC phase response curve PVN paraventricular nucleus PVT thalamic paraventricular nucleus PXR pregnane X receptor RBCs red blood cells REM rapid eye movement RCT reverse cholesterol transport RGCs retinal ganglion cells RIP140 receptor-interacting protein 140 ROR(α/β/γ) retinoid-related orphan receptor α/β/γ gene ROR(α/β/γ) retinoid-related orphan receptor α/β/γ ROREs ROR-response elements ROS reactive oxygen species RREs Rev-erb response elements RXR(α/β/γ) retinoid X receptor α/β/γ s. muscle skeletal muscle SCD1 stearoyl-COA desaturase 1 SCN suprachiasmatic nucleus SGLT-1 sodium glucose cotransporter 1 SHP small heterodimer partner SIRT1 sirtuin 1 SMRT silencing mediator of retinoic acid and thyroid hormone receptor SNS sympathetic nervous system SOD superoxide dismutase SRCs steroid receptor coactivators SREBP(1c/2) sterol regulatory-element binding protein 1c/2

The Biology of Time stAR SXR

steroidogenic acute regulatory protein steroid and xenobiotic sensing nuclear receptor TCA tricarboxylic acid TEF thyrotroph embryonic factor TG triglyceride TGR Takeda G protein-coupled receptor TNF-1 tumor necrosis factor-1 TRE time-restricted eating TRF time-restricted feeding TR(α/β) thyroid hormone receptor α/β TSH thyroid stimulating hormone TTFL transcriptional-translational feedback loop T2D type 2 diabetes T3 triiodothyronine ULK1 autophagy activating kinase UPR unfolded protein response Vit B3 complex vitamin B3 complex VDR vitamin D3 receptor VIP vasoactive intestinal peptide VLDL very low-density lipoprotein VO2 max maximal volume of oxygen consumption VO2 submax below the maximal volume of oxygen consumption WT wild-type

Chapter Overview Time is a concept that we are all acutely aware of, especially of its passing, but would have great difficulty defining in precise terms. It’s a relational quantity. We measure it in terms of some controllable processes using devices such as clocks, or in relation to the cycles of the Sun, the Moon, or galaxies in the night sky. Einstein demonstrated that time is relative and there is no universal frame of reference for time or space in this matter. The most fundamental cycle in biology is the metabolic cycle that sets the clock rate, or number of cycles per unit of time, for the whole body. All living systems age and die and the average length of time between birth and death is called life expectancy, but it differs significantly between men and women as well as different populations analyzed by country, ethnicity, and even profession. In this chapter, we delve into the all-important topic of the biology of time, a topic that has now produced astonishing insights into the existence of molecular clocks. This is intimately related to two major physical issues involved, namely the cyclicity of biochemical reactions and its gradual degradation due to the increased entropy production as our bodies age and lose their synchronized perfection. Biological cycles are categorized as circadian (24 hours), infradian (longer than 24 hours), and ultradian (shorter than 24 hours) systems, which together are intricately interactive and interconnected. The aging process is a manifestation of the desynchronization away from the exquisitely orchestrated beauty biologically perfect cyclical processes, at all levels of organization, that operate as a singular whole in youthful states of optimal health.

133 The overarching message of this chapter is the notion of a biological cycle. We also underline the strong connection between biological cycles and the superfamily of thyroid and steroid nuclear hormone receptors. These receptors act as transcriptional regulators of hormone- and lipid-derived ligands to maintain the acid-base, redox, and energy branches of metabolic homeostasis organism-wide. Time is an essential variable in biological systems, measured in terms of cycles. The constant influx of energy in a living system maintains it in a far from equilibrium state. Time is measured externally with mechanical clocks composed of physical oscillators. Biological processes are measured and conducted by internal endogenous clocks, molecular machinery present in all cells that have DNA. These molecular clocks are the astonishing evolutionary incarnate of the Earth’s rotation around its own axis. The cell’s endogenous timepieces include central (SCN) and peripheral (non-SCN) circadian oscillators that link metabolic pathways of physiology and behavior to 50% of the human genome. This temporal organizing strategy is essential for maintaining energy and redox homeostasis, and hence life itself. The SCN receives primary sensory cues in the form of visible light and, thus, synchronizes to the diurnal light– dark cycle of the external environment. The circadian pattern of neurotransmission originating from the master pacemaker reaches many other regions of the brain such as the hypothalamus and the pineal gland. Central circadian regulation of these areas of the brain from the SCN in turn provides neural and hormonal cues to different tissues and organ systems throughout the body, thus temporally coordinating many aspects of physiology. These cues include autonomic fibers, hypothalamic-pituitary-adrenal gland axis (HPA axis) and melatonin. Accordingly, while the autonomic nervous system and HPA axis mediate the body’s stress response, and melatonin promotes sleep induction and slow wave sleep, these are also central conductors of systems biology within and between tissues of the body. This allows the time organizational coherence of physiology to function as a system whole. It follows that diurnal external light cues coming in through the retina of the eyes ultimately entrain the cell-autonomous circadian peripheral clocks that drive the timing of organ system physiology. Entrainment is the stable synchronization of external cycling events of the environment to the internal cycling pathways that conduct physiology. Teleologically, this orchestration between the central and peripheral clocks allows the anticipation and accordingly the adaptation to environmental changes, promoting maximum metabolic efficiency and homeostasis. There are many inputs received by the body that can entrain physiology, with the two strongest cues being light (for the master clock) and food for peripheral clocks. Coordination with the major cycling external cues of light and food includes but is not limited to behavioral cycles of fasting/feeding, sleep/wake, and rest/activity. Additionally, aligned to external cues and to behavioral cycles are physiological cycles of core body temperature, neuroendocrine function, and autonomic function (Figure 4.S1). The master metabolic regulator, AMP activated protein kinase (AMPK), and sirtuin 1 (SIRT1) are energy sensors with a complex and strong bidirectional interplay between

134

Metabolism and Medicine

FIGURE 4.S1  Light serves as the primary visual cue which transmits information about the environment to the master clock, the suprachiasmatic nucleus (SCN). The SCN in turn signals to numerous brain regions and tissues that regulate hormone systems, the autonomic nervous system, and behavior.

themselves and with clock function in several tissues, most notably in the hypothalamus and the liver. AMPK and SIRT1 are intricately coupled to the steroid and thyroid superfamily of nuclear hormone receptors (NHRs) and other transcriptional regulators that govern the circadian cycles of the energy and redox programs of metabolic homeostasis. Accordingly, these programs in states of excellent physiological health align with circadian behaviors of the sleep–wake and fasting–feeding cycles. During nocturnal fasting, energy consuming pathways are inhibited while energy (ATP) producing pathways are stimulated. Thus, for example, NHR peroxisome proliferator-activated receptor gamma (PPARgamma), which promotes anabolic pathways of adipogenesis and in parallel adipocyte filling lipogenesis, is upregulated during the daytime feeding phase of the circadian cycle (Figure 4.S2). Conversely, NHR PPARalpha, which promotes fatty acid oxidation, is diurnally activated during the nocturnal and fasting phase. The timing of eating plays a key role in the timing, coordination, and efficiency of metabolic pathways. It appears evident that 12 hours, and even up to 18 hours, of consistent fasting on a daily basis of time restricted eating (TRE), particularly during the night, is a powerful if not crucial method for achieving optimal physiological bodyweight and health. This is rooted in the circadian rhythm of the synchronized symbiotic intestinal microbiota with human host metabolism. When we eat at a time that our body anticipates it, as is the case of TRE, the feeding cue reinforces and amplifies the circadian rhythms. However, when we eat at irregular times, when our body is not prepared for it, it provides conflicting cues to the circadian pathways that guide physiology and behavior. Nocturnal eating induces impaired fasting glucose, fasting hyperlipidemia, insulin resistance, and weight gain through a

number of mechanisms. These include carbohydrate and fat consumption superimposed on a malalignment of nocturnal processes of hepatic glucose output and adipose tissue release of fatty acids respectively. These events may lead to glucose toxicity and lipotoxicity which induce inflammatory and redox stress, and insulin resistance that disrupt metabolic homeostasis. An additional contribution is the diurnal releasing pattern of melatonin at night. Melatonin inhibits pancreatic release of insulin and, thus, is another exacerbatory factor that potentiates not only hyperglycemia with nocturnal eating, but other manifestations of insulin resistance. Eating patterns at times that conflict with other cues to the circadian clocks, and hence at a time when the body is not prepared, compromise metabolic function. Summarily, in addition to diet and other circadian behaviors, control parameters of biological time in the form of cycles include the stress response and the microbiome. Spatial-temporal desynchronization of metabolic pathways is consequent to a conflict in behavioral and physiological circadian cues. What ensues is a feedforward self-amplifying matrix of reverberating cascades whereby the control parameters and the primary markers of disease itself, i.e. redox, energy and inflammatory stress, cannot be extricated. Taken together, human disease may be defined from the perspective of a breakdown in the temporal organization of physiological processes and control parameters.

4.1 Historical Context Chronobiology, the study of the timing of biology, has a rich history. To explain how it got from de Mairan to where the

The Biology of Time

135

FIGURE 4.S2  Metabolic/physiological fitness landscape of changing bodyweight. a) Metabolically healthy obese—persistent dietary overconsumption in the context of a pear-shape body type, or pharmacologic drug prescription with a PPARγ agonist, promotes weight gain in the absence of developing pathogenic metabolic parameters. In these individuals there is greater adaptive storage capacity for excess lipids that correlates with the predominance of subcutaneous adipose tissue. Accordingly, there is resilience to the evolution of insulin resistance features (such as dysglycemia, hypertension and dyslipidemia), and correspondingly a decline in the amplitude of the metaphorical physiological fitness landscape stable state. b) Metabolically unhealthy obese—persistent dietary overconsumption in the context of an apple-shape body type has less adipose tissue storage capacity. Consequently, there is less resilience to the loss of metabolic fitness, represented in a decline in the altitude of the metaphorical stable state within the topological terrain of the fitness landscape.

field is today would comprise a novel in its own right. In the interest of time, I will briefly cover the origins of the field and some key research relevant to this chapter. Chronobiology is a field that was born and driven by curiosity. In 1729, Jean-Jacques d’Ortous de Mairan performed the first experiment to demonstrate the existence of circadian rhythms. Intrigued by the daily opening and closing of the Mimosa pudica plant, he questioned if the Sun was responsible for this daily movement. To test this, he put the mimosa plant in a closet to keep it in constant darkness and noted its behavior. He found that the plant continued to open and close even without access to sunlight. However, he did not conclude that there were internal rhythms, but rather that the plant had a way of sensing the Sun distinct from light exposure. In the 1900s, Colin Pittendrigh, known as the “father of the biological clock” and founder of the modern field of chronobiology alongside Jurgen Aschoff and Erwin Bünning, made great progress in the field with the observation and descriptions of circadian behavior in Drosophila and mice. However, until the 1980s, it was still highly debated if circadian rhythms were driven from within an organism or rather just a response to the external environment (light, temperature, food

availability, etc.). In 1990, it was finally determined that circadian rhythms were produced and maintained internally using SCN-transplant experiments in which the SCN of a mutant hamster who had a daily period of 20 hours was reciprocally exchanged with the SCN from a wild type (WT) hamster (24hour period). Before transplantation, SCN lesions rendered each mouse behaviorally arrhythmic, revealing the necessity of the SCN for behavioral rhythms. Following SCN transplantation, the period length of the mouse was shown to be determined by the donor SCN. When the 20-hour mutant SCN was transplanted into the WT hamster, the WT hamster displayed a 20-hour behavioral period and vice versa. This proved that not only are circadian rhythms produced internally but that in mammals the daily period is determined by the SCN (1). In 1971, Ron Konopka and Seymour Benzer identified the first genetic locus in Drosophila that controlled circadian behavior by modifying the circadian period and thus named it the period (per) locus (2). A decade later, Young, Roshbash, and Hall (3) cloned the responsible per gene within the locus discovered by Konopka and Benzer. The groundbreaking discovery that a gene governed behavioral outputs and that it had health implications earned Young, Roshbash, and Hall

136 the Nobel Prize in Medicine or Physiology in 2017. Per is a generator of this 24-hour circadian rhythm, and mutations in the per gene disrupt this 24-hour cycle, extending it to 29 hours or shortening it to 19 hours (4, 5). This pioneering work launched the era of “clock genetics”. Chemical mutagenesis and positional cloning identified the genetic components of circadian clocks in flies. By the late 1990s, Joe Takahashi’s lab used forward genetic screens and positional cloning to identify the clock gene in mice (6). Circadian locomotor output cycles kaput (CLOCK)’s binding partner, Bmal1 (originally named Mop3) was identified in 1997 by John Hogenesch and colleagues (7) and Ikeda and Nomura (8). Together, CLOCKBMAL1 are core regulators of the positive transcriptional arm of the core circadian oscillator in all cells. The circadian field has expanded to explore the structure and the importance of the circadian system at the genetic, molecular, and network levels across many organisms. Too many scientists have made crucial contributions to the field to mention here, but I will highlight a few. Susan Golden, Carl Johnson, and Takao Kondo discovered the Kai complex as the molecular clock of bacteria. Amita Sehgal, (who was a postdoc with Michael Young and part of the team that discovered components of the molecular clock in Drosophila [fruit flies]), also did groundbreaking work in Drosophila to understand sleep and how the circadian clock regulates behavior. Carrie Partch has made huge strides in understanding the molecular structure of clock proteins in different functional states. John Hogenesch has made many contributions in addition to discovering Bmal1, such as identifying that about 43% of protein-coding genes have oscillations in their expression that are regulated by the circadian clock (9) and the importance of dosing time for medications (10). Charles Czeisler and colleagues (including Jeanne Duffy and Derk-Jan Dijk) paved the way in studying circadian rhythms in humans including the sensitivity of human circadian clocks to light (11) and the average daily period in humans (24.18 hours) (12). Louis Ptacek and Yi-Hui Fu identified circadian mutations in the human molecular clock that resulted in extreme sleep phases (13). A field that was rooted in curiosity has now been recognized for its physiological importance, and research has expanded to apply circadian interventions to improve health. Over the past decade, the importance of temporal eating patterns has emerged as an accessible circadian intervention. Multiple labs including Joseph Bass, Oren Froy, Satchidananda Panda, Courtney Peterson, Krista Varady, Frank Scheer, Marta Garaulet, Gerda Pot, and more have contributed to understanding the significance of the timing of eating. This includes the variation, phase, calorie distribution across the day, and duration of calorie intake (14). Specifically, time-restricted eating (TRE) has emerged as a popular dietary intervention to improve cardiometabolic health. TRE was based on the observation from Joseph Bass’s lab, that when mice were put on a high-fat diet (a typical protocol for diet-induced obesity), they also changed when they ate (15). Rather than consolidating food consumption to the night (when they are awake), they began to eat across the day as well (when they would normally be sleeping/at rest). This disrupted the daily rhythms of feeding and fasting. This finding inspired Satchidananda Panda’s lab to perform the simple but powerful experiment to restrict

Metabolism and Medicine the availability of the same high-fat diet to their night (normal eating time), i.e. time-restricted feeding (TRF). They found that TRF with the same macronutrients and caloric intake prevented weight gain and associated cardiometabolic health consequences such as fatty liver (16). Since then, TRF has been widely tested in rodents and fruit flies (17–19) and has shown widespread health benefits. Dr. Panda also developed a smartphone application called myCircadianClock to assess eating patterns and implement time-restricted eating in human populations. His team found that over 50% of adults have an eating window of 14.75 hours or more (20). TRE interventions of six to ten hours in humans have been found to be feasible and improve cardiometabolic health (weight, blood pressure, glucose regulation, and cholesterol) (20–26). These benefits have only been seen on a short timeframe (four weeks to one year) and clinical TRE interventions that have been published to date are mainly smaller pilot studies. Yet there are larger, much needed clinical trials underway internationally. Within the coming years, we are likely to gain great insight into how we can optimize our circadian rhythms to support overall health.

4.2 Introduction Clocks exist in virtually every cell of the body. Circadian clocks keep 24-hour time. Human physiology is governed by both central and peripheral circadian clocks that interact to maintain the homeostatic balance of vitals, nutrients, hormonal signaling, and metabolism across the day (9, 27). These clocks drive cell-autonomous circadian oscillators that can function independently. They are temporal housekeeping genes and allow cells, tissues, and organ systems to generate autonomous circadian rhythms. This allows for anticipation and coordination of cellular events which optimizes temporal expression and increases cellular efficiency. Disruption of circadian rhythms leads to adverse metabolic outcomes. Interestingly, each biological clock can have a slightly different period, so as to coordinate clocks throughout the body, there are multiple levels of networks. For instance, the master clock is the SCN, located in the anterior hypothalamus of the brain, is comprised of about 16,000–20,000 cells that communicate through both direct and indirect neural and paracrine signaling. The SCN then sends both direct and indirect neural and humoral signals outside of the SCN to coordinate rhythms throughout the body. These peripheral clocks also send signals back to the SCN. The SCN determines the period (day length) of the organism and is the main regulator of locomotor activity and sleep/ wake cycles. Although the SCN is sufficient to produce and maintain circadian rhythms independently, it also incorporates light to entrain (synchronize the internal period with the period of the environment). Activity and sleep patterns are commonly measured experimentally in animal models using wheel running or laser beam break assays, or in people using activity watches. Although peripheral clocks are coordinated by the SCN, they also respond to nutrient cues directly. Thus, the timing of calorie intake can directly override the temporal cues from the SCN in the periphery.

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All living systems are comprised of a system of cycles within cycles across many hierarchical scales. The fidelity of the cycle, that is the returning to a proximity of its starting point, is the ultimate parameter of the state of health as well as the rate of aging. The cycle is what defines biological time, like the cycle of a mechanical clock. Deviation from this cycle is tantamount to the aging process, and exaggerated deviation is a manifestation of premature aging and disease. When one process breaks down, so does the other because they represent inseparably entangled and dynamic parameters to the fabric of any living system. This ineluctable direction from order, information and complexity to randomness and entropy represents the arrow of time. We cannot inherently avoid movement through the cycle of time as a living system, but instead rely on the arrow of time to moderate our rate of deterioration. Maximum coherence and synchronicity of biological clocks at the organism level correspond to the maximum of the underlying fitness function for a human being.

4.3 Physical Time, Biological Time, and Physiological Aging Physical laws can and should be used to understand biology and medicine, two very important fields that are currently under exponential growth, but which don’t have their own laws and instead rely on empirical observations. In this section and throughout this chapter, we juxtapose physical and biological treatments of time and draw useful parallels between them to guide the reader’s understanding of sleep, metabolism, and physiological aging.

4.3.1 Physical Time Applied to Biology In physical terms, the arrow of time is a metaphor that signifies the unidirectional passage of time from the past through the present to the future. As described in detail in Volume 1 of this book, the arrow of time is marked by an increase in entropy with accompanying heat release. Entropy can stay the same or increase, but cannot decrease, thus leading to a perception of directional flow of time. Of course, time is not a material substance, only a relationship between events that is often linked to causality in the material world, which means that a cause must precede its effect and not the other way around. In biological terms, heat represents the inflammatory process accompanying redox stress that degrades the structure and function of biological systems and dysregulates the cycles that are the representation of time. This inflammatory process accelerates morbidity and aging (Figure 4.1). Time dilation is a concept proposed by Albert Einstein in his Special Theory of Relativity, which was discussed at some length in Volume I of this book. It refers to the difference in elapsed time when measured by two sources, and as we argued in this book it can also be correlated to the process of aging. The faster the aging process, the more dyssynchronous metabolism becomes. As we age, organizational complexity of biological and physiological dynamics declines (28) and the bioenergetic efficiencies involved in carrying out physiological processes deteriorate. With both age and disease progression, an ever-increasing

FIGURE 4.1  The rate of aging. Several important bidirectional relationships accelerate the pace of aging resulting in chronic diseases.

fraction of metabolic energy results in the formation of unusable energy (some of it stored as excess weight) or heat. All of this leads to the acceleration of life processes along the arrow of time. Human biology, which can be thought of as a system of systems, is faced with the exponentially increasing lack of coordination (decoherence) and an accompanied entropy production due to the dissipation of heat. This gradual disorganization of biology over time also underpins the degradation of biological structure from the level of genetic mutations to protein misfolding, cell damage, and organ failure. This emerging state of increased entropy and decreased communication metaphorically incinerates the living systems in accordance with the rise of entropy governed by the second law of thermodynamics, which asserts that no spontaneous physical process can lead to a decrease of the system’s entropy. Perfectly periodic processes do not generate entropy, and hence do not dissipate heat. Such synchronization for a complex system requires coherence and it is still a scientific mystery how biological coherence is achieved across many length- and time-scales. The second law of thermodynamics stipulates entropy growth for processes which are not perfectly

138 reversible. In human physiology, this is linked to structural and functional disorganization, at least partly due to the accumulation of reactive oxygen species causing oxidative damage, resulting from normal mitochondrial energy production. Eventually, pathological processes set in with inflammation, which in the chronic state leads to diseases of various types including cancer. The question that is of crucial importance in this context is: What causes accelerated aging and how can this be maximally slowed down? Based on the conclusions from the stress response discussion in Chapter 2, it can be concluded that the key factors in accelerated aging are chronic stress at a high level, dietary intake (including that which provides conditions for healthy gut microbiota), and proper synchronization of the molecular clocks by the circadian system. Circadian rhythms are natural, internal processes that regulate and carry out essential biological processes at various points over the 24-hour cycle. These circadian rhythms include many physiological processes such as body temperature and blood pressure that vary with a given periodicity within the daily cycle. These processes, as well as the metabolic cycles driven by the hormonal endocrine and autonomic systems, synchronize with the light/dark daily cycle. There are many hierarchical scales, from microscopic to macroscopic, that are coherently and synchronously integrated to orchestrate a biological system of cycles within cycles. These cycles lie at the core of the dynamic living systems, allowing homeostatic control that is also adaptive in response to specific environmental conditions. This resistance against the change of the homeostatic state of the complex adaptive living system can be understood as the resistance against the loss of lifespan. Loss of lifespan due to disease is linked to the accelerated entropy production. Entropy production in physical systems means dissipation of thermal energy, or heat. The biological equivalent of the notion of heat is the process of inflammation in tissues containing redox modifications that accompany the inflammatory process. Analogous to the randomness of molecular collisions that accompany the dissipation of heat in physical systems, redox modifications are a source of random chemical processes that are similarly inseparable from the process of inflammation in the body. To relate it back to physics, this process is also characterized by the loss of information since heat dissipated in random biochemical reactions removes the free energy that would be otherwise available to do useful work. As a consequence, homeostasis of the far-from-equilibrium metabolically active state is irreversibly altered. The resultant loss of biological efficiency adversely affects the biological system’s lifespan. The importance of circadian rhythms is at the foundation of the relatively novel scientific field of chronobiology and is now becoming highly recognized as to its importance in maintaining health. Molecular clocks mediate the timing of our metabolic function and hence human physiology synchronizing it with the 24-hour cycle of the Earth’s rotation around its own axis and the circadian rhythm of light–dark cycles. The synchrony of molecular clocks across all tissues is essential for the timely delivery of the right type of nutrient fuel for a given part of the body. For example, glucose is needed to fuel the brain and sufficient fatty acids are needed for the myocardium

Metabolism and Medicine throughout the 24-hour day, including fasting periods. When food is available during the normal active phase of the circadian cycle, it synergistically and powerfully synchronizes the peripheral circadian clocks with the central master clock in the brain. Metabolic efficiency is critical for healthy aging and is determined by quantity, quality, and timing of sleep and food. However, if nutrient availability only occurs during the night, when the body is expected to be at rest, and in contrast to lighting cues, it can lead to a misalignment of peripheral and central rhythms. Additionally, lower overnight metabolic rate and sleep deficiency leads to dampened biological rhythms throughout the body, disrupting both behavioral rhythms (such as the sleep–wake cycle) and physiology. The acceleration of aging may be understood as the stress response manifesting as physiological circadian misalignment with the extrinsically controlled normal sleep/wake cycle. The timing, quantity, and quality of dietary intake represents extrinsic control parameters for health and disease. A highfat diet influences many physiological systems including the central and peripheral circadian clocks. The main effect is the change in blood glucose, triglyceride and free fatty acid levels, resembling the state of the metabolic syndrome. Feeding induces the release of insulin into the bloodstream. Insulin, in turn, influences many organs and tissue, especially liver, adipose tissue, skeletal tissue and brain. On a practical level, shifting of dietary consumption from the majority of calories from the early part of the day to the evening and prior to bedtime results in desynchronized insulin secretory patterns in response to meals. In a nutshell, metabolic energy is essential to a human body but it must be delivered to the right place at the right time and in the right amount. Either oversupply or undersupply leads to dysregulation and when sustained over a long period of time could result in pathologies such organ failure or inflammation leading to metabolic disease, cardiovascular disease, Alzheimer’s disease, and sometimes to tumorigenesis. All chronic diseases can be related to redox disturbances, usable energy imbalance, and acid base imbalance. The aging process may be thought of as incineration of organismic complexity stemming from a gradual deterioration of the underlying structures of biological and physiological systems. Biological thermodynamics refers to the energy that is both transformed for useful purposes (first law of thermodynamics; Figure 4.2) and energy that is lost as heat. Hence, the cycles that represent time of a living system are metaphorical clocks in an interwoven fabric of space-time. This integrated structure-function is insidiously degraded as a process that moves from maximum organized complexity (i.e., thermodynamic disequilibrium, the state of optimum health) to increasing loss of complexity (i.e., thermodynamic equilibrium, the cessation of life). Inflammation in biological systems is a manifestation of excess heat production. Inflammation is inextricably parallel with redox disturbances and detrimental modification of cellular structures, leading to inefficiency and progressive desynchronization. The affected subcellular structures include nucleic acids (e.g. RNA, DNA), proteins (e.g. enzymes), and lipids (e.g. cell membranes). The associated loss of free energy to heat occurs at the expense of efficient metabolic processes (Figure 4.3). In a healthy state, this energy builds and supports

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FIGURE 4.2  Principle of the first law of thermodynamics. The first law of thermodynamics can be applied to both physical and biological engines. Its interpretation in both cases states that the total energy of a system (kinetic and potential) must be conserved. Energy can only be transformed in both types of systems but it cannot be destroyed or created. *ATP = adenosine triphosphate.

FIGURE 4.3  Free energy and entropy. Gibbs free energy is the energy associated with a chemical reaction that can be used to work i.e. maintain structure and function of biological systems. Loss of free energy as inflammatory heat increases entropy and is part of an aging process. *ΔF = free energy; ΔG = Gibbs free energy; ΔS = entropy.

and finally stop. It is emboldening that this process is malleable to some degree in a biological system. It stands to reason that the more efficient the energy production from our bioenergetic machinery the more synchronized the hierarchical scale of cycles and endogenous molecular clocks, and the slower in a relative sense the pace of biological time compared to chronological time. The more desynchronized and disorganized the system of cycles, the greater the entropy production rate (EPR) and the more divergently biological time moves relative to chronological time or aging. The main driver of circadian cycles is the endogenous clockwork, consisting of an interlocked feedback loop, which interacts with nuclear hormone receptors (NHR) and co-activators to regulate bioenergetic machinery.

4.3.2 Biological Time proper functions. This exponential rate of incineration that occurs over the course of time during aging in every individual underscores the relevance of the theory of special relativity in biology whereby the periodic nature of the ticking of a clock is lost as biological time accelerates with the progression of disease and deterioration of the state of health. Hence, time should be recognized as a fixed income that must be spent wisely. Moreover, because special relativity time is inflationary, we don’t have as much of it as we may think. To quote the popular song title recorded in 1949 by Guy Lombardo: “Enjoy yourself (It’s Later Than You Think)” (Decca Records, 1949). Absolute periodicity of the movements of the hands of a clock returning to the starting point repetitively at exactly the same interval of time is analogous to a perpetual motion machine. The friction of one object against another eventually brings the moving object to stop. Similarly, over time, the battery of a clock wears, causing the hands of the clock to slow,

Altering the response of biological systems in relation to geophysical time allows for the separation of mutually-incompatible events. Four main temporal structures characterize the manifestation of geophysical time on Earth: the tides (12.5 hours), the day (24 hours), the lunar month (28.5 days), and the year (365.25 days). By its very nature, biological time applies only to biological systems. Whereas physical systems are considered to be at a thermodynamic equilibrium, biological systems are never at homeostatic equilibrium. In fact, living systems by definition are far from thermodynamic equilibrium due to their constant external energy supply (nutrients) and subsequent conversion (metabolism). Time in a biological system, in contrast to a physical system, en route to its equilibrium state, can be measured in terms of progress through a particular cycle, or in terms of number of cycles elapsed (Table 4.1). The concept of biological time is rooted in the idea of cycles (e.g. circadian: ~24 hours such as sleep–wake and fast–feeding

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TABLE 4.1 Physical and Biological Time Physical Time In a thermodynamic equilibrium Physical systems exhibit perfect periodicity (e.g. atomic clocks) Time doesn’t apply to physical systems in equilibrium Metabolism has no effect on physical time

Biological Time Never in homeostatic equilibrium Biological systems are quasiperiodic (e.g. biological rhythms). Time applies to all biological systems Metabolism can affect biological time

FIGURE 4.5  Quantum metabolism versus classical metabolism. Quantum metabolism provides greater organizational complexity than classical metabolism. *ATP = adenosine triphosphate; EPR = entropy production rate.

FIGURE 4.4  Overview of cycles within circadian rhythm cycle. Within a circadian cycle, several biological cycles exist. Source: adapted from Cradewise, Inc (2020), https​:/​/cr​​adlew​​ise​.c​​om​/ bl​​og​/ bo​​dy​-cl​​ock​-c​​ircad​​​ian​r​​hythm​/.

cycles and the metabolic pathways that mediate them; infradian: longer than 24 hours such as a lunar cycle, menstrual cycle, annual cycles, etc., and ultradian: shorter than 24 hours such as breathing, pulse, heart rate, some hormonal secretions etc.) Biological cycles apply to all human physiology (and all living systems). Biological processes occur periodically, repetitively, and with small variations due to the inherently noisy nature of biological systems and environments. Physical systems exhibit perfect periodicity (e.g. atomic clocks) whereas biological systems exhibit quasi-periodicity, or irregular periodicity (e.g. biological rhythms). In biology, therefore, there are cycles within cycles but none of them are represented by a perfectly periodic time series (Figure 4.4). The systems’ robustness also allows for a degree of adaptability to the environment from the internally determined period, but also prevents a single environmental cue from completely disrupting the system. For example, we tend to go to bed around the same time each night, but if you stay up very late, or do not go to bed at all for a night, your internal sleep-cues will not be reset due to a single disruption. Time is only relevant to biological systems and not to physical systems in equilibrium. The distinguishing feature of living systems is metabolism. In fact, the presence of metabolism tells us whether an object is alive (i.e. a biological system) or dead (i.e. an inanimate system). We can slow biological aging by increasing metabolic rate and efficiency, but we cannot stop it. Higher metabolic rates correspond to the lower levels of reactive oxygen species (29). This is in accordance with

quantum metabolism that provides the greatest organizational complexity and interaction necessary for cognitive problemsolving and prolonged survival in a reduced entropic state (30) (Figure 4.5). For instance, human beings have the potential to affect their own physiology at the molecular and even quantum scale of biology. They provide the energetic input that enables work to be applied to promote maintenance of the biological state. This work includes active cell motility, ion and molecular transport, locomotion of motor proteins, biosynthetic reactions and signal transduction processes including biochemical, and electrical and mechanical signaling. Over the course of the physical human existence, organizational complexity deteriorates. The favorable bioenergetics to carry out life’s processes erode to unusable energy or heat. This can be seen as the acceleration of the arrow of time. Conversely, in order to slow the arrow of time and optimize psychophysiological health, maximum effort or energy input is required. When Einstein said, “Life is like riding a bicycle, you have to keep moving to keep from falling”, he was referring to his theory of special relativity. Time dilates, or slows down, relative to the energy you put into maintaining life. The more energy you put into it, the greater the amount of energy flows through biological chemistry to do work instead of losing energy to heat. Quantum phenomena, such as metabolic energy production or cognitive processes regulating emotion and physiology, maximally accommodate this reduced entropy state. In his first law of thermodynamics, Sir Isaac Newton stated that removing friction from an object is required to keep the object in motion. Objects remain stationary or continue moving at a constant velocity unless acted upon by an externally applied force. Friction slows down the motion of objects by generating heat. The collision between the constituent molecules of the object and the surface providing friction is the molecular basis of heat generation and hence increased temperature. At the molecular level, molecules collide, generate heat, and define temperature. Local generation of heat cannot be eliminated however, because the second law of thermodynamics defines the arrow of time (see Volume 1). Zero heat generation only occurs in reversible physical processes and life does not qualify. Moreover, our body needs to generate heat to maintain the

The Biology of Time proper functioning of many catalytic reactions. As explained in the thermodynamics chapter of Volume 1, every heat engine operates at a less than 100% efficiency. Viewing the human body from a thermodynamic perspective, our body temperature is different from that of the environment. That fact alone indicates that our body’s thermodynamic efficiency is less than 100%. This difference amounts to heat dissipated into the environment and waste products excreted through our bodily functions, as a byproduct of simply being alive. The consequence of this simple observation is entropy increase, a natural process that is accompanied with material structural and consequent degradation with associated loss of heat into the atmosphere. Over time, there is a dispersion of particles and associated heat, homogeneously distributed over the available space. An example of this is any biological system, such as a human being, which decomposes to its most elemental parts, returned to the atmosphere and entropy of the universe. Entropy increase degrades all structures over time by a tendency to equilibrate or redistribute material system concentrations over the available space entirely in agreement with the second law of thermodynamics (31). While living systems slow down the arrow of time by producing metabolic cycles when using nutritional energy for their functions, they do not stop, let alone reverse the arrow of time (see Volume 1 for more information on the arrow of time). Only work supplied by an external source can overcome or partially reverse this trend. A biological consequence of this statement is that metabolic energy is necessary to maintain biological structure and function. Not only is metabolic energy essential, but it must be delivered to the right place at the right time and in the right amount. Hence, living systems define their own arrow of time with its inescapable companion, eventual death. Science-fiction and mythology-inspired ideas about reversing aging or finding “a fountain of youth” while attractive to the aging population stand in direct contradiction to the science of metabolism and thermodynamic laws.

WHY ARE CIRCADIAN RHYTHMS ESSENTIAL TO HEALTH? The circadian system coordinates behavior, physiology, and individual cell function. Simply, it keeps everything in the right place, at the right time, doing the right thing. First, the circadian system is anticipatory. It prepares the body for what it will need a few hours in the future. For instance, there is a peak of cortisol upon waking, Melatonin is increased at night to help you fall asleep and to regulate glucose throughout the night while your body if fasting, enzymes are produced when your body expects you to eat, alertness oscillates throughout the day, and sleep is consolidated into one bout. Second, the circadian system prevents incompatible events from occurring at the same time. Such as the release of insulin (to store energy) and glycogen (to breakdown energy), and hunger and insulin resistance/ melatonin.

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Finally, the circadian system coordinates your internal clocks with your environment. 1) It aligns your sleep–wake cycle with light, temperature, and for animals in the wild, predator avoidance. 2) It coordinates behavioral (activity, eating, alertness, etc.) patterns of all living organism including bacteria, plants, and animals (humans included). In seasonally reproductive animals, biological clocks also track the time of year, and based on light, preemptively start the six-to-eight-week process to shut down the male reproductive system so they do not reproduce in the winter when there aren’t enough nutrients to sustain the gestation and feed the pups.

Human health is a living biological system. Therefore, it is critical to consider the fundamental notion of time because health, aging, and longevity are maximal when time is linked to cyclical processes. Cyclicity in physics is related to periodic motion, which is characterized by momentum. One iconic example of cyclical processes in physics is the harmonic oscillator. The pendulum is a mechanical example of a harmonic oscillator. Another example is the Earth orbiting around the Sun. In this case, the rotating object is endowed with a physical property called angular momentum. Angular momentum is defined as the product of angular velocity and the moment of inertia of a rotating object. This is analogous to linear momentum being defined by the product of mass and velocity. Newton’s first law of motion also applies to rotating objects. Unless opposed by a torque, a rotating object will continue in its cyclical motion, which is an expression of the conservation of angular momentum. This can be related to the core of Einstein’s quote, “Life is like riding a bicycle, you have to keep on moving to keep from falling”. In the case of riding a bicycle, the opposing torque is given by the friction of the ground acting on the tires that reduce the angular momentum, and hence, decelerate the angular velocity of the wheels. Life is composed of many cycles of different duration: daily cycles, weekly cycles, monthly cycles, annual cycles, and decades of life, all of which need a kind of torque, or rotational force, to maintain our physical, mental and emotional stability. An active torque consists of proper nutrition, exercise, emotional support, intellectual engagement, social involvement, etc. Disease, poor diet, stress, financial and emotional hardship are all part of life but these things, like an opposing torque, exert a friction force on our daily, weekly and annual cycles. Either oversupply or undersupply of bioenergetics leads to dysregulation and when sustained over a long period of time could result in pathologies such as organ failure or inflammation leading to metabolic disease, cardiovascular disease (CVD), Alzheimer's, and sometimes to tumorigenesis (see Volume 1). Human disease inextricably includes a breakdown in the temporal organization that orchestrates physiological processes. An orchestra needs a conductor that defines the rate at which a piece of music is played by the ensemble of musicians. The timekeeping performed by a conductor can be viewed as similar to a pacemaker, or clock. We may consider biological clocks as molecular timekeepers present in virtually all cells

142 across different tissues of the body, including the brain. If these biological clocks are tuned and synchronized (maintaining a proper phase relationship, not necessarily all in the same phase) with one another, the passage of time is reflected in an almost perfectly cyclical repetition of biochemical processes at a cellular level. These internal clocks are present in almost every cell, but the ability of the organism to produce biological rhythms requires multiple levels of coordination. To keep clocks in the correct phase relationship, there is a master clock in the brain, the suprachiasmatic nucleus (SCN) of the hypothalamus, that sets the period (the time elapsed for an entire cycle) of the organism and coordinates biological rhythms throughout the body through a variety of still poorly defined neural and humoral cues. Even within the SCN, there is complex coordination between neural networks and astrocytes in order to maintain robust rhythmic output. Additionally, organ systems feedback on each other as a regulatory mechanism, adding an additional layer of complexity. All of these mechanisms are able to maintain circadian rhythmicity even in the absence of external cues. However, except in defined laboratory conditions, animals are exposed to a myriad of external cues, such as changing light–dark cycles, that can reset the internal system. This allows an organism to adjust their internal biology so as to be optimal for alterations in environmental conditions. Health and disease are mediated through intrinsic control parameters including time, biological cycles, the stress response, diet, and the microbiome. The interwoven nature of these crucial factors in the onset of pathology is seen through molecular mechanisms as they drive inflammation by causing an oxidative modification of organic compounds. Accordingly, each of these control parameters causes further disturbances in the others in a vicious self-amplifying feedback loop. For example, the prolonged stress response in the human body alters circadian timing, as well as diet and microbiota, which occurs reciprocally in all directions leading to the nonlinear compounding of detrimental effects on health. The neuroendocrine and autonomic nervous systems rooted in the hypothalamus mediate allostasis but if prolonged, allostatic overload ensues and disturbs the homeostasis of redox and free energy, which are the fundamental basis for how the above control parameters translate to disease. To be able to disentangle this complex web of interactions, we propose to use the concept of a fitness landscape. In a fitness landscape, external control parameters (such as caloric intake, amount and intensity of physical exercise, or dose of a pharmacological agent) are quantified and represented as axes of the coordinate system and the vertical axis maps the fitness function of the human body measured in response to these control parameters (Figure 4.6). Valleys in the multi-dimensional surface constructed from stress response data correspond to parameter regions of stability whereas peaks and ridges delineate boundaries between these areas of stability. For example, these areas can refer to optimal health, a pre-diabetic state, and a fully-developed disease state. However, it is important to stress that virtually all chronic diseases of aging have the same external control parameters in common, hence instead of the fragmented approach to diagnostics and therapeutics of aging processes,

Metabolism and Medicine

FIGURE 4.6  Physiological Fitness Landscape. Control parameters, (such as caloric intake, amount and intensity of physical exercise, or dose of a pharmacological agent) fitness function of the human body are quantified and plotted. Valleys correspond to regions of stability whereas peaks and ridges delineate boundaries between these areas of stability.

a common framework should be developed. A final continuous downward sloping area describes an irreversible transition to the person’s terminal state. Elsewhere in the book we have given numerous examples of such fitness landscapes. In this chapter, we specifically refer to the three critical aspects that have been somewhat on the periphery of modern medical interventions until now: chronophysiology, microbiota, and prolonged stress. Recent advances in understanding how these factors crucially affect our health are gradually bringing these topics into the mainstream of medical research. We hope that this book will contribute to an increased appreciation of these aspects by both researchers and clinicians (Figure 4.7).

4.3.3 Measuring Time We are all aware of the passage of time. We also experience the subjective, often circumstantial, rate of time passage. Time appears to flow slowly when we are bored with nothing to do or don’t like what we are doing. However, it seems to race feverishly forward when we are facing a looming deadline or enjoying ourselves. Nowadays, there are extremely precise ways to measure time. Electronic, or even subatomic, processes are used to accurately and precisely measure time. Mechanical clocks are timekeeping instruments made up of physical oscillators. The wheels, cogs, springs and gears are engineered to maintain a constant rate at which the clock’s hands move around the dial. The ticking of a clock, typically at one tick per second, is the essential characteristic that defines its rate. Biological processes also require timekeeping mechanisms. Time is measured internally by endogenous biological clocks because biological processes require periodicity of biochemical reactions. Biological clocks (e.g. menstrual cycle, hibernation, seasonal, circadian, etc.) are evolutionarily conserved endogenous timekeeping systems with their own molecular machinery (33). This timekeeping mechanism couples an

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FIGURE 4.7  Organization of the circadian clockwork in humans. Light acts as the major entrainment cue for the central pacemaker in the SCN, the timing of which can adjust by up to 1 hour each day in response to altered light cycles. By communication with other brain clocks and clocks in the periphery, using mechanisms including hormonal signaling, the autonomic nervous system and control of rhythmic behaviors, the SCN sets the internal rhythm of the organism. Clocks in peripheral tissues control key aspects of daily metabolic function, the outcome of which is in the healthy state is homeostatic control of energy and redox homeostasis. Entrainment agents may act on brain or peripheral tissue clocks, with timing of food availability having been demonstrated as a potent zeitgeber for peripheral clocks, with peripheral rhythms entraining to the timing of feeding-fasting cycles, whilst the central clock remains unaffected. Source: adapted from (32). *ANS = autonomic nervous system.

organism’s nutrient intake, storage and catabolism to meet synchronously the bioenergetic demands of physiology that are essential for species survival. In all cases, both physical and biological, the process of measuring time involves comparison to a known time interval. Even the ancient Egyptians or Romans relied on it when they used sundial or hourglass, respectively, to measure the passage of time and the unit of time used for comparison was one day. The day became subdivided into 24 hours, each hour into 60 minutes, and each minute into 60 seconds. Today, physicists use atomic clocks to measure time with amazing precision. Although our society relies on synchronizing time for all of its citizens so it can operate efficiently and in a coordinated fashion, at a personal level, we all have our own perception of the rate of time flow, which is dictated by our life’s goals and the stage in life we are at. Hence, in a sense, it is meaningless when time is synchronized and moving at the same rate for everyone because we all feel it differently (see Volume 1). There is some solid physical basis for this perception. It has been demonstrated that time does move slower for astronauts in space, however only by tiny fractions of seconds due to the effects of gravitational fields on the body as elaborated on in Einstein’s theory of general relativity. However, Einstein’s theory of special relativity makes a more important and easily testable impact on the flow of time since it defines a time dilation as a function of the speed at which an object or a person is moving. As argued earlier in this book, the special theory of

relativity can also be applied to biological aging. We have posited that it should have a much greater, substantive and even fundamental universal influence on the aging process, which is related to the speed of biological processes and their synchronization across the human body. Einstein has been quoted to say that “life is like riding a bicycle, you have to keep moving to keep from falling”. This quote may have been intended at several different levels. On the one hand, it refers to the resilience necessary against adversity as a force to maintain balance. On a more fundamental level consistent with his theory of special relativity, it may refer to the cycle of time that turns like the chainrings of a bicycle. One of the lessons of Special Relativity is that time as an absolute quantity does not exist in a non-biological sense. However, in a biological system such as a human being, the faster the metabolic cycle of ATP, the slower the progression of time and the resultant aging process. Metabolic energy production here is understood in the special sense of quantum metabolism, which is more efficient than its classical counterpart. This means that the more energy is produced per unit time, the slower time moves per unit of energy produced in a reverse relationship between time and energy. Less energy wasted in the process keeps the chain of cycles away from the destructive effects of the arrow of time. It is important to point out that in biological systems, periodic processes (cycles) are superimposed on the linear processes (arrow of time). In cyclic processes, the system keeps

144 returning to the same states after each period of the cycle. Hence, there is no “aging” and no entropy production. Linear processes advance through time as they dissipate energy, creating entropy. The greater the linear component, the faster the aging process and the system’s degradation. In other words, cyclicity prolongs the longevity of the living system, which is characterized by a reduced state of entropy. This prevents the system from undergoing a transition to one in which entropy rises along a linear path in parallel with the arrow of time (Figure 4.8). A phase transition into a process that lacks periodicity and only follows a linear path occurs at the time of death. During the period between death and thermodynamic equilibrium, the increase in entropy is no longer circular but rather approaches linear. Biological aging accelerates in parallel with the degradation of a coherent and synchronized nature of biological and physiological cycles. This represents an intermediate state between optimum health and death and is a susceptibility state to chronic disease. The moving chainring of a bicycle is necessary to keep the bike in motion and is hence metaphorically appropriate to the maintenance of a healthy physiological state. The two inferences of Einstein’s quote described above are not mutually exclusive. Resilience, which increases in all living systems as a consequence of surmountable stressors, equates to increased thresholds for handling subsequent stressors. Improved stress response equates to a faster metabolic rate in the sense of time efficiency and thus a slower aging process.

4.4 Biological Clocks, Metabolism, and ATP Metabolic cycles are the basis of living systems—this is most fundamental to understanding health and disease. Metabolism is essential for life to exist and begins at the successful acquisition of food. In humans and other animals, the brain is critical in the development of sensory, cognitive, and other phenotypic traits that enhance the successful acquisition of food. In plants, the quantum processes of solar nuclear fusion and fission, and of photosynthesis in chlorophyll to nutrient fuels are the essential prerequisites for human and all animal life to exist. The transformation of energy harnessed in the hydrocarbon bonds

Metabolism and Medicine of these nutrients into the biological currency of energy— ATP—is the manifestation of the first law of thermodynamics that provides the means to achieve the goal of life in a physical universe. Infrared heat released from the unstable bonds of ATP is utilized to do biological work, purposed to maintain the homeostasis of vital organ systems. The end product of the arrow of time is total entropy, or randomness. This is an equilibrium state with no usable energy and the absence of organized structure and function. In contrast, living systems have exquisite organizational complexity, defined as a farfrom-equilibrium state. Time and metabolism are intricately linked. In metabolism, time defines the rate of conversion of substrates into products. Molecular clocks epitomize the notion of time in biological systems. The more tightly connected the molecular “timepieces”, the more synchronous the dynamic organization of energy production and the more efficient the utilization of that energy into the work of physiological processes. On the other hand, the degradation of the physical structure and function of those clocks equate to the loss of ample synchronicity of time coordinated at both micro- and macro-scales of bio-physiology. A cycle is represented by a circle that returns to a starting point with a defined temporal periodicity. A cycle is the time organizing strategy of living systems. It requires energy and is the teleological purpose of metabolism. If the physical universe is defined by the arrow of time, consistent with the second law of thermodynamics (the progressive dissipation of heat and rising entropy), then a cycle represents the strategic goal of resisting this fundamental force of nature. The separation from the initial starting point over time is the aging process, and the rate of aging is the entropy production rate (EPR). Systems of cycles, and cycles within cycles are arranged four dimensionally, across time and space, providing the necessary resilience against the forces of entropy to slow down the metaphorical arrow of time. Biological cycles may be designated as circadian (approximately 24 hours), ultradian (less than 24 hours), or infradian (longer than 24 hours). The metabolic cycle of ATP energy production (see Volume I) provides the currency for doing the work of maintaining all cycles. These include the spatially most microscopic biological

FIGURE 4.8  Cyclicity prolongs the longevity of the living system. In this figure, we will use the analogy of a car driving on a track where the length of the track along the x-axis represents time. A) Cyclic process is represented by driving on a circular track, no net entropy production can drive on it forever. B) Linear process is represented by diving on a straight track. In this case, you will very quickly produce energy, but will run out of time quickly. C) Cyclical processes embedded in a linear process are represented by driving from one circular track to the next. Entropy is still produced, but the lengthened track along the x-axis slows down entropy production.

The Biology of Time chemistry occurring on the scale of microseconds and less, to longer time scales such as approximately one second for the cardiac contraction that produces the heart rate, and ultimately the life–death cycle. Notably, transcriptional cycles occur at approximately 80-minute intervals, which promote the synthesis of proteins, including those that form the endogenous core clock components. These timepieces are the generators of circadian, and consequently, infradian metabolism, and physiology. The highest frequency cycle time (fastest, occupying the shortest period) is that of producing a single molecule, or quantum, of ATP. It is worth noting that there is a subtle but important difference between the definition of the metabolic rate used by clinicians and used in the context of quantum metabolism. Clinicians equate high metabolic rate with, for example hyperthyroidism, with high oxidative stress. Therefore, it can be fairly precisely measured by the rate of oxygen consumption, although this is only linked to oxidative phosphorylation and does not account for the glycolytic mode of ATP production (Figure 4.9). For example, parameters such as VO2 max or VO2 submax liters of O2 consumed per kilogram bodyweight per minute are used as a measure of fitness in athletes. Hence, we believe they can be introduced as the fundamental orders and control parameters to quantify susceptibility disease states within the fitness landscape model. We can also make a case for connecting the reciprocally related insulin resistance and mitochondrial dysfunction with impaired VO2 max. This is premised on the loss of metabolic efficiency as fundamental to senescence and chronic disease with metabolism being the distinguishing feature of living systems and also metabolic efficiency being a measure of physical fitness. On the other hand, in the physical theory of quantum metabolism, it is differently defined as turnover of a unit of substrate per unit of usable energy per unit time making it directly related to the caloric intake. In the former case, it is not defined as the rate of efficiently used energy production but rather the amount of energy lost as heat.

FIGURE 4.9  ATP production. ATP production via glycolysis, the Citric Acid (Krebs) Cycle and the electron transport chain. Source: adapted from (34). *ATP = adenosine triphosphate.

145 Mitochondrial health and insulin sensitivity is foundational. Hence, the distinguishing feature of living systems (as long as they are alive) is metabolism. Conversely, temperature is a constant parameter for most biological systems while it greatly affects physical systems when it changes, including phase transitions occurring when the temperature approaches the critical point. Metabolism tells us whether a system is alive, since a biological system is entirely dependent on metabolism for survival, versus a dead or an inanimate system that either does not need or perform metabolic activity. We can slow biological aging by increasing metabolic rate and efficiency but we cannot stop it. Perhaps this is one of the many reasons why we humans can never achieve immortality, in spite of the fanciful pronouncements of the proponents of transhumanism and fervent believers in the power of nanotechnology. Maximal metabolic rate and efficiency parallel the minimum reactive oxygen species generation beyond that which is useful physiologically. This is in accordance with quantum metabolism, that provides the greatest organizational complexity and interactions between neuronal components, which are necessary for cognitive problem solving and prolonged survival in a reduced entropic state. Human beings do have the potential to affect this physiology at the molecular and even quantum scale of biology by providing the energetic input that allows this work to be applied to promote this biological state. This work includes active ion and molecular transport, locomotion, and cell motility achieved through the use of motor proteins, biosynthetic reactions, and signal transduction processes. Arguably, metabolism is the key property that distinguishes living systems from inanimate ones. Hence, time as a relative quantity is captured in cycles and hierarchical systems of cycles within the larger living organismic system. The hands of the clock serve the inextricable and dual purpose of regulating energy balance and reaching the far-from-equilibrium state that defines the direction of time. Hence, circadian cycles regulated by clock genes and their transcribed proteins are tightly coupled to metabolic cycles (35), including the most fundamental cycle of substrate-to-ATP production, which determines synchronicity. The redox disturbance generated at the level of this higher frequency, more fundamental cycle can disturb the correlated nature of the innate oscillators across cells of different tissues. This is often a function of energy excess that exceeds the “take-over threshold” of the electroncarrying capacity of the oxidative phosphorylation electron transport chain mode of energy production. This threshold is surpassed when the β scaling exponent of the allometric scaling law relating metabolic rate to body size changes and the metabolic mode of energy production moves from the highly efficient quantum metabolism regime to the less efficient classical mode. Alternatively, redox disturbance may be generated at the more macroscopic scale of biology with a slower cycling frequency such as the transcription of nucleic acids or translation of proteins. This is fundamentally rooted in the prolonged allostatic overload of the stress response and the resultant pro-inflammatory response mediated or potentiated by the development of pathogenic microbiota. This, in turn, disturbs mitochondrial structure and function intertwined in a feedforward process of inflammation, redox disturbance, and energy

146 lost to unusable heat. A state of health protects the quantum metabolic mode of energy production from de-coherence of its quantum wave functions, which are exquisitely sensitive to heat. Cyclical processes manifested in living systems are not only epitomized in the machinery of core molecular clocks present in the cells of the body as parameters of time, but the metabolic cycle of ATP production is the generator of biological time. The more efficient the production of energy, the more coherent or synchronized the work performed by the energy produced, including the work of running the timepieces of the molecular oscillations themselves. Moreover, the level of efficiency of energy production and correlation of that energy used to do biological work parallels the extent of the robustness of biological complexity, and, accordingly, the stronger the parameter of time which is a distinctive feature of life. Time runs slowest in the context of maximum physiological health, and in the sense that metabolic rate is lower (metabolic rate = α × weightβ with a β scaling exponent of ¾) when in the quantum mode of energy production, that is, quantum metabolism, but higher and with a higher frequency cycle time when averaged out per quanta of ATP per unit mass per unit time. Metabolic efficiency in the quantum mode of energy production per quanta of ATP per unit mass is greater than in the classical mode. In this former case, time is maximally dilated and biological aging is relatively slow in contrast to the case of declining physiological health. In the latter case, metabolic cycles of energy production are in the classical regime whereby the β scaling exponent is one, or isometry, which means the metabolic time runs faster but with a slower frequency cycle time per quanta of ATP per unit mass per unit time, and with lower metabolic efficiency. Mitochondrial biogenesis and oxidative aerobic metabolism are most characteristic during the nocturnal fasting phase of the daily cycle. Non-oxidative glycolytic metabolism is more characteristic of the feeding and active phase of the daily cycle. The impairment of mitochondrial structure and function, inseparably and bidirectionally linked to insulin sensitivity, leads to mitochondrial dysfunction and insulin resistance that represents the core and sine qua non of accelerated pace of biological aging relative to chronological aging and premature chronic diseases of aging. Physiologically optimal levels of reactive oxygen species generated along the mitochondrial electron transport chain prevent the inflammation induced by oxidative stress. Thus, inflammatory production of heat that causes the collapse of quantum interactions is abrogated. Accordingly, the associated entropy production rate that occurs on a biological scale is minimized. The physical property of entropy can be equated to redox in biological terms as abnormal modifications of cell molecules. Therefore, physiologically optimal redox allows a maximally reduced state of entropy characterized by preserved organizational complexity. Crucial to this is the notion that quantum interactions provide a synchronized and coherent state of physiology. This is underpinned by a quantum metabolic state of ATP production, the most fundamental cycle of any biological system defined as a system of cycles within cycles. Maximal metabolic rate in this case should be understood in a special correlated sense tantamount to energy

Metabolism and Medicine produced per unit time per unit mass transformed to useful biological work. The classical mode of ATP production is continuous and rapid on a local scale. By distinction, the effects of energy produced in the quantum regime are nonlocal and more efficient. Hence, less ATP production is required, and, in parallel, excessive oxidative species production does not occur. It follows that the organizationally complex and adaptive systems are maintained. This allows for such things as optimal cognitive functioning and prolonged survival (36). The overarching theme of cyclical processes in living systems is to maintain a far-from-equilibrium, complex, adaptive state. The endocrine and nervous systems are unique and crucial for integrating the various functions of the structurally different tissues and organ systems of the body into an organismic whole. Cycles at many spatial and corresponding temporal scales are the evolutionary design at the most basic level intended to capture and sustain the information of the living state. That is, they mount resilience against the forces favoring the generation of positive entropy, which degrades the structural and functional organization of the living system. As these cycles degrade over time, they incinerate and move living complex adaptive systems, such as a human being, away from the far-from-equilibrium state toward thermodynamic equilibrium. In parallel, time itself dissipates away from the cycles that maintain mortal life to the physical universe of which it becomes a part. During this transition from biological to physical state, time, which is a relative but the fundamental quality of the living state, is lost. The relative nature of time is inextricably linked to the cycles embodied within the living systems. The robustness and coordinated synchronicity of these cycles diminishes, and so does biological time. This is the hallmark and signature of aging, and chronic diseases of aging are its manifestations. Maximum health generally peaks at around age 30, after which it gradually deteriorates. The notion of cycles gives new meaning to the process of aging and to optimum health. As will be discussed at length below, the perfect periodicity of biological cycles highlights this optimal health and the associated circularity of time without entropy production. Entropy production, on the other hand, introduces an axis of time, which can be seen as a linearity of time associated with aging. The conceptual design of cycles is that of periodicity. Each turn of a process returns to where it was initially. The inherent nature of these “turns” defines both the health and resilience of the living system as well as fidelity to the process of time itself. Absolute synchronicity of the automated cyclical processes coordinated by the endocrine and autonomic nervous systems organism-wide is tantamount to a biological perpetual motion “machine”. This is a theoretical construct that is intriguing and tantalizing because it is impossible. Such a living or physical system would defy the second law of thermodynamics. The closest we can come to a practical and tangible strategy for slowing the aging process is by protecting or restoring the quantum metabolism mode of energy production. Quantum metabolism is the correlated or coherent production of ATP currency that mediates the work of cell biology and physiology. This work is rooted in the cyclical processes across temporal and spatial hierarchical scales. This quantum mode of energy production involves a wave

The Biology of Time function that can be conceptualized as a bioenergetic glue holding together dynamic processes over the course of time. The quantum wave function is the same physical idea introduced here to biology that has already been implemented in the design of quantum computer algorithms. Critically, these quantum effects are highly sensitive to heat, which causes collapse or decoherence of the wave function and highlights the enormous cryogenic requirements of quantum computers to maintain functional efficiency in view of the ubiquitous thermal noise. Analogously, in biological systems, heat is generated by inflammation, which is reciprocally tightly coupled to the process of redox disturbance with detrimental oxidative modifications of molecular structures, including the bioenergetic machinery of mitochondria and the protein and DNA components of endogenous molecular clocks. This also affects the structures of the clock-controlled outputs responsible for orchestrating or coordinating synchronous activities of metabolism, growth, reproduction, cell replication, and tissue repair that underpin healthy circadian behavior and physiology. The endogenous molecular clocks present in virtually all cells of the body are biological manifestations of cycles. These clocks are actually simple and elegant molecular designs that control the genetic output of the essential functions of metabolism and related processes. The coherent or synchronous nature of these biological clocks (coherence is a correlated relationship of wave functions, classical or quantum, whereas synchronous implies more specifically that these wave functions are superimposable in time) temporally and spatially. This is a crucial and indispensable requirement of the maximally healthy state that unleashes the potential of quantum metabolism. When one process breaks down, so does the other because they represent inseparably entangled and dynamic parameters to the fabric of any living system. Maximum coherence and synchronicity of biological clocks at the organism level correspond to the maximum of the underlying fitness function for a human being. This can be reflected by metabolic efficiency and metabolic rate according to the allometric scaling laws in the special sense of quantum metabolism. Accordingly, this underpins maximum available free energy (specifically Gibbs free energy) that can be utilized to do the work of cell biology and physiology. In the context of the physiological fitness landscape, control parameters promote the greatest metabolic efficiency.

147 Domain Protein 2) and Brain and Muscle ARNT-like Protein 1 (ARNTL; more commonly referred to as, BMAL1), which comprise the positive arm of the TTFL. CLOCK and BMAL1 are transcription factors with a basic-helix-loop-helix domain (bHLH)-PER-ARNT-SIM (PAS). A bHLH structure is formed when two proteins (each with their own alpha helices) dimerize. It is an important functional component of many transcription factors. The structure is two alpha helices connected by a loop, hence the name. The CLOCK-BMAL1 heterodimer is an example. The bHLH enables protein binding and creates a unique functional component of the dimer. Proteins can form both homodimers and heterodimers, each with unique functions. Typically, bHLH structures bind to an E-box, which regulates the transcription of other genes. Some dimers, such as CLOCK-BMAL also contain a PAS domain (bHLH-PAS family of proteins) which can bind to other palindromic sequences similar to E-boxes for other forms of genetic regulation. CLOCK and BMAL1 form a heterodimer and bind to regulatory elements containing enhancer boxes (E-boxes) within the promoters of downstream target genes. These target genes include repressors of the CLOCK/BMAL function, the period (per1-3) and cryptochrome (cry1,2) genes, which comprise the negative arm of the TTFL (Figure 4.10). Translation of PERs (PER1, PER2, PER3) and CRYs (CRY1, CRY2) occurs in the cytoplasm where they form complexes and are actively transported into the nucleus in a large complex through importin beta (encoded by karyopherin subunit beta 1 (KPNB1) gene) (37). In the nucleus, the PER/CRY repressive complexes

4.5 Molecular Clocks Keep Biological Time Molecular clocks mediate the timing of physiology over the 24-hour day. They are found in all living organisms including cyanobacteria, plants, and animals. Just as the wheels, cogs, springs, and gears of a mechanical clock keep precise time, the core machinery of the circadian clock exploits an interlocked transcriptional-translational feedback loop (TTFL) to keep molecular time in the body. The molecular clock is a transcriptional-translational feedback loop (TTFL) consisting of two main arms: the positive regulatory elements that promote transcription and the negative protein products that suppress transcription. The mammalian core activation loop has two key transcriptional activators, CLOCK (and its homolog NPAS2; Neuronal PER-ARNT-SIM

FIGURE 4.10  CLOCK-BMAL1 complex. The CLOCK-BMAL1 complex activates Per and Cry transcription. The Per-Cry complex regulates the CLOCK-BMAL1 complex as a feedback mechanism. Source: adapted from (38). *BMAL1 = brain and muscle Arnt-like protein-1; CLOCK = circadian locomotor output cycles kaput; Cry = cryptochrome circadian regulator gene; CRY = cryptochrome circadian regulator; E-box = enhancer box; Per = period circadian regulator gene; PER = period circadian regulator.

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FIGURE 4.11  CLOCK-BMAL1 and PER-CRY regulation. Negative feedback at E-box target genes regulated CLOCK-BMAL1. Source: adapted from (40). *BMAL1 = brain and muscle Arnt-like protein-1; CLOCK = circadian locomotor output cycles kaput; CRY = cryptochrome circadian regulator; E-box = enhancer box; PER = period circadian regulator.

repress CLOCK-BMAL1 complex transcription at E-boxes and thus shut down their transcription. Timed degradation of molecular clock proteins is tightly regulated and is one mechanism to determine the period of the molecular clock (39). The PER and CRY proteins are phosphorylated by kinases (DYRK1a (dual-specificity tyrosinephosphorylated and regulated kinase 1A), GSK3B (glycogen synthase kinase 3β), CSNK1e (Casein kinase Iε), CSKN1d (Casein kinase Iδ)). PERs, nuclear CRY, and cytoplasmic CRY proteins are targeted for proteasomal degradation by proteins BTRCP1/2 (beta-transducin repeat containing 1/2), FBXL3 (F-Box and leucine-rich repeat protein 3), and FBXL21 (F-Box and leucine-rich repeat protein 21), respectively. In turn, degradation of the repressor complex relieves negative feedback repression at E-box target genes and CLOCK-BMAL1 can begin a new transcriptional cycle (Figure 4.11). In humans, mutations in core clock and related genes (PER2, PER3, CRY1, CRY2 CSNK1E, CSNK1D, and DEC2 [differentiated embryonic chondrocyte gene 2]) lead to changes in sleep phase, diurnality, sleep duration, and nuclear response to sleep-deprivation. In several examples of familial advanced sleep phase syndrome (FASPS), mutations often disrupt the phosphorylation-dependent degradation of PERs and CRYs. For example, a mutation in PER2 disrupts the CSKN1E phosphorylation site (41), a mutation in CSNK1D significantly reduces kinase activity (42), and a missense mutation within the flavin adenine dinucleotide (FAD)-binding site of CRY2 increases the binding affinity for its E3-ubiquitin ligase, FBXL3 (13). While in delayed sleep phase disorder (DSPD), mutations in CRY1 contribute to localization defects that enhance transcriptional repression (43). Other transcriptional regulatory loops fine-tune the robustness of the circadian clock. The first loop consists of another class of clock-controlled transcriptional activators called retinoic-related orphan receptors (RORs) as well as repressors part of the nuclear hormone receptor family (Rev-erbs) that bind Rev-erb response elements (RREs) within the BMAL1 promoter (Figure 4.12). Therefore, BMAL1 transcription is also clock controlled.

Metabolism and Medicine

FIGURE 4.12  ROR induces BMAL1 activation. While ROR-induced BMAL1 activation, Rev-erb inhibits BMAL1 instead. Source: adapted from (44). *BMAL1 = brain and muscle Arnt-like protein-1; CLOCK = circadian locomotor output cycles kaput; E-box = enhancer box; RORα = retinoid-related orphan receptor α.

This same RRE loop regulates gene expression of the destruction box (D-box) transcriptional repressor, NFIL3 (nuclear factor interleukin 3, also known as E4BP4). In the second transcriptional loop, NFIL3 competes with the transcriptional activator DBP (D-site albumin promoter binding protein), a canonical E-box target and PAR bZIP (proline- and acid-rich subfamily of basic region leucine-zipper) transcription factor family member, to regulate D-box target gene expression, including the RORs. Other bHLH transcription factor family members, such as DEC1/2, further regulate the molecular machinery through direct interactions with BMAL1. CIART (circadian-associated transcriptional repressor; also known as CHRONO) can also directly interact with BMAL1 and functionally repress molecular rhythms independent of the CRYs (45, 46). These integrated transcriptional regulatory loops, in conjunction with the core transcriptional/ translational feedback loop, control the majority of cycling transcripts genome-wide (Figure 4.13). Several NHRs, such as the glucocorticoid receptor, are also clock regulated at the transcriptional level in both mice (48) and humans (10) and mediate clock function or output (see Section 4.8.1). While core clock components are ubiquitously expressed, output gene expression is tissue specific. Up to 50% of the mammalian genome is clock regulated in at least one tissue of the body (9, 10, 27). Most layers of gene expression including splicing termination, polyadenylation, nuclear export, microRNA regulation, translation, and RNA degradation are also under circadian control (Figure 4.14). Beyond transcriptional regulation, the molecular clock also regulates circadian protein expression and post translational modifications (49– 51), as well as downstream metabolites (52, 53).

4.6 Cellular and Organ System Clock Organization 4.6.1 The Suprachiasmatic Nucleus (SCN) Roughly 45,000 neurons comprise the human SCN (20,000 in mice) and together with their glial cell counterparts, represent the central circadian oscillator (i.e. master pacemaker) that drives rhythmic behavior (e.g. rest and activity) and physiology (e.g. core body temperature, autonomic function, and

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FIGURE 4.13  A primary loop of CLOCK- BMAL1 and PER-CRY complex. CLOCK-BMAL1 heterodimers bind to E-box elements genomewide, but also to PERs and CRYs, and drive clock output gene expression, including many endocrine hormones, nuclear receptors, and rate-limiting enzymes essential for metabolic function. RORs and Rev-erbs are clock controlled nuclear hormone receptors that feedback to regulate the transcriptional output of core clock genes (BMAL1). Source: adapted from (47). *BMAL1 = brain and muscle Arnt-like protein-1; CLOCK = circadian locomotor output cycles kaput; CRY 1/2= cryptochrome circadian regulator 1/2; E-box = enhancer box; PER 1/2/3 = period circadian regulator 1/2/3; ROR = retinoid-related orphan receptor.

FIGURE 4.15  Melatonin and metabolism. Melatonin, a sleep promoting hormone regulated by the SCN, affects metabolism and the rate of aging. *M1/2 = melatonin receptor 1/2; GH = growth hormone.

FIGURE 4.14  Activators and repressors of circadian output genes. Gene expression, including mRNA expression levels, is under circadian control. Source: adapted from (54). *BMAL1 = brain and muscle Arntlike protein-1; CLOCK = circadian locomotor output cycles kaput.

neuroendocrine function). Ablation of the SCN renders an animal arrhythmic. In the hamster, transplantation of an intact SCN can rescue arrhythmic animals and instill the donors’ period on the transplanted animal (1). Unlike other organs, circadian rhythms persist in the SCN indefinitely in culture (55), a property thought to be due in part to the nature of synaptic connections between these specialized cells The SCN coordinates many aspects of physiology through temporal regulation of many brain regions. The SCN synchronizes and regulates the release of circulating melatonin (a sleep promoting hormone) (Figure 4.15) and glucocorticoids through the pineal gland and the hypothalamic pituitary

adrenal (HPA) axis, respectively. The SCN tightly regulates melatonin synthesis and secretion. Although melatonin secretion is also inhibited by light, even in constant darkness, the SCN consolidates melatonin release from the pineal gland solely during the dark phase.

MELATONIN AND METABOLISM The consolidation of melatonin solely during the dark phase is not only important for sleep consolidation but also influences metabolism. Melatonin inhibits insulin release from the pancreas. Thus, if melatonin is present in high amounts during food intake it can compromise glucose tolerance. This is one example of how the circadian system temporally separates incompatible events. For example, most components of the hypothalamicpituitary-adrenal axis (HPA) are regulated by the SCN (Figure 4.16). Within the hypothalamus, the SCN controls the circadian release of vasopressin (AVP). Peak AVP release

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FIGURE 4.16  Neural circuitry of SCN regulation on HPA axis. The SCN regulates most components of the HPA which are influenced by light and food. The central pacemaker resides in the SCN, but other clocks exist in various regions of the brain. A metabolic signal, such as feeding, can be delivered to the CNS via a local clock in the MBH region. Source: adapted from (56). *Arc = arcuate nucleus; CNS = central nervous system; OB = olfactory bulb; MBH = medial basal hypothalamus; PVT = thalamic paraventricular nucleus; PVN = paraventricular nucleus; SCN = suprachiasmatic nucleus.

occurs during the light phase. The hypothalamic paraventricular nucleus (PVN) receives the temporal AVP signal and consequently releases corticotropin-releasing hormone (CRH) and AVP. In turn, the pituitary cyclically secretes adrenocorticotropic hormone (ACTH) in response to CRH and AVP. This process is synchronized to the light–dark cycle via the SCN (57). ACTH travels through the blood to the adrenal cortical cells where it binds on the cell surface to the ACTH receptor or

Metabolism and Medicine melanocortin receptor (MC2R). This G protein coupled receptor (GPCR) transduces the ACTH signal through the adenylyl cyclase/cAMP/PKA signaling pathway. In turn, this activates the transcription factor cAMP response element binding protein (CREB) on the promoter regions of several steroidogenic genes including the rate-limiting step in cortisol synthesis, steroidogenic acute regulatory protein (StAR). Cholesterol is mobilized, transferred to the mitochondria, and to cortisol (Figure 4.17). Additionally, the adrenal cortex clock gates its own physiological response to ACTH by regulating MC2R expression to a specific time window for maximum response and corticosterone release. Ablation of the rat SCN eliminates rhythms of ACTH and corticosterone (59) and blunts the negative feedback of corticosterone on the release of pituitary ACTH. Arrhythmic mice (Cry1-/-;Cry2-/-) have constitutively high corticosterone levels (60). In humans, cortisol levels peak in the early morning, decline throughout the day, and reach a nadir around mid-sleep. Chronic stress elevates daytime cortisol levels and blunts the normal circadian variation. Glucocorticoids are also used to synchronize circadian rhythms in peripheral organ systems and at the cellular level in vitro. For example, SCN lesions ablate rhythms in the liver transcriptome. Supplementation with glucocorticoids is sufficient to restore these rhythms in animal models. The magnitude of the resetting effect is tissue specific. While glucocorticoids can reset rhythms in the liver, feeding cues provide a more robust entrainment cue in this peripheral tissue than in the SCN (Figure 4.18).

FIGURE 4.17  Adrenal clock dependent mechanism. Signaling pathways in the CLOCK system and HPA affect the rate-limiting step in cortisol synthesis known as StAR. Source: adapted from (58). *ACTH = adrenocorticotropic hormone; AVP = vasopressin; CLOCK = circadian locomotor output cycles kaput; CRH = corticotropin-releasing hormone; GR = glucocorticoid receptor; HPA = hypothalamic-pituitary-adrenal axis; PVN = paraventricular nucleus; SCN = suprachiasmatic nucleus.

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FIGURE 4.18  SCN and the adrenal clock. The SCN and the adrenal clock regulate the time window of corticosterone release in animal models. Source: adapted from (61). *ACTH = adrenocorticotropic hormone; ANS = autonomic nervous system; AVP = vasopressin; BMAL1 = brain and muscle Arnt-like protein-1; CLOCK = circadian locomotor output cycles kaput; CRH = corticotropin-releasing hormone; GC = glucocorticoid; GR = glucocorticoid receptor; HPA = hypothalamic-pituitary-adrenal axis; PVN = paraventricular nucleus; SCN = suprachiasmatic nucleus; stAR = steroidogenic acute regulatory protein.

4.6.2 Clock Synchronization: External Cues Across organ systems, the cellular clocks interact to coordinate both internally and externally with the environment. Synchronizing the internal period with the period of the environment is referred to as entrainment. This process allows human physiology to both anticipate and adapt to changes in the environment. There are many inputs received by the body that can entrain physiology, with the two strongest cues being light and food.

4.6.2.1 Light (SCN) Light is the predominant entrainment cue for the master circadian clock (SCN). To entrain the SCN, light is perceived through the retina by special retinal ganglion cells (RGCs) that contain melanopsin and can directly respond to light. These are known as intrinsically photoreceptive RGCs (ipRGCs) or melanopsin RGCs (mRGCs). Signals from rods and cones that communicate with RGCs that do not have melanopsin are not sufficient for entrainment. The signal from ipRGCs is transduced via the retinohypothalamic tract directly to the SCN. Some projections also go to the visual cortex and are thought to help with contrast for vision, however, it seems that their main role has nothing to do with conscious vision. In fact, even individuals that are completely blind can still entrain to light if their ipRCGS are still intact. Unfortunately, this is frequently not the case.

NON-24 SYNDROME Everyone has a period slightly different from 24 hours, and individuals that cannot entrain to light will be misaligned with their environment. For example, if a person has a 24.5-hour period and cannot adjust to the 24-hour day, every 24 days they will be 12 hours out of phase with their environment: it will be 12 noon but their body will think that it is midnight. This is a serious problem for these individuals and the disorder is referred to as non-24 syndrome. Non-24 is currently treated with melatonin or a melatonin agonist to help entrain through another cue. Light can entrain the circadian system by resetting the SCN at specific times of day (also called specific phases; Figure 4.19). The signal from the ipRGCs acts on VIP (vasoactive intestinal peptide) neurons in the SCN to induce cAMP and CREB which upregulate transcription of PER. If this happens during the internal day, when PER is already high, nothing will happen. However, if light is present when PER was low in the internal night, this stimulus will reset the clock to think that it is the day. This can be used to advance the period for people that have one longer than 24 hours or lengthen the period for people that have a period of fewer than 24 hours. As light controls the timing of behavior, once the SCN is

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Metabolism and Medicine feeding (TRF) in animal models (time-restricted eating, TRE, in humans) is a strong entrainment cue for peripheral organ clocks including, but not limited to, liver, pancreas, adipose tissue, skeletal muscle, gut, and even skin independent of the SCN that remains phase-locked to the light–dark cycle (i.e. melatonin phase is unchanged; Figure 4.20). While meal timing alone only strongly affects peripheral clocks, the SCN is responsive to metabolic challenges (i.e. amount or quality of dietary intake). For instance, calorie restriction is capable of modifying the effect of light on SCN clock phase (62). Peripheral clocks can also feedback to fine-tune phase and amplitude of the central SCN clock, albeit with less effect than light.

FIGURE 4.19  Phase response curve (PRC). Light is capable of resetting the SCN at specific times of day. *PRC = phase response curve; SCN = suprachiasmatic nucleus.

entrained, it communicates with the rest of the body to entrain peripheral clocks.

4.6.2.2 Food: Feeding/Fasting Cycles (Liver, Pancreas, Adipose Tissue, Skeletal Muscle) In the same way that light signals the time of day to reset and entrain the SCN, food intake/nutrient availability (i.e. fed versus fasted state) directly signals peripheral clocks (e.g. liver) involved in energy metabolism. Normal feeding behavior occurs during the active phase of the circadian cycle or the light phase of the light–dark cycle in humans. Alternatively, fasting occurs during the inactive phase, which is the dark phase of the light–dark cycle in humans. Time-restricted

STATED SIMPLY, LIFE IS ALL ABOUT TIMING Nutrient intake (food, beverages, supplements, etc.) is the single greatest voluntary control parameter of human health and disease. This is not surprising given that the energy harnessed in food is the basic source for growth, development, and maintenance of all animal and human life. However, it is not only the quantity and quality of diet, but also the timing, that is important for health. Metabolic function is optimal when we eat during active hours (usually day time) when our body clocks expect it. Conversely, the very early and very late hours of the day (usually nighttime) are the least anticipated hours of activity. Accordingly, energy extracted from food during expected high levels of activity needs to be efficiently and readily available for the body’s needs. What is not immediately used for physical and/or

FIGURE 4.20  Circadian control of metabolism. Light and time-restricting eating signal the time of day to reset, entrain the SCN, and directly signals peripheral clocks (e.g. liver) involved in energy metabolism. Source: adapted from (63). *ACTH = adrenocorticotropic hormone; SCN = suprachiasmatic nucleus; SNS = sympathetic nervous system.

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cognitive performance must be stored in such a way that it can be easily mobilized and metabolized. This allows the body to burn more calories and prevents weakness and subjective fatigue. Nighttime eating imposes a stress by mistiming the nutrient intake with our internal metabolic clocks. This can lead to an increase of fat to store energy that is not being used. This underscores the connection between such behavior and obesity, as well as other manifestations of insulin resistance. A significant underlying mechanism responsible for promoting insulin resistance is the pro-inflammatory (and associated cascades of oxidative stress) deposition of energy as fat into tissues not designed to store fat as bioenergetic reservoirs. The quality of food can also impact circadian behavior. For example, mice on a high-fat diet change their eating pattern from consuming their food during their active (night) phase, to eating around the clock, thus, blunting the amplitude of the rhythms of nutrient availability (15). The timing, amount, and quality of dietary intake represent extrinsic control parameters for health and disease. For example, mice fed a high-fat diet have altered numbers of metabolites and temporal oscillations that are tissue-specific (53). The timing of food impacts the circadian system and physiology. In humans, shifting the majority of calories consumed early in the day (active phase) to late-night eating just prior to bedtime (inactive phase) results in desynchronized insulin secretory patterns in response to meals. Additionally, leptin and melatonin circadian diurnal patterns are disrupted. Exposure to chronic circadian misalignment in young healthy adult males was sufficient to cause metabolic dysfunction similar to the metabolic syndrome, including decreased insulin sensitivity and insufficient beta cell compensation (64). This metabolic dysfunction resolved once the subjects returned to normal. In rodents, a high-fat diet at the end of the activity phase increased adiposity and insulin resistance with elevated insulin and leptin levels compared to consuming the same diet early in the activity phase (36). These studies and others underscore that the timing of meals earlier in the activity phase entrained circadian rhythmicity in metabolic tissues such as the liver, skeletal muscle, adipose, and pancreas in contrast to late timing of meals which disrupts the synchronized metabolic regulation between these tissues.

WHAT IS THE DIFFERENCE BETWEEN INTERMITTENT FASTING (IF) AND TIME-RESTRICTED EATING (TRE)? Intermittent fasting can take many forms (alternate day fasting, daily fasting for 14 hours or more, two days of fasting each week, or periodic fasting), but in all forms consists of calorie restriction and periods of fasting. Time-restricted eating consists of a consistent 4–12 hour daily eating window with no calorie restriction required.

Although IF and TRE in some instances could be the same thing, the two main differences are:

1) Time consistency: IF does not have a consistent eating/fasting period, which means it does not support the circadian system in the same way as TRE. 2) Calories: IF requires some aspect of calorie restriction and TRE does not. Intermittent fasting, a diet where eating is paused for hours or even days, is an increasingly popular strategy for weight loss. Restricting feeding to a ten-hour time interval in overweight adults demonstrated a 4% weight loss (19, 24, 25). This diet is thought to promote weight loss primarily because people eat less. But a second reason may also be important: leveraging the body’s clock. For example, patients who ate half their calories at breakfast lost more weight than those who ate half at dinner (65). These benefits also extended past weight loss. People who ate earlier in the day lowered their blood pressure and low-density lipoprotein (LDL) cholesterol as much as those on an antihypertensive drug (24). Even a single fasting interval can also reduce basal concentrations of metabolic biomarkers such as glucose and insulin and reduce the risks of obesity and obesityrelated conditions, such as nonalcoholic fatty liver disease, and chronic diseases, such as diabetes and cancer. However, most of this work has been done in rodents and nocturnal mammals. Clinically, it is unclear whether intermittent fasting can facilitate long-term metabolic improvements, long-term body weight management, and a longer lifespan (66).

WHY CAN TIME-RESTRICTED DIETS HELP US LOSE WEIGHT (LOWER BLOOD GLUCOSE, BP, ETC.)? Weight: Daily fasting allows us to use energy stores, such as fat, that we already have. If you are constantly consuming calories then these stores are never used. Blood Pressure (BP): Blood pressure is regulated by multiple factors including epinephrine, norepinephrine, cortisol, cardiac vagal tone, and kidney function. Each of these is in turn regulated by the circadian system. For instance, one of the core clock genes, Period, regulates aldosterone production in the adrenal glands to modulate blood pressure by signaling the kidney, colon, salivary glands, and sweat glands. Additionally, 13% of genes, 8% of proteins in the heart, and ~13% of proteincoding genes in the kidney also display circadian patterns of expression/function (9). Mistimed food sends conflicting cues to the circadian system. Over time, this dampens the rhythms throughout the body and leads to compromised cardiometabolic health. Eating during expected rest phases and eating at erratic times are also associated with obesity and compromised glucose regulation, which can also lead to increased blood pressure.

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HOW DO TIME-RESTRICTED DIETS HELP PREDIABETICS AND DIABETICS LOSE WEIGHT AND INDEPENDENTLY IMPROVE BLOOD PRESSURE AND/OR GLUCOSE CONTROL? In November 2017, the Nobel Prize in Medicine and Physiology was awarded for the elucidation of astonishing evolutionary biological cell clocks present in all cells of the body. In fact, these molecular timepieces link metabolic pathways that mediate physiology and behavior to 50% of the human genome (10). They are microcosm incarnates of the Earth’s rotation around its own axis, and they are a prototype for cycles and the cycles within cycles that define the relative quantity of biological time. Their purpose is to temporally organize all biological systems synchronously with the outside environment. There are optimal weight set points which are personspecific, teleologically intended for maximal metabolic efficiency and most fundamentally supported by the bioenergetic cycle of ATP production. Thus, it is not surprising that the timing of external control parameters— such as diet—has powerful implications for not just physiological versus pathophysiological bodyweight set points, but for parameters of human health and disease including the glycemic control of a diabetic and abnormal blood pressure regulation often due to insulin resistance. It appears evident that 12 hours (and even up to 18 hours) of consistent fasting on a daily basis (TRE), particularly during the night, are powerful if not crucial for optimal physiological bodyweight and health. This is rooted in the circadian rhythm of the synchronized symbiotic intestinal microbiota with human host metabolism. Insulin secretory patterns and peripheral insulin sensitivity are core parameters of metabolic health. Accordingly, food consumed at night has a very different physiological response pattern than when eaten earlier on during the daylight hours. Nighttime is evolutionarily designed to coincide with reduced activity and sleep accompanying a state of fasting and insulin resistance, while daytime represents the active and insulin sensitive phase. This is in part due to melatonin, which inhibits the release of insulin from the pancreas, and thus compromises the ability of the body to process glucose. Melatonin is controlled by the circadian system to be released when your clocks expect you to rest, with production being suppressed by light. Thus, during the evening and very early morning when melatonin is high, insulin sensitivity is decreased. Although this internal timing system is sustainable on its own, it also incorporates external signals, such as light and food, to coordinate with the environment. Light is a strong cue to clocks in the brain, and nutrient availability is the strongest cue to peripheral clocks. Thus, the timing of when we eat plays a key role to determine the timing and ability of our metabolism.

Metabolism and Medicine

When we eat at a time that our body anticipates it, as is the case of TRE, the feeding cue reinforces and amplifies the circadian rhythms. However, when we eat at irregular times, when our body is not prepared for it, it provides conflicting cues to the circadian clocks, decreasing the amplitude of the rhythm and compromising metabolic function.

4.6.3 Exercise, Stress, and Hypoxia 4.6.3.1 Exercise In addition to the influence of light and feeding on setting central and peripheral rhythms, exercise has recently been identified as a zeitgeber. Studies on mice subjected to exercise bouts (via wheel running or treadmill), have revealed that exercise is capable of influencing circadian timing in peripheral tissues. When mice are exercised in their rest phase, this results in a phase advance (a forward shift of the internal timing of circadian clocks, see Section 4.4.4) of two to three hours of circadian clocks in peripheral tissues such as the liver and muscle, versus a phase delay of similar magnitude when mice exercise during end of their active phase (67, 68). In these studies, central clock timing is unaffected, indicating that exercise does not act as a zeitgeber for the SCN clock. Therefore, in a similar manner to the time-restricted feeding described above (see Section 4.4.2.2), time-restricted exercise may represent a tool by which peripheral clocks can be manipulated. Approaches in which mice are given free, rather than scheduled, access to running wheels have also been reported to affect clock timing in peripheral tissues (69, 70), though these effects may in part be explained by alterations in feeding behavior via these manipulations (70). The mechanisms through which scheduled exercise influences clock function in peripheral tissues are poorly understood; glucocorticoid signaling (through HPA axis activation) as well as the sympathetic nervous system have been identified as potential mechanisms in mouse studies (67). Limited studies have been performed in humans addressing the role of exercise on circadian clock function, however studies on human biopsies of skeletal muscle taken after a single bout of exercise, have revealed that exercise may affect expression levels of several clock genes in muscle (71). Similar studies in blood leukocytes also show an effect of exercise on the phase of core clock genes such as Bmal1 and Cry1 (72). In both humans and rodents, exercise increases cortisol release (73) and activates the sympathetic nervous system (74), therefore these represent potential mechanisms through which exercise may regulate clock function in peripheral tissues. Intriguingly, studies have also reported that timing of exercise can affect the phase of melatonin rhythms in humans, which may indicate effects on the central clock (75–79). More work is required to define the most appropriate type and timing of exercise in order to bring about desired phase shifts in either peripheral and/or central clock timing in humans. Intriguingly, even a single bout of exercise can have dramatic effects on metabolic function in the muscle that varies according to the time of day performed (80). When mice are exercised via treadmill at early active phase versus rest phase there

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is an increased utilization of glycolytic substrates along with lipid oxidation and breakdown of branched-chain amino acids. Such effects may be related to the fed/fasting state of these mice, highlighting a potential mechanism for overlapping circadian and metabolic systems in the regulation of muscle and organismal physiology. Intriguingly, the muscle circadian clock has been linked to changes in the regulation of sleep (81), therefore long-distance signals from the muscle could represent potential mechanisms through which exercise could affect circadian function in the brain.

4.6.3.2 Stress Similar to exercise, stress is capable of entraining circadian clocks (see Section 2.7.1.1). Acute stress activates both the HPA axis (see Figure 4.27) and the autonomic nervous system, collectively resulting in an increase of circulating glucocorticoids and norepinephrine. Glucocorticoids (GCs) can act as entrainment signals for peripheral clocks (82) (see also Section 4.6.10) through binding to glucocorticoid receptors (GRs) on cell membranes of target tissues, followed by translocation to the nucleus and binding of glucocorticoid response elements (GREs) on target genes. Binding of GRs to GREs on clock genes such as Per2 triggers rhythmic clock gene expression in peripheral tissues and is important for control of systemic metabolism including glucose homeostasis (83). Since the SCN is devoid of GRs, it is unaffected by fluctuations in circulating GCs. In agreement with this, acute bouts of stress do not affect rhythms of the SCN in experiments performed on mice (84). However, the effects that long-term stress may have on central clock function are controversial (85, 86). Circadian variations in epinephrine have been demonstrated to control function of immune cells such as CD8+ T cells (87), therefore the misregulation of circadian epinephrine signaling as a result of stress may be a contributory factor to changes in immune function observed as a result of exposure to stress (88).

4.6.3.3 Hypoxia Research in mice now indicates that changes in oxygen levels within tissues can entrain peripheral clocks both in vitro and in vivo (89–92). Tissue oxygen levels oscillate with a 24-hour rhythmicity during normal physiological states (89), and furthermore can be severely impacted as in hypoxia, in which low oxygen levels occur in response to pathological insults such as heart failure. Oxygen levels are sensed by the hypoxia inducible factor 1 (HIF1), a heterodimer of HIF1α and HIF1β. HIF1β is constitutively expressed, whereas HIF1α levels change in response to changing oxygen levels. During normoxia, HIF1α is unstable and subject to degradation, whereas upon hypoxia, HIF1α is stabilized which leads to HIF complex formation and transcription of HIF1 targets (93). Evidence from mouse studies suggests that the circadian clock controls the expression and stabilization of HIF1α under hypoxic conditions in peripheral tissues (89, 91, 92). The positive and negative limbs of circadian clocks (Figure 4.14) affect the response of HIF1α to hypoxia in opposing ways; the positive regulator BMAL1 promotes stabilization of HIF1α under hypoxia, whereas Cry1 induces destabilization (91). In line with this finding, there are

FIGURE 4.21  Role of HIF1 as an oxygen sensor and interplay with the circadian clock. At normal oxygen conditions, the HIF1α is subject to degradation by the ubiquitin-proteasome system. When oxygen levels drop, HIF1α is stabilized and interacts with HIF1β in the nucleus to form HIF. Binding of HIF to hypoxia response elements (HRE) promotes expression of hypoxia responsive genes. Recent evidence also indicates that HIF can bind the canonical E-box sequences present on clock genes, indicating a mechanism through which HIF may translate changes in oxygen availability into altered circadian rhythms. Source: figure created with Biorender​.co​m. *BMAL1 = brain and muscle Arnt-like protein-1; CLOCK = circadian locomotor output cycles kaput; E-box = enhancer box; HIF1α/β = hypoxia inducible factor 1 α/β; HREs = hypoxia response elements

daily circadian changes in the response to hypoxia in mice (92). Furthermore, metabolic function may be impacted due to the circadian clock-HIF1 crosstalk; in muscle, loss of BMAL1 leads to defects in anaerobic glycolysis (91). If a similar mechanism is described in humans, HIF1a may represent an important mediator in ensuring proper circadian and metabolic function in the muscle. The relationship between HIF1a and the clock is bidirectional; in cells depleted of HIF1a, oxygeninduced circadian rhythms are perturbed (89, 92). The functional relationship between HIF1a and the clock may depend on their interaction at DNA (Figure 4.21); HIF1α binds many of the same genes as BMAL1, hinting at a synergistic transcriptional mechanism through which period length and amplitude of oxygen-sensitive circadian genes is influenced by oxygen levels (92). Intriguingly, studies in mice have revealed that alteration of feeding rhythms, through time-restricted feeding (TRF) (see Section 4.6.2.2), can also impact systemic oxygen rhythms as measured by VO2 (90), suggesting a possible crosstalk between feeding–fasting cycles and oxygen cycles in regulation of circadian function. The extent of impact of HIF1a-circadian clock crosstalk may also extend to regulation of the central clock in the SCN (see Section 4.6.1). Research in mice has revealed that a transient reduction of atmospheric oxygen levels from 21% to 14% for two hours can accelerate the realignment of SCN-dependent behavioral rhythms upon simulation of jet lag (89). If confirmed in humans, such transient deprivations in oxygen content could represent a novel treatment for circadian perturbations induced by jet-lag or shift work. Circadian clock-HIF1a crosstalk may have implications for human health and performance. For example, strenuous exercise induces a hypoxic challenge in muscle, and is accompanied by changes in HIF1a-dependent gene expression (91). Circadian regulation likely plays a key role in gating this response to exercise, since the extent of induction of HIF1adependent gene expression changes according to time of day

156 (80, 91). Interestingly, in humans there is a time-of-day dependent effect on exercise performance as well as the effect of exercise on systemic metabolism (94, 95). Exercise performed in the late active phase results in a lower oxygen consumption than when performed during early active phase, coincident with increased utilization of carbohydrates as an energy source (94). These results support findings from humans that report increased exercise performance in the afternoon/evening versus early morning (95). The role of HIF1a and the circadian clockwork may also have implications for diseases associated with hypoxic damage. For example, myocardial infarction (heart attack) is reported to cause more tissue damage in the early morning (96, 97). In agreement with this, in a mouse model of heart attack, tissue death was more pronounced in the active phase versus rest phase (92). Genetic deletion of the circadian clock components Per1 and Per2 exacerbated tissue damage, suggesting the circadian clock may play a protective role in diseases that induce hypoxic damage. Hence, the clock system may represent a potential therapeutic target to be modulated under pathological conditions to reduce hypoxic damage.

4.6.4 Phase Shifts The time at which an entrainment cue is received by internal clocks determines the phase shifting response. For example, in humans, light exposure 1) early in the active phase (dawn) causes a phase advance, 2) late in the active phase (dusk) causes a phase delay, and 3) during the light phase causes no shifting. Note, this is reversed in nocturnal animals (Figure 4.22). These points illustrate the phase response curve for circadian entrainment. There are sensitive times of exposure where the circadian clock is primed to respond (advance or delay) and insensitive times where the exposure evokes no response. This concept is

Metabolism and Medicine defined by a stimulus’s phase response curve (PRC) or the magnitude of the shift plotted against the timing of the stimulus.

4.7 Hormones Display Circadian Rhythmicity Hormones all have circadian rhythmicity. They also provide, for example, the function of the neuroendocrine branch of the critical stress response accompanying the autonomic component. Together, the hormonal and autonomic divisions of the stress response seek to maintain allostasis of vital organ system function in reaction to real or perceived stress. This is mediated by regulatory perturbation of the immune, gut and other systemic biology. Allostasis in general terms is the maintenance of stability through change. The stability that it seeks is the most fundamental parameter of metabolic homeostasis. These parameters in a biological system are Gibbs free energy, redox, and acid-base, which all have a striking parallel and inextricable relationship rooted in the equations of Gibbs free energy, Nernst and Henderson Hasselbalch. Metabolism is the defining feature of any living system. Metabolic processes have a physiological purpose to maintain them far from thermodynamic equilibrium complex and ordered state that is the hallmark of health. By contrast, thermodynamic equilibrium is a totally random state, lacking information and order. It is tantamount to a dead or inanimate state. The most central and foundational strategy for metabolism to maintain a healthy and far from the equilibrium state is by invoking the notion of cycles. Indeed, all living systems, humans included, are comprised of systems of cycles within cycles across many hierarchical scales. The fidelity of the cycle, that is, the returning to the proximity of its starting point, is the ultimate parameter of the state of health as well as the rate of aging. The cycle is what defines biological time,

FIGURE 4.22  Phase shift and phase response curve (PRC). PRCs are used to show how measurable output of the biological clock, such as onset of activity, is affected by an external cue (also known as a zeitgeber) across the 24-hour day. In this case, the PRC represents the phase shifts in activity in response to light. A) A depiction of an actogram of a nocturnal rodent, such as a hamster, in constant darkness. Grey bars indicate the time of activity on a given day. Circadian time (CT) indicated the internal timing of hamster, with CT 12 indicating the onset of activity. Arrows indicate a 15-minute light pulse on a given day at different phases. B) The PRC depicts how the animal’s phase of activity responded to each light pulse, with negative values (e.g. CT15) indicating phase delays, and positive values (e.g. CT 21) indicating phase advances. Note, a light pulse at CT 6 leads to no phase shift because it is during a subjective day, and thus, will not shift the clock. *CT = circadian time; PRC = phase response curve.

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FIGURE 4.23  Circadian rhythms in humans. Humans are comprised of a systems of cycles within cycles. Source: adapted from (98).

as the cycle of a mechanical clock. Deviation from this cycle is tantamount to the aging process, and exaggerated deviation is a manifestation of premature aging and disease. This ineluctable direction from order, information, and complexity to randomness and entropy represents the arrow of time. Although we cannot avoid the movement from the cycle of time as a living system, to the arrow of time, the goal is to moderate the rate of deterioration. The most fundamental cycle is the metabolic cycle of ATP production, which is responsible for more macrocosm hierarchies of cycles, such as the circadian cycles. Other scales of cycles including ultradian (less than 24 hours) and infradian (more than 24 hours) within and across cells, tissues, and organ systems are richly enmeshed in the reciprocal top-down and bottom-up mutual regulation of one another (Figure 4.23). While hormonal allostasis maintains metabolic homeostasis of control parameters of human health, the notion of allostatic overload denotes pathological chronicity of the stress response. Accordingly, there is a loss of the capacity to maintain the parameters of metabolic homeostasis within the narrow ranges necessary for a healthy physiology. It is not surprising, as an example, that early menopause, the loss of reproductive cycles before the age of 40, is associated with greater risk for cardiovascular disease and that cardiovascular disease risk is doubled in women under 60 with premature menopause (99). Further, early menopause poses a greater independent portent for cardiovascular premature mortality than any of the conventional Framingham risk factors, such as dyslipidemia, hypertension, obesity, and diabetes. Despite evidence of sex-specific risk factors, early menopause is not included in the Framingham’s risk factors. In addition to menstrual cycleassociated cardiovascular risk, day/night physiological patterns present varying risk to cardiovascular function. Typical morning behaviors (such as waking from sleep, changing posture from recumbency, increasing activity and/or psychological stress) increase heart rate, blood pressure, sympathetic tone, and vasoconstriction and decrease vascular endothelial function (100). While these cardiovascular changes are generally advantageous for healthy individuals’ reaction to daily changes in the

environment and behaviors, these morning fluctuations can precipitate cardiovascular adverse events in susceptible individuals. Based on this circadian rhythmicity, new research suggests optimizing effectiveness of cardiovascular medications by timing prescribed doses with endogenous biological time.

WHY ARE HEART ATTACKS MORE LIKELY AFTER WAKING? Many aspects of the cardiovascular (CV) system are regulated by the circadian system. These include blood pressure heart rate variability, and clotting factors (i.e. platelet activation via plasminogen activator inhibitor-1; PAI-1) (101). These rhythms are achieved through multiple levels of circadian control. As the circadian system regulates several aspects of the CV system, it is not surprising that CV events occur in a circadian fashion. For instance, heart attacks (myocardial infarctions), ischemic stroke, sudden cardiac death, and ventricular arrhythmias are all increased in the morning hours (102, 103). Although BP peaks in the evening, the sharpest rise in BP occurs in the morning, and was originally thought to be a factor in the morning increase of CV incidents. However, further studies have indicated that this is quite unlikely due to the time delay between the BP morning rise and CV events (101, 104). Instead, it is hypothesized to be caused by morning impairment of vascular endothelium function (105), which inhibits platelet adhesion (106–108), and an increased clotting ability. Additionally, blood clot formation is increased in the morning due to increased platelet aggregation and high concentrations of PAI-1(109). Although these circadian patterns of CV function may be beneficial in healthy individuals, they pose a potential risk for cardiovascular events for those at risk for heart diseases. Treatments aimed at ameliorating circadian disruption show promise in reducing CV risk (110).

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WHY IS TAKING CERTAIN DRUGS AT SPECIFIC CIRCADIAN TIMES BENEFICIAL? Nearly 50% of protein-encoding genes have circadian patterns. 12% (nearly 1,000) of these genes are also drug targets that have circadian patterns (10). Thus, taking the medication at the right time allows the drug to act on the target at its peak, whereas taking the medication when the target is scarce or inactive would have a significantly reduced effect. This will depend on both the time of day that the drug target is active, and the half-life of the drug itself. The best example of this is cholesterol lowering medications known as statins. For a long time, statins had a short half-life of under one to three hours (111). Cholesterol is made at night, so statins are taken a night to stop cholesterol from being produced. If statins are taken during the morning, they would have a significantly reduced effect. This is because cholesterol is not made during the day, and by the next night, the medication would have left the system. There are now statins that have a 12–24 hour half-life so that you can take them at any time of day, but that also means you have medication in your system when it isn’t needed.

4.8 Chronobiology and Nuclear Hormone Receptors The intersection of circadian and metabolic pathways is an intriguing and evolving area that involves the coupling of nuclear hormone receptors to circadian clocks, driving divergent metabolic outputs. Nuclear hormone receptors are endocrine receptors that bind fat-soluble hormones, nutrients and other signals, such as the thyroid hormone receptor (TR). There are also so-called orphan receptors with (or without) undiscovered natural ligands. They are evolutionarily related members of DNA binding transcription factors. Transcription factors may be heterodimeric nuclear receptors by their binding to the retinoid X receptor (RXR) in response to a metabolic ligand such as a fatty acid or vitamin D or homodimeric nuclear receptors following binding to steroid hormone ligands. Alternatively, the transcription factor may be activated in response to factors such as the growth factor IGF-1 (insulin growth factor 1) or insulin through a MAPK (mitogen-activated protein kinase) or through the PI3/AKt/PKB pathway (phosphoinositide 3-kinase protein kinase B) (see Chapter 3 for details). Nuclear hormone receptors are involved in virtually all facets of human metabolism and physiology in which disturbances in signaling results in a wide span of disease states including diabetes, hypertension, dyslipidemia, cardiovascular disease, myocardial infarctions, strokes, and cancers. Nuclear hormone receptors and other energy sensors gauge cellular energy status to meet metabolic demands accordingly. For example, DNA repair and antioxidant system anabolism that occurs in the context of delta wave sleep. The body has

calibrated delta wave sleep (stage three non-REM (rapid eye movement) sleep) to be the optimal time for slowing down active catabolic demands and using stored energy resources for the critical purpose of preserving homeostasis by maintaining tissue and DNA structural and functional fidelity. These nuclear hormone receptors help guide the synchronous behavior of molecular clocks across tissues. Importantly, the synchronicity of the clock-controlled output gene products and their function is a manifestation of the quantum metabolism mode of energy production. (See Volume 1, Chapter 4 for more discussion on this topic.) Nuclear hormone receptors Rev-erbα and RORs are products of core clock-controlled output genes and represent the auxiliary loop of the clock mechanism as discussed in Section 4.5). Molecular clocks regulate temporal expression of nuclear hormone receptors, and nuclear hormone receptor signaling often feeds back to regulate clock gene function and/or expression. These are temporally coordinated processes that underpin the potential for growth, regulated cell replication, redox homeostasis, and organism reproductive functions. There is strong evidence to support the critical role of the circadian clock in maintaining energy homeostasis. Many clock gene mutant mice have metabolic alterations including altered glucose and fat homeostasis. Nuclear hormone receptors are covered in greater detail in Chapter 3, but here we will cover some examples of nuclear hormone receptors (such as thyroid or steroid receptors) and how they are both regulated by, and feedback on, circadian clocks.

4.8.1 Steroid Receptors The nuclear hormone receptors of the steroid superfamily are categorized as classical hormone receptors with high-affinity ligands. This group of nuclear receptors includes steroid hormones: glucocorticoid receptor (GR), mineralocorticoid receptor (MR), androgen receptor (AR), estrogen receptor (ER), and the progesterone receptor (PR). These steroid-regulated nuclear hormone receptors bind to DNA as homodimers inducing transcription. These classical nuclear hormone receptors evolved to regulate carbohydrate metabolism, development, reproduction, and electrolyte balance. The regulation of ligands to these hormone receptors is by the classical hypothalamic-pituitaryaxis (HPA) negative feedback mechanisms (Figure 4.24).

4.8.1.1 Glucocorticoid Receptor (GR) Adrenal glucocorticoids modulate energy metabolism, stress response, immunity, and cognition. In humans, glucocorticoids (e.g. cortisol) have a prominent and robust circadian rhythm. They peak early in the activity phase around the sleep–wake transition and trough in the evening. The glucocorticoid (NR3C1; Nuclear Receptor Subfamily 3 Group C Member 1) and mineralocorticoid (NR3C2; Nuclear Receptor Subfamily 3 Group C Member 1) receptors are expressed in many central and peripheral tissues and modulate local circadian clock function and physiologic outputs. For example, gluconeogenesis and lipid metabolism in the liver are modulated by cortisol. GR gene expression is regulated by the molecular clock in many human tissues investigated thus far including

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FIGURE 4.24  HPA and circadian clocks. Interactions between glucocorticoid signaling and the synchronization of circadian clocks. Source: adapted from (61). *ACTH = adrenocorticotropic hormone; AVP = vasopressin; CRH = corticotropin-releasing hormone; GC = glucocorticoid; PVN = paraventricular nucleus.

visceral fat, liver, thyroid, and the heart (10, 112) (Figure 4.25). CRY1 and CRY2 interact with ligand-bound GRs to repress transcription (60). GRs can also directly interact with CIART (Circadian Associated Repressor of Transcription) to mediate glucocorticoid response independent of the CRY (46). Moreover, 11-β-hydroxysteroid dehydrogenase type 1 and type 2 (HSD1, HSD2), regulating the tissue balance between cortisone to cortisol, are circadian in mouse liver and lung (48, 112). Taken together, these regulatory layers from gene expression to ligand release define an optimal physiological effect that is time-dependent and tissue-specific.

4.8.2 Retinoid X Receptor (RXR) Heterodimeric Receptors Retinoid X receptors (RXR) are nuclear hormone receptors that form heterodimers with other nuclear hormone receptors to drive transcription of response genes. Examples of these receptors that bind to DNA as heterodimers with RXR include the vitamin D receptor (VDR), retinoic acid receptors (RARs α, β, and γ), peroxisome proliferator-activated receptors (PPARs α, β/δ, and γ), farnesoid X receptor (FXR), liver X receptor (LXR), and thyroid hormone receptor (TR α and β). These receptors are also critical for sensing hormones, lipids, or other metabolites. In addition, several RXR heterodimers bind to xenobiotic ligands and play an important role in metabolic detoxification including the constitutive androstane receptor (CAR) and pregnane X receptor/steroid and xenobiotic sensing nuclear receptor (PXR/SXR). RXR heterodimers play a role in metabolism regulation and RXR-deficient mice present disrupted circadian cell cycle regulation.

4.8.2.1 Thyroid Hormone Receptor (TR) There is evidence of transcriptional regulation of thyroid stimulating hormone (TSH), and thyroid hormones by the circadian clock. Rodents have a robust oscillation of circulating TSH, as well as thyroid hormones T3 (active) and T4 (precursor thyroxine). In humans, TSH is also driven by the circadian clock. T3 and T4 are food entrainable as restricted feeding to the inactivity phase results in an antiphase rhythm.

4.8.2.2 Farnesoid X Receptor (FXR) Hunger signaling following an overnight fast is adaptive and motivating for food seeking behavior. When a surplus of nutrient resources is required during the active light phase of the daily cycle, clock-controlled output genes including glycogen synthase in the liver promote glycogen storage. Another circadian clock regulation involves bile acid synthesis mediated by the clock-controlled output genes CYP7A1, utilizing cholesterol as a substrate and converting it into bile acids to be used for intestinal absorption of dietary lipids. Bile acid bound FXR regulates hepatic glucose metabolism switching its activity in the fed and fasted state along with hepatic lipid metabolism. This is mediated by direct and indirect actions via the induction of the small heterodimer partner (SHP). This atypical nuclear hormone receptor, which lacks a DNA-binding domain, is a clock-controlled output gene transcription product. Other clock-controlled output genes in the liver, such as the transcription factor SREBP1c (sterol regulatory elementbinding protein 1), is inhibited by FXR-SHP resulting in the inhibition of lipogenesis and reduction of hepatic triglyceride secretion as very-low-density lipoproteins (VLDL) into the

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FIGURE 4.25  Neural and humoral signals. The influence of circadian rhythms on several humoral signals. Source: adapted from (61). *GC = glucocorticoid; SCN = suprachiasmatic nucleus.

circulation. Moreover, the same bile acid liganded FXR-SHP pathway strongly represses CYP7A1 gene transcription of bile acid synthesis. In addition to a means of maintaining energy homeostasis, the prevention of excessive hydrophobic bile acid accumulation protects the liver from cholestasis, hepatic inflammation, and fibrotic injury. FXR has been found to interact with the cofactor PGC1α (PPARγ coactivator 1α), another clock-controlled output gene, which promotes the oxidative metabolism of fatty acids, as well as mitochondrial biogenesis (113). Bile acid bound FXR also promotes, independently of SHP, the expression of PPARα, which regulates fatty acid oxidation. Taken together, the molecular endogenous clocks invoke a metabolic design that eloquently calibrates energy resources such that the export of glucose, lipids, and cholesterol is reserved for the fasting phase of the daily cycle. While bioenergetic processes and machinery are most upregulated during the active phase of the daily cycle, because it is also the fed phase, it also coincides with the priority for energy storage of surplus nutrients. The balance ApoC2/ApoC3 is also regulated by FXR, resulting in the activation of lipoprotein lipase (LPL) and consequently triglyceride clearance from the circulation into adipocytes for lipid storage. Following the hydrolysis of circulating triglycerides, constituent glycerol and fatty acids are taken up into the adipocytes where they are resynthesized and packaged as triglyceride lipid droplets (Figure 4.26).

4.8.2.3 Constitutive Androstane Receptor (CAR)-Xenobiotic Metabolism Constitutive Androstane Receptor (CAR) gene (NR1I3; Nuclear Receptor Subfamily 1 Group I Member 3) transcription

is mediated by the PARbZIP family of transcription factors (DBP (D-box binding) transcription factor, HLF (hepatic leukemia factor), and TEF (thyrotroph embryonic factor)) and peaks prior to the onset of activity in mice (48). Circadian regulation of peak CAR expression suggests a crucial role of circadian timing in optimizing toxin clearance.

4.8.3 Lipid Sensors Lipids regulate a wide array of cellular functions. Lipids are the main structural components of cell membranes, serve as a major form of energy storage, and also function as key signaling molecules. There is a strong interplay between circadian clocks and lipid metabolism (Figure 4.27). In mammals, circadian clocks regulate the daily physiology and metabolism, and disruption of circadian rhythmicity is associated with altered lipid homeostasis and pathologies such as fatty liver and obesity. Here, in this section we will discuss RORs, PPARs, PGC1α, and Rev-erbs, at the intersection of lipid homeostasis and circadian rhythm. Further details on NHRs are found in Chapter 3.

4.8.3.1 Retinoid-Related Orphan Receptor (RORs) RORs are nuclear receptors that bind to specific DNA sequences called ROR-response elements (ROREs). There are three ROR isoforms: RORα, RORβ, and RORγ. Various conserved ROREs are found in several clock gene promoters and positively support the expression of clock genes such as Cry1, BMAL1, CLOCK and NPAS2 (CLOCK homolog) (116, 117). RORα and RORγ are expressed in the liver and participate

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FIGURE 4.26  FXR pathways. FXR is activated by bile acids. FXR in the liver induces SHP that inhibits HNF4α and LRH-1, which regulate CYP7A1 expression. Liver FXR enhances intra-vascular triglyceride-lipolysis, NF-kB in macrophage. Bile acids also activate the GPCR TGR5 in the intestinal L-cell. FXR in pancreas induces insulin release, which induces glycogen synthesis in the liver, in the postprandial phase. Source: adapted from (114). *AC = adenylate cyclase; ATP = adenosine triphosphate; cAMP = cyclic adenosine monophosphate; Choleste = cholesterol; COX-1 = cyclooxygenase 1; CYP7A1 = cholesterol 7α hydroxylase; FXR = farnesoid X receptor; GLP-1 = glucagon-like peptide-1; GPCR = G protein coupled receptor; GSK3β = glycogen synthase kinase 3β; HNF4α = hepatocyte nuclear factor 4 α; IL(-1β/6) = interleukin-1β/6; LRH-1 = liver receptor homolog 1; NF-κB = nuclear factor kappa B; PKA = protein kinase A; PEPCK = phosphoenolpyruvate carboxykinase; PPARα = peroxisome proliferator-activated receptor α; SHP = small heterodimer partner; SREBP(1c/2) = sterol regulatory-element binding protein 1c/2; TGR(5)= Takeda G protein-coupled receptor (5); TNF-1 = tumor necrosis factor-1.

FIGURE 4.27  LXR regulates liver lipogenesis. LXR regulates liver lipogenesis by induction of fatty acid and triglyceride biosynthesis by direct regulation of key lipogenic factors including the binding protein of sterol regulating elements 1c (SREBP1c), fatty acid synthase (FAS) and stearoylCOA desaturase 1 (SCD1). Source: adapted from (115). *ACC = acetyl-CoA carboxylase; FAS = fatty acid synthase; FBP1 = fructose-bisphosphatase 1; GLUT(1/4) = glucose transporter 1/4; G6P = glucose-6-phosphate; LXR = liver X receptor; PEPCK = phosphoenolpyruvate carboxykinase; SCD1 = stearoyl-COA desaturase 1; SREBP1c = sterol regulatory-element binding protein 1c.

162 in the regulation of lipid biosynthesis, absorption, and their expression is clock-dependent, and controlled by CLOCKBMAL heterodimers and Rev-erb nuclear hormone receptors (118, 119). The RORβ isoform is primarily expressed in a circadian manner in various regions in the central nervous system, SCN, pineal gland, and retina, which are important elements responsible for the control of circadian rhythms, for example, RORβ mutant mice display extended period length in locomotor activity under persistent darkness conditions (120). Taken together, it is conceivable that RORs are key members of the clock feedback loop alongside their function as lipids sensors (Figure 4.13).

4.8.3.2 Peroxisome ProliferatorActivated Receptors (PPARs) There are three PPAR isoforms: PPARα, PPARγ, and PPARβ/δ. The PPAR subfamily of nuclear hormone receptors plays a major regulatory role in energy homeostasis and metabolic function (121). It has long been known that there is a tight interplay between metabolism and circadian clocks. PPARα and PPARγ isoforms directly regulate core clock proteins Bmal1 and Rev-erbα (122). Recent studies using knockout mice show that all PPARs in mouse tissues are expressed synchronously and exert their given metabolic functions in a circadian manner. For example, PPARα transcripts cycle in white adipose tissue, brown adipose tissue, and liver but do not cycle in muscle. PPARγ transcript selectively cycles in white adipose tissue and liver, while PPARδ transcripts exclusively oscillate in brown adipose tissue and liver (118).

4.8.3.3 Peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α) PGC1α is an inducible and potent transcriptional coactivator. PGC1α is expressed in tissues with high oxidative capacity, and is responsible for regulating various cellular energy-related metabolic pathways, including mitochondrial biogenesis and respiration, thermogenesis, and gluconeogenesis (123). PGC1α expression varies rhythmically both in liver and muscle and overexpression of PGC1α also, in turn, induces the expression of core clock genes such as Bmal1, Clock, Rev-erbα, and Rev-erbβ. Although PGC1α does not seem to bind directly to lipids, its key function in regulating lipid homeostasis and its functional interaction with PPARγ suggests the possibility that PGC1α might play a significant role in coupling signals originating from lipid signaling to the core circadian rhythm (124).

4.8.3.4 Rev-erbs: A Family of Nuclear Hormone Receptors Rev-erbs are members of orphan nuclear receptors but differ from other family members as they lack a co-activator-binding domain and as such function as transcriptional repressors. There are two isoforms Rev-erbα and Rev-erbβ, and both are implicated in lipid metabolism and display significant crosstalk with the RORs. RORα and Rev-erbα are major regulators of the cyclic expression of BMAL1. Rev-erbα is a negative regulator of Bmal1 expression and also the CLOCK-BMAL1

Metabolism and Medicine heterodimer regulates the expression of Rev-erbs in a circadian manner. Rev-erb primarily binds to and serves as a heme sensor (125). Several lipid-responsive nuclear receptors, such as ROR and PPARγ together with PGC1α regulate Rev-erb expression and it has been shown that high-fat diet can induce alteration in its expression (15). Studies with Rev-erbs double knockout mice demonstrated their major role in the circadian rhythm as these mice demonstrated arrhythmic gene expression, aberrant locomotor activity and metabolic disorders (126, 127) (Figure 4.28).

4.8.4 Nuclear Hormone Receptors in Metabolism and as Exercise Mimetics A range of NHRs have been revealed to enhance glycolytic metabolism in skeletal muscle whereas others promote oxidative metabolism in fast-twitch and slow-twitch fibers. These NHRs are transcriptional regulators of myogenesis and the metabolic machinery of glycolytic metabolism (in the case of PPARα, VDR, ERs α and β, GR and AR) and aerobic oxidative metabolism (in the case of PPARβ/δ, and γ, Rev-erbα, RORα and ERRs α and γ). In the former case fast-twitch fibers are promoted, simulating resistive training effects, whereas in the latter case slow-twitch fibers are promoted, simulating the effects of endurance training. It is also apparent that thyroid hormones at a low dose induces fast- and slow-twitch muscle fibers via the thyroid hormone receptors α and β, respectively. Rev-erb is a core clock component that regulates the circadian expression and signaling axis of AMPK—SIRT1— PGC1α. PGC1α promotes mitochondrial biogenesis, fatty acid oxidation and other parameters of mitochondrial oxidative metabolism. Furthermore, PGC1α promotes BMAL1 transcription and, accordingly, BMAL1 clock heterodimermediated clock controlled output genes, e.g. NAMPT (nicotinamide phosphoribosyltransferase). This drives NAD+ levels higher, consequently activating SIRT1 resulting in a salutary self-amplifying cascade of enhanced mitochondrial bioenergetics, improved insulin sensitivity, anti-inflammatory, and antioxidant effects as well as other upregulated cell resistance programs including DNA and cell repair, autophagy and even apoptosis. These effects incite a coordinated expression of circadian transcriptional regulators and expression of metabolic genes. Cortisol, the GR ligand, may be activated by exercise, severe calorie restriction and other metabolic stressors such as sepsis. GR is expressed in many tissues. In skeletal muscle, cortisol-liganded GR mediates the breakdown of fast-twitch fibers acutely following resistive training. This precedes the anabolic building phase of muscle mediated by testosteronebound AR. Interestingly, chronic overtraining inhibits this androgenic effect, producing a disquieting and seemingly paradoxical effect of loss of muscle mass. ERRs α and γ both promote the anabolic effects of increased endurance and mitochondrial oxidative metabolism. Although they have distinct profiles of gene expression there is significant overlap. Thus far there are three agonists of NHRs that have been developed as “exercise mimetics”, Rev-erbα, ERRγ, and PPARβ/δ. These are appealing strategies for the prevention and treatment of metabolic disease, noting the high rates of exercise non-compliance. Moreover, they appear potentially to be particularly

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FIGURE 4.28  Insulin, NR, and circadian biology. The loss of healthy circadian insulin sensitivity, resistance and secretion patterns are core features in the development and progression of chronic disease. Source: adapted from (128). *Bmal1 = brain and muscle Arnt-like protein-1 gene; BMAL1 = brain and muscle Arnt-like protein-1; Clock = circadian locomotor output cycles kaput gene; CLOCK = circadian locomotor output cycles kaput; Cry = cryptochrome circadian regulator gene; CRY = cryptochrome circadian regulator; E-box = enhancer box; FXR = farnesoid X receptor; GR = glucocorticoid receptor; GREs = glucocorticoid response elements; HDAC = histone deacetylase; LXR = liver X receptor; NCoR = nuclear receptor corepressor; NR = nuclear receptor; NRE = nuclear receptor response element; Per = period circadian regulator gene; PER = period circadian regulator; PGC1(α/β) = peroxisome proliferator-activated receptor gamma coactivator 1α/β; PPAR(α/γ) = peroxisome proliferator-activated receptor α/γ; Rev-erb(α/β) = Rev-erb(α/β) gene; RIP140, receptor-interacting protein 140; ROR(α/β/γ) = retinoid-related orphan receptor α/β/γ gene; ROR(α/β/γ) = retinoid-related orphan receptor α/β/γ; RXR = retinoid X receptor; SMRT = silencing mediator of retinoic acid and thyroid hormone receptor; SRCs = steroid receptor coactivators.

valuable for individuals who are unable to exercise, e.g. due to disorders such as congestive heart failure and chronic obstructive pulmonary disease. However, they are not without risk, and their safety and efficacies continue to be studied.

4.9 Synchrony and Desynchrony of Environmental and Internal Timing: Clocks and Disease States Einstein was a master not only of theoretical physics but also of powerful quips. He once said: “Life is like riding a bicycle, you have to keep moving to keep from falling”. The moving he mentions refers to his theory of special relativity. We can paraphrase it by saying that time dilates, or slows down relative to the energy one puts into life. The more energy that is put in, the greater the amount of that energy flows through biological chemistry to do work and less of that energy being irretrievably lost to heat. This resultant reduced entropy state is best described in terms of quantum phenomena as the metabolic manifestation of energy production in what we referred to earlier as quantum metabolism. Another quantum biology area, which is seemingly unrelated to quantum biology is quantum consciousness. But is it really unrelated? Since cognitive processes, including mental stress, apply to a top-down regulation of emotion, through psychosomatic interactions they also affect human physiology. Being in a chronic state of stress or anxiety can negatively affect the digestive system in addition to other aspects of compromised health. The opposite direction of psychosomatic interactions also exists. Think about how our state of mind changes after a satisfying meal.

A person can be in a depressive mood but a hearty meal in the company of friends can lift the spirits and change an outlook on life in a relatively short period of time. This can be a more effective practical approach to mood improvement than taking antidepressants. The connection between cognition and metabolism, both of which are essential features of living systems is clear although not very well quantified. Both of these phenomena have been part of the quantum biology framework. Hence quantum metabolism may indeed be linked if not controlled by quantum consciousness. Daily oscillations in the expression of the core clock genes and proteins are present in nearly all cells of the body. These endogenous rhythms appear to be designed to parallel the diurnal light–dark cycle of the external environment. When the endogenous circadian system is not in the correct phase angle with the environment (desynchronized), the fitness of the organism is compromised (Figure 4.29). While most research in this area derives from non-human systems (rodents, flies, bacteria, plants), there is emerging research involving humans. For example, epidemiological studies show an increase in obesity, type 2 diabetes, cardiovascular disease (CVD), cancer, depression, and other disease states in chronic shift workers. Indeed, disrupted circadian clockwork in animal models promotes the development of not only conventional metabolic disorders of obesity and type 2 diabetes, but all major forms of chronic diseases of aging (e.g. CVD, cancers, accelerated cognitive decline, and Alzheimer’s disease) which is consistent with the process of accelerated aging. This makes sense in the context of the premise elaborated on in the body of work of this book that diminished metabolic efficiency underpins the acceleration of aging. The notion that the metabolic cycle is fundamental to a rich

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FIGURE 4.29  Synchronized and desynchronized clocks. When the circadian system is desynchronized with the environment, the fitness of the organism is compromised.

network of cycles across spatial and temporal scales defines the health of any living system. In fact, cycles are the manifestation of time, and since time in an absolute sense does not exist is consistent with the Theory of Special Relativity, the relative nature of time in a living system parallels the relative robustness of this network of cycles. The metabolic cycle of ATP production (Figure 4.9) is fundamental to fueling the bioenergetic demands of the human body across all hierarchical scales of space and time. In this hierarchy, the most microscopic spatial scale is characterized by the highest frequency time scale while the most macroscopic spatial scale corresponds to the lowest characteristic frequency. Intrinsic peripheral clocks and metabolic functioning are synchronized with maximal robustness and amplitude, and with minimal loss of free energy or disturbance in redox balance. Accordingly, this preserves metabolic fitness, and hence promotes health. The broader perspective recognizes a diurnally partitioned metabolic organization, governed by cell biological clocks, evolved to harmonize with the Earth’s rotational rhythm in a circadian fashion. Accordingly, the optimal timing of dietary consumption coincides evolutionarily with the acquisition of food (Figure 4.30). Modern humans evolved due to their environmental conditions with the priority to be active, hunt, gather and eat during the daylight hours (Figure 4.31). The timing of cell clock transcriptional activity evolved to external cues of light/dark adaptively to allow optimized metabolic physiology and behavior. The key to this adaptive evolution is the capacity to anticipate the opportunity

for acquiring food, a metabolic motivation for the sustenance of life. The feeding–fasting cycle may be thought of as a reinforcing external cue further entraining the synchronization of circadian clocks. The tight temporal coupling of clockinduced metabolic pathways promotes energy storage versus energy utilization, which is temporally partitioned into active/ light and inactive (rest–sleep)/dark diurnal phases. This represents an eloquent adaptation to the feeding/fasting cycle. However, in modern human society untimely eating when biological clock activity is geared for fasting and energy storage predisposes to obesity and metabolic disease. This further desynchronizes circadian physiology in a self-amplifying pernicious cascade.

4.9.1 Metabolism Explained by Scales of Time and Space The role of time in metabolism can be viewed in a much broader context than is typically discussed. Scales of time in the universe are interlinked with scales of space. Organization of matter in the universe is hierarchical which means that subatomic structures of elementary particles occupy dimensions below a femtometer (10 -15 m) and are engaged in processes occurring on a time scale shorter than a femtosecond (10 -15 s). The part of physics with relevance to chemistry and hence to biology begins here. Atomic dimensions span a range from an angstrom (10 -10 m), which is roughly the size of a hydrogen atom, all the way to the macromolecular dimensions. Correspondingly, atomic bond vibrations are cyclical processes

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FIGURE 4.30  Hunter-gatherer lifestyle. The optimal timing of dietary consumption coincides evolutionarily with the acquisition of food. Source: adapted from (129). *CNS = central nervous system.

that take place on the time scale of a picosecond (10 -12 s). The world of biomolecules, biomolecular ensembles, their superstructures and higher organizational compositions including organisms covers an enormous swath of sizes between nanometers (10 -9 m) which correspond to protein dimensions to meters corresponding to the dimensions of large organisms with cellular dimension in the range of tens of micrometers. The spread of time scales in biological processes is even larger and it begins at the nanosecond (10 -9 s) range for rapid conformational changes, through microseconds (10 -6 s) for cellular diffusion processes, to milliseconds (10 -3 s) for ion channel opening/closing events to hours (103 -104 s) for cell division to tens of years for life spans of organisms (109 s). Beyond these scales we enter into geological scales of transformations of our planet taking millions of years and thousands of kilometers. The ultimate scale of spatio-temporal organization of matter is that of the Universe itself, which is believed to be 14 billion years old and its size is estimated to be 93 billion light years in diameter, which is an unimaginably large number. This discussion is not only intended to give a humbling perspective on the comparisons of scales of time and space relative to our own physiological scale but also a realization that the Universe operates on the principle of cycles within cycles. We have made a strong emphasis on this idea when discussing our own metabolic cycles and the molecular clocks. Our lives revolve around the cycles of metabolic energy production (1 ms per ATP molecule production), which then combine multiple times to give rise into diurnal cycles governed by the light/dark cycles. Additionally, we are also susceptible to lunar (monthly) cycles and solar cycles of seasons of the year. This is

also important in view of aging which is due to the emergence of the arrow of time resulting from entropy production when perfect periodicity of cyclical reactions becomes compromised due to the wear and tear of the machinery of all living cells. Perfectly cyclical processes, including chemical reactions, do not produce entropy by virtue of being reversible. Only when a process becomes irreversible, does entropy increase between the initial and final states and hence an arrow of time emerges. As we age, this becomes more and more pronounced and many of us unleash a losing battle trying to erase the visible signs of aging. Instead, as we amply advocated in the many sections of Volume 2 of this book, a better approach is to continuously optimize our state of health. We do this by respecting the physiological cycles of sleep/wakefulness, fasting/feeding and other circadian behaviors, adhering to a qualitatively and quantitatively healthy diet, being meaningfully connected to our social network of family, friends and communities, as well as encouraging vitalizing stressors and minimizing toxic stress.

It’s intriguing that this message links physiology once again to physics through some of the most unexpected metaphors. Special theory of relativity teaches us about the possibility of time dilation when we move at a high velocity with respect to the reference frame. This means that time is related to the speed of moving through space compared to a stationary frame of reference. In the limit of attaining the speed of light, time stands still. Hence, we can imagine this as metaphorically

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FIGURE 4.31  Modern-day humans. Modern humans evolved due to their environmental conditions with the priority to be active, hunt, gather and eat during the daylight hours. *ATP = adenosine triphosphate; FA = fatty acid; L/D = light/dark; s. muscle = skeletal muscle.

akin to the relative measure of human lifespan depending on the rates at which internal molecular clocks operate compared to the person’s chronological age. In this vein, when proper synchronization occurs across the human body, these molecular clocks slow down and operate in perfect synchrony leading to a maximum lifespan possible, say 120 years. On the other hand, when they speed up due to the metabolic demands that require faster operations or when they become decoupled from each other as a result of disease states, the lifespan (and the

health span) is shortened. Time dilation in the case of perfect health corresponds to the slowing down of molecular clocks as a function of scale. Time scales are hierarchically linked to spatial dimensions. Fast processes take place on molecular levels while slow processes, due to intricate coupling of many networks, occur on macroscopic levels of organs, tissues, and organisms. Decoupling leads to desynchronization resulting in a speed-up of local processes. This is evident through allometric laws of physiology discussed in connection

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The Biology of Time with quantum metabolism in Volume 1 of this book. Quantum biological processes transcend the classical aging process and slow it down while classical metabolism speeds it up by excessive entropy production leading to biological aging which produces an accelerated diversion from chronological time. For example, an individual whose chronological age is 60, within a one-year period of experiencing chronic stressors or clinical illness, may incur accelerated biological aging of ten years such that at the chronological age of 61, the new biological age is 71 years. In this case, the allometric scaling laws come into play whereby the beta exponent of 3/4 in the quantum metabolic regime changes to isometry (exponent of 1) in classical metabolism increasing the metabolic rate and speeding up aging. However, this is another interesting parallel between relativistic physics and physiology. Namely, time dilation occurs also in the general theory of relativity when an object moves close to a large mass, which “bends” the spatiotemporal continuum. Correspondingly, we can say that we can effectively increase our lifespan by being within the range of attraction of larger masses, which can be understood here as our network of family and friends. This effect helps us reduce the stress we live under by spreading the “toxic load” among our social support system. An anecdote about one of the greatest cosmologists of all time, Stephen Hawking, speaks directly to the important role of the deep human connections to other humans in maintaining our health and extending the lifespan, sometimes even against all odds. When Hawking was diagnosed with amyotrophic lateral sclerosis (ALS) at the age of 22, he told his fiancée that: “The Universe would have no meaning if it were not the home of people you love”. He was given only two years to live by his doctors, which is indeed typical for this stage of the disease. At that time he was only two years into his Ph.D., which he completed two years later at 24, then went on to marry, have three children, and hold the Lucassian Professorship in Mathematics at the University of Cambridge, the most prestigious academic position in the world established in 1663 that had been held in the past by none other than Sir Isaac Newton. Hawking contributed more to the physical sciences than anyone since Einstein, creating legacies along the way that gave him the will and the purpose that with the support of others helped him survive for 54 years following this dreadful diagnosis! He played an iconic role in science, both high-brow and popular, by attracting the fascination of fellow researchers in the field of modern cosmology as well as generating public interest in science and in scientists. Writing popular books and giving public lectures and interviews may have equaled or even exceeded his personal contributions to scientific literature. In connection with the Physiological Fitness Landscape, examples like this may pose an important challenge to incorporate in its quantitative algorithms such aspects as the meaningful life, a life lived with a purpose, grit and determination as well as the support network of family, friends and professional colleagues. This invokes the notion of physiological purpose, and the significance of networks of support systems that promote survival of life forms at all scales. One of the closest collaborators of Hawking’s was Sir Roger Penrose. In a recently published breath-taking prediction, this 2020 Nobel Prize winning physicist, and another cosmologist

of greatest caliber, proposed the idea of a cyclical Universe, which oscillates between a Big Bang and a contraction to a massive black hole, followed by another Big Bang, etc. forever into the future. These cyclical universes are envisaged to be all born at the moment of a Big Bang and die with a black hole collapse of all matter and light into a singularity point. The period of these enormously long oscillations has been named an aeon. If true, the superposition of both cyclic and entropic processes that manifest our human physiology as we have stressed repeatedly in this book is a metaphor for the entire Universe where the emergence of a first black hole in the tapestry of galactic matter signals a gradual descent into a cosmic period of aging culminating with a total collapse. One can’t help but marvel at how beautifully poetic and optimistic is Penrose’s promise of a rebirth of the Universe following its collapse into a singularity point.

4.9.2 Common Causes of Circadian Disruption There are many common causes of circadian disruption. The most obvious are shift-work, jet-lag, or caring for an infant. However, circadian disruption can also easily be caused by social jet-lag (shift sleep–wake and/or eating patterns by more than an hour on days off compared to workdays), erratic eating patterns (large variation in first and last mealtime and/or long eating window greater than 12 hours), and even with natural aging. This is because in each scenario, the body’s internal clocks are receiving inconsistent and/or conflicting cues to reset which causes circadian rhythms to dampen. When the peripheral clocks receive conflicting signals from the brain and gut, such as eating overnight or alternating shift work, metabolic pathways within and between tissues become desynchronized and may then undergo pathological changes. This can manifest, for example, in disturbances of glucose metabolism and cardiovascular disease. This may be illustrated by the dyssynchrony that occurs in type 2 diabetes when postprandial hyperglycemia accompanies relative hypoinsulinemia, or alternatively, three-hour postprandial hypoglycemia accompanies hyperinsulinemia. Similarly, fasting hypoglycemia often occurs in the setting of hyperinsulinemic insulin resistance in the absence of type 2 diabetes. The concept of insulin resistance deserves further mention, which is particularly applicable to circadian rhythms. It has been largely overlooked that insulin resistance may be considered a sine qua non of cardiovascular disease. Lipolytically active adipose tissue’s release of free fatty acids inhibits catabolism of apoB lipoproteins in the liver. This promotes the formation of small dense LDL particles, the atherogenic underpinnings of cholesterol as a Framingham cardiovascular disease risk factor. Furthermore, hyperinsulinemia drives tissue growth including intimal hyperplasia, vascular smooth muscle mitogenesis, and fibromuscular hypertrophy. The state of insulin resistance is a hypercoagulable, antifibrinolytic and prooxidative/ pro-inflammatory state, all characteristics of cardiovascular disease. Additionally, the conventional Framingham cardiovascular disease risk factors (obesity, low HDL and type 2 diabetes) are all powerfully connected to insulin resistance, and it should be proposed (as this author has in a still unpublished document entitled “Framingham Reframed”)

168 that insulin resistance is a more primary control parameter. Nonetheless, it is worth keeping in mind that hypertension poses residual risk after controlling for insulin resistance. This makes sense in the context that free energy compromise and redox/inflammatory stress, as the most fundamental control parameters of disease, are bidirectionally and directly linked to insulin resistance. This book has emphasized the importance of these factors within a framework for a fitness landscape model of medicine. These ideas cannot be extricated from clock-driven physiology and pathophysiology. Thus, as one relevant conclusion, the high incidence of cardiovascular disease in alternating shift workers is rooted in a disturbance in circadian clock mediated metabolic disease (Figure 4.32).

4.9.3 Sleep The regulation of sleep–wake cycles is under a strong influence from SCN-dependent signals (see Section 4.6.1) in combination with homeostatic sleep-pressure that builds throughout waking hours. There is evidence to suggest that circadian systems may have a role in sleep pressure, and vice versa, since genes involved in both processes have shown reciprocal regulation (130). Moreover, the circadian system regulates the consolidation of sleep, helping to maintain sleep once the homeostatic drive for sleep is lifted (131). Indeed, recent evidence suggests that circadian clocks and the sleep– wake cycle work in concert to support proper physiological function. Studies in mice have revealed that both circadian clocks and the sleep–wake cycle contribute to synaptic function in the forebrain (132). In this manner, circadian clocks are responsible for establishing 24h rhythms in levels of the messenger RNA coding for many proteins involved in synaptic function, whereas intact sleep–wake cycles are required for proper translation (132). Should such a finding be demonstrated to hold physiological relevance for humans, this may hold implications for understanding the negative impacts of altered sleep schedules caused by rotating shift work schedules on cognition and mental health (133). Coincident with misalignment of sleep timing with endogenous signals emanating from the central circadian clock, cycles of alternating shift work are associated with a decrease in the amount of sleep (134). Sleep deprivation, reduction in sleep duration, and poor sleep quality have been linked to a variety of adverse health outcomes, ranging from depression to metabolic disorders such as type 2 diabetes, obesity and cardiovascular disease (135, 136). The extent of sleep loss caused by rotating shift work can be mitigated in part by reducing the speed of change of the shift schedules for workers (137). In children, reduced sleep duration is linked with an increased risk of becoming overweight (138). A gradual decline in sleep duration or an extension of activity during the night might interrupt synchrony between sleep–wake cycles and create irregular periods of feeding, fasting, energy storage, and energy utilization. Furthermore, the stimulation of hunger might be related to reduced circulating levels of leptin (which suppresses hunger), and increased levels of the ghrelin (orexigenic hormone which

Metabolism and Medicine stimulates appetite), both of which are induced by sleep deprivation. Aside from the amount of sleep, research indicates that shift work can also affect the timing and quality of sleep. In an animal model of environmental circadian disruption, in which mice were subjected to 10h:10h periods of light/dark, the amount of sleep remained constant, but timing and quality of sleep was altered (139). This model of environmental disruption was also associated with alterations in immune responses in these mice (139), which may mirror immunological effects observed in shift workers (140). Using the United States as an example, approximately 2.7% of the working population are engaged in rotating shift work (141), that is alternating between different schedules of day and night work, therefore finding ways to reduce circadian desynchrony and improve health outcomes is critical. An important point regarding the disruption of the sleep/ wake cycle and its impacts on biological function is that the sleep/wake cycle occurs in antiphase with periods of feeding/ fasting and activity. Therefore, modern disturbances on sleep such as those induced by alternating shift work cannot be considered as an effect on sleep alone (see Figure 4.32). In particular, evidence suggests that the effect of shift work must also be considered in regard to its impact on feeding/fasting cycles. Timing of food consumption in humans plays a significant role in controlling systemic metabolism; alteration of the feeding-period even within waking hours can induce changes in tissue and serum metabolites (142), indicative of altered metabolic function. Such changes in feeding behavior may underlie the myriad changes in 24-hour rhythms of circulating metabolites detected in human laboratory studies mimicking the adaption from day shift to night shift work (143). Hence, adverse effects of altered sleep cycles cannot be considered in isolation to these other contributory factors to metabolic and overall health. Importantly, diseases related to changes in the quality of sleep and sleep duration are also connected with metabolic disorders. For instance, sleep apnea, which is prevalent in metabolic syndromes, is associated with dysfunction of clock genes, while the treatment of sleep apnea leads to improved glucose homeostasis and energy metabolism. One important hormone, melatonin, is the key physiological sleep regulator in humans. Genome-wide association studies have recently reported that melatonin is implicated in the regulation of circadian rhythms and may be important in governing whole-body glucose homeostasis. Moreover, melatonin supplementation improves sleep in hypertensive patients (144). Dysregulation of melatonin production is associated with hypertension, type 2 diabetes and cardiovascular disease (145–148). Taken together, these studies indicate that misalignment between the circadian timing system, and daily rhythms of wake-sleep behavior and food intake contribute to the development of obesity, obesitylinked diabetes, and chronic insulin resistance. However, understanding the molecular mechanism of metabolic syndromes in states of disrupted sleep requires further investigation.

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FIGURE 4.32  Shift work and metabolism. Shift workers have disturbed circadian clocks that mediate metabolic disease. *FOXO = Forkhead Box O; GH = growth hormone; IR = insulin resistance; Mt = mitochondria; M1 = melatonin receptor 1; OSA = obstructive sleep apnea; SCN = suprachiasmatic nucleus.

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4.9.4 Circadian Interactions with Nutrient Balance in Health and Disease Extension of human lifespan is among the most ancient and eagerly sought endpoints of scientific investigation. While countless non-pharmacologic strategies have been proposed throughout history, a few have emerged as being particularly consistent in their ability to increase longevity across research paradigms—calorie restriction, intermittent fasting, and routine exercise. The mechanisms underlying this benefit are not yet fully elucidated but appear to involve circadian metabolism and biological clock functions. In essence, each of these physiological states appears to exert some influence on the fundamental mechanisms that regulate the passage of biological time. In addition, they collectively suggest that nutrient sensing and metabolism play a role in the “biology of time” and provide a potential target for enhancing longevity. The major cellular energy sensors in the body are sirtuin 1 (SIRT1) and the “fuel gauge” AMP-activated protein kinase (AMPK). SIRT1 is a nicotinamide adenine dinucleotide (NAD)+-dependent deacetylase enzyme, which is upregulated by the rhythmic expression of the clock-controlled output gene product nicotinamide phosphoribosyltransferase (NAMPT). The latter serves as the rate-limiting biosynthetic enzyme for NAD+ and its reduced form, NADH (nicotinamide dinucleotide hydrogen). The upregulation of SIRT1 deacetylase activity is crucial to counterbalance the acetylase activity of the CLOCK protein. CLOCK is a core circadian element that modulates gene transcription/chromatin conformation and appears to demonstrate a “yin-yang” biochemical relationship with SIRT1. For example, SIRT1 possesses histone deacetylase (HDAC) activity, while CLOCK manifests histone acetyltransferase (HAT) activity (Figure 4.33). HDAC enhances gene expression by forcing histone away from the promoter region of the gene. This induces a conformational change in chromatin structure that increases the available space for transcriptional machinery. Inversely, HAT condenses chromatin and reduces gene expression. This competitive relationship of SIRT1 and CLOCK extends well beyond histone modification and appears to be represented in circadian networks. In the case of core clock proteins, CLOCK provides stabilizing acetylation of both BMAL1 and PER2. Meanwhile, SIRT1 has been noted to promote destabilization of these proteins. Even with regard to sensation of cellular energy, SIRT1 and CLOCK exhibit counter-regulatory activation by NAD+- and NADHdependent energy pathways, respectively (Figure 4.33). Analogous to SIRT1 activation, which depends on the ratio of NAD+/NADH, AMPK activation depends on the ratio of AMP/ATP. Much like the reciprocal relationship of SIRT1 and CLOCK, SIRT1 and AMPK demonstrate differential responses to nutrient depletion. In the context of ATP depletion, SIRT1 transcriptionally regulates liver kinase B1 (LKB1) to promote activation of AMPK and replete ATP stores. This is accompanied by the rapid phosphorylation of rate limiting enzymes for fatty acid oxidation (acetyl-CoA carboxylase, ACC) and cholesterol synthesis (3-hydroxy-3-methyl-glutaryl-coenzyme A reductase, HMGCR). AMPK also promotes long-term fatty acid oxidation by inducing phosphorylation of peroxisome proliferator-activated receptor gamma coactivator 1α (PGC1α). This drives glucose metabolism by

Metabolism and Medicine augmenting PGC1α-dependent glucose transporter type 4 (GLUT4) expression and translocation to the cell membrane. In addition to supporting ATP production, AMPK also mitigates ATP consumption by inhibiting ATP-demanding biosynthetic processes (e.g. anabolism and cell replication). In this sense, AMPK serves as a biomarker for energy depletion by responding to the stimuli that restrict ATP availability (i.e. calorie restriction, fasting, and exercise) and engaging counterregulatory pathways (e.g. hunger and food seeking behavior in the hypothalamus). It is notable that this effect of AMPK activation occurs in response to any stimulus that impairs ATP production, including ischemia, hypoxia, and oxidative redox stress (Figure 4.33). The prevailing theme of this discussion is that SIRT1 and AMPK are inextricably implicated in healthy aging. These ancient systems serve to liberate energy stores (e.g. mitochondrial lipid oxidation) and engage feeding behavior during times of scarcity. This has great clinical relevance to modern society, as living conditions have rapidly diverged from those in which we evolved. Humans have spent millennia in the face of nutrient scarcity, with the rare opportunities to feed being burdened by a high energy demand. The principles of Darwinian fitness have necessitated that that we seek meals persistently, consume ravenously, store fat efficiently, and conserve energy in order to survive; however, advances in agricultural science (e.g. fertilizers, pesticides) and manufacturing have witnessed an unprecedented expansion of the global food supply chains. With an abundance of calorie-rich foods and little to no physical demand for obtaining it, obesity and its medical comorbidities have run rampant in developed countries. While medical intervention has increased lifespan in these regions, health span has appeared to stagnate. Modern day humans are now spending greater proportions of their lives in infirmity due to chronic illness caused by cancers, cardiovascular disease, accelerated cognitive decline, and dementia. In this regard, adaptive mediators like SIRT1 and AMPK may prove to be viable targets for future pharmaceutical development or personalized medicine. While such advances remain to be substantiated, several non-pharmacologic strategies can be leveraged in the present. Calorie restriction and intermittent fasting have been demonstrated to amplify the mitochondrial enzyme activity responsible for burning fat through oxidative phosphorylation. When coupled with moderate intensity exercise, oxygen consumption and ATP utilization increase dramatically. This raises the ratios of NAD+/NADH and AMP/ATP, potentiating the activity of SIRT1 and AMPK. This activation also extends to circadian networks in a feedforward reciprocal fashion. For example, AMPK phosphorylates CRY1 core clock components, promoting negative feedback regulation of the circadian rhythm. As described above, SIRT1 regulates clock rhythm via deacetylation of clock components like BMAL1. This occurs in temporal antiphase with the acetylation activity of the CLOCK protein. Circadian clock acetylation activity, as well as the counter-regulating deacetylase actions of SIRT1, are linked to functions of several mitochondrial enzymes involved in oxidative metabolism. Similar behavior is apparent for the regulation of mitochondrial biogenesis (e.g. mediated by PGC1α) and redox stress resistance of the cell (e.g. mediated by forkhead box O (FOXO) transcription

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FIGURE 4.33  The intersection of circadian and metabolic rhythms. AMPK and SIRT1 are master metabolic regulators and energy sensors of metabolism. They are central to the coupling and decoupling of circadian and metabolic rhythms which are critical for maintaining health and developing chronic disease.

172 proteins) (149). Further, AMPK appears to regulate SIRT1 activity via NAMPT, directly or indirectly. (The latter proposed via AMPK activation of NAMPT, increasing intracellular NAD+ concentration, and the NAD+/NADH ratio.) Noting that AMPK and SIRT1 sequentially phosphorylate and deacetylate PGC1α and FOXO, respectively, one can appreciate the feedforward, self-amplifying nature of these pathways. Indeed, dietary restriction practices and exercise can even induce SIRT1 deacetylation of LKB1, the upstream activator of AMPK (Figure 4.33). The core clock components (Figure 4.14) can be likened to the proverbial gears of a mechanical clock. In this regard, various tissues and cells occupy specific “time zones” with differential physiological conditions and clock-controlled gene output. The “hands” of the clock signify circadian phase progression and vary according to the cell types and pathways that are locally present. When a subset of clocks coherently aligns (e.g. via clock-controlled gene output), their activity is coordinated to promote adaptive physiology and homeostasis. Activation of AMPK and SIRT1 are fundamental responses to energy stress and teleologically rooted in nutrient scarcity. They are activated at a critical threshold of calorie restriction to prevent the maladaptive repercussions of starvation, including immunocompromise, catabolic metabolism, and generalized dysregulation of homeostasis. However, as the challenge facing modern society morphs into one of energy excess, the clinical strategy of medicine must also adapt to accommodate it. That is, to manipulate nature’s design of circadian rhythmicity and the metabolic physiology that evolved for over 200,000 years. A non-trivial task, to be certain, but one that begins with a depth of understanding for the systems involved. This may be exemplified by the modulation of ion transport illustrated in the figure below. Inhibitory in some cases and stimulatory in others, it enhances the energy expending processes that burn excess adiposity and prevent chronic disease. In general, metabolic regulation enriches mitochondrial function (e.g. via the transcriptional coactivator PGC1α). Meanwhile, mitochondrial dysfunction is a hallmark of insulin resistance and metabolic disease. In this framework, it is not surprising that AMPK and SIRT1 demonstrate insulinsensitizing effects, orchestrated by nuclear hormone receptors and transcription factors. These include the inhibition of hepatic glucose output, lipogenesis, and cholesterol synthesis. In the case of lipogenesis, this serves to prevent excess adipose deposition and the ischemic/inflammatory changes that occur as a result. When fatty acids and proinflammatory cytokines spill into circulation, they seed ectopic lipid accumulation in systemic tissues (e.g. liver, skeletal muscle, pancreas, and brain). This process both causes and amplifies the metabolic disturbances that lead to insulin resistance. Exceptions do exist, however, in the way that SIRT1 modulates fatty acid and lipid synthesis. Somewhat paradoxically, SIRT1 activity actually promotes lipogenesis via LXR. It is notable, however, that LXR also serves to prevent cellular toxicity by allowing the esterification of free cholesterol. Indeed, an increasing ratio of free cholesterol to phospholipid produces membrane stiffness that impairs the function of surface receptors and transporters. Further, the actions of LXR occur in temporal antiphase to

Metabolism and Medicine those of SIRT1 and AMPK (i.e. LXR in the fed state, SIRT1 and AMPK in the fasted state). Perhaps more perplexing is the opposing action of LXR and FXR. Both appear to be active in the fed state and the active phase of the circadian cycle. These two nuclear factors lower total body cholesterol—FXR by converting cholesterol to bile acids and LXR by inhibiting cholesterol biosynthesis and reversing cholesterol transport (Figure 4.33). Insulin secretion is also under circadian regulation. For example, nuclear receptors LXR and PPARγ are entrained to the fast–feeding cycle that is mediated, in part, by the stimulating effects of insulin. When insulin levels are low (i.e. during the fasted state), PPARγ has been noted to promote energy mobilization from fat stores and liver. This effect is reversed in the presence of insulin (i.e. during the fed state), with PPARγ causing fat storage and insulin sensitivity. This is consistent with the insulin clamp studies, which demonstrate PPARγ agonist therapy to upregulate skeletal muscle glucose uptake. It may also explain how PPARγ simultaneously correlates with both regression of visceral adiposity (e.g. hepatic steatosis) and increasing peripheral subcutaneous adiposity. Further, deacetylation of PPARγ by SIRT1 appears to reduce the lipogenic response driven by LXR and insulin. This effect demonstrates negative feedback such that PPARγ may bind its response element on the SIRT1 promoter or incite direct inhibition of SIRT1 activity. This increases lipogenesis when energy consumption exceeds expenditure. The metabolic range prior to the development of insulin resistance may be the extent that the PPARγmediated adipogenesis continues to occur. This process comes at a cost, however, given that the feedback inhibition of SIRT1 effectively compromises its ability to regulate other metabolic pathways (Figure 4.33). This includes insulin sensitization (e.g. mediated by AMPK, PPARγ, and mitochondrial biogenesis by PGC1α), anti-inflammatory actions (e.g. inhibition of NF-kB), metabolic flexibility, and stress resistance programs (e.g. mediated by FOXO transcription factors). PPARγ inhibition of SIRT1 may represent a compensatory mechanism for governing the over-abundance of net positivity energy. In the absence of clinical insulin resistance, the “space” over which this occurs is characterized by synchrony of the oscillations and magnitudes for the transcriptional regulators modulated by the fast–feeding and activity-rest cycles. In other words, the behaviors that contribute to energy balance (e.g. feeding, physical activity, sleep) must be qualitatively and quantitatively paired to ensure optimal health and prevent disease.

4.9.5 Glucose, Insulin, and Metabolic Disease Insulin resistance is a key conduit to the transition from the prolonged allostatic stress response to chronic disease states (Figure 4.34). Energy availability is fundamental to survival, and insulin resistance is an outcome of the stress response because an animal or predecessor human in danger has no time to stop and feed. This is probably a response adaptation to promote survival because access to energy resources become unavailable. In this context, insulin resistance is adaptive for the provision of energy when it is inaccessible extrinsically. Alternatively, insulin resistance is also adaptive in the setting

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FIGURE 4.34  The development of insulin resistance. Insulin resistance abrogates the circadian cyclicity patterns that are fundamental to healthy metabolism, physiology, and behavior. *ACC = acetyl-CoA carboxylase; Apo B = apolipoprotein B; ATP = adenosine triphosphate; CD36/FAT = fatty acid translocase; CHO = carbohydrate; CoA = coenzyme A; ER stress = endoplasmic reticulum stress; FA = fatty acid; FADH2 = flavin adenine dinucleotide hydrogen 2; GCK = glucokinase; GTP = guanosine triphosphate; IR = insulin resistance; Mt = mitochondria; mTOR = mechanistic target of rapamycin; NADH = nicotinamide dinucleotide (reduced form); Ox phos = oxidative phosphorylation; PI3/AKt/PKB pathway = phosphoinositide 3-kinase protein kinase B pathway TCA = tricarboxylic acid; TG = triglyceride; VLDL = very low-density lipoprotein; UPR = unfolded protein response.

174 of excess energy stores in the body such as adipose tissue spilling over fatty acids and hepatic fat accumulation causing endoplasmic reticulum stress. In these latter cases, insulin resistance protects metabolic tissues from further energy influx that threatens the health of the tissue and by extension the life of the animal or human. In this latter context despite extrinsic energy resource availability, the body has evolved mechanisms of self-imposed restriction of nutrient uptake into cells of metabolic tissues. However, the adaptive nature of these responses, like the neuroendocrine and autonomic stress response in general, are only transient. It is up to the free will and self-restraint of the individual to self-impose dietary calorie restriction. Insulin resistance, like the broader stress response, is only adaptive when temporary in nature. Otherwise, it abrogates the circadian cyclicity patterns that are fundamental to healthy metabolism, physiology, and behavior. Allostasis maintains homeostasis within the temporal dynamics of natural cycles. If it extends beyond the circadian cycle, such as circannual (annual cycle) insulin resistance in hibernating bears or migrating birds, it is referred to as allostatic overload (150), but is nonetheless adaptive in these species in the sense that it promotes survival. However, chronic insulin resistance in humans is maladaptive, and is called allostatic overload. It follows that the purpose of physiological insulin resistance is an adaptation to provide energy to nonmetabolic tissues, such as the brain, in energetically demanding circumstances that invoke the responses of calorie restriction. Exploiting the evolutionary advantages of calorie restriction is one method to achieve post-reproductive longevity and prolonged health span. This can be achieved through dietary or pharmacologic means whereby AMPK activation cues the body that there is low energy availability. Accordingly, when the fuel gauge is low the cell recognizes energy deprivation triggering the activation of catabolic pathways for ATP production (Figure 4.35).

FIGURE 4.35  AMPK and ATP production. AMPK activation cues the body that there is low energy availability which triggers ATP production. Source: adapted from (151). *AMPK = AMP-activated protein kinase; ATP = adenosine triphosphate; CD36/FAT = fatty acid translocase; GLUT4 = glucose transporter 4.

Metabolism and Medicine The adaptive nature of insulin resistance is rooted in the cyclical context that alternates insulin-resistant periods of fasting with insulin-sensitive non-fasting. Insulin resistant periods of fasting are coupled to metabolic pathways that break down energy stores to increase free energy that is needed to maintain cell homeostasis. Crucial components of cell homeostasis are the programs of cell resistance that 1) repair (e.g. DNA endonuclease or telomerase) or remove organelles (autophagy) and 2) restore antioxidant systems that have been damaged or depleted by redox stress. Redox stress is increased by metabolically challenging the feeding phase of the daily cycle, i.e. by eating at the wrong time of day. The predicted feeding phases also coincide with the metabolic demands of energy expenditure from visceral activity (i.e. heart, lungs, gut, etc.). Feeding provides an influx of electrons into the mitochondrial electron transport chain that exceeds the extent of influx during the non-fed fasting state. Often, this influx is beyond the threshold of the capacity for transferring those electrons to oxygen forming water molecules coupled to the production of ATP. This occurs when caloric intake is greater than the composite of the energy expended by activity in addition to the demands of biosynthetic anabolism. That is, there is more energy consumed than is used. Not all of the electron carrying capacity of the electron transport chain is transferred to oxygen in the formation of water coupled to the production of ATP. There is a physiological degree of superoxide and other reactive oxygen species that are important for cell signaling. Similarly, there is a physiological degree of uncoupling of electron transport and loss of the associated proton gradient to ATP production necessary for physiologic thermogenesis. Nevertheless, the phenomenon of quantum metabolism described by Demetrius et  al. suggests that the metabolic mode of energy production switches from quantum to classical regime when electron transfer exceeds the “take-over” threshold (152). In this case, the entropy production rate is increased in association with redox stress. Interestingly, many of the processes of biosynthetic anabolism are temporally synchronized to occur in the fasting state when they do not compete with the energy expenditure of activity and the stress response. There is a narrow range of energy and redox homeostasis in both the fasting and feeding states in terms of supply and demand. In the fasting state, relatively low insulin signaling occurs in the metabolic tissues (skeletal muscle, adipose and liver), allowing nutrient availability to non-classical “metabolic” tissues, those that do not require insulin signaling for glucose and lipid uptake and regulation. When circadian rhythms of insulin secretion and peripheral sensitivity are maintained, insulin levels during fasting are substantially lower than in a fed state. In non-classical “metabolic” tissues, insulin sensitivity is maintained even in a fasted state. Accordingly, lower insulin levels are sufficient to mediate cellular anabolic and mitogenic effects of these tissues and organ systems. However, the circadian insulinopenia and accompanying resistance does limit insulin signaling in classical “metabolic” tissues during the nocturnal fasting state. Insulin resistance is due to the down-regulation of insulin receptors. Reduced insulin sensitivity in skeletal muscle and adipose tissue during the fasting state, and thus decreased glucose uptake and increased fatty

The Biology of Time acid release respectively, increases the availability of these nutrient substrates to tissue cells systemically (Figure 4.38). Synchronously, physiological circadian insulinopenia and insulin resistance contribute to the disinhibition of suppressive effects of glucose and lipid output from the liver. It follows that in the context of the loss of circadian rhythm, with coexisting relative hyperinsulinemia and accompanying high levels of fatty acids and glucose available to the cells of epithelial tissues, pathological effects ensue (see Chapter 6). Such driving effects include those on cell anabolism and mitogenesis that fuel, for example the growth and proliferation of cancers. Indeed, cancer is an unfortunate sequela in chrono-physiologically impaired states, including non-circadian insulin resistance and associated type 2 diabetes (Figures 4.36 and 4.37).

4.9.6 Cyclical Insulin Resistance and the Role of Forkhead Box O (FOXO) Transcription Factors Cyclical insulin resistance can have an annual cycle (circannual) in some animals as well as a daily cycle (circadian) in humans. In some animals, circannual insulin resistance is an adaptive phenomenon in response to prolonged fasting when food availability is low. During prolonged fasting, AMPK is increased and activates FOXO transcription factors that promote gene transcription that drive glucose output from the liver and fatty acids from adipose tissue. They also activate stress resistance programs in various tissues. AMPK also activates PGC1α that in turn promotes mitochondrial energy production and mitochondrial biogenesis. It appears that this phenomenon of circannual insulin resistance coupled to prolonged fasting exploits the notion of hormesis, such that the accumulation of energy stores preceding the prolonged period of fasting ensures that the level of stress of the non-fed state

175 is not so severe that the cell is unable to recruit the necessary resources. AMPK in a number of animal models has been demonstrated to promote longevity. This is likely mediated by enhancing mitochondrial fitness of aerobic oxidative metabolism via triumvirate activation of FOXO transcription factors, SIRT1 and PGC1α. Although it is very difficult to separate the roles of SIRT1 and PGC1α, it appears that SIRT1 is an important regulator of lifespan (Figure 4.38). SIRT1 deacetylation and AMPK phosphorylation of FOXO transcription factors combine their effects leading to activation of FOXO proteins in the setting of dietary nutrient deprivation (Figure 4.39). Once activated, FOXO transcription factors play an important role in the expression of genes that increase hepatic glucose production by up-regulating glucose 6 phosphatase activity, a rate limiting enzyme of both glycogenolysis and gluconeogenesis. FOXO transcription factors also repress glucokinase in the liver which further promotes the release of glucose from the cell to be made available to tissues systemically. In insulin resistance, FOXO transcription factors are abnormally upregulated due to the impaired responsiveness of insulin signaling that prevent FOXO migration into the nucleus where these transcription factors can interact with DNA binding sites. Thus, both energy deprivation and insulin resistance share a common molecular link to FOXO proteins to promote glucose availability to non-metabolic cells in the body. In the context of cyclical insulin resistance (circannual or circadian), it is important to distinguish the regulatory role of FOXO transcription factors to redox stress in non-cyclical pathology of increased insulin resistance in muscle. During the active phase, to accommodate physically demanding metabolic circumstances, insulin secretory patterns that match the feeding state maintain euglycemia, while inhibiting the output of lipids and glucose from the liver and adipose tissue.

FIGURE 4.36  Insulin resistance (IR) pathways. Skeletal muscle insulin resistance versus systemic insulin resistance. *AD = Alzheimer’s disease; DAGs = diacylglycerides; Dysfx = dysfunction; FAO = fatty acid oxidation; FFA = free fatty acid; IMCL = intramyocellular lipid; IR = insulin resistance; Mt = mitochondria; PKC = protein kinase C; s. muscle = skel. muscle = skeletal muscle; T2D = type 2 diabetes.

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FIGURE 4.37  Major zeitgebers and circadian cycles. Summary of metabolic pathways associated with major zeitgebers and nervous system regulation of these pathways. *ATP = adenosine triphosphate; BAT = brown adipose tissue; BMAL1 = brain and muscle Arnt-like protein-1; CAD = coronary artery disease; CVD = cardiovascular disease; CRY1/2= cryptochrome circadian regulator 1/2; DHEA = dehydroepiandrosterone; DMV = dorsal motor nucleus; GH = growth hormone; HDF = high-fat diet; HPA = hypothalamic-pituitary-adrenal axis; HPG = hypothalamic-pituitary-gonadal axis; HPT = hypothalamic-pituitary-thyroid axis; HTN = hypertension; IGF(1) = insulin-like growth factor(1); LC/NS = locus coeruleus/nervous system; L/D = light/dark; LHA = lateral hypothalamus; MS = metabolic syndrome; NTS = nucleus tractus solitarius; PER1/2/3 = period circadian regulator 1/2/3; PFC = prefrontal cortex; PVN = paraventricular nucleus; ROR = retinoid-related orphan receptor; SCN = suprachiasmatic nucleus; T2D = type 2 diabetes; VLM = ventrolateral medulla; VTA = ventral tegmental area.

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FIGURE 4.38  SIRT1, AMPK, and aging. SIRT1 is an important regulator of lifespan. Increase in the NAD+/NADH ratio activates SIRT1, which acts positively on AMPK. AMPK increases as the AMP/ATP ratio does. SIRT1 and AMPK activate PGC1, which induces mitochondrial biogenesis, and FOXOs, which induce autophagy. Source: adapted from (153). *AMP = adenosine monophosphate; AMPK = AMP-activated protein kinase; ATP = adenosine triphosphate; eNOS = endothelial nitric oxide synthase; FOXO = Forkhead Box O; FXR = farnesoid X receptor; LKB1 = transcriptionally regulates liver kinase B1; NAD+ = nicotinamide dinucleotide; NADH = nicotinamide dinucleotide (reduced form); NAMPT = nicotinamide phosphoribosyltransferase; NF-κB = nuclear factor kappa B; NHRs = nuclear hormone receptors; PGC1α = peroxisome proliferator-activated receptor gamma coactivator 1α; SIRT1 = sirtuin 1.

Alternatively, overnight fasting represents the timeframe of physiological circadian insulin resistance when neither physical activity nor feeding behavior are required from an anticipatory perspective. Accordingly, nutrient and energy requirements are provided by output of substrates from the liver and adipose tissue. This occurs in parallel with reduced skeletal muscle uptake consistent with the pattern of metabolic tissue insulin resistance that promotes organism wide homeostatic stability (Figure 4.40). It is in the context of these cyclical patterns of insulin sensitivity followed by insulin resistance, whether in the circannual or the circadian timeframe that the upregulation of FOXO transcription factors in the insulin phase are adaptive both in terms of nutrient output as well as upregulation of cell resistance to redox stress that mounted during the insulin sensitive phase.

4.9.7 Circadian Misalignment of Endogenous Oscillating Cycles Contribute to Metabolic Disease and Chronic Disease of Aging The extrinsic control parameters that cause human disease can largely be categorized as 1) circadian misalignment of light–dark and feeding-fasting cycles, 2) the stress response, and 3) the quantity and quality of diet. The misalignment of endogenous circadian cycles to the light–dark and feeding-fasting cycle represents a temporal disorganization of metabolic processes and the energetic demands of biological and physiological processes that they subserve. The stress response is in fact an intrinsic control parameter for the reality of external

177 circumstances, which an individual faces and adjusts his/her behavior to. Depending on this interpretation of the stress, the limbic system activates autonomic pathways to the hypothalamus, largely the paraventricular nucleus within the hypothalamus, which in turn ultimately mediates neuroendocrine hormonal and sympathetic nervous system output (Figure 4.41). The latter may represent allostatic adaptive physiology. Alternatively, if this stress response is prolonged or severe, the autonomic and neuroendocrine responses suppress the immune system. This can have a number of punitive effects on human physiology. Immune system dysfunction, for example, results in a pro-inflammatory response with upregulation of reactive oxygen species. This results in oxidative stress that impairs the antioxidant regulatory system by overburdening it. It also leads to such changes as ultimately disturbing the circadian alignment to the light–dark cycles. For example, the neuroendocrine stress response that results in the loss of circadian rhythm of cortisol production may prevent the induction of slow wave sleep. This in turn leads to reduced nocturnal growth hormone and testosterone (in males), both of which play critical roles in regulating telomerase and antioxidant systems. This regulation is necessary for maintaining homeostasis of redox and of DNA repair so that cell replication can occur while preserving the integrity of the telomeres at the ends of chromosomes. Telomere integrity is needed for maintaining the structural integrity and function of the genes that compose the chromosomes. The converse, in fact, is an important point of departure for mutagenesis and carcinogenesis such as breast and prostate cancer, which are well-known to be associated with circadian misalignment. Immune suppression from prolonged activation of the HPA axis leads to resistance of immune cells to cortisol suppression, which in turn is an important mechanism for the pro-inflammatory response that ultimately occurs with a prolonged stress response. This is one of the mechanisms through which the pro-inflammatory dominance germinates from immune dysfunction. Also, it should be noted that the sympathetic nervous system’s autonomic branch of the stress response, similar to the HPA axis suppression of the immune system, also faces the development of resistance phenomena from the immune cells. Another fundamental player in the pathogenesis of immune dysfunction in human disease is the effect on the gut microbiota. Both immune suppression states of the stress response as well as the resistance that follows the immune suppression contribute to an altered pathogenic composition of the gut microbiota. In the case of immune suppression of cortisol, which is the predominant suppressor, the T helper 1 branch of the immune response is preferentially affected. Accordingly, intracellular viral infections, for example herpetic processes, are allowed to get out of control, escaping normal immune regulation. In recent years, this has been proposed to be a cause of diabetes type 1 by making its way into the peripancreatic lymph nodes and causing a generalized autoinflammatory response within the pancreatic tissue. This is notably different from the antibody-mediated directed beta cell mechanism of type 1 diabetes. Alternatively, the resistance to immune suppression that ultimately develops leads to an overactive humoral immune

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FIGURE 4.39  AMPK induces mitochondrial biogenesis, calorie restriction, and exercise. In hyperinsulinemia, nutrient abundance or GR presence activates AMPK which acts on mTOR and, in turn, inhibits Ulk1. In a state of caloric restriction, AMPK is produced and acts on SIRT1 and Ulk1. SIRT1 induces FOXO1 expression as soon as Ulk1 provokes autophagy. *AMP = adenosine monophosphate; AMPK = AMP-activated protein kinase; ATP = adenosine triphosphate; CHO = carbohydrate; CR = calorie restricted; IF = intermittent fasting; FOXO = Forkhead Box O; Mt = mitochondria; NAD+ = nicotinamide dinucleotide; NADH = nicotinamide dinucleotide (reduced form); NAMPT = nicotinamide phosphoribosyltransferase (visfatin); PGC1α = peroxisome proliferator-activated receptor gamma coactivator 1α; SIRT1 = sirtuin 1; s. muscle = skeletal muscle; T3 = triiodothyronine; ULK1 = autophagy activating kinase.

response, which may be posited as the basis for bacterial microbial overgrowth. There, healthy commensal and symbiotic bacteria that overwhelmingly occupy the epithelial surface of the gastrointestinal tract are accordingly disproportionately targeted by the immune system allowing the pathogenic bacteria to compete. This results in a circle of dysbiosis altered microbial composition and is an important driver of the systematic pro-inflammatory response. The other major extrinsic control parameter to human disease is the quantity and quality of diet. Importantly, not only does an abnormal diet, whether too little, too much or of poor nutritional quality, promote and alter microbial composition of the gut microbiota, which is a synergistic process with the chronic stress response, but the chronic stress response independently promotes such abnormal dietary patterns (Figure 4.42).

Moreover, preference for food with poor nutritional quality is increased at night. Thus, late night eating can lead to both circadian misalignment and poor diet quality. The fitness landscape of an individual that characterizes the person’s state of health may be described using these three basic extrinsic control parameters. These specific three control parameters form a subspace of a multidimensional landscape of intrinsic control parameters known as secondary order parameters. Together with their associated order parameters, they completely characterize healthy and disease states for each individual.

4.9.8 Nocturnal Eating and Insulin Resistance It has been proposed that the brain’s evolutionary purpose is to successfully acquire food. Humans have therefore evolved

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FIGURE 4.40  Exercise, fasting, AICAR, metformin. SIRT1 and AMPK promote deacetylation and direct phosphorylation with resultant activation of FOXO transcription factors. Source: adapted from (154). *AICAR = 5-ami​noimi​dazol​e-4-c​a rbox​amide​-1-β-​D -rib​ofura​ nosid​e; AMP = adenosine monophosphate; AMPK = AMP-activated protein kinase; ATP = adenosine triphosphate; FOXO = Forkhead Box O; NAD+ = nicotinamide dinucleotide; NADH = nicotinamide dinucleotide (reduced form); PGC1α = peroxisome proliferator-activated receptor gamma coactivator 1α; SIRT1 = sirtuin 1.

to hunt, gather and eat primarily during daylight hours (diurnally). During nocturnal hours, humans evolved to rest, sleep, and resultantly, fast. Accordingly, our metabolic regulation is governed by circadian timing linked to our internal molecular clock. The body is able to predict the need to produce ATP during rest, which may occur overnight. Alternatively, excess energy consumed during the daytime gets stored as glycogen and fat. This process is most efficient when the circadian timing of our metabolism is entrained and synchronized to the light/dark cycle (156). One pathway that entrains and synchronizes these processes induces the activation of PPARα by fatty acids (157). Clock-mediated nocturnal PPARα transcription synchronizes

179 with the nocturnal insulin resistant phase, during which there is a bioenergetic reliance on fatty acid metabolism. During this nocturnal insulin resistant phase, there is a lipolytically active period when fatty acids are released from adipose tissue. PPARα binds these fatty acids and promotes fatty acid oxidation into ATP by upregulating the hormone lipoprotein lipase (LPL) in peripheral tissues such as cardiac and skeletal muscles. Therefore, the lipolytic release of fatty acid substrates from adipose tissue supplies the nocturnal energetic demands of insulin responsive metabolic tissues, and the transcription of PPARα is an anticipatory behavior of circadian biology. Glucose remains the primary fuel source during the nocturnal insulin resistant phase in non-insulin dependent tissues, especially the brain. Products of the glycolysis pathway, such as lactate, pyruvate, and the amino acids alanine and glutamine from muscle, are the other major substrates for gluconeogenesis during nocturnal fasting (158). The upregulation of clock-controlled gene output is intricately governed by insulin and cortisol, such that the biogenesis of new mitochondria occurs during the resting phase (159). This transcriptional process takes approximately 8 hours, allowing new mitochondria to be ready for action during the daylight feeding phase if biosynthesis begins at night. This is a logical set of circumstances since this crucial energy requiring anabolic function is not forced to compete with any high energy expending processes of the daytime’s active phase. Furthermore, compared to fatty acid oxidation, mitochondrial oxidation of glucose is a more efficient substrate utilization in terms of oxygen consumed per amount of ATP produced. More ATP is technically produced per molecule of fatty acid through their oxidation, but glucose as a substrate translates to a cleaner burning fuel and less produced oxidative stress due to its lower O2/ATP ratio. Mitochondrial function is therefore preserved and non-circadian insulin resistance is prevented.

FIGURE 4.41  Hypothalamus at the center of stress, diet and circadian cycles. The hypothalamus mediates neuroendocrine hormonal and sympathetic nervous system output. Source: adapted from (155). *CCK = cholecystokinin; CGRP = calcitonin gene-related peptide; GLP-1 = glucagon-like peptide-1; NPY/AgRP = neuropeptide Y/ agouti-related protein; POMC/CART = proopiomelanocortin/cocaine and amphetamine regulated transcript.

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FIGURE 4.42  Circadian cycles and metabolism. Circadian cycles of physiology and behavior influence metabolic activity and are influenced by control parameters of the physiological fitness landscape. *CHO = carbohydrate; L/D = light/dark; GH = growth hormone; GI = gastrointestinal; PEPCK = phosphoenolpyruvate carboxykinase; PK = pyruvate kinase; SCN = suprachiasmatic nucleus; s. muscle = skeletal muscle.

Our Physiological Fitness Landscape (PFL) framework can model a phase transition from healthy circadian cycling of insulin resistance to pathogenic non-circadian insulin resistance induced by unhealthy nocturnal eating patterns. In such a model, diet would comprise the extrinsic control parameter, while microbiota composition would comprise the intrinsic. The consumption of carbohydrates and lipids during the natural insulin resistant phase of the light/dark synchronized circadian cycle results in a rise in circulating glucose and fatty acids to excess. Levels reach such magnitudes because dietary

ingestion of these compounds would be superimposed on the substrates of fatty acids and glucose already being output from the processes of adipose tissue lipolysis and hepatic gluconeogenesis respectively. In addition to disturbed synchronized circadian energy balance, nocturnal energy disrupts the circadian cycling composition of gut inhabiting microbiota (160). Dietary nutrients are just as vital an energy source for gut microbiota as they are for the human host. Along with our metabolism, unanticipated food intake at night ambushes the microbiota, catching it by surprise. This leads to an altered

The Biology of Time balance in microbiota composition and gut dysbiosis—a desynchronization of the intricate symbiosis between human host and microbiota metabolisms and physiologies. The ensuing pathogenesis arising from the disturbed microbiota causes disruption in gut barrier integrity due to the disassembling of tight junction complexes between epithelial cells. This makes it possible for the endotoxin component of gram-negative bacterial walls to translocate into human portal circulation. At times, this could even apply to whole bacteria. This phenomenon underlying subclinical endotoxemia, also known as endotoxicosis, is now recognized to be a hallmark feature in the pathogenesis of visceral adipose tissue and hepatic insulin resistance, and often subsequently, type 2 diabetes. The external stressor of nocturnal eating promotes both direct and indirect (mediated by host gut dysbiosis) fitness impairment which is characterized by overcoming the energy barrier of metabolic stability and promoting instability and metabolic inefficiency, which includes the loss of free energy as inflammatory heat, an aging process. These metabolic consequences escalate along with metabolic inflexibility due to the loss of coordinated energy availability to synchronized circadian physiology and the development of pathogenic non-circadian insulin resistance, all leading to chronic diseases of aging. Accelerated aging, modeled by the trajectory of PFL’s topological terrain is represented by the selfamplifying nature of feedforward interactions between many intrinsic and extrinsic stress parameters that push to overcome the energy barriers of resilience and form the valleys along the trajectory of the PFL. Such parameters can include disturbed dietary timing and microbiota composition, the integrated web of diet quality and quantity, abnormal physical activity, and exaggerated responsiveness to stress. Thus, metabolic stability zones are unable to resist challenges from control parameters, as order parameters of human physiology, such as free energy, exhibit a sharply declining rate of change. In other words, accumulation of severe chronic disease states rapidly drives fitness’ free energy levels towards zero. Notably, glucose oxidation coupling with glycolytic metabolism during the diurnal feeding plus the inflexible metabolic switch from fatty acid oxidation to glucose uptake in insulin responsive tissues at the transition of fasting to feeding, parallels the loss of allostatic flexibility leading to allostatic overload. This loss of metabolic and physiological flexibility is topologically represented in the PFL as dynamic transitions of valleys into hilltops adjoining shallower valleys with declining altitudes. It follows that non-circadian eating behaviors disrupt efficient bioenergetic metabolism that predispose the body to metabolic inefficiency and instability, thereby leading to accelerated susceptibility to the chronic diseases of aging.

4.9.9 Redox Status and Circadian Rhythms Redox status is a fundamental parameter of homeostasis in living systems that must be maintained within a narrow range. It is tightly coupled to a change in energy available to do useful work in any defined system within the living system. Deviation from this range defines disease or a susceptibility

181 state for disease as well as for accelerated aging in the sense of allostatic overload whereby allostatic parameters are unable to maintain homeostasis of vital organ system function. The coevolution of redox and circadian systems in mammals may have been rooted in the oxidative stress that coincides with photosynthetic potential of plants and bacteria to use water as the major donor in the Calvin cycle liberating oxygen into the atmosphere (Calvin cycle: CO2 + H20 + solar energy → C6H12O6 + 02). The oxygen consumed by mammals such as humans becomes the final electron acceptor along the electron transport chain by combining with protons being restored through ATP synthase across the inner mitochondrial membrane. This reaction results in the generation of a molecule. However, not all oxygen, electrons and protons are so conveniently configured with the production of ATP in the absence of inefficiency. Electron leakage along the way reduces oxygen to form superoxide, in addition to other reactive oxygen species. Thus, antioxidant redox proteins evolved in this context of oxidative metabolism to prevent cell and tissue damage in addition to other sources of oxidative stress coincident with high atmospheric oxygen and ultraviolet radiation. Another co-evolutionary linkage between redox proteins, metabolism with bioenergetic ATP production and circadian rhythm is the coupling of the molecular oscillating clock to the regulation of NAD+ production (Figure 4.43). Energy absorbed in uphill endothermic reactions, such as breaking bonds, is provided by exothermic reactions releasing energy, such as by forming bonds. The energy released or absorbed is described as negative Gibbs free energy or positive Gibbs free energy, respectively and the value of each is the enthalpy of heat generation. The metabolic pathways of energy production of NADH and FADH2 (flavin adenine dinucleotide hydrogen 2) capture the positive energy released from the exothermic reactions of the pathways that couple to the electron transport chain along the inner mitochondrial membrane. The electrons are transferred along the electron transport chain coupled to a proton gradient perpendicularly aligned whereby the collapse of the gradient is captured in the bonds of newly formed ATP. The efficiency of this process defines whether physiology is orchestrated in a quantum versus classical regime. This efficiency varies in an inverse relationship with entropy. A hypothetical zero entropy production would mean absolute energy balance between substrate and product of ATP, that is, all of the energy harnessed in the bonds of the metabolized nutrient is transferred and captured in the bonds of the universal biological currency of ATP subsequently utilizable in the work of physiology. The balance of energy determined as ATP produced relative to the metabolic demand of cell biology and physiology equates to the balance of redox processes whereby deviation from normal of either parameter results in a parallel disturbance in the other. That is, disturbance in the flow of free energy from nutrients to the bonds of ATP and subsequently into biological and physiological processes, which become impaired, corresponds to a parallel disturbance in redox with resultant redox stress. The lack of homeostasis at the level of cell biology or physiology reflects disturbance at the bioenergetic pathway level (162).

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FIGURE 4.43  ATP, oxygen, and the ETC. The oxygen consumed by mammals becomes the final electron acceptor along the electron transport chain with the successive production of ATP. This reaction results in the generation of a molecule. However, not all oxygen, electrons, and protons are producing ATP in the absence of inefficiency. Electron leakage along the way reduces oxygen to form superoxide, in addition to other reactive oxygen species. Source: adapted from (161). *Fe+2/+3 = iron (II/III) ion; GSH = glutathione; GSSG = Glutathione disulfide; G6P = glucose-6-phosphate; HO - = hydroxide; H2O = water; H2O2 = hydrogen peroxide; LPO = lactoperoxidase; O2 = oxygen; O -2 = oxide; PEG = polyethylene glycol; PHS = prostaglandin H synthase; SOD = superoxide dismutase; NADP+ = nicotinamide adenine dinucleotide phosphate; NADPH = nicotinamide adenine dinucleotide phosphate (reduced form); P450 = cytochrome 450.

4.9.10 Adrenal Insufficiency The natural designs of evolution serve to optimize metabolic homeostasis and responsiveness to stressful stimuli. It is indeed clinically relevant to consider the limitation of physiological replacement therapy for adrenal insufficiency given the dynamic nature of the circadian and ultradian oscillatory cortisol pulsing cycles. It is commonly thought that physiological replacement glucocorticoid therapy for adrenal insufficiency is given as a fixed dose, two-thirds in the early morning upon awakening and one-third between two and four in the afternoon. In the setting of mucosal inflammation or other acute nonsurgical stress, that dose is doubled. However, this therapeutic strategy fails to provide the high pulse secretion of cortisol prior to the awakening anticipation of the high physical, cognitive, and metabolic demands at the immediate start of the day. Moreover, this standard replacement practice does not replicate the ultradian dynamics throughout the day that is engaged in response to stressful stimuli. Accordingly, it has been shown that this regimen doubles mortality risk from cardiovascular diseases, infections, and cancer. In addition, social vigor, enervation, and impaired cognitive function is significantly greater with this regimen (163). Furthermore, not only is standard physiological replacement therapy problematic but pharmacologic steroid treatment for autoimmune and malignant disease is likely suboptimal at best in terms of how timing of administration influences therapeutic efficacy

and adverse effects. This highlights the need for further study in this area to better understand these dynamics. The fitness landscape model we propose would be an ideal assessment tool here capable of mathematically determining the likelihood of inducing a phase transition in the context of highly personalized multidimensional order parameters. Phase transition may include both therapeutically desirable as well as adverse ones.

4.9.11 Cortisol, Cushing’s, and Obesity Like many endocrine factors, glucocorticoids, such as cortisol, have a circadian pattern of release and can also be acutely triggered by the environment. Glucocorticoids reset circadian rhythms by phase shifting peripheral clocks (observed in liver, heart, and kidney), which under typical circumstances return to the normal synchrony with the master central clock (82). Glucocorticoids do not have the same phase shifting ability on the master clock (SCN). However, chronic stress drives the disease susceptibility state of perpetuating circadian dyssynchrony with loss of glucocorticoid receptor diurnal clock regulation. This underscores the pathogenic potential of states that are mistakenly too often discussed as benign, such as, “pseudo-Cushing’s”, the thought often is, “it’s okay, it’s not Cushing’s”. Even modest elevations of time-integrated cortisol in the absence of cushingoid features represent an order parameter of a susceptibility state to a wide range of

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The Biology of Time metabolic disease states. For example, hyperinsulinemia and insulin resistance is a consequence of cortisol elevation including compromised nocturnal blunting. This is due both to the antagonistic effects of cortisol on insulin signaling and to phase shifting and increased amplitude of insulin secretion. Disturbed cortisol-bound glucocorticoid receptor impairs the molecular clock transcription factor BMAL1, which binds to fibrinogen homolog, plasminogen activator inhibitor-1 (PAI-1) contributing to the hypercoagulable state and pathogenic potential for cardiovascular disease. These are only a few examples of how loss of synchronous rhythm links to metabolic and chronic disease. However, the implications are fundamental and the number of potential ways this can interface with human disease and the aging process is vastly wide-ranging (58).

4.10 Therapeutic Interventions: Fitness Landscape Model The intracellular regulatory pathways of circadian metabolism are still incompletely understood but there is more and more data emerging that relate circadian biology to metabolic disease, accelerated aging, and chronic diseases of aging, particularly cancers. In the opinion of this author, the value of this material is to underscore the significance of the periodicity of physiological processes. It is hoped that this discussion will enhance the reader’s appreciation for understanding, for example, nuclear receptors as metabolic sensors of hormones and certain lipid nutrient signals and fat-soluble vitamins that couple metabolic processes with molecular level clocks and circadian physiology. Both the clinical and research communities should appreciate that these relationships mapped out in numerous fitness landscapes, and ultimately in a single multidimensional fitness landscape with extrinsic and intrinsic control parameters and order parameters, can be studied in great detail. This may lead to insights of clinical importance. From a clinician’s perspective just recognizing, for example, the importance of light–dark, sleep–wake, fast–feeding, and other lifestyle and social cues, may be helpful in translating these findings into circadian health, physiology, aging, and chronic disease (Figure 4.44). At the research level, the various physiological measures expressed as order and control parameters can be studied and drug research and development may be influenced accordingly.

4.11 Future Advances in Circadian Biology and Circadian Medicine Chronobiology is one of the few fields founded on curiosity. A majority of research was done on the basic understanding of circadian biology and its importance. However, until recently, the field had not focused on circadian effects on fields or on possible interventions to support or improve circadian health. Although the widespread importance of circadian rhythms has been established, due to a lack of

knowledge and/or difficulty, many fields have still ignored circadian biology. Thus, the future of circadian biology lies in 1) discovering the full influence of circadian rhythms and accounting for them in research in many areas, such as regulation of nuclear receptors and epigenetics, 2) developing interventions/therapies to be used to support circadian health, and 3) examining the circadian medicine: the effect of time of administering medications, vaccinations, and performing surgeries. Nuclear hormone receptors. There are nearly 50 nuclear hormone receptor transcription factors in humans. Nuclear hormone receptors bind endogenous ligands to respond to environmental stimuli. This inherent feature makes nuclear hormone receptors amenable to pharmacological targeting by synthetic drugs (e.g. glucocorticoids, thyroid hormone, tamoxifen, thiazolidinediones, fibrates, etc.). Roughly onethird of all nuclear hormone receptors are targets of currently marketed drugs, including 20 of the top 200 prescribed. Nuclear hormone receptors are intrinsically linked to the mammalian circadian clock. Most are clock-controlled in at least one tissue of the body. In addition, recent evidence suggests nuclear hormone receptors are indispensable to circadian physiology possessing input, pace-making, and output functions of the clock. Light/dark cycles align with fasting/feeding cycles for better health. The oscillating light–dark cycles generated by the Earth rotating around its axis provide the most foundational external temporal cues entraining the intrinsic molecular clocks in the cells of human and all living systems. This imposes a “timestamp” on physiology, an evolutionary pressure that forces the entrainment of a temporally coherent circadian rhythm of a total body-wide system of clocks. When feeding behavior is aligned with light/dark signals, circadian rhythms are likely to be coherently and synchronously coordinated manifesting in healthy systemic physiology. However, when feeding/fasting patterns are misaligned with the light/ dark cycle, or chronically erratic, metabolic rhythms are disrupted (164). Over time, this circadian disruption increases the risk for chronic disease. Thus, behavioral modifications to align feeding/fasting cycles with light/dark and sleep/wake cycles, has the potential to significantly improve metabolic health (18, 165, 166).

4.12 Take-Home Messages • Physical laws can and should be used to understand biology and medicine. • Time dilates, or slows down, relative to the energy you put into maintaining life. • Chronobiology is the study of time. The field started from curiosity and is now understood to be a core part of healthy physiology across lifeforms. • All living organisms have circadian rhythms in physiology and behavior to adapt the 24-hour oscillations in environmental changes caused by the Earth’s rotation.

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FIGURE 4.44  Human aging and chronic disease. Light–dark, sleep–wake, fast–feeding, and other lifestyle and social cues, orchestrate circadian health, physiology, aging, and chronic disease. *ATP = adenosine triphosphate; NAD+ = nicotinamide dinucleotide; NF-κB = nuclear factor kappa B; SIRT1 = sirtuin 1.

• Endogenous biological rhythms are maintained in the absence of external cues, but also use external cues to coordinate physiology and behavior with the environment. • Daily oscillations in the expression of the core clock genes and proteins are present in nearly all cells of

the body. These endogenous rhythms appear to be designed to parallel the diurnal light–dark cycle of the external environment. • The molecular clock is a transcriptional-translational feedback loop (TTFL) consisting of two main arms: the positive regulatory elements that promote

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transcription and the negative protein products that suppress transcription. In mammals, the suprachiasmatic nucleus (SCN), determines the period of the organism and coordinated clocks throughout the body. Light and food are the two strongest external cues to the circadian system. Light directly inputs to the SCN and influences behavioral rhythms most quickly. Whereas food (nutrient cues) directly influence molecular clocks throughout the body. When the endogenous circadian system is not in the correct phase angle with the environment (desynchronized), the fitness of the organism is compromised. Disrupted circadian clockwork in animal models promotes the development of not only conventional metabolic disorders of obesity and type 2 diabetes, but all major forms of chronic diseases of aging (e.g. CVD, cancers, accelerated cognitive decline, and Alzheimer’s disease) which are consistent with the process of accelerated aging. When the peripheral clocks receive conflicting signals from the brain and gut, such as eating overnight or alternating shift work, metabolic pathways within and between tissues become desynchronized and may then undergo pathological changes. Intrinsic peripheral clocks and metabolic functioning are synchronized with maximal robustness and amplitude, and also with minimal loss of free energy or disturbance in redox balance. Accordingly, this preserves metabolic fitness, and, hence, promotes health. A fitness landscape is a model that can be used to understand the multidimensional interaction of external control parameters, (such as caloric intake, amount and intensity of physical exercise, or dose of a pharmacological agent) with overall fitness or health. The extrinsic control parameters that cause human disease can largely be categorized as 1) circadian misalignment of light–dark and feeding-fasting cycles, 2) the stress response, and 3) the quantity and quality of diet. Virtually all chronic diseases of aging have the same external control parameters in common, hence instead of the fragmented approach to diagnostics and therapeutics of aging processes, a common framework should be developed. Linear processes advance through time as they dissipate energy creating entropy. The greater the linear

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component, the faster the aging process and the system’s degradation. In other words, cyclicity prolongs the longevity of the living system, which is characterized by a reduced state of entropy. The closest we can come to a practical and tangible strategy for slowing the aging process is by protecting or restoring the quantum metabolism mode of energy production. Quantum metabolism is the correlated or coherent production of ATP currency that mediates the work of cell biology and physiology. All hormones display circadian patterns of secretion and can feedback on the circadian system. Classical hormone nuclear receptors evolved to regulate carbohydrate metabolism, development, reproduction, and electrolyte balance. Toxic stress can be minimized by supporting circadian health, keeping to a healthy diet, being meaningfully connected to our social network of family, friends and communities, and encouraging vitalizing stressors. Insulin resistance, like the broader stress response, is only adaptive when temporary in nature. Otherwise, it abrogates the circadian cyclicity patterns that are fundamental to healthy metabolism, physiology, and behavior. Both immune suppression states of the stress response as well as the resistance that follows the immune suppression contribute to an altered pathogenic composition of the gut microbiota. The balance of energy determined as ATP produced relative to the metabolic demand of cell biology and physiology equates to the balance of redox processes whereby deviation from normal of either parameter results in a parallel disturbance in the other. From a clinician’s perspective, just recognizing, for example, the importance of light–dark, sleep– wake, fast–feeding, and other lifestyle and social cues, may be helpful in translating these findings into circadian health, physiology, aging, and chronic disease. At the research level, the various physiological measures expressed as order and control parameters can be studied and drug research and development may be influenced accordingly. Circadian medicine such as chronopharmacology (optimizing the timing of medications), and optimizing exposure to light and calorie intake (such as time-restricted eating) may play a significant role in prevention and treating chronic disease.

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5 Calorie Restriction, Intermittent Fasting, Ketogenic Fasting, and Time-Restricted Feeding

Abbreviations ACC Akt AMPK BDNF Cyt c ETC ERRα FOX FOXO GLUT4 GR GSK3 IMCL IR IRS JNK LPL MAPK MnSOD mTOR mTORC1 mTORC2 NRFs OH• p53 PDK4 PEPCK PGC1α PI3K PPARs S6K1 SIRT1 TFAM ULK1 UPR VLDL

acetyl CoA carboxylase protein kinase B AMP-activated protein kinase brain-derived neurotrophic factor cytochrome c electron transport chain estrogen-related receptor α forkhead box FOX gene O subclass glucose transporter type 4 glucocorticoid receptor glycogen synthase kinase 3 intramyocellular lipid insulin receptor insulin receptor substrate c-Jun N-terminal kinase lipoprotein lipase mitogen-activated protein kinase manganese superoxide dismutase mammalian target of rapamycin mTOR Complex 1 mTOR Complex 2 nuclear respiratory factors hydroxyl radicals tumor protein 53 pyruvate dehydrogenase kinase 4 phosphoenolpyruvate carboxykinase peroxisome proliferator-activated receptor gamma coactivator 1-alpha phosphoinositide 3 kinase peroxisome proliferator-activated receptors S6 kinase beta-1 sirtuin 1 mitochondrial transcription factor A Unc-51 like autophagy activating kinase-1 unfolded protein response very low-density lipoprotein

Chapter Overview The goal or physiological purpose of any living system is the survival of the organism and species as a whole. Survival requires meeting the continually changing metabolic DOI: 10.1201/9781003149897-5

bioenergetic demands of the body. This demand is met by acquiring nutrients from the environment in order to provide the body with the energy required to perform biological functions and maintain homeostasis. Like most things in life, there is an optimal level of nutrient consumption, and both too little or too much can precipitate chronic diseases of aging. Chapter 5 of this book focuses on calorie restriction, intermittent fasting, and time-restricted feeding with biological and clinical discussions including 1) how the energy sensors and the fuel gauges of the body (AMPK and SIRT1) promote survival and slow the pace of aging in a way that increases longevity; 2) the notion of hormesis concerning the optimal metabolic balance between and among systems; 3) the importance of endogenous circadian biology (both synchronized and dyssynchronous) on insulin signaling and underlying molecular cascades; 4) the interwoven relationship between nutrient intake, energy sensing, insulin resistance, mitochondrial dysfunction, and chronic diseases of aging; 5) and, finally, the effects of chronic overnutrition on metabolic signaling and accelerated aging. Survival early in life is more metabolically demanding and requires higher energy input. It is during these years that higher levels of physical fitness, aerobic capacity, and endurance are supported. During post-reproductive years, longevity is the main goal. It has been demonstrated that calorie restriction is beneficial in promoting longevity and preventing agerelated chronic disease. Not only are there changes in optimal energy consumption based on the stage of life, but there are different genes that promote survival early or later in life. The most favorable of these lifestyle parameters are fundamentally connected to the optimal activation of the energy sensors AMPK and SIRT1 to promote survival and slow the pace of aging, thereby increasing longevity. These energy-sensing fuel gauges are coupled to gene programs of stress resistance, including DNA and cellular repair, antioxidant systems, autophagy, cell differentiation, and apoptosis. AMPK activity is upregulated during circumstances of calorie restriction, fasting, and exercise associated with accelerated ATP consumption. It is thought that the health benefits of calorie restriction are induced by AMPK-dependent inhibition of mTOR, acting to improve insulin resistance, promote mitochondrial biogenesis, prevent obesity and metabolic disease, and increase overall lifespan (Figure 5.0). Optimal insulin sensitivity is known to coincide with calorie restriction, while excess nutrient intake has been associated with the development of insulin resistance. One characteristic 191

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FIGURE 5.0  Calorie restriction overview. Excess nutrient consumption increases insulin levels and leads to desynchronization of biological clocks resulting in negative outcomes of cell growth, mitogenesis, mitochondrial dysfunction, and suppression of longevity genes. Alternately, calorie restriction maintains low insulin levels that preserve synchronized clock function and result in beneficial effects such as induction of longevity gene transcription, activation of stress resistance programs, and mitochondrial biogenesis.

of insulin resistance that makes it pathological is the loss of the circadian cyclicity of insulin secretory and sensitivity patterns in metabolic tissues. A common pathogenic behavior is chronic dietary overconsumption, not just in terms of total daily caloric intake, but the quantity of intake relative to the time of the day. Nuclear hormone receptors lie at the intersection between the endogenous clocks and metabolism, coupling metabolic processes to cyclical circadian output. In a negative feedback loop/ bidirectional relationship, poor sleep results in insulin resistance due to increased stress response and disruption of endogenous clock synchronicity, while insulin resistance promotes poor quality sleep by inducing obstructive sleep apnea. Chronic overnutrition can be defined as the long-term nutrient intake that exceeds energy expenditure demands, which can then exceed the capacity for mitochondrial production of ATP, resulting in mitochondrial dysfunction. When there is mitochondrial dysfunction or overload, oxidation of nutrients is prevented and is instead diverted to storage within the cell. Lipid accumulation that exceeds the storage capacity of the hepatocyte eventually leads to insulin resistance and ultimately accelerates aging. One underlying message of this chapter is the notion of hormesis, the perfect balance of stress. It is thought that stress at a lower level can be vitalizing, while stress at higher levels can be harmful or lethal. This balance is individual and depends on the stage of the life cycle, and can change dynamically over the course of a lifetime. This concept of hormesis can be used for physical exercise. The beneficial effects of activity and diet, both intensity and quantity, should be considered relative to the stage in the life cycle. Hormesis, importantly, can also be applied to caloric intake. There is an optimal level; based on energy expenditure as well as the stage in the life cycle. Intake that is too low or too high can lead to oxidative stress and inflammation as well as insulin resistance and/or hyperinsulinemia. Many of the signaling pathways mentioned previously depend on a balance between nutrient depletion and nutrient overabundance. Allostatic load is “the wear and tear on the body;” chronic stress over time can lead to increased susceptibility to chronic disease.

5.1 Philosophical and Mechanistic Perspectives From a philosophical and molecular perspective, why and how do physiological energy-sensing fuel gauges promote healthy physiology?

The goal or physiological purpose of any living system is the survival of the organism, and species as a whole. It seems counterintuitive that these systems are adaptively regulated in an environment of low energy intake when human society for the most part is flooded with a surplus of available nutrient energy for consumption. Human energy consumption, over roughly the last 265 years alone, has more than doubled the totality of that consumed by the hunter/gatherers who occupied more than 90% of human evolutionary history. This excess in available nutrient supply and overconsumption leads to the pathological acceleration of biological aging and chronic disease.

5.1.1 Physical and Biological Systems Picture a perpetual motion machine. The machine has no friction, generates no heat with use, does not wear out, and can perform its task indefinitely. In contrast, a biological engine produces inflammation with use, which causes it to gradually wear out—the process of aging. Inflammation generates free radicals, producing heat. Heat causes entropy (the progressive randomization of particles and dissipation of heat from warmer to cooler regions). When the heat is spread evenly, the biological engine has reached thermodynamic equilibrium. However, the energy liberated as heat is irreversible and becomes unusable for any form of work. This is known as the classical mode of metabolism. Unlike the classical mode of metabolism, which produces high amounts of heat, the quantum mode of metabolism produces very little heat. Heat causes quantum decoherence (loss of the quantum wave, loss of energy production in the quantum mode, and switching to the classical mode). A human in the quantum mode of metabolism would theoretically stop aging

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Calorie Restriction and Metabolism and extend their healthspans and lifespans by 30–40 years. Unfortunately, living in the quantum mode is not a realistic goal; the second law of thermodynamics states that systems produce more entropy over time, which causes more heat to be lost with aging. Once the aging and inflammation process begins, entropy increases, further accelerating wearing out of the biological engine. Caloric excess directly accelerates biological aging by fueling cellular pathways that promote oxidative and inflammatory stress, as well as mediators of pathogenicity. Caloric restriction starves these pro-aging pathways, preventing inflammation and free radical stress. Caloric restriction also promotes the biological engine to switch from the energy-inefficient classical mode to the more efficient quantum mode of metabolism.

5.1.2 Longevity, Aging, and Chronic Diseases Chronic diseases that occur are generally disease states of aging. They do not impact reproductive fitness and, hence, the ability to reproduce, which is consistent with the Darwinian survival of the fittest. The purpose here is for the “survival of the species”. Darwinian fitness relates to the ability to acquire food, escape a predator, and secure a dominant territory to allow for the attraction of mates. It also relates to a phenotype that is resistant to the harsh weather conditions of winter and an immune system competent enough to fight infections. The latter often occurs during the “fight-or-flight” stress response with physical altercations in the process of securing dominance or interacting with predators and prey. This long-taught theory, robustly credible, is however not fully applicable to longevity. Human longevity is fostered largely by the unique capacity to control external stressors, for example, insulation from weather conditions, the acquisition of food, protection against or avoidance of any natural predator, and the availability of medical care for acute injuries or infections. In pre-civilization times, death was often the result of being killed by a predator, an accident such as falling from a tree, infection, or starvation. These extrinsic causes of mortality are now relatively rare because they can be avoided in the modern world of industrialized countries. Consider that in the wild, less than 10% of mice are expected to live beyond ten months. However, in the protected environment of captivity, the normal life expectancy of a mouse is roughly two years. The theory of Natural Selection proposes that genes that enhance fitness (the ability to have numerous, healthy offspring) are favored. Attracting a mate and reproducing are resourcedemanding stages of life that require calorie-rich diets. Postreproductive years (beginning roughly at the onset of middle age) favor longevity genes rather than fitness genes in order to thrive. Further, post-reproductive years do not have as high of a caloric demand, as there is no need to maintain energetically demanding secondary sex characteristics (i.e. the peacock’s tail). This evolutionary perspective might explain why caloric restriction enhances longevity in seniors. However, caloric restriction can make it impossible to maintain the same levels of muscle strength, muscle size, aerobic capacity, and endurance.

Since it appears that the brain evolved to acquire food, the metabolic processing of food both in the brain and elsewhere in the body is a fundamental priority. Thus, metabolism is the central function that determines human health and disease. Teleologically, the challenge was the acquisition of enough energy for self-organizing complex adaptive systems, which pushed human beings and all living systems to adapt competitively, allowing growth, reproduction, and care for the young. While it is controversial whether human evolution is still occurring for the purpose of longevity, perhaps the advantage of caring for third and fourth younger generations, the notion of exploiting energy sensory molecules with the goal of increasing lifespan and healthspan has generated vigorous enthusiasm. There is indeed evidence in mammals to support the salutary role of endogenous energy-sensing molecules on the fundamental control parameters of vital organ system function homeostasis including upregulating antioxidant enzyme systems, DNA repair, and autophagy of damaged organelles and unfolded proteins. Accordingly, these energy sensor molecules achieve the goal of improving the amplitude of the inseparable and reciprocal processes of redox stress and inflammation that are both cause and effect of the deterioration of the intricate and wondrous biological design of the body. Furthermore, the intertwined parallel degradation of usable energy and acid-base homeostasis occurs entangled in the inflammatory and redox turbulence as defined by the strikingly similar Gibbs free energy, Henderson-Hasselbalch, and Nernst equations. It is ironic that given the evolutionary priority for securing nutrient resources, it is the gluttony and sloth in modern industrialized human society that threatens metabolic function and efficiency, and hence physical health. It follows intuitively, therefore, the motivation for natural and pharmaceutical calorie restriction and exercise mimetic agents “in a pill”. Such pharmaceutical designs exploit the biological design of energy sensors co-opting their downstream targets that regulate metabolism. Accordingly, the concept of “dieting in a pill” without the necessity of dieting per se or of “exercise in a pill” without requiring exercise per se, undoubtedly will evoke both enthusiasm and sensationalism as well as skepticism. Intriguingly, these pharmacological approaches, mediated in part by the nuclear hormone receptor family, do show some level of scientific validation and may be a reality in the armamentarium of clinical medicine for combatting metabolic disease states and susceptibility states.

5.2 Stress Responses to Calorie Restriction 5.2.1 Hormesis, Vitalizing Stress, and Devitalizing Stress Despite evidence in insect and rodent models, it has not yet been shown directly that human lifespan is increased with calorie restriction. The health benefits of calorie restriction are explained by concepts such as Brownlee’s unifying hypothesis (2004 Banting Lecture) (1), and by Demetrius’s notion of the “take-over” regime of quantum metabolism (see Chapter 8, Section 8.3.3.2 for discussion of these areas). The notion of

194 hormesis has been discussed earlier (see Chapter 2, Section 2.2.2) and is relevant in the present context because of the fundamental nature of this concept in promoting successful aging. Hormesis refers to a “sweet spot” of mild-to-moderate vitalizing stress at some lower level in contrast to devitalizing and potentially lethal stress at a higher level. Sydney Baker, a Yaletrained physician, pioneer of Functional Medicine, and previous Director of the Gesell Institute of Human Development refers to the notion of hormesis to describe organic greens, containing inflammatory toxicants produced by the plant as natural pesticides. However, when ingested by humans, many species of greens promote healthy phytonutrient antioxidant effects by binding to antioxidant response elements on genes (Figure 5.1). This concept is equivalent on a different scale to psychogenic stressors that confront humans in present society. In both cases, these stressors activate autonomic and neuroendocrine branches of the stress response. This response adaptively mediates metabolic responses, immune system regulation, and cognition. Alternatively, the stress response can be maladaptive when prolonged or severe. This may result in compromising immune system function, altering gut microbiota composition, and impairing cognition while amplifying emotional outflow. Accordingly, the adaptive and maladaptive interpretation of stress, nutrient and psychosocial (and crucially, all forms of stress), can be equated to physical stressors and defined by the notion of hormesis; lower levels are vitalizing, whereas higher levels may be harmful or even lethal. Psychogenic stress at the adaptive lower dose along the spectrum of hormesis is considered controllable and as having the resilience or capacity to activate behavior to meet the challenge. The healthy stress response provides energy substrates for the bioenergetic production of ATP. It also promotes focus. A repetitive healthy stress response drives synaptic plasticity in parts of the brain such as the prefrontal cortex and hippocampus. Alternatively, toxic stress is predominantly mediated through the amygdala (the emotional center of the brain) and

FIGURE 5.1  The natural physiological response to vitalizing stress helps build the resilience of a living system through both psychological and physical challenges.

Metabolism and Medicine ventral striatum (often responsible for maladaptive addictive behavior pursuing emotional non-goal-oriented rewards; see Chapter 2, Section 2.4). Importantly, the prolonged exaggerated stress response promotes insulin resistance and mitochondrial dysfunction, which are central control parameters for accelerated aging and chronic disease states.

5.2.2 Cell Stress Leading to Allostatic Overload The protective behavior in response to cell stress includes upregulation of antioxidant enzyme systems, DNA repair and autophagy, and even total cellular apoptosis. These effects represent an evolved adaptation to energy stress. DNA repair and antioxidant biosynthesis themselves require energy as likely does the process of autophagy, either due to the energy requirements of biosynthetic processes or motor protein activity. Reactive oxygen species and associated modification of subcellular molecules such as DNA proteins and lipids are more likely a result of energy excess rather than energy deficiency. It does make intuitive sense that protein folding would be impaired and hence require a process of autophagy in the case of energy deficiency. When a cell undergoes many mutations that could make it cancerous, failure of DNA repair processes results in apoptosis. Apoptosis can occur when a cell in the body is infected with a virus. The cell undergoes apoptosis before the virus inside it completes its reproductive cycle and releases thousands of viral particles. Apoptosis can also be triggered by environmental stress conditions such as thermal stress, osmotic stress, or stress radiation from ultraviolet light or gamma radiation. In the setting of insulin resistance and hyperinsulinemia, metabolic tissues including muscle, fat, liver, pancreas, and brain are probably not affected to the same extent as nonmetabolic tissues, the latter having much more sensitivity to the hyperinsulinemia that is associated with the insulin resistance than the insulin-resistant tissues themselves. Insulin affects all tissues, but metabolic tissues suffer more than non-metabolic tissues. The circadian rhythmicity in the case of insulin resistance/hyperinsulinemia is impaired, which leads to redox disturbances in addition to compromised stress resistance programs of the cell under mild stress, or the induction of apoptosis under more severe stress. Importantly, insulin resistance, prediabetes, and diabetes, the latter two states with an undercurrent of insulin resistance, are all associated with a significantly elevated risk of cancers. This is consistent with the demonstrated relationship of endogenous hyperinsulinemia with cancer (2). Out-of-phase sleep/wake or fasting/feeding cycles with the light/dark cycle are of course the signature extrinsic control parameters that result in the dyssynchronous circadian output of clock-controlled genes (see Chapter 4, Section 4.9). Fundamentally, the products of clock-controlled output genes and the processes that they control are metabolic, growth, and reproductive in nature. The framework of physiological axes that link the central and peripheral cell molecular clocks are the neuroendocrine and autonomic systems, largely arising from regions of the hypothalamus. These are the same axes that are amplified and dysregulated by the other two major intrinsic control parameters proposed in this chapter, the

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Calorie Restriction and Metabolism emotional stress response and a disturbed microbiota secondary to poor quality and/or abnormal quantity of dietary intake. The dysregulated neuroendocrine, autonomic and subsequent immune function becomes the common fabric of an interwoven derangement of all three intrinsic susceptibility states for chronic disease and accelerated aging. Dysregulation of the control axes of autonomic, neuronal, hormonal, and immune systems represents allostatic load. Once this dysregulation has gone awry and surpasses the critical threshold of metabolic or chronic disease, it represents allostatic overload (3). It is proposed here that in addition to invoking allostatic load, metabolic abnormalities of obesity and insulin resistance may also be included as manifestations of allostatic overload. Accordingly, allostatic overload states should be recognized as susceptibility states to chronic disease or as chronic disease states per se. Susceptibility states inherently have a disturbed oxidative metabolism, a decoherence in energy production of ATP through mitochondrial oxidative phosphorylation, and, as a result, a decay in synchronous physiology. Fundamentally, this represents the aging process itself. The inextricable and bidirectional relationship between mitochondrial dysfunction and insulin resistance is significant, as well as similar to the interwoven fabric of redox disturbance, inflammation, and impaired bioenergetics. These bidirectional relationships have been restated throughout this chapter (Figure 5.2). The processes that drive the accumulation of covalent oxidative modifications of cell constituents represent the most basic level of disease. These processes cause the dyssynchrony of the circadian clock-controlled output of metabolic physiology. This, in turn, leads to exaggerated and prolonged responses to external stressors, which typically results in abnormal quality and quantity of diet as well as a disturbed quality and temporal patterns of sleep that do not align with the natural light/dark cycle. These processes perturb the microbiota, which further becomes entwined into an inseparable web of a feedforward fabric of reverberating circuits of intrinsic and extrinsic control parameters. All of this pathologically fuels fundamental oxidative damage to biological systems and impairs bioenergetic production and efficiency. This parallels the loss of usable energy transformed into unusable heat, that is, inflammation and entropy production.

FIGURE 5.2  The bidirectional relationship between mitochondrial dysfunction, insulin resistance, oxidative stress, and inflammation.

5.2.3 Metabolic Rate and Take-Over Threshold Biological systems have an optimal metabolic rate. AMPactivated protein kinase (AMPK) is an energy-sensing enzyme that signals the preferred metabolic rate. AMPK activates the metabolic network of enzymes, signaling molecules, transcription factors, and nuclear hormone receptors, which all impact mode of energy production. During the quantum mode of energy production, metabolic rate is maximal, and metabolic efficiency (the amount of ATP produced/mass/time) is maximized. The quantum mode is exquisitely organized temporally and spatially, coordinating complex cellular, biological, and physiological processes. High-efficiency metabolic systems waste minimal energy in the form of unneeded heat. Caloric excess floods the electron carriers in the electron transport chain (ETC), leading to electron leakage and the formation of reactive oxygen species (ROS). ROS cause redox disturbance, inflammatory stress, and compromise Gibbs free energy production, ultimately reducing ATP availability. These side effects of caloric excess force the body to switch from the high-efficiency quantum mode to the low-efficiency classical mode of metabolism (i.e. glycolysis). The switch from the quantum mode to the classical mode of metabolism causes a loss of complexity in organization that parallels chronic metabolic diseases of aging. This loss of complexity is complementary to the loss of circadian expression of cell clock genes, which have temporally synchronized metabolic output and function. Circadian rhythms lie at the heart of healthy physiology and energy sensors of calorie restriction.

SIDEBAR 5.1: THE “UNIFYING HYPOTHESIS” AND THE TAKE-OVER THRESHOLD Dr. Michael Brownlee’s “unifying hypothesis” posits that metabolic dysfunction and disease are rooted in overloading the mitochondrial electron transport chain (1). Excess glucose and/or fatty acid oxidation increases nicotinamide adenine dinucleotide (NADH) and flavin adenine dinucleotide (FADH2) electron donors, which promotes electron leakage along the electron transport chain, causing the production of reactive oxygen species (ROS). ROS inhibit distal glycolytic enzymes, particularly glyceraldehyde 3-phosphate dehydrogenase (GAPDH). Inhibition of GPDH leads to cellular damage through unchecked polyol, hexosamine, protein kinase C, and AGE pathways. The “take-over threshold” is the tipping point between the quantum and classical modes of metabolism. In a sense, the take-over threshold is an extension of the Unifying Hypothesis. Since glucose and fatty acid oxidation pathways are the major energy sources for all tissues of the body, surpassing the takeover threshold could be a mechanism of mitochondrial dysfunction and insulin resistance. Mitochondrial dysfunction and insulin resistance have bidirectional effects on each other, exacerbating chronic diseases of aging.

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5.3 Energy Signals and Metabolic Response 5.3.1 Energy Sensing Functions of AMPK and SIRT1 How do energy sensors, the fuel gauges of the body AMPK and SIRT1, promote survival and slow the pace of aging in a way that increases longevity?

The ratio of AMP/ATP is a fundamental barometer of energy status at the cellular level. An increased ratio signals energy stress promoting the activation of AMPK. AMPK is a heterotrimeric enzyme consisting of alpha, beta, and gamma subunits. The alpha subunits are the catalytic domain and the beta subunits contain a glycogen binding domain; when glycogen stores are high, AMPK is inhibited. The gamma subunits bind to either AMP or ATP molecules interchangeably. When ATP availability is low, AMP is more likely to bind to the gamma subunit of AMPK. Upstream kinase activating enzyme liver kinase B1 (LKB1) upregulates AMPK through constitutive phosphorylation. In the absence of AMP binding to the gamma subunit, phosphatase activity removes these phosphate groups immediately. However, AMP binding promotes a conformational change that prevents dephosphorylation from occurring. Accordingly, AMPK couples to the immediate upregulation of catabolic pathways of glycolysis and fatty acid oxidation maintaining cellular homeostasis against the stress of an energyefficient state. Circumstances that promote AMPK activity include tissue ischemia or hypoxia, settings of calorie restriction, as well as settings of fasting or exercise associated with accelerated ATP consumption. Furthermore, AMPK promotes mitochondrial biogenesis for long-term bioenergetic machinery that enhances the capacity for catabolic metabolism and the production of ATP. Moreover, AMPK maintains homeostasis by inhibiting energetically costly anabolic processes. Similarly, an increase in NAD+/NADH ratio activates sirtuin 1 (SIRT1), which acts as a deacetylase on downstream signaling molecules and transcription factors (4–6). The deacetylase activity of SIRT1 is also known to aid in the stimulation of autophagy in cells (7). Sirtuins have been suggested to be associated with improving insulin sensitivity. Studies have shown

that SIRT1 levels are decreased in cells with high insulin resistance and conversely, high levels of SIRT1 expression were observed to improve sensitivity to insulin (8). SIRT1 is also an energy sensor that is activated by both calorie restriction and exercise. Together SIRT1 and AMPK act as the central energy sensors of the cell and orchestrate metabolic responses according to the energy requirements of the cell (Figure 5.3).

5.3.1.1 The Role of AMPK in Mitochondrial Biogenesis AMPK is regarded as the master regulator of mitochondria biogenesis and mitochondrial bioenergetic pathways of oxidative metabolism. AMPK directly phosphorylates the transcriptional coactivator peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α which allows for subsequent deacetylation required for PGC1α activation (9). Deacetylation in this context is mediated by NAD-dependent SIRT1. Moreover, AMPK also increases intracellular NAD+ by phosphorylating a number of coactivator molecules. This includes core components of clock-controlled output genes resulting in the transcription and subsequent translation of nicotinamide phosphoribosyltransferase (NamPT), responsible for converting nicotinamide to NAD+. In this manner, activation of PGC1α promotes nuclear as well as mitochondrial gene transcription factors resulting in mitochondrial gene replication and mitochondrial biogenesis. AMPK phosphorylates transcription factors peroxisome proliferator-activated receptor (PPAR)α and PPARδ, which contribute to mitochondrial biogenesis as well as to fatty acid oxidation and a plethora of other heme transcription products. By increasing pAMPK levels, activation of the phosphoinositide 3 kinase (PI3K)/ protein kinase B (Akt) pathway of mammalian target of rapamycin (mTOR) activation is also suppressed, which reduces phosphorylated ribosomal protein S6 kinase beta-1 (S6K1). Inhibition of p-S6K1 has been shown to retard the production of adipose cell formation and thereby may potentially increase lifespan (10–12). mTOR is a central regulator of protein synthesis and cell division. Insulin and insulin-like growth factor 1 (IGF-1)

FIGURE 5.3  Summary of metabolic adaptations that occur in response to calorie restriction, intermittent fasting and exercise. Under these conditions AMPK and SIRT1 work in concert to maintain energy homeostasis and improve mitochondrial function and insulin signaling, leading to a prolonged healthspan. *AMPK = AMP-activated protein kinase; ATP = adenosine triphosphate; AMP = adenosine monophosphate; NAMPT = Nicotinamide phosphoribosyltransferase; SIRT1 = sirtuin 1; NAD = nicotinamide adenine dinucleotide; NADH = nicotinamide adenine dinucleotide (NAD) + hydrogen (H); CR = calorie restriction; IF = intermittent fasting.

Calorie Restriction and Metabolism modulate mTOR activity. Conversely, mTOR can act as a signaling molecule, relaying information about insulin; mTOR provides information about energy surplus and growth factors, such as insulin. This information modulates biological activities, such as protein synthesis and cell replication. Excess insulin stimulation by mTOR signaling pathways can lead to insulin resistance. In mice, interrupting the downstream signaling of mTOR improves insulin resistance and mitochondrial biogenesis, preventing obesity and metabolic diseases, ultimately increasing lifespan (13). AMPK, which is upstream of mTOR, inhibits the mTOR pathway, inducing the same health benefits as caloric restriction. The antifungal agent rapamycin also inhibits the mTOR pathway, impairing growth and cell replication. Future research is needed to determine if inhibiting the mTOR signaling cascade is able to enhance longevity in humans. The role of AMPK in phosphorylation of core clock components, mediating the activation of PGC1α underscores it as a central factor in the maintenance of the temporal organization of metabolic homeostasis and mitochondrial biogenesis. This once again supports the inextricable connection between metabolic function, temporal coherence, and physiological health. Classical endocrinology teaches the notion of biological timepieces of transcriptional/translational feedback loops as a core mechanism for clock-controlled output gene transcriptional regulation. The discoverers of these endogenous molecular clocks, Jeffrey C. Hall, Michael Rosbash, and Michael W. Young, were in fact awarded the Nobel Prize in Physiology or Medicine in September 2017 for this work. Members of the nuclear hormone receptor family are encoded by clockcontrolled output genes. They regulate the expression of these

197 gene components, and in some cases, represent core components of an ancillary loop of the molecular clocks themselves. These endogenous clocks are responsible for the rhythmic circadian metabolic output and consequently, much of physiology and behavior. Biophysics supports the notion of spatial and temporal coherence of energy production. Hence, biology, medicine, and biophysics provide a complementary convergence of perspectives for understanding the beautiful and exquisite organizational complexity and perfection that underpins the health state of human physiology. Conversely, the degradation of this complexity equates to metabolic disease with loss of temporal organization, which in turn essentially parallels mitochondrial dysfunction and, as will be described ahead, insulin resistance-related chronic disease states.

5.3.1.2 AMPK, Mitochondrial Function, and Fitness The activation of PGC1α by AMPK- and SIRT1-promoted phosphorylation and deacetylation, respectively, is analogous to the actions of these transcriptional activators on FOXO (Figure 5.4). The increase in mitochondrial capacity enhances the ability to utilize oxygen for aerobic oxidative metabolism. Given a bidirectional relationship between insulin and mitochondrial function, the induction of mitochondrial biogenesis by calorie restriction, mediated by AMPK and SIRT1, is also central to insulin sensitivity. This increase in mitochondrial function gets to the heart of the fitness function of a human being. Optimal physical fitness that occurs typically within the span of the reproductive years is measured in terms of the volume of oxygen utilization determined by maximum exercise tolerance, or VO2 max.

FIGURE 5.4  Mechanistic links between the energy-sensing molecules AMPK and SIRT1. AMPK phosphorylation and SIRT1 deacetylation lead to activation of FOXO-induced stress resilience programs and to PGC1α-induced mitochondrial biogenesis. *AMPK = AMP-activated protein kinase; SIRT1 = sirtuin 1; FOXO = forkhead box (FOX) FOX gene O subclass; PGC1α = peroxisome proliferator-activated receptor gamma coactivator 1-alpha.

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SIDEBAR 5.2: VO2 SUBMAX AND FITNESS IN POST-REPRODUCTIVE YEARS In the post-reproductive years, fitness function may be assessed by submaximal tolerance, or VO2 submax, to avoid the risk of cardiovascular and associated vital organ system injury. In today’s society, older age groups increasingly identify with high levels of physical exercise as healthy goal-oriented behavior. This is more and more frequently associated with attempts to achieve a fitness function that is ideal for someone several decades younger. While laudable in principle, this attitude may in fact be detrimental to those individuals for several different reasons. The intensity of activity may be excessive for the level of conditioning or coexisting morbidity states. Moreover, the genes that define physiological fitness in the older stages of life are very different from those engaged to promote growth (in the young) or strength and conditioning associated with a high VO2 max (in the reproductive years). In counter-distinction to the postreproductive years, the earlier stages of life are bioenergetically more demanding. High-calorie intake to subserve the needs of physiological growth or ambitious activity in earlier life stages is associated with a higher entropy production rate, which parallels the pace of senescence. Alternatively, exercise may upregulate AMPK, such that only moderate levels are consistent with the concept of adaptive hormesis. Higher levels may also turn off these genes in part by depleting the substrates for AMP. Notably, an increased ratio of AMP/ATP induces the production of AMPK. Similarly, an increased NAD+/NADH ratio is required for the deacetylating activity of SIRT1 (Figure 5.5).

5.3.1.3 The Role of PGC1α in the Activation of Downstream Transcription Factors Optimal insulin sensitivity with low fasting levels of circulating insulin coincides with the notion of calorie restriction. AMPK and SIRT1 are activated by both calorie restriction and exercise. They act as sensors of energy stress coupled to promoting the production of ATP in order to satisfy the cell’s metabolic demands (14). Activation of PGC1α is required for recruitment of AMPK and SIRT1 to regulatory regions of DNA by their interaction with transcription factors such as nuclear respiratory factors (NRFs), PPARs, and estrogen-related receptor (ERR)-α. PGC1α promotes transcriptional activity by coactivating these nuclear hormones and respiratory receptors via the interaction with hormones and NRF response elements of oxidative phosphorylation and other mitochondrial genes (Figure 5.6). Specifically, NRF1 induces the expression of proteins involved in mitochondrial biogenesis mediated by the transcription of mitochondrial transcription factor A (TFAM). TFAM not only induces mitochondrial DNA transcription but is also critical for mitochondrial DNA replication. PPARs are important in the transcription of the enzyme program mediating the process of beta-oxidation of fats. ERRα, an orphan

FIGURE 5.5  PGC1α is the master regulator of mitochondrial biogenesis. An increase in the ratio of AMP/ATP and NAD+/NADH leads to an increase in AMPK and SIRT1, respectively. AMPK and SIRT1, in turn, activate PGC1α leading to mitochondrial biogenesis. *AMPK = AMPactivated protein kinase; SIRT1 = sirtuin 1; PGC1α = peroxisome proliferator-activated receptor gamma coactivator 1-alpha.

nuclear receptor, has special clinical relevance because it cooperates with PGC1α to induce mitochondrial biogenesis as well as fatty acid oxidation. ERRα induces the effects of exercise, improving oxygen consumption and its utilization for bioenergetic production. The strong correlation between mitochondrial function and insulin sensitivity mechanistically underscores the favorable impact of exercise, which positively regulates both of these parameters on metabolic health, insulin resistance, and diabetes.

5.3.1.4 The Role of FOXO and Stress Resilience Programs The notion of hormesis is also invoked by moderate calorie restriction that upregulates the coupling of the energy sensors AMPK and SIRT1 to gene programs of stress resilience. These stress resilience programs include DNA and cell repair, antioxidant systems, autophagy, and apoptosis (15). These processes are complementary or compensatory responses to redox cell damage. The corresponding gene output programs are mediated by the activation of the forkhead box (FOX) gene family, particularly the O subclass (FOXO), which controls a wide range of physiological processes in health and disease. FOXO can be phosphorylated or deacetylated by AMPK and SIRT1, respectively, which leads to the activation of stress resistance programs (Figure 5.3). FOXO also promotes cell differentiation, which additionally protects against cancer cell transformation, a prototypical age-associated chronic disease (16, 17). Gene programs of cell stress resistance, in general, appear to have been designed for the purpose of retarding the aging process and, thus, delaying mortality.

5.3.1.5 FOXO Transcription Factors and Autophagy The induction of FOXO transcription factors promotes autophagy, which is protective against cell stress from dysfunctional cell components, including, for example, misfolded proteins or

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FIGURE 5.6  Activation of PGC1α by AMPK and SIRT1 leads to interaction with transcription factors such as NRFs, PPARs, and ERRs to promote transcription and metabolic functions.

entire organelles such as mitochondria (Figure 5.7). The latter process is referred to as mycophagy, but this process may involve other organelles and even the entire cell itself, known as autophagy. Thus, the combination of activated PGC1α and FOXO enhance the structure and function of mitochondria. Healthy and robust mitochondrial structure and function is arguably the most essential parameter of human health; its compromise is the most fundamental determinate to metabolic and chronic disease.

5.3.1.5.1 Autophagy and Nutrient Scarcity It appears that an evolutionarily adaptive purpose for the process of autophagy is to reduce the metabolic burden of cells in the context of nutrient scarcity. This is consistent

with different effects on the autophagy process mediated by FOXO1, upregulated by calorie restriction and AMPK. Insulin signaling energy availability involves a cascade of P13K phosphorylation of Akt, which in turn phosphorylates FOXO1 promoting the nuclear exclusion of FOXO1. This prevents its occupation on the promoters of autophagy-related genes, inducing their expression. Insulin signaling also notably prevents FOXO1 occupation of response elements on genes such as phosphoenolpyruvate carboxykinase (PEPCK) and other hepatic glucose output genes intended to promote energy systemically to other tissues in the setting of nutrient scarcity. AMPK activates not only FOXO1, but also SIRT1, hence upregulating FOXO1 deacetylation, thereby promoting the autophagy function.

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FIGURE 5.8  In hyperinsulinemia, nutrient abundance or GR presence activates AMPK, which acts on mTOR, and in turn inhibits ULK1. In a state of caloric restriction, the production of AMPK is upregulated and activates SIRT1 and Ulk1. SIRT1 induces FOXO1 expression, which acts with ULK1 to promote autophagy. *GR = glucocorticoid receptor; AMPK = AMP-activated protein kinase; mTOR = mammalian target of rapamycin; SIRT1 = sirtuin 1; ULK = Unc-51 like autophagy activating kinase-1; FOXO = forkhead box (FOX) FOX gene O subclass.

FIGURE 5.7  SIRT1 and AMPK promote deacetylation and direct phosphorylation with resultant activation of FOXO transcription factors. *AMPK = AMP-activated protein kinase; SIRT1 = sirtuin 1; FOXO = forkhead box (FOX) FOX gene O subclass; PGC1α = peroxisome proliferator-activated receptor gamma coactivator 1-alpha.

FOXO is a fundamental molecular transcription factor that mediates metabolic flexibility. It is activated by energy sensors of calorie restriction and repressed by energy surplus in circadian fashion. The cyclical pattern of anabolic pathways that generate glycogen and lipid reserves alternating with catabolism of these bioenergetic stores parallel the phases of feeding and fasting, respectively. FOXO transcription factors are crucial regulators of downstream suppressive insulin signaling and activate redox stress. Accordingly, the former inhibits lipolytic and gluconeogenic pathways when they are not required to meet energy demands. In the natural healthy state, this occurs in the active phase during the daytime when food is acquired. Digested carbohydrates generate glucose monosaccharides that stimulate insulin secretion from the pancreas. Peripheral insulin sensitivity of metabolic tissues is enhanced in parallel. Redox stress is produced and accumulates during the active daytime hours that are energy-demanding. This promotes the FOXO-mediated upregulation of stress resistance programs during the nighttime hours including the anabolism of antioxidant systems and the processes of autophagy and apoptosis. These examples of circadian rhythms underpin the principle of metabolic flexibility as well as the synchronized cycle of redox allostasis. They are fundamental to maintaining metabolic and physiological homeostasis. The state of insulin resistance refers to the loss of not only metabolic flexibility

but of overall circadian flexibility including the critical stress resistance programs. Another critical kinase regulating cell homeostasis is Unc51 like autophagy activating kinase-1 (ULK1), which triggers a series of signaling steps resulting in autophagy (18). This critical kinase is upregulated by AMPK. However, in the setting of nutrient abundance and increased growth factors such as hyperinsulinemia or insulin resistance, the upregulation of mTOR inhibits the process of autophagy through its inhibitory effects on ULK1. AMPK, alternatively, when upregulated by calorie restriction, activates both the kinase enzyme ULK1 and the deacetylation enzyme SIRT1. In the latter case, SIRT1induced deacetylation of FOXO1 (as well as FOXO3) enhances FOXO binding to promoter genes of the autophagy process (Figure 5.8). Thus, the context of nutrient-sensing dictates the physiological responses of this evolutionarily tuned interplay of regulating factors on the process of autophagy as well as many metabolically-mediated processes that translate external cues into adaptive versus maladaptive signaling.

5.3.1.5.2 Autophagy and Insulin Signaling While chronic insulin resistance is clearly pathological, there is physiological eloquence to the circadian phase of insulin resistance. In fact, this crucial temporal design is necessary to prevent the acceleration of biological aging and associated premature chronic disease states. For example, autophagy activity may be caused by removing damaged components and organelles of the cell as a result of oxidative modifications. FOXO1 and FOXO3, both negatively regulated by insulin, interact with the promoter regions of genes to upregulate autophagy processes (19). The circadian regulation of FOXO transcription factors governed by insulin is a consummate example of the organizational beauty and fine-tuning of human metabolism. Insulin signaling through the Akt pathway promotes the phosphorylation of FOXO that inhibits its translocation into the nucleus. Hence, insulin inhibits the downstream interaction

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Calorie Restriction and Metabolism of FOXO-induced transcription that mediates stress resistance programs (including autophagy). This is a powerfully adaptive biological function. The value of diurnal patterns of insulin sensitivity and resistance can be understood in the context of (or loss of) redox homeostasis. Redox stress accumulates during the bioenergetically demanding insulin sensitive daytime phase of the daily cycle. The majority of redox species, especially superoxides, form along the electron transport chain, the final pathway of bioenergetic metabolism. This in turn causes the redox stress that disturbs the fidelity of biological chemistry. It generates inflammation by activating cytokines, which reciprocally results in redox stress. Inflammation in a biological system equates to the deterioration in free energy available to do the work of maintaining homeostasis (reducing entropy). The inescapable and progressive rise in inflammation and associated redox in a biological system is tantamount to that of entropy and associated heat of a physical system. There are also many other functions mediated by FOXO transcription factors that must be exquisitely timed to calibrate physiological demands with energy resource availability. During the insulin-resistant nighttime phase of the daily cycle, FOXO induces stress resistance programs. The metabolic processes of gluconeogenesis and lipolysis are also activated to provide nutrient substrates from stored energy during this fasting state.

5.3.1.5.3 Autophagy and Antioxidant Systems FOXO transcription factors play a critical role in enhancing the health span of mammals by protecting against cell stressors such as energy stress, that is reduced energy availability, and oxidative stress. Accordingly, FOXO transcription factors upregulate transcriptional programs of autophagy as well as antioxidant response systems including manganese superoxide dismutase (MnSOD), peroxiredoxins, and catalase (20). FOXO transcription factors are important in DNA repair as well as in the regulation of the cell cycle, cell differentiation, and apoptosis, all functions critical in the prevention of cancer. Metabolic cues such as insulin, as mentioned above, are significant regulators of circadian function mediated by FOXO transcription factor binding to the promoter region of the clock gene and thus, the transcription of the CLOCK protein. Circadian uncoupling of metabolic and light signals is exemplified in insulin resistance, whereby fasting hyperinsulinemia inhibits FOXO1 binding to response elements on the promoter regions of the clock gene.

5.3.1.6 FOXO Regulation of Cellular Metabolism FOX genes, in particular FOXO1, mediate a range of metabolic processes with manifestations that are contextual. FOXO1 regulates glucose homeostasis including hepatic output and uptake in skeletal muscle and adipose cells. The effect of FOXO1 on glucose uptake by muscle and adipose tissues is indirect and involves an interplay with insulin signaling (21). In the context of chronic and pathological insulin resistance, the loss of insulin signaling impairs the differentiation of myoblasts into skeletal muscle myocytes. Additionally, it prevents terminal differentiation from preadipocyte clonal expansion

into mature adipocytes. Accordingly, these may be important mechanistic insights into the relationship of insulin resistance, obesity, and sarcopenia, as well as associated metabolic disturbances including impaired postprandial glucose uptake into adipose and skeletal muscle tissues. In the setting of fasting or exercise that accelerates energy consumption, FOXO1 induces a metabolic switch in skeletal muscle from glucose to the more energetically efficient mitochondrial fatty acid oxidation. Additionally, in this setting FOXO1 promotes gluconeogenesis, thus increasing glucose availability to the brain and peripheral tissues.

Here’s how:

1) FOXO1 binds to its response element on the pdk4 gene that codes for the enzyme pyruvate dehydrogenase kinase 4 (PDK4). PKD4 is the inhibitory kinase of the pyruvate dehydrogenase complex (PDC). 2) PDC catalyzes the decarboxylation of pyruvate (the end product of glycolysis) to form acetyl CoA inside the mitochondria. Thus, FOXO1-induced transcriptional activation of the pdk4 gene leads to the translation of the PDK4. 3) PDK4 phosphorylation of PDC inhibits mitochondrial oxidative metabolism of glucose, which is involved in promoting the reversal of the glycolysis pathway. This allows pyruvate to reverse course with the reformation of glucose via gluconeogenesis. Also coordinated with this adaptive metabolic switch in the setting of fasting or exercise, FOXO1 induces lipoprotein lipase (LPL), which hydrolyzes circulating triglycerides into fatty acids and glycerol. Transcriptional expression of LPL occurs on the outer surface of vascular endothelial cells lining capillaries at their interface with skeletal muscle and is activated by apolipoprotein C2. Fatty acids are transported across the myocyte cell membrane by CD36 while glycerol circulates to the liver and kidneys to be utilized in hepatic and renal gluconeogenesis, respectively. Under settings of fasting or exercising, upstream transcriptional regulation of FOXO in skeletal muscle is mediated by cortisol binding to glucocorticoid receptors (GR). Conversely, in the postprandial setting of energy surplus, LPL enzymatic activity at the surface of adipose tissue cells is unregulated by insulin. Analogous to the situation in skeletal muscle, triglycerides are hydrolyzed to fatty acids and glycerol, with fatty acids transported across the cell membrane by CD36. However, in the context of energy surplus, adipose tissue takes up glycerol, which forms the backbone for the reesterification and storage of triglyceride. Furthermore, FOXO1 recruits CD36 to the cell membranes of skeletal muscle, enhancing the intracellular transport of the fatty acids. This promotes the formation of lipid droplets in the cytoplasm as energy storage to serve the metabolic demands of exercising muscle. FOXO1 also induces the expression of adiponectin receptors, which in turn signal fatty acid oxidation. AMPK, a core biological energy-sensing molecule, works organizationally in concert with the family of FOXO

202 transcription factors. FOXO1 in particular represents the metabolic switch responsible for shifting bioenergetic reliance from glucose to fatty acids. The rich complexity of transcriptional regulation also includes the synchronizing tapestry of nuclear receptors, such as the catabolic cortisol liganded GR, PPARα, and PPARδ that together promote fatty acid oxidation in skeletal muscle. Conversely, anabolic insulin signaling upregulates PPARδ-mediated lipogenesis and adipogenesis to accommodate energy storage in the context of nutrient surplus. The cycling of insulin resistance and sensitivity entrained with fasting-feeding circadian rhythm is a central organizing principle of human physiology. FOXO1, furthermore, antagonizes PPARδ, the master regulatory nuclear receptor promoting adipogenesis from mesenchymal cells in the context of low nutrient availability or accelerated consumption of available energy. In other words, PPARδmediated subcutaneous formation of fat cells is promoted in the setting of energy surplus, whereas FOXO1 inhibits this activity in the context of these resources being needed for purposes of biological work. The setting of insulin resistance highlights the regulatory role of insulin on FOXO1 mediating metabolic homeostasis. Insulin and FOXO transcription factors co-regulate an organizationally synchronized metabolism, which is essential for human health. Desynchronization is a foundation of disease with central control parameters of deregulated insulin resistance, and feedforward disturbances of glucose and lipid bioenergetic processes. This promotes carcinogenesis and virtually all chronic diseases of aging. Indeed, the inappropriate rise in blood sugars due to hepatic glucose output and impaired glucose uptake occurs as a result of resistance to the suppressive effect of insulin on FOXO1 in insulin-responsive tissues. Consonantly, FOXO1 also inhibits the appropriate compensation of pancreatic beta-cell mass and hyperinsulinemic response in the setting of insulin resistance. In genetically predisposed individuals, this compromised physiological function results in relative insulinopenia and impaired glucose tolerance or type 2 diabetes. Accordingly, metabolic tissues are deprived of glucose availability in the setting of insulin resistance. The contextual nature of the manifestations of FOXO1 is highlighted by the promotion of adipogenesis in the setting of insulin resistance, which represents the setting of energy surplus. Alternatively, in the context of starvation with nutrient depletion, FOXO1 may induce the expression of genes that promote muscle atrophy. The notion of hormesis in terms of relative calorie restriction is counterbalanced to calorie excess and insulin resistance. The energy stress of calorie restriction is optimal and adaptive, consistent with the concept of hormesis if it is sufficient to promote a ratio of AMP/ATP and the signaling pathways of AMPK without disturbing the temporal circadian interplay of insulin and FOXO signaling. This latter circumstance of chronic insulin resistance and FOXO activation promotes pathological gene expression patterns leading to such things as muscle atrophy, ectopic fat deposition, and proinflammatory cytokine dominance, and worsening sarcopenia. On the other hand, excess calorie intake promotes mTOR activity of anabolic processes. The loss of this temporal organizational synchrony manifesting as chronic insulin resistance is hallmarked not only by a catabolic metabolism but also by maladaptive visceral adiposity and clinical obesity. FOXO1 promotes the production of proinflammatory

Metabolism and Medicine cytokines in macrophages, which impair insulin signaling in classical insulin-responsive tissues. Moreover, in the pancreas, inflammatory cytokines contribute to the decline of beta-cell function, and accordingly the progression to diabetes.

5.3.1.7 The Importance of Circadian Fluctuations in Insulin Signaling and FOXO Activation The effect of calorie restriction on energy-sensing molecules such as AMPK and SIRT1, in addition to inducing pathways that upregulate ATP production to meet the metabolic demands of the cell, is to promote stress resistance programs that attenuate redox-induced cell stress (see Chapter 4, Section 4.9.4). Insulin-regulated FOXO transcription factors are crucial regulators of these programs. Healthy circadian fluctuations promote a synchronous physical integration of insulin signaling and FOXO activation. When insulin levels are high (during daylight feeding hours) it promotes the capacity for rapid glucose utilization to produce ATP. Increases in insulin also prevent FOXO from continuously entering the nucleus and unremittingly inducing transcription of insulin resistance genes. Conversely, when insulin levels are low (during nighttime fasting hours) FOXO levels increase and activate the transcription of stress resistance programs. Conversely, in the setting of pathological non-circadian insulin resistance and hyperinsulinemia, the suppression of FOXO, from hyperinsulinemia, in peripheral insulin-sensitive tissues accompanies the continuously unsuppressed FOXO-mediated insulin resistance in metabolic tissues (Figure 5.9). This circumstance leads to sarcopenia, obesity, and chronic disease such as cancers, cardiovascular, and Alzheimer’s disease. Active FOXO protein transcription factors that are upregulated in the context of dietary energy restriction underscore the link between strategies of calorie restriction and healthy physiology including regulation of the cell cycle as well as DNA repair and protection against oxidative stress, all of which favorably impact the incidence of cancer. Conversely, inactive FOXO transcription factor function is a provocative stimulus for a wide spectrum of cancers and cancer proliferation (22, 23). Thus, this is consistent with the growing support for the importance of time-restricted behaviors such as both diet and exercise.

SIDEBAR 5.3: CIRCADIAN CYCLES, DELTA SLOW WAVE SLEEP, AND MELATONIN An analogous situation applies to the circadian physiology of delta slow-wave sleep. Melatonin plays a role in the induction of slow-wave sleep. It appears to play a crucial role in the upregulation of telomerase-mediated DNA repair as well as in the upregulation of the antioxidant response systems that occur during this phase of sleep. Moreover, poor-quality sleep and insulin resistance are strongly connected in a likely bidirectional relationship independent of obstructive sleep apnea. For example, poor sleep architecture promotes insulin resistance by 1) increasing the stress response, 2) stimulating orexinergic pathways with excessive diet-induced weight gain, and 3) disrupting the endogenous clock synchronicity. This may be a result of exposure to artificial blue light overnight after

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FIGURE 5.9  During physiological conditions of synchronized circadian rhythms, insulin levels are high during waking (feeding) hours and low during sleep. Insulin inhibits FOXO by phosphorylating it and, therefore, FOXO levels are low during waking hours and high during sleep. This regulation of FOXO allows for the rapid utilization of glucose during waking hours and to the activation of stress resistance programs during sleep, which in turn contributes to metabolic flexibility and a normal aging process. Conversely, dyssynchronous circadian metabolic physiology results in hyperinsulinemia throughout the day that continuously suppresses FOXO and, thus, impairs glycolysis and disrupts stress resistance programs. This combination of events creates a state of metabolic inflexibility causing an accelerated pace of aging and ultimately metabolic disease, obesity, diabetes, and cancer. *FOXO = FOX gene O subclass (FOXO); TFs = transcription factors.

waking from sleep. Notably, disruption of the endogenous light/dark cycle may occur following as little as 5 minutes of light exposure during the sleep hours (24). Conversely, insulin resistance promotes poor quality sleep by inducing obstructive sleep apnea and by the redox/inflammatory stress-mediated disruption of endogenous circadian clock synchrony, including compromised melatonin-mediated sleep induction and delta wave sleep. This can occur by redox modification of clock genes or proteins themselves.

Summarily, the benefits versus harmful effects of activity and diet, in terms of intensity and quantity, respectively, should be considered relative to the stage in the life cycle. Accordingly, higher levels of both dietary intake and exercise are required to promote optimum fitness earlier in life compared to in later years. The iconic Darwinian concept “survival of the fittest” describes the strongest or the fastest in the jungle, most capable of acquiring food and attracting a mate during the earlier reproductive years. Conversely, the optimal quantity of diet and intensity of exercise for promoting fitness and longevity in the post-reproductive years are more modest. In both cases, the most favorable quantities of these lifestyle parameters are fundamentally connected to the optimal activation of the energy sensors AMPK and SIRT1, and their downstream transcriptional programs of metabolism (Figure 5.10).

The synchronized circadian timing of these functions to systemic physiology is also crucially linked to optimal healthy aging. Circadian functions have a profound relationship to physiological parameters of human health versus disease, including metabolic diseases such as obesity, diabetes, and

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FIGURE 5.10  The goal of AMPK and SIRT is to maximize metabolic efficiency by increasing resistance to stress and maintaining circadian synchronicity. *AMPK = AMP-activated protein kinase; SIRT = sirtuin.

cancer. Insulin resistance is a significant driver in the majority of these pathogenic states. Furthermore, it appears that there is a bidirectional relationship between insulin resistance and sleep disturbance, compromised synchronicity of endogenous clock-controlled output genes, and associated metabolic physiology and behavior. These are all positively regulated in selfamplifying reverberating circuits that promote an accelerated pace of aging and chronic disease processes in general.

SIDEBAR 5.4: FOXO3A AND HUMAN LONGEVITY FOXO3 targets the promoter region of clock genes and insulin as a metabolic signal negatively regulates this transcriptional activity mediated by circadian rhythms. While insulin negatively influences FOXO3 transcription, low insulin levels do not inhibit FOXO3 transcription and clock gene transcription. Thus, insulin is likely a negative regulator of the transcriptional activity of FOXO3 and of the clock gene. This disturbs the synchronous nature of the circadian output of peripheral clocks with the master suprachiasmatic nucleus (SCN) clock and the extrinsic light/dark cycle. Consequently, rhythmic functions of FOXO transcription factors such as antioxidant, autophagy, and cancer prevention activities are disturbed. FOXO3 happens to have some intriguing clinical significance including an association with human longevity. The variant FOXO3A in fact is strongly associated with human longevity and is found in most centenarians in the US and other regions in the world (25). Deregulation of FOXO3A is associated with cancer formation (26).

5.4 Mechanistic Insights of Insulin Resistance at the Cellular Level Increased insulin signaling through the PI3/Akt pathway suppresses SIRT1 deacetylase activity that in turn promotes cell resilience functions mediated by FOXO proteins. The above discussion integrates the notion of hormesis and the psychogenic stress responses mediated by the neuroendocrine and autonomic nervous systems. It, therefore, lends itself to the implications of prolonged, exaggerated, and hence unhealthy,

Metabolism and Medicine emotional stress responses to parameters of insulin resistance. Insulin resistance in metabolic tissues with accompanying endogenous fasting hyperinsulinemia impairs the circadian cyclicity of insulin signaling and associated synchronicity of metabolic circadian rhythms. This disturbs the metabolic flexibility dependent on the cycling of FOXO-mediated cell stress resistance programs. Accordingly, the adaptive longevity effect provided by FOXO1 is lost in the context of insulin resistance. Furthermore, insulin resistance has an inextricable relationship with mitochondrial dysfunction, which is bidirectional and fundamental, as discussed previously. Thus, the prolonged emotional stress response impairs insulin signaling in metabolic tissues and promotes fasting hyperinsulinemia, a central pathogenic control parameter. Another two notable extrinsic control parameters include diet and composition of the gut microbiota.* The importance of circadian dietary restrictions and influence on the microbiota composition, which has its own circadian rhythm critical to the health of the human host, should be underscored; the synchronous (or dyssynchronous) relationship between endogenous molecular clocks mediating circadian rhythmicity, metabolism, and physiology. The endogenous biological clocks are entrained by the extrinsic control parameter of a lifestyle that is in sync (or out of sync) with the external light/dark daily cycle. The endocrine system in a cyclical fashion controls every aspect of our lives, including our moods, energy levels, physical strength and growth, appetite regulation, cognition, sexual appetite and reproduction, sleep, cell, and DNA repair, as well as antioxidant systems. It regulates the stress response and is responsible for the exquisite organizational coherence spanning all domains of the human system as an organism or being. As discussed above, energy-sensing molecules in the cell upregulate stress-signaling responses to provide energy when energy balance is negative. These metabolic responses to the stress of energy demand involve engaging endocrine hormonal systems and the thyroid and steroid family of nuclear hormone receptors. This activity is innately influenced by the circadian rhythmicity of endogenous molecular clocks and clock-controlled gene output. Nuclear hormone receptors lay at the intersection of metabolism and endogenous clocks and play a fundamental role in the response to energy stress. The endogenous molecular timepieces are a stunning evolutionary mechanism for temporally organizing metabolic physiology and behavior of living systems. All three major extrinsic control parameters that frame the physiological fitness landscape proposed in this writing may be definable as inherently unhealthy when bidirectionally coupled to systemic insulin resistance in classical metabolic tissues * The gut microbiota may be considered both an intrinsic control parameter (hence, a secondary order parameter) as well as an extrinsic control parameter. In the former case, it is by recognizing the commensal and symbiotic microbiota as a fundamental part of the intrinsic nature of a human being underscored by the endogenous immune system tolerance of these organisms. Alternatively, in the latter case, the mucosal lining of the gut lumen represents the interface between the internal milieu of the body and the external environment. Accordingly, even the healthy commensal and symbiotic microbiota may be considered “extrinsic”. Notably, the gut lumen, from the mouth to the anus, should be considered analogous to the “outside” center hole of a donut or a bagel.

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Calorie Restriction and Metabolism with supraphysiological fasting insulinemia and upregulation of signaling in insulin-responsive tissues. Insulin signaling, which is associated with nutrient availability, suppresses cell resistance gene programs mediated by, for example, the FOXO transcription factors described above. Additionally, the ratio of AMP/ATP (and ADP/ATP), as well as that of NAD+/NADH, are reduced by the surplus of energy availability, hence downregulating the activation of low fuel gauge energy-sensing molecules AMPK and SIRT1. Consequently, consistent with an overabundance of food supply, there is a continuous repressive effect on FOXO-activated gene transcription programs.

5.4.1 Nodes of Insulin Signaling It is paramount to recognize relationships and perspectives of disturbed insulin signaling in metabolic disease states that represent susceptibility states for premature chronic diseases of aging. This can be useful on several levels. On a clinical scale, it hones intuitive instincts, for example, considering the nuanced therapeutic strategies of calorie restriction, and overlapping approaches of exercise and exercise mimetics to promote adaptive insulin signaling. Even more valuable would be to invoke the quantitative fitness landscape model. However, it should also be recognized that at both the molecular basic science and clinical levels, insulin resistance affects different tissues in different ways. Impaired signaling of insulin in insulin-resistant metabolic tissues such as skeletal muscle, liver, and adipose will be affected differently than insulin-sensitive tissues will be, under the influence of hyperinsulinemia. Furthermore, hyperinsulinemia promotes crosstalk with other signaling pathways, for example in the breast where it co-opts estrogen signaling cascades and vice versa. These mechanisms of crosstalk provide further therapeutic opportunities; for example, estrogen receptor blockade that diminishes hyperinsulinemia-induced mitogenic effects through estrogen signaling pathways in addition to insulin signaling pathways (PI3K/Akt and Ras/mitogen-activated protein kinase (MAPK; Figure 5.11). The insulin signaling field of molecular biology is fantastically complex. From the perspective of the need to understand these pathways sufficiently to apply a top-down approach with targeted therapy, the challenges are daunting. There are over 1,700 signaling pathways with two critical nodes that have been discovered by the work of C. Ronald Kahn at the Joslin Diabetes Center in Boston. These two critical nodes include the central pathways of PI3K/Akt and Ras/MAPKs. Insulin inhibition of pro-apoptotic signals FOXO transcription factors and glycogen synthase kinase 3 (GSK3) represent alternative branches of the PI3K/Akt node. Insulin is a survival signal, consistent with the idea that insulin resistance in metabolic tissues and resultant hyperinsulinemia mediate cancer cell transformation in insulin-responsive (non-classical metabolic) tissues. However, GSK3 may also serve as a survival signal, in which case insulin inhibition of this molecule may intuitively be protective. The contextual nature of GSK3 as a survival versus an apoptotic signal underscores its complexity consistent with all molecular biological systems; in general, their hallmark is nonlinearity and unpredictability. Another branch of the PI3K/Akt node is the PI3K/Akt/mTOR pathway. This

FIGURE 5.11  Crosstalk between molecular pathways activated by insulin and estrogen, which is promoted by hyperinsulinemia. *PI3K = phosphoinositide 3 kinase; Akt = Protein kinase B; MAPK = Mitogenactivated protein kinase.

branch promotes protein synthesis, cell growth, and survival via activation of mTOR. Alternatively, the Ras/MAPKs nodes are mitogenic by their effects on the cell cycle. Furthermore, there is crosstalk between survival and mitogenic pathways at multiple levels, with context dictating reciprocal activation or inhibition of one another. For example, at low doses of insulin or other growth factors, PI3K/Akt activates Ras/MAPK pathways, whereas, at higher doses, Ras/MAPK exerts inhibitory effects on PI3K/Akt (27). It appears that the teleological design of insulin as a metabolic regulator is to promote the uptake of alternative fuel substrates, primarily lipid or glucose, into cells for its subsequent conversion to ATP. This feeds the energy demands of the cell, including that needed to accommodate additional insulin signaling programs of intricately coordinated cell survival, growth, and replication. These insulin-mediated metabolic functions of cell biology are signaled through central nodal pathway cascades of PI3K—>Akt—> GLUT4 (glucose transport type 4); PI3K—>Akt—>CD36 (fatty acid transport); PI3K—>Akt—>mTOR (cell survival and growth/anabolism); and Ras—>Raf—>MAPK (cell survival and replication; Figure 5.12).

SIDEBAR 5.5: RECENT REPORTS A recent study from Steve Mittelman and colleagues (28) examined a group of 40 adolescent patients with a 20% calorie deficit during the induction treatment for acute lymphoblastic leukemia (ALL). This calorie deficit was achieved through a combination of diet and exercise and resulted in a decrease of fat mass gain in patients who were overweight or obese at the time of diagnosis. It also showed an overall decrease in minimal residual disease and an increase in the leptin to adiponectin ratio in all

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FIGURE 5.12  Central insulin signaling pathways that promote metabolic functions of the cell. *PI3K = phosphoinositide 3 kinase; Akt = protein kinase B; GLUT4 = glucose transporter type 4; CD36 = cluster of differentiation 36; mTOR = mammalian target of rapamycin; MAPK = mitogen-activated protein kinase.

patients compared to historical controls. These results further support the beneficial effect of exercise and calorie restriction on body fat in those individuals with hypertrophic adipocytes and associated insulin resistance, hyperinsulinemia, lower levels of adiponectin (which improves insulin sensitivity and the proinflammatory milieu), and higher levels of leptin. Hyperinsulinemia drives the autophosphorylation of tyrosine kinase insulin receptors and insulin heterodimers with IGF-1 receptors, which drive signaling through IRS/Ras/Raf/MAPK as well as IRS/Ras/ PI3K/AKT/mTOR pathways to promote cancer cell survival, increased cancer cell growth and proliferation, and increased angiogenesis. Additionally, these same effects are promoted by a high ratio of leptin to adiponectin signaling through the IL-1/JAK-STAT/NFkB pathway.

5.4.2 The Role of GSK3 in Cell Resistance Insulin signaling transduction also inhibits GSK3, promoting the disinhibition (i.e. activation) of the enzyme glycogen synthase and glycogen synthesis. Moreover, despite its name, GSK3 has functions beyond the inhibition of glycogen synthesis. In a healthy state during the daytime feeding phase of the daily cycle glycogen synthesis occurs primarily in metabolic tissues, skeletal muscle, and the liver. However, in the state of pathological insulin resistance these tissues are resistant to insulin during this daytime circadian phase when they should be sensitive. Conversely, in a healthy individual circulating insulin levels are low during the anticipated fasting nocturnal hours. However, primary or compensatory hyperinsulinemia in this phase has pathological consequences to the cells and tissues organism-wide. This exemplifies a breakdown in the synchronization and coherence of molecular clock-generated circadian physiology between tissues of the body, a basic hallmark of disease. It has central importance in the pathways of proliferation and apoptosis. It targets β-catenin, which it phosphorylates, resulting in degradation through a process known as ubiquitination. In this way, it inhibits the Wnt/β-catenin pathway, which when active, promotes cell proliferation. Thus, the inactivation of GSK3 by insulin during the feeding

Metabolism and Medicine

FIGURE 5.13  Insulin and Wnt signaling pathways. Insulin inhibits GSK3 and, thus, reduces glycogen synthesis through disinhibition. In the absence of insulin, GSK3 is active leading to an increase in glycogen synthesis and additionally promotes cell death through its interaction with pro-apoptotic p53. Wnt signaling inactivates GSK3, allowing for the Wnt/β-catenin “survival pathway” to promote the transcription of proliferation stimulating target genes. In the absence of Wnt, GSK is active and phosphorylates β-catenin, thus, marking it for ubiquitination. *PI3K = phosphoinositide 3 kinase; Akt = protein kinase B; GSK3 = glycogen synthase kinase 3; p53 = tumor protein 53.

phase of the daily cycle allows the utilization of nutritional resources for anabolism and cell replication. However, in the state of chronic insulin resistance and hyperinsulinemia that is present during the nocturnal and natural fasting phase, the inactivation of GSK3 results in negative outcomes. That is, epithelial cell replication of many tissues, including gastrointestinal, urogenital, and reproductive tracts, loses its normal circadian inhibition. It follows, in the oncogenic coenvironment of inflammation and disturbed redox with associated mutagenesis, chronic insulin resistance is a susceptibility state for cancer cell proliferation. In addition to GSK3 inactivating the “survival pathway” of Wnt/β-catenin, it also promotes cell death, i.e. apoptosis, by activating proapoptotic factors such as p53 (Figure 5.13) (29, 30). GSK3 is also involved in the upregulation and production of proinflammatory cytokines by the innate immune system (31, 32). Overactivated GSK3 is associated with a number of clinical pathogenic states including Alzheimer’s disease, cancer, and type 2 diabetes. It also has a role in bipolar disorder; lithium, a mainstay therapy for bipolar disorder, appears to work by selectively inhibiting GSK3 (31).

SIDEBAR 5.6: GSK3 INHIBITORS AS A TREATMENT FOR ALZHEIMER’S DISEASE AND CANCER GSK3 promotes the accumulation of amyloid-β deposits in the brain. GSK3 also hyperphosphorylates tau proteins, causing neurofibrillary tangles (30–32). Both accumulation of amyloid-β and hyperphosphorylation of tau proteins lead to Alzheimer’s disease. Another disease promoted by GSK3 overactivation is glioma and pancreatic cancer development. Therefore, GSK3 inhibitors are undergoing

Calorie Restriction and Metabolism preclinical testing as possible treatments for these diseases of aging therapy in various stages of drug research and development for the treatment of both Alzheimer’s disease and cancer. GSK3 interacts with many signaling pathways. Preclinical cancer research often uses genetically identical mice with identical disease states. In contrast, the human population has tremendous genetic variation, with cancer states at different stages of progression. This wide variation between inbred mice and outbred humans makes it difficult to predict how effective GSK3 inhibitors will be in cancer patients. Individualized quantitative precision modeling uses algorithms to forecast how GSK3 inhibitors might work in a specific cancer patient, taking into account the specific cancer type and subtype, stage, the type of insulin receptor, presence or absence of insulinlike growth factor (IGF) receptor, paracrine levels, and circulating insulin and IGF levels. Up to a million different parameters can be factored into these analyses! GSK3 is relevant to the connection of endogenous molecular clocks and nuclear hormone receptors to limited energy resource availability as it is the type of stress signal that regulates redox stress resistance programs in the cell. Specifically, GSK3 is important in the stabilization of nuclear receptor Reverbα which regulates circadian clock rhythmicity (33, 34). GSK3 serves as a molecule with significant implications for Medicine as a signal of the nutrient energy state of the body, reciprocally correlating with insulin signaling in many tissues. It speaks to the importance of calorie restriction as a potential therapeutic and preventive health strategy in a wide spectrum of human health and chronic disease, as well as to the central role of insulin resistance in the case of the latter.

207 when such resources are not. Activation of insulin receptors promotes a signaling cascade mediated by insulin receptor substrate (IRS) → phosphoinositide 3 kinase (PI3K) → Akt/ protein kinase B (Akt/PKB). Insulin activated Akt/PKB promotes inhibitory phosphorylation of FOXO and of AMPK to signal nutrient-rich conditions (Figure 5.14). Accordingly, this signals that there is a reduced need to generate ATP production from endogenous sources of energy. AMPK acts as a primary sensor of low energy states. Triggered by a low ratio of AMP/ATP, AMPK is a key regulator of FOXO, such as in the liver where it is activated in response to low amounts of dietary energy sources coming from the gut. mTORC1 is inhibited by FOXO by more than one mechanism, including FOXO upregulation of AMPK activity (35). Both FOXO and AMPK upregulate cell stress resistance programs designed in circadian fashion to protect against redox stress. These rescue programs, as outlined in the accompanying figure (Figure 5.15), reduce oxidative stress and consequently preserve redox and free energy homeostasis. This in turn slows the progression of cell senescence and reduces chronic diseases of aging. Conversely, mTORC1 inhibits cell stress resistance programs while promoting energy-requiring anabolic processes of cell growth and cell proliferation (36). The associated high bioenergetic demands for ATP production are responsible for the generation of ROS that drives oxidative stress, challenging redox and free energy homeostasis. Synchronized organizational timing is of critical importance. mTOR-mediated processes induce redox stress that is followed in a circadian manner by FOXO-mediated pathways that provide resistance to redox stress. Additionally, while mTORC1 promotes cell proliferation including that of cancer cells, FOXO upregulates tumor suppressor activities, such as decreasing cellular proliferation and promoting cell cycle

5.4.3 The Role of mTOR in Cell Resistance Insulin signaling, in addition to inhibiting GSK3- and FOXOmediated pathways, also upregulates mTOR), which regulates downstream protein synthesis and anabolism. mTOR acts as a ‘master switch’ of cell energy, requiring anabolic processes as well as energy-yielding catabolic processes. An example of this would be an upregulation of glycolysis in order to supply energy for cell replication in cancer cells, mediated by the Warburg effect. Basically, mTOR is an atypical serine/ threonine protein kinase that coordinates cellular supplies and demands to promote cell growth, proliferation, and survival. There are two major forms of mTOR, mTOR Complex 1 (mTORC1) and mTOR Complex 2 (mTORC2), which differentially regulate energy-requiring physiological processes. mTOR derives its name, mammalian target of rapamycin (formerly called mechanistic target of rapamycin), by the previously considered sensitivity of yeast containing mTORC1 isoform versus the insensitivity of yeast containing mTORC2 to the antimicrobial agent rapamycin. Insulin receptors (IRs) are the most well-known of the growth factor receptors; they are activated when nutrient resources are available, yet inhibited

FIGURE 5.14  The activation of insulin receptors by nutrient availability signaling through PI3K, which in turn activates Akt. Insulin-activated Akt then phosphorylates FOXO and AMPK leading to their inhibition, preventing FOXO from activating stress resistance programs. Akt activation also stimulates mTOR activity, which leads to cell growth and proliferation as well as protein synthesis. *IRS = insulin receptor substrate; PI3K = phosphoinositide 3 kinase; Akt = protein kinase B; AMPK = AMP-activated protein kinase; mTOR = mammalian target of rapamycin; FOXO = FOX gene O subclass.

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FIGURE 5.15  Cell redox stress resistance programs. FOXO and AMPK promote stress resistance programs of antioxidant systems, DNA and cell repair, autophagy, cell differentiation, and apoptosis, while mTORC1 inhibits these programs and activates energy-requiring anabolic processes. *AMPK = AMP-activated protein kinase; mTOR = mammalian target of rapamycin; FOXO = FOX gene O subclass.

arrest. This exemplifies the exquisite organizational beauty that defines the health of any living system. Biological systems evolved on the fundamental basis of cycles and cycles within cycles that create the biology of time purposed to slow the arrow of time. It is the temporal coherence and balance of interactions between systems of cycles that are central parameters of health. Activation of FOXO follows the downregulation of insulin receptor signaling in the setting of calorie restriction, such as dietary restraint or when resource availability is limited. Accordingly, one way that activation of FOXO maintains cell energy homeostasis is by lowering nutrient energy demand. It does this by decreasing cell proliferation and growth, reducing the metabolic demands for ATP production. It follows, therefore, that the natural combustion byproduct of inflammatory and entropic processes of ATP production that challenges redox and free energy homeostasis is reduced. This is all part of the natural circadian design to maintain biological homeostasis. Consonant to this temporal design, FOXO activation submits to the upregulated expression of insulin receptors on the cell surface. The enhanced insulin sensitivity mechanistically increases preparedness for nutrient resources when they do become available. Thus, in circadian fashion, appropriate anabolic activities of cell growth and cell proliferation occur, mediated by mTOR once dietary glucose activates insulin signaling. mTOR accordingly promotes the energy-requiring processes of lipid and protein biosynthesis, which are driven by the molecular signaling pathway of insulin receptor (IR) -> insulin receptor substrate (IRS) → PI3K → Akt/PKB → mTOR. When nutrient resource limitations persist within a range of optimal duration calorie restriction, this is responsible for the salutary health benefits via FOXO induction of cell resistance programs to redox stress. These include the induction of antioxidant systems, DNA and cell repair processes, along with autophagy and apoptosis-promoted rescue mechanisms. Notably, when oxidative stress conditions are present independent of nutrient status, stress kinases that activate FOXO such as c-Jun N-terminal kinase (JNK) are dominant over the insulin signaling Akt/PKB-mediated inhibition of FOXO (Figure 5.16). It’s all about the balance of redox stress generation, from both dietary excess and non-dietary sources, and the level of resistance to it. Timing is critical for the dietary restriction that upregulates these resistance programs and factors into the cumulative burden of redox-mediated molecular damage. Both the PI3/Akt and RAS/MAPK pathways of insulin signaling in the metabolic environment of nutrient excess promote

FIGURE 5.16  Under circumstances of nutrient availability, signaling through insulin receptors via PI3K and Akt inhibits FOXO-mediated transcription of stress resistance genes. During conditions of oxidative stress, kinases such as JNK mediate the activation of FOXO and downstream stress resistance programs. *IRS = insulin receptor substrate; PI3K = phosphoinositide 3 kinase; Akt = protein kinase B; FOXO = FOX gene O subclass; ROS = reactive oxygen species; JNK = c-Jun N-terminal kinase.

the bioenergetically demanding processes of cell growth and mitogenesis and competitively inhibit the longevity gene programs activated in an energy-restricted environment. A paragon example of longevity genes can be seen in the cell redox stress resistance programs (Figure 5.17), upregulated by activated, low energy state sensor molecules AMPK and SIRT1. It is crucial to understand that the actions of insulin cannot be regarded qualitatively as a good or bad hormone signal. It signals the availability of dietary nutrients and has diverse pleiotropic effects, for example inhibiting stress resistance pro-apoptotic signals (such as FOXO transcription factors and GSK3) versus promoting protein synthesis, growth, and cell replication (such as through mTOR and RAS/MAPK pathways). However, the outcome of salutary effects on health versus disease-causing detrimental effects is entirely contextual, and an important function of timing.

SIDEBAR 5.7: INSULIN—GOOD COP, BAD COP, OR BOTH? Insulin cannot be categorized as a “good cop” or “bad cop” in an analogous sense that it cannot be described categorically as a pro-apoptotic, survival, mitogenic,

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SIDEBAR 5.8: CALORIE RESTRICTION— IS THERE AN OPTIMAL DOSE?

FIGURE 5.17  Nutrient excess (increased insulin) leads to signaling pathways that inhibit the transcription of longevity genes promoting the acceleration of aging. Conversely, calorie restriction (decreased insulin) enhances the expression of longevity genes and is associated with the natural progression of aging. *PI3K = phosphoinositide 3 kinase; Akt = protein kinase B; MAPK = mammalian target of rapamycin; AMPK = AMP-activated protein kinase; SIRT1 = sirtuin 1.

inflammatory, or anti-inflammatory signal. It is entirely contextual, dependent on the conditions of the cell. Similarly, insulin resistance despite its pejorative association with metabolic disease, in and of itself, is part of a greater whole in a temporal sense in the context of healthy physiology. That is, when insulin resistance follows a periodic cyclicity such as circannual insulin resistance in hibernating bears or migratory birds, or feeding/fasting circadian cycles in humans, it is a healthy phenomenon. Accordingly, this important perspective that the environment influences behavior is applicable to many domains in the life and behavioral sciences. Changing the environment of a cell results in the change of the characteristics of that cell. A cop who has been assimilated within a corrupt culture will likely behave very differently than if he/she has been assimilated into a healthy culture.

5.5 Circadian Insulin Signaling 5.5.1 Hormesis and Circadian Insulin Signaling The application of the notion of hormesis to levels of circulating insulin and its receptor sensitivity, i.e. what is optimal versus detrimental for healthy physiology, is contextual to the timing within the circadian cycle. This informs important clinical therapeutic relevance to strategies of intermittent fasting, for example restricting calorie intake to the daylight hours. Accordingly, the lower circulating insulin levels that occur nocturnally are in sync with the natural circadian pattern of resistance programs to redox stress in cells. This provides maximum attenuating effects and resistance against the redox stress and damage imposed during the more metabolically demanding daylight hours. Moreover, the role of oxidative stress and its bidirectional relationship to inflammation, together as a precipitating cause of insulin resistance/hyperinsulinemia, is in turn caused by excess caloric intake.

Caloric intake can also be understood in the context of hormesis in the sense that some optimal “dose” is necessary and beneficial, while too little or too much is unhealthy and promotes oxidative stress and inflammation, and thus also insulin resistance/hyperinsulinemia. While there is no lower limit to the optimal dietary consumption within the dark phase of the daily cycle (i.e. optimal is zero food consumption), the quantity of healthy food consumption during the daylight hours has both low and high limits. Caloric intake that exceeds bioenergetic capacity equates to breaching the “take-over threshold” of quantum metabolism. This results in the transition of the temporal-spatial synchronously correlated nature of oxidative phosphorylation to a less efficient classical mode of ATP energy production and release. This is a critical transition point that promotes the formation of superoxide and other reactive redox species, the biological analog to the entropy of a physical system. The critical transition of exceeding the optimal upper dietary limit marks Demetrius’s “take-over threshold”, whereby leakage of electrons from the electron transport chain drives formation of ROS as a susceptibility state for chronic disease. This also parallels Brownlee’s unifying hypothesis described in his 2004 Banting Lecture. Brownlee contends essentially that insulin resistance is a central control parameter for chronic disease states of aging, such as cardiovascular disease, and hence arguably, the pace of aging itself. In this case, leakage of electrons results in a pathological degree of inflammation, manifesting in insulin resistance. The post-reproductive phase of the human life cycle that begins roughly at the onset of middle age in women (and, on rare occasions, later in men), is accompanied by an increasing incidence of insulin resistance manifestations. Sequelae include parameters of metabolic syndrome such as hypertension and dyslipidemia. Even more fundamental are the anthropometric measures of sarcopenia and adiposity, which parallel mitochondrial content and function, and importantly, insulin resistance. It follows that beyond the onset of middle age, advancing age correlates at a basic level with the decline of mitochondrial capacity and the onset and progression of insulin resistance (see Chapter 8, for the molecular basis of insulin resistance and mitochondrial function relationship). As mitochondrial dysfunction progresses, so does the generation of ROS and subclinical inflammation. The rate of progression of this process may be considered the entropy production rate and molecular basis of senescence. It appears that insulin resistance/hyperinsulinemia in many, if not most cases, is an inseparable feature of this decline. These parameters also coincide in parallel with a progressive lowering of the healthy upper limits of dietary consumption with aging. Moreover, the measures of hormesis relative to diet, and likely all extrinsic control parameters of health, change dynamically over the course of a lifetime.

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FIGURE 5.18  Interconnected control parameters of human disease including diet (extrinsic), circadian behavior (extrinsic), stress response (intrinsic; psychogenic/physical stress extrinsic), and microbiota composition (may be considered intrinsic or extrinsic).

Other central extrinsic and intrinsic control parameters to which diminishing biological resilience promotes human disease include poor quality and timing of diet, and timing of other behaviors (extrinsic), the psychogenic stress response (intrinsic; psychogenic/physical stress extrinsic), and the microbiota composition (intrinsic and extrinsic; Figure 5.18). Senescence is the biological deterioration of beautiful organizational complexity over the course of a lifespan, beginning with middle age. It is insuperably and fundamentally tethered to a declining capacity to manage extrinsic challenges at levels to which there was previous resilience. This is another hallmark of context dependence relative to the notion of hormesis.

5.5.2 Circadian Insulin Resistance and Cell Redox Stress Resistance Programs The most fundamental control parameters of metabolic health are rooted in energy and redox homeostasis. Endogenous energy stores are utilized to generate ATP during the fasting state when much of the metabolic demand is employed to maintain oxidative cell stress in balance; these functions are teleologically linked to the nocturnal circadian phase of the daily cycle. This is the phase when metabolic sensors AMPK and SIRT1 are activated and intricately tethered to clock-controlled genes and gene output metabolic programs of transcriptional regulation. These regulators include NHRs, their hormonal ligands, and hormones such as melatonin, which induces slow-wave sleep. They synchronously orchestrate pathways of redox resistance, bioenergetic production of ATP and inhibit anabolic pathways that consume ATP. While these pathways occur on a cellular scale, they regulate the macroscopic manifestations of the cognitive and emotional stress response and in this sense many voluntary behaviors. Even more sensational is that these pathways are foundationally responsible for the exquisite organizational coherence spanning all domains of the human system as an integrated organism. However, when things go awry, for example, due to emotional stress that promotes deterioration in lifestyle dietary and circadian behaviors, obesity and other manifestations of insulin resistance with or without type 2 diabetes often result, with the consequence of premature aging and chronic disease susceptibility.

Metabolism and Medicine In low energy states, energy sensing molecules in the cell promote repairing of oxidative injury to the cell that limits associated inflammation. Accordingly, this reduces the entropic process of aging and disease. Nuclear hormone receptors lie at the intersection between the endogenous clocks and metabolism, coupling metabolic processes to cyclical circadian output. This is critical because the quality of biological health is determined by the cyclical and synchronized nature of metabolic functions. These endogenous molecular timepieces are a stunning evolutionary design for the temporal organization of metabolic physiology and behavior of living systems.

Insulin resistance is a central basis for more chronic disease states than it is typically attributed. Insulin resistance and chronic disease state manifestations are promoted by all the major extrinsic control parameters (diet, circadian behaviors, and microbiota) and the major central secondary order parameters (stress response and microbiota) that frame the fitness landscape proposed and discussed throughout this book. In fact, insulin signaling is thought to be a more fundamental regulator of clock-controlled genes (genes whose products directly feedback onto the clock) and clock-controlled output genes are thought to be mediators of the fasting-feeding cycle rather than nutrients per se. The caveat is the exception being of nutrients that directly interact with nuclear receptors which are either clock components or regulators of the clock.

SIDEBAR 5.9: INSULIN RESISTANCE— ADAPTIVE UNDER CIRCADIAN CONTROL BUT PATHOGENIC UNDER NON-CIRCADIAN CONDITIONS Classical insulin targeted tissues are traditionally considered on the basis of insulin suppression of glucose output from the liver, insulin-stimulated GLUT4-mediated glucose uptake in skeletal muscle, insulin-stimulated LPL-mediated fatty acids (facilitated by insulin-stimulated CD36), glycerol uptake with triglyceride reesterification into adipose tissue, and insulin suppression of hormone-sensitive lipase (HSL) in adipose tissue. However, low to moderate levels of cyclical insulin resistance are metabolically adaptive to maintain homeostasis during periods of fasting or starvation. It does this by providing adequate hepatic and adipose tissue output of glucose (and lipids primarily as triglyceride-containing very-low-density lipoprotein (VLDL) particles) and lipid substrates, respectively, to support the energy demands of tissues beyond the classical metabolic insulin targeted organs. Similarly, with prolonged fasting, skeletal muscle selfishly catabolizes to provide amino acid energy substrates to fuel hepatic gluconeogenic output for use by the brain and other tissues. Adaptive cycles of physiological insulin resistance provide the necessary energy storage for circannual hibernation of bears or migration of birds, the human circadian patterns of hormonal activity and metabolic rhythm, and the latter half of gestation. These examples represent different temporal scales of synchronized biological organization.

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5.5.3 Transition from Circadian to Chronic Non-Cyclical Insulin Resistance A hallmark of pathological human insulin resistance is the desynchronization of the circadian cycling of insulin sensitivity and resistance. This occurs within and between classical insulin targeted tissues that are essential for maintaining energy homeostasis. Furthermore, there is a breakdown of synchronous physiology between these tissues and others organism-wide, resulting in the loss of metabolic homeostasis, which defines the transition from the state of health to disease. A finely tuned temporally coordinated balance between resource supply and demand is critical for maintaining parameters of metabolic homeostasis within narrow physiological ranges. When these conditions are not present, it creates a metabolic crisis. Insulin is a hormone with strong patterns of secretory release and peripheral sensitivity. Pathological insulin resistance is associated with disturbed circadian patterns typically characterized by some degree of dyssynchrony; there is relative insulinopenia in the postprandial period but relative hyperinsulinemia in the fasting state. This runs counter to the normal circadian physiological rhythm innately generated by endogenous clocks. The significance and central nature of this to chronic human disease are underscored by the strength of insulin as a critical feeding/fasting signal. Cyclical human insulin resistance is a teleologically adaptive time-restricted pattern that is in sync with the biological rhythm of the integrated molecular clock of the body, and entrained with the light/dark cycle. However, the compartmentalization and breakdown of this correlated rhythm increasingly occurs with advancing age, representing a fundamental susceptibility state for a wide range of pathological sequelae and chronic diseases. Even more fundamental in the sense

of the assimilated biological systems of parts and wholes across hierarchical scales that manifest as a macroscopic scale of physiology, are the underlying impaired bioenergetics and redox. Reduced availability of Gibbs free energy flow accompanying oxidative stress impacts many scales of biology, and ultimately insulin resistance, in bidirectional reverberating and self-amplifying cascades (Figure 5.19). These pathogenic bidirectional loops affect controllable behaviors such as the timing of when we eat, sleep, rest, exercise, work, and socialize; the quantity and quality of what we eat; and, the amplitude and quality of our stress response. These cascading loops and inextricably interwoven behavior patterns entrain and amplify one another, creating the dynamic portrait of a deteriorating Physiological Fitness Landscape. In parallel with this portrait is the changing composition of gut microbiota. This further stimulates the systemic inflammatory response and redox stress that disturbs energy homeostasis and voluntary pathological behaviors. Also inextricably connected in this web is the dyssynchronous temporal organization of endogenous clocks.

5.5.3.1 Energy Sensor Responses to Non-Cyclical Insulin Resistance The characteristic of insulin resistance that makes it pathological is the loss of the circadian cyclicity of insulin secretory and sensitivity patterns in metabolic tissues (see Figure 5.8). It is featured by fasting hyperinsulinemia and the overexpression of insulin signaling mitogenic and inflammatory pathways in non-classical metabolic tissues. Concurrently, the ratios of AMP/ATP as well as of NAD+/NADH are reduced by the energy surplus while FOXOs are unemployed in these tissues due to the relatively inactive state of SIRT as well as

FIGURE 5.19  Impaired bioenergetics and redox stress accompanied by a decrease in Gibbs free energy flow lead to states of insulin resistance and chronic inflammation. This alters behavior patterns of diet, sleep, exercise, stress responding, socialization, and work while concurrently creating mitochondrial dysfunction, alterations in gut microbiota, and impairing clock synchronicity.

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5.5.3.2 Nocturnal Eating, Overconsumption, and the Development of Metabolic Disease

FIGURE 5.20  Fasting hyperinsulinemia resulting from insulin resistance leads to a decrease in the ratio of AMP/ATP and NAD+/NADH. Increased insulin signaling also causes a reduction in FOXO, resulting from both decreased SIRT1 signaling and directly from the increase in insulin signaling. *SIRT1 = sirtuin 1; FOXO = FOX gene O subclass.

by insulin inhibition as a feeding signal (Figure 5.20). Hence, energy-sensing molecules AMPK and SIRT1, respectively, are suppressed during the nocturnal phase when they should be activated. Alternatively, FOXO in insulin-resistant classical metabolic tissues is not suppressed by insulin, allowing, for example, inappropriate glucose production in the liver and release into the bloodstream when it is not needed. However, there is suppression of FOXO activation and downstream gene transcription programs in insulin-responsive non-classical metabolic tissues. Consequently, the desynchronized loss of temporal organization of metabolic housekeeping compromises the capacity to maintain the parameters of energy, redox, and acid-base foundationally essential for the state of health.

A common pathogenic behavior is chronic dietary overconsumption (discussed in detail at the end of this chapter in Section 5.7). This is not only in terms of total daily caloric intake, but also the quantity of intake relative to the time of the day. An interlocking discussion of why nocturnal eating leads to obesity and metabolic disease in the context of circadian physiology can be found in Chapter 4 (Section 4.6.2.2). Energy storage and utilization are temporally organized in a circadian manner to synchronize with metabolic anticipated supply and demand. The optimal timing of food consumption further reinforces entraining of behavior to healthy physiology. Conversely, dyssynchrony of meals and eating behavior from the organizational design of circadian biology is a major and woefully underrecognized control parameter of metabolic disease, overburdening mitochondria with energy substratecausing redox damage and resultant mitochondrial dysfunction (Figure 5.21). In the case of overconsumption, the supply of metabolic substrates delivered to the mitochondria and its ETC exceeds the capacity to efficiently convert energy to the biological currency of ATP. Accordingly, the energy is lost as heat, unavailable to do useful biological work carried out by ATP; associated entropy in a biological system equates to ROS formation and redox stress. The mitochondria are the organelle where most ROS are formed, and therefore proximity makes these organelles susceptible to destructive oxidative modification. Furthermore, mitochondrial DNA is not protected by histones, leaving it particularly vulnerable. This is a major basis of mitochondrial dysfunction, which amplifies oxidative

SIDEBAR 5.10: THE ROLE OF NUCLEAR HORMONE RECEPTORS Insulin is an important regulator of a number of nuclear hormone receptors including farnesoid X receptor (FXR) and liver X receptor (LXR). Both FXR and LXR have significant regulatory effects on cholesterol and lipid homeostasis (37) (see Chapter 3, Section 3.3.1). FXR has a salient regulatory role on gut microbiota composition and on the integrity of the epithelial barrier of the gut (38). LXR has an important role in reverse cholesterol transport and cardiovascular disease protection. There is also the potential to beneficially exploit LXR agonist agents for their effect on various cancers including prostate, breast, and melanoma as well as on Alzheimer’s disease. However, these nuclear hormone receptors are intricately and inherently part of the temporal framework of the circadian rhythm. Accordingly, when the temporal organization of this endogenous rhythm becomes disturbed, it promotes fasting hyperinsulinemia and pathological insulin resistance, representing another circuitous self-exacerbating loop. Thus, insulin resistance is part of a cyclically synchronous organ system and organismic metabolic physiological design; however, whether it is a control and order parameter of health versus disease is contextually dependent.

FIGURE 5.21  Excess energy substrate (hyperglycemia) induces the production of superoxides by the mitochondrial ETC leading to redox damage and ultimately mitochondrial dysfunction. When there is a high level of glucose in cells, a critical threshold in the voltage gradient across the mitochondrial membrane is reached, which blocks the transfer of electrons along the protein complexes of the ETC. These backed up electrons interact with coenzyme Q to form superoxides. Source: adapted from (1). *Cyt c = cytochrome c; e- = electron; Mn-SOD = manganese superoxide dismutase.

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Calorie Restriction and Metabolism stress in a feedforward self-exacerbating bidirectional fashion. Thus, the efficiency of bioenergetics is compromised, forcing a greater reliance on glucose and the metabolically less efficient glycolysis pathway. Fatty acid metabolism production of ATP is entirely mitochondrial-dependent, and is therefore impaired in the setting of dysfunctional mitochondria. Notably, the amount of ATP produced per molecule of glucose through the glycolysis pathway is less than 1/15th that produced via mitochondrial oxidation. Consequently, this dictates a need to deliver high levels of glucose to cells systemically, and thus may underscore a maladaptive compensatory coupling of insulin resistance to mitochondrial dysfunction. The higher hepatic glucose output and reduced skeletal muscle uptake promote a hyperglycemic environment that is excessive for the needs of supply requirements for glycolytic ATP production in tissues throughout the body. The Brownlee unifying hypothesis describes non-energy producing pathways originating from various proximal intermediates of the glycolysis pathway that induce cellular and mitochondrial damage (glucotoxicity). In addition, this model attributes a dual cellular pathogenicity of hyperlipidemia (lipotoxicity) together with hyperglycemia to produce the synergistic combined effects of “glucolipotoxicity”. Exaggerated visceral adipose tissue lipolysis is responsible for the outpouring of fatty acids and glycerol into the portal circulation. This causes a hallmark manifestation of insulin resistance and ectopic hepatic steatosis, which in turn sets up the defining lipocentric triumvirate of insulin resistance: hypertriglyceridemia, low high-density lipoprotein (HDL), small dense low-density lipoprotein (LDL). Exaggerated adipose tissue lipolysis also causes elevated circulating nonesterified fatty acids, which together with continued dietary excess promotes the ectopic deposition of lipids in many tissues and organ systems of the body. Insulin resistance prevents adipogenesis and hyperplasia of mesenchymal cell-derived subcutaneous adipose tissue and its coupled lipogenesis; this limits the buffering storage capacity of excess fat in the body (39). In contrast, the visceral adiposity is innately inflammatory; it is derived from bone marrow myeloid progenitor cells (40). Encouraged by insulin resistance, visceral adiposity is considered by many to be central to the pathogenesis of systemic low-grade inflammation and peripheral insulin resistance. Visceral adipose has a diverse and robust arsenal of inflammatory adipokines and cytokines, which it secretes into the bloodstream to induce insulin resistance in skeletal muscle and other tissues. Furthermore, insulin resistance in adipose tissue (visceral and subcutaneous) directs the traffic flow of fatty acids from, and inhibits their entry into, adipocytes. This, together with a chronically positive energy balance from persistent dietary excess, and existing hypertrophied visceral and subcutaneous cell adiposity with overflowing lipids into the bloodstream, is the driving force to the formation of ectopic fat in many tissues. Provocatively, visceral adiposity and subsequently hepatic steatosis may be manifestations of insulin resistance that follow the overfilling of subcutaneous adipose storage capacity. Ectopic fat is the basis of lipotoxicity, which is central to the pathogenesis of metabolic and chronic disease sequelae of insulin

resistance. It is important to recognize this in often unsuspected clinical phenotypes of individuals with a generally asthenic body habitus and only mild unstriking central abdominal protuberance. These people have relatively little subcutaneous generalized adiposity, and often have so-called sarcopenic (low muscle mass) obesity, the latter typical in type 2 diabetics of Asian ethnicity; “obesity” of this type does not meet the BMI criteria of conventional obesity.

5.6 Ketone Body Metabolism CASE STUDY: FASTING-INDUCED NEUROGLYCOPENIA IN A TYPE 1 DIABETIC A 42-year-old man presented with acute nausea, vomiting, and abdominal pain. He has a history of type 1 diabetes since childhood complicated by gastroparesis and is on a regimen of long- and rapid-acting insulins. He was admitted with metabolic decompensation of diabetic ketoacidosis accompanying severe hyperglycemia and volume depletion. For three to six months prior to the current hospitalization, the patient reports increasing bouts of hypoglycemia with blood glucose levels in the range of 30–40–mg/dL and confusion with the absence of adrenergic symptoms such as tremors, palpitations, or diaphoresis. His appetite has been poor, causing prolonged involuntary fasting, lasting a full week prior to admission. His self-management decisions were to decrease his long-acting insulin dose to a fraction of his baseline dose, and to hold the rapid-acting insulin in the absence of meals. Despite the repeated occurrences of hypoglycemia, his mental clarity has not diminished over the past month. The patient was treated with i.v. insulin, fluid, and electrolyte therapy to reverse the metabolic abnormalities and dehydration. Nonetheless, he continued to experience a poor appetite, abdominal pain, epigastric tenderness, and severe episodes of hypoglycemia. Despite glucose levels as low as 30 mg/dL, he showed full mental clarity with absent adrenergic symptoms. It was empirically considered that despite i.v. insulin, ketosis persisted consequent to anorexia and prolonged ketosis-induced insulin resistance. Anorexia is intertwined with gastroparesis causing symptoms of bloating, early satiety, nausea, vomiting, and weight loss. Ultimately, these manifestations perpetuate anorexia and weight loss in a self-amplifying loop of persistent and worsening gastroparesis. Accordingly, pantoprazole and metoclopramide were started to reduce gastric acidity and to stimulate gastrointestinal motility, respectively. Within 24 hours the patient’s abdominal pain and appetite improved. The following day he had a large, solid bowel movement. His glycemia began to rise and he tolerated incrementally increased, prandial insulin. Basal insulin was initially maintained at low doses due

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to the depleted availability of precursor substrates for gluconeogenesis. After three days he tolerated his full weight-based long-acting insulin, and on day four he was discharged. From a therapeutic perspective, a few points are worth noting. One is the life-threatening nature of neuroglycopenia (hypoglycemia unawareness and unresponsiveness). Adrenergic activity responsible for tremors, palpitations, diaphoresis, and headaches for example, also promotes hepatic glucose output purposed to maintain euglycemia. Consider the consequences of prolonged insufficient glucose supply to the brain, such as lethargy, stupor, coma, and even death particularly precarious overnight while sleeping when it goes unobserved. Neuroglycopenia, like gastroparesis and orthostatic hypotension, all manifestations of autonomic neuropathy, portend an increased risk of fatal cardiac arrhythmias. A potentially life-saving clinical pearl as a general rule for neuroglycopenic patients, is the absence of hypoglycemia for three days restores hypoglycemic awareness and responsiveness for three months. Ketosis is a starvation adaptation intended to replace glucose as a fuel particularly for the brain in the setting of prolonged calorie restriction and starvation. As described in the discussion below, ketones act as a superfuel, with a higher ratio of ATP produced per oxygen consumed than occurs with the complete oxidation of glucose. In the setting of prolonged calorie restriction this offers a valuable life-saving adaptation in nature by improving strength, energy, and alertness, the reversal of that experienced in the context of hypoglycemia. This patient portrays a fascinating clinical manifestation in his absence of lethargy or diminished mental capacity.

5.6.1 Evolutionary Insights into Ketone Body Metabolism Over 3 million years of evolution, humans have become increasingly less dependent on foods such as bananas, other fruits, fibers, and vegetables, that require a high level of intestinal energy to extract ATP from these food sources. Our earlier primate ancestors had larger guts and relatively smaller brains because of the high level of energy required to extract ATP from carbohydrate sources relative to the amount of energy provided in these foods. Thus, earlier primates ingested robust quantities of dietary carbohydrates (that provided four calories per gram) to sustain their energy needs. Carbohydrate bioenergetically produces less ATP than does fat. Pathways of carbohydrate metabolism include both glycolysis, which does not require oxygen, and the TCA cycle linked to the electron transport system, which does require oxygen. Alternatively, dietary fat is calorically dense and has a lower ratio of energy required for intestinal extraction of nutrient fuel to provide the energy demands of the body. Thus, over the course of evolution humans turned to hunting for sources of fat that are more robustly supplied in meat and fish than in plants. Over the course of three million years, human gut

Metabolism and Medicine size shrank while brain size dramatically increased 3.5-fold, and oxygen-carrying blood flow to the brain increased at a rate that was 6-fold (41–43). After coming down from the trees as meat-eaters, the pursuit of hunting animals in the wild by early humans was difficult and physically demanding. Frequent long periods between kills and the unavailability of food equated to prolonged fasting. However, it should be mentioned that there remains considerable debate and controversy about the natural history of intermittent fasting among our Stone Age ancestors. There is a fondness for the culture and wisdom of early humans that romanticizes them as strong and healthy, and free of obesity, diabetes, and chronic diseases that plague modern society. There is also an entrepreneurial spirit to connect this nostalgia to book writing and other promotional opportunities that endorse modern fads, such as intermittent fasting, “paleo”, or “keto” diets. In reality, the alleged truth about the conditions of our ancient ancestors cannot be known for certain, and thus they are only hypotheses. Nonetheless, powerful insights invoking perspectives of physiology can plausibly be extended to suppositions about selective pressures and teleological explanations that shaped human evolution. It can be theorized that the presumed conditions of prolonged fasting and intense physical activity, imposed by the hunter-gatherer lifestyle, were interdependently entwined with the evolution of an adaptive metabolic and physiological design that promotes survival. During the initial stage of starvation, at approximately 36–48 hours of fasting, the increased appetite and weakness that prevailed is now lost. This accompanies the rise in ketogenesis and a higher state of ketosis that is also responsible for increased mental clarity, increased strength, and endurance, as well as enhanced hydraulic efficiency and performance of the heart. The mechanisms for this from the perspective of bioenergetic metabolism and the electron transport system are discussed in Chapters 1 and 8.

5.6.1.1 Fasting, Ketogenesis, and Cognition In the behavioral neurosciences, there is an emerging understanding of the phenomena of neuroplasticity and synaptic plasticity. This is the brain’s capacity to adapt and reorganize neuronal connections in response to changes in the environment, and the capacity for synaptic connections between neurons to strengthen (or weaken) over time, respectively. These processes, encouraged by cognitive therapy practices, appear not only to apply to areas of the brain responsible for memory storage and retrieval, such as the hippocampus and amygdala, but also to actual gray matter areas of the brain. That is, plasticity involves the actual cortex accountable for emotion and cognition. These potentially very favorable effects on the brain are mediated by the transcription factor brain-derived neurotrophic factor (BDNF). It has been shown that exercise upregulates the expression of BDNF, mediated by the ketone body beta-hydroxybutyrate. Thus, both prolonged fasting and exercise promote ketogenesis. This in turn drives increased cognitive function and likely was the major contributor to the growth of a larger brain over the span of human evolution. Taken together, there is a compelling interpretation that the metabolic state of ketogenesis promoted by prolonged fasting,

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Calorie Restriction and Metabolism increased the mental and physical capacity, and motivation to endure the physical challenges of hunting and survival in early humans. Moreover, the non-fasted state of hunter-gatherers, which likely followed an energy-dense high-fat animal diet with a relatively small amount of carbohydrate, also promoted an adaptive ketogenic metabolism. Although not without controversy, it is credibly considered by many that intermittent fasting over the course of human evolution, has until modern times, always been a natural occurrence. It follows that adaptive physiology is encouraged by the metabolic conditions under which it evolves. Thus, it is not surprising that ketone body energetics in starvation states of prolonged fasting not only teleologically enhances cognitive and physical capacity, but also favorably influences physiology and health.

5.6.2 Ketosis—A Danger or a Health Signal? Before the discovery of insulin by Frederick Banting in the 1920s, a diagnosis of type 1 diabetes from ketoacidosis was uniformly lethal. Today, the most common endocrinological emergency that presents in the hospital setting is diabetic ketoacidosis, diagnosed by the presence of ketones in the blood. Accordingly, ketosis has become misunderstood as necessarily equating to impaired carbohydrate utilization and a danger signal of the metabolic decompensation of type 1 diabetes. Moreover, in certain contexts, the acidic properties of ketone bodies indicate a potential for ketoacidosis even in type 2 diabetes. An expanding availability of alternative classes of medication includes a class of drug known as sodium-glucose transport 2 (SGLT-2) inhibitors. These agents lower blood glucose by reducing the threshold for the excretion of glucose in the urine from ~200 mg/dL (in the absence of the drug) to ~140 mg/dL (in the presence of the drug). Reports began to surface that patients on SGLT-2 drug therapy who also followed a carbohydrate-restricted diet developed ketoacidosis (44–46). High visceral body fat content with unsuppressed lipolysis, due to the state of insulin resistance, results in a high flux of fatty acids pouring into the liver from the portal circulation. Low blood glucose suppresses insulin secretion, which further promotes adipose tissue lipolysis. High levels of fatty acids in the mitochondria of hepatocytes undergoing beta-oxidation produce more acetyl CoA groups than the TCA cycle can burn. Accordingly, the acetyl CoA molecules form ketone bodies that are released from the liver to the peripheral circulation to be used as an energy source for extrahepatic tissues, such as the brain, skeletal and cardiac muscle. Ketone bodies, to maintain the balance of energy substrates, further reduce blood glucose by inhibiting hepatic gluconeogenesis in addition to suppressing pancreatic insulin secretion. In a feedforward fashion, the insulinopenia provides yet an additional potentiating effect on adipose tissue lipolytic activity. This further drives hepatic ketogenesis and ultimately the decompensation of type 2 diabetes into a ketoacidotic state (Figure 5.22). Confusion among the general public extends to the medical community, where the understanding of what ketosis is and its role in physiology, remains vague. This underscores an important opportunity to discuss an overview of the science of ketosis. Moreover, mechanistic explanations, including

FIGURE 5.22  Stages in the development of ketoacidosis.

comparisons with other nutrient energy sources, particularly glucose and fatty acids, provides valuable insight to health and disease from the fundamental perspective of metabolism. There are additional reported antioxidant properties of ketone bodies not primarily rooted in their effects on mitochondria. Beta-hydroxybutyrate is now recognized as a stress response molecule with function beyond its role as an energy metabolite. Significantly, calorie restriction represents an energy stress that upregulates hepatic ketogenesis; the vibrant link between beta-hydroxybutyrate and the redox stress response powerfully underscores the fundamentally intertwined nature of energy and redox states in health and disease. Intriguingly, beta-hydroxybutyrate has also been shown to act as a direct antioxidant scavenger of hydroxyl radicals (OH•). Beta-hydroxybutyrate has also been demonstrated in mammalian rodent models to preserve organ integrity of the brain, heart, liver, and kidney in the setting of ischemia and reperfusion. Enhanced ketone body bioenergetics requiring relative low oxygen consumption explains it being a preferred fuel in the setting of ischemia. Its suppressive effects on oxidative stress underscores its benefit in the setting of reperfusion (47). Additionally, taken together with the favorable effects of ketone body metabolism on mitochondrial generated oxidative stress and free radical generation, the therapeutic implications for a wide span of disease states, including accelerated cognitive decline, seizure disorders, neurodegenerative and cardiovascular diseases, cancer, among others, can be appreciated.

SIDEBAR 5.11: BETA-HYDROXYBUTYRATE AND FOXO SIGNALING Beta-hydroxybutyrate acts as a histone deacetylase class 1 and 2a inhibitor, which serves to remove the repression of FOXO3 transcription. FOXO3 promotes the transcription of antioxidants catalase, superoxide dismutase 2, and glutathione peroxidase. In addition to the biosynthesis of antioxidant enzymes, FOXO3 orchestrates broad but tailored redox stress resistance programs including cell and DNA repair, autophagy, and even apoptosis when cell redox damage is severe. Included in the general orchestration of this program is deacetylase activity of SIRT1 and 3, which in turn induce FOXO3-mediated redox cell stress programs.

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5.6.3 Approaches to Achieve Ketosis .

Ketogenic approaches are enlisted by many in the general public to accomplish weight loss. However, other clinical effects of ketosis have attracted the interest of Medicine and even the Military. In the latter case what is most appealing is the apparent increase in mental and physical performance, and endurance. The potential beneficial effects in the prevention and treatment of chronic diseases holds significant promise for the practice of Medicine. Most commonly, the state of ketosis is generated by fasting, or alternatively by a carbohydrate-restricted, high-fat diet. The latter was popularized in the 1990s as a weight loss diet known as the Akins diet, promoted by New York City Cardiologists’ Robert Atkins. Ironically, Dr. Atkins died of congestive heart failure with underlying cardiomyopathy in 2003, at the height of the diet’s popularity. Indeed, high levels of saturated fat is a key component of the ketosis-inducing Atkins diet, which is atherogenic (48–50). Furthermore, high levels of circulating fatty acids are cardiotoxic and have been reported to cause dilated cardiomyopathy (48). Regarding the atherogenicity, and likely the cardiotoxic high fat diet that replaces saturated fatty acids with polyunsaturated and medium-chain fatty acids is preferred. However, it is less palatable, and reports of compliance are mixed. Prolonged fasting is achievable by various intervals of intermittent fasting. Time-restricted dieting, with overnight 12-hour periods of fasting during the dark phase of the daily cycle, is likely to be the most beneficial for physiology and health. This invokes the principles of circadian biology discussed in Chapter 4. In short, the benefits derive from the cycled timing of food, as an entrainable oscillator that synchronizes peripheral clocks and metabolic activity within tissues. Accordingly, lipid and glucose profiles and insulin sensitivity improve, supporting redox and energy homeostasis. However, the health benefits from cycled 12-hour fasts are likely to derive more from the circadian effects than from ketosis. The development of significant ketosis requires ~48 hours of fasting, equating to early starvation. While some ketosis is present after an overnight 12-hour fast, it is unclear how clinically significant these low levels are. Taken together in terms of strategies to achieve ketosis, fasting requires two days, which is not easy, and diet should replace saturated with the less palatable unsaturated fat, to which compliance is the challenge.

5.6.3.1 Beta-Hydroxybutyrate Esters as a Metabolic Performance Enhancer for Military Use Another alternative for inducing ketosis are the salts or preferably non-salt esters of ketone bodies as pills or dietary drink supplements. Non-salt esters are preferable to avoid fluid retention and hypertension. One formulation for such esters was the discovery of Richard Veech, a Harvard-trained medical physician who earned his doctorate under Sir Hans Krebs at Oxford. He then spent 52 years at the NIH where he remained until his passing in February 2020. Veech was lauded as a scientific genius in the field of biochemistry alongside pioneers such as Hans Krebs and Otto Warburg. His major legacy from the NIH was contributing to ketone body metabolism, including

Metabolism and Medicine the development, in collaboration with University of Oxford biochemist Kieran Clarke, of a specific formulation of betahydroxybutyrate ester. A flurry of publications touted favorable outcomes from the experimental use of beta-hydroxybutyrate on physical and cognitive performance, metabolic efficiency and endurance. In 2004, the US military special forces responded to Veech’s work and his interest to develop a beta-hydroxybutyrate ester as a metabolic performance enhancer to improve mental resilience and physical stamina of combat soldiers under extreme emotional and physiological challenges. Particular findings of Veech’s previously published work piqued the interest of the military. These included a 30% increase in hydraulic cardiac function of mammalian rodents requiring less oxygen consumption; a 30% reduction time for solving mazes by these animals; and suppression of skeletal muscle glucose uptake, lowering glycolysis pathway production of lactate by 40%, thus reducing muscle fatigue during intense activity. In fact, the NIH U.S. Defense Advanced Research Projects Agency (DARPA) issued an unprecedented $10 million for metabolic research to Veech.

5.6.3.2 Beta-Hydroxybutyrate Esters as a Metabolic Performance Enhancer in Athletes Not surprisingly, study results in highly trained elite, including prior Olympian bicyclists given the same beta-hydroxybutyrate drink developed by Veech and Clarke for military soldiers similarly showed positive results. On average, the athletes rode for an additional 400 meters over a 30-minute workout (51). One obstacle to the commercialization of this particular formulation of beta-hydroxybutyrate is the extraordinary cost to produce, with an estimated cost to the consumer of an eyepopping $3,000/25 ml. Another is that the taste is bitter and unpalatable. In contrast to fasting and ketogenic diets, ketone body supplements in the absence of carbohydrates restricted to 5–10% of total calories, will not adequately suppress insulin secretion. Accordingly, adipose tissue lipolysis inhibition by insulin prevents weight loss from occurring. In theory, ketone body salts and esters would confer cognitive and muscle performance and health benefits. However, differences between proprietary brands without the regulatory scrutiny of an FDA approval process, have wildly inconsistent efficacy.

5.6.4 How Long Can Human Health and Survival Endure Fasting? The induction of ketosis requires two days of fasting, that is starvation stage 1, with robust levels of ketones developing by approximately day six. The efficiency of ketone bodies as a fuel, particularly beta-hydroxybutyrate in the brain and muscle, promotes vibrant alertness and vigorous physical strength. However, this does not continue indefinitely. Indeed, prolonged starvation is inconsistent with survival. Some historically high-profile hunger strikes have been politically motivated forms of protests. One thing learned from these is that there is a surprisingly narrow time span for the onset of mortality, occurring in otherwise healthy, young individuals at approximately 60 to 70 days. The duration of survival

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Calorie Restriction and Metabolism is sustained by lipolytically active adipose tissue lipid stores. This provides the necessary surplus of fatty acid precursors for ketogenesis in the liver to occur. When these adipose tissue stores of fat are depleted, and no longer provide the liver with a surplus of fatty acids, ketone biosynthesis ceases to occur. Thus, the depletion of this “backup fuel” to maintain energy homeostasis and support physiology results in death. Notably, endogenously produced glucose alone would only be capable of maintaining survival for an estimated two to three weeks. Progressive morbidity from starvation follows the exhaustion of glucose sparing fatty acid and ketone body fuels derived from fat. Thus, impoverished body fat depletes the capacity to compensate for low glucose availability. Accordingly, the total body protein sources of the amino acids that supply the carbon skeleton of glucose are not spared. Ultimately, profound muscle cachexia ensues along with the auto cannibalization of the liver that mediates gluconeogenesis and glucose output. Energy is the single most basic essential requirement for maintaining the far from equilibrium state that defines a living system; its absence leads to a state of thermodynamic equilibrium, tantamount to death.

SIDEBAR 5.12: A PERSPECTIVE OF KETONE BODIES AS A “BACKUP” FUEL When glucose availability is exhausted in the setting of illness, poor appetite, or voluntary fasting, ketone bodies provide an effective backup fuel to support physiology and health. The blood glucose level during a state of ketosis can be as low as 30 mg/dL in the absence of symptoms of hypoglycemia and reduced levels of consciousness or seizures. This speaks to the notion that the absence of hypoglycemia is not a requirement for healthy bioenergetics and physiology so long that ketosis, as an alternative energy source, is present. In fact, it has been experimentally demonstrated that individuals fasting for over a month with robust levels of ketosis, who were then administered intravenous insulin causing profound hypoglycemia, were clinically and cognitively unimpaired (52). After roughly two days of fasting, during the first stage of starvation, ketone bodies rise. Plausibly, the purpose of this is to compensate for the carbohydrate-restricted state of insulinopenia. It follows that there is a reciprocal relationship between blood levels of ketone bodies and insulin. Both ketone bodies and insulin have been demonstrated to increase the hydraulic work of cardiac contractility per amount of oxygen consumed, in the range of 25–30%. The combination of glucose, insulin, and ketosis increases the hydraulic efficiency of the heart by 35%.

5.7 Chronic Overnutrition When nutritional intake is excessive it is proposed that several mechanisms, including insulin resistance, adaptively prevent the storage of unnecessary deposits of nutrient fuel in the liver and adipose tissue. That is, insulin resistance is proposed to

prevent obesity in the short term. However, like any allostatic adaptive response to stress in the body, the beneficial effect is limited to the short term. Indeed, chronic nutrient excess provokes allostatic mediators that further promote insulin resistance. This exemplifies allostatic overload. Insulin resistance is tantamount to metabolic inflexibility. The classical understanding of metabolic flexibility is the capacity for skeletal muscle to transition between lipid and carbohydrate fuel sources for oxidation to produce ATP, the biological currency of energy. However, there are other examples of metabolic flexibility definable from the perspective of normal healthy circadian transition between insulin secretory patterns and between peripheral insulin signaling sensitivity and resistance responses.

5.7.1 The Role of Metabolic Flexibility in Insulin Sensitivity Examples of healthy metabolic flexibility involving the transition between insulin sensitivity and resistance encompass an orchestra of tissues. These metabolic tissues include skeletal muscle, the liver, and the endocrine pancreas, as well as other tissues, such as the kidney and gastric epithelium. Moreover, cell types are only recently becoming recognized and their mechanisms and significance being elucidated (53). For example, during the periods of increased insulin sensitivity and pancreatic insulin secretion that occur during the active and feeding phase of the daily cycle, the fuel source in skeletal muscle is predominantly carbohydrate. This, for example, is mediated by the insulin signaling cascade, the initial effect of which is the translocation of glucose into the cell. The process of anaerobic glycolysis of glucose into pyruvate followed by the insulin-promoted decarboxylation of pyruvate into two acetyl CoA molecules that occurs in the mitochondria by the actions of pyruvate dehydrogenase enzyme complex. Acetyl CoA combines with oxaloacetate to form citrate, beginning the TCA cycle that completes the oxidative combustion process coupled to the final phase of ATP production along the electron transport chain. During this active phase of the daily cycle, feeding behavior provides glucose availability to tissues systemically, most importantly the brain and skeletal muscle. In parallel, the liver stores excess glucose in the process of glycogenesis. The myocardium is the major tissue that uses fatty acids as the primary energy source in the postprandial state, while excess lipids are stored in adipose tissue in the process of lipogenesis. The pancreas as a member of this orchestra functionally secretes insulin during the active and feeding phase of the daily cycle to promote these processes in the liver, skeletal muscle, and adipose tissue. Alternatively, during the fasting overnight phase of the circadian cycle, pancreatic secretion of insulin is diminished. Synchronous metabolic processes that accompany the switch to lipid fuel oxidation in skeletal muscle as well as lipid and glucose output from the liver by the processes of lipoprotein secretion, glycogenolysis, and gluconeogenesis (54). Insulin disinhibition of FOXO transcription factors, that mediate the manifestations of metabolic flexibility just mentioned, also regulate cell resistance to redox stress in many tissues, including but not limited to the classical metabolic tissues. During

218 the overnight hours when cell activities do not compete with the high physical and cognitive energy expenditure that occurs during the active wake phase of the daytime, rescue processes take place and clean up the oxidative species that damage and pose risk to redox homeostasis. These cell resistance programs themselves are energy-requiring including the anabolism of building antioxidant systems, molecular motor-assisted DNA, and cell repair and autophagy. Insulin resistance that evolves as a result of unremitting excessive nutrient caloric intake disrupts metabolic flexibility. The cycles of insulin secretion and peripheral insulin sensitivity is a powerful regulator indirectly linked to many circadian rhythms organism-wide. In this sense, there is a loss of dynamic coordination between the metabolic activities of organ systems and tissues throughout the body. This underscores the relationship of insulin resistance in terms of being a significant contributor to the dysregulation that occurs among molecular clocks of cells of different tissues and the clock-controlled output gene products. The thyroid and steroid superfamily of nuclear hormone receptors that sit at the intersection of these endogenous biological clocks, with metabolic physiology and behavior, is significantly influenced by insulin signaling. Thus, metabolic inflexibility that is tantamount to the loss of normal circadian insulin signaling patterns results in the loss of temporal synchronicity between component members of the hormonal and metabolic orchestra of the living system of a human being. When the cycles are broken or disrupted, the health of any living system is impaired because the fidelity of cycles define the dynamic architecture that keeps it alive. Disturbed cell and tissue energy and redox homeostasis disrupts cycles and moves the system from a state of beautiful and exquisite organizational complexity into the loss of negative entropy, i.e. information, in the direction of the arrow of time towards maximum randomness and entropy. This breakdown in synchronous coordination parallels a rise in the rate of entropy production mediated by heat—energy in transition, that is incapable of doing the work of maintaining biological homeostasis. This is a self-amplifying process of many feedforward mechanisms that make the case for the application of Special Relativity to biological systems. It defines the phenomenon of accelerated biological aging relative to chronological age that predisposes individuals to premature chronic diseases of aging.

5.7.2 Ectopic Lipid Deposition during Chronic Overnutrition An important mechanism of underlying insulin resistance includes oxidative stress that occurs within mitochondria as a result of dietary excess overloading the carrying capacity of the electron transport chain. There is a significant intertwined and reciprocal relationship between insulin resistance and mitochondrial dysfunction. Chronic overnutrition also places excessive demands on the endoplasmic reticulum for protein folding, resulting in endoplasmic reticulum stress. Endoplasmic reticulum stress, as a result of the unfolding response, promotes inflammation, which in turn inhibits insulin signaling. Additionally, the inextricable and bidirectional relationship between inflammation and oxidative stress both contribute to

Metabolism and Medicine the onset and progression of insulin resistance. Furthermore, chronic overnutrition leads to the overflow of lipid storage capacity in adipose depots. This is a manifestation of insulin resistance whereby dietary-induced insulin secretion does not suppress adipose tissue lipolysis. Free fatty acids and glycerol thus enter the circulation at supraphysiologic levels and are forced to be deposited ectopically in cells and tissues not evolutionarily designed for the storage of fat. Examples of tissues where ectopic fat is known to occur include skeletal muscle, the myocardium, the liver, pancreas, and brain (Figure 5.23). There seems to be a genetic susceptibility for ectopic fat accumulation in the cytoplasm of skeletal muscle, intramyocellular lipid (IMCL), which represents another contributing etiology of insulin resistance. This IMCL includes reactive species such as ceramides and diacylglycerol, which in turn impair insulin signaling. Whatever the cause of peripheral insulin resistance, pancreatic hypersecretion of insulin occurs in an attempt to compensate. In the liver, hepatic steatosis evolves as a function of this compensatory hyperinsulinemia. Even before the evolution of prediabetes or diabetes, this initial phase of endogenous hyperinsulinemia and hepatic steatosis represents a predisposing susceptibility state to chronic diseases of aging, including cardiovascular disease and cancers. The metabolic signals of chronic overnutrition including carbohydrates and fats largely enter the cell as glucose and fatty acids, respectively. In the hepatocyte, fatty acid entry is facilitated by the enzyme fatty acid translocase, often denoted as CD36. Once inside the cell, fatty acids and glycerol may be re-esterified into triacylglycerol or enter into the mitochondria. Inside the mitochondria, fatty acids undergo a process of beta-oxidation, whereby energy is produced by the process of breaking down the carbon chain of the fatty acid molecule into two carbon links of acetyl CoAs. For example, most dietary fats are composed primarily of the 16-carbon saturated fatty acid palmitate which is beta oxidized into eight acetyl CoA molecules. Within the mitochondria, acetyl CoA combines with oxaloacetate to form citrate in the process that begins the citric acid cycle, or TCA cycle, which is the hub of bioenergetic metabolism pathways. Glucose entry into the cell may or may not be facilitated by insulin-dependent glucose transport molecules such as GLUT4, which is primarily found in skeletal muscle cells. In the liver, glucose is primarily transported by noninsulin-dependent transport molecules. Once inside the hepatocyte, glucose is phosphorylated by the insulin-stimulated enzyme glucokinase. This traps the glucose molecule inside the cell, which subsequently undergoes the anaerobic energy-producing catabolic process of glycolysis into pyruvate. Pyruvate then enters the mitochondria and is decarboxylated by the enzyme pyruvate dehydrogenase complex into acetyl CoA. One molecule of glucose is, thus, converted into two molecules of pyruvate, each of which produces one molecule of acetyl CoA. Acetyl CoA, like that derived from fatty acids, combines with oxaloacetate to form citrate, thus, entering the citric acid (TCA) cycle (Figure 5.24). Chronic overnutrition of these calorie-containing molecules results in exceeding the capacity to handle the energetic input and subsequent transformation into the biological currency of ATP (Figure 5.22). The final phase of nutrient oxidation largely occurs along the respiratory chain in the process of

Calorie Restriction and Metabolism

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FIGURE 5.23  Downstream effects of chronic overnutrition on redox homeostasis and metabolic flexibility. *ER stress = endoplasmic reticulum stress; Mt = mitochondria; e- = electron; s. muscle = smooth muscle; CHO = carbohydrate.

oxidative phosphorylation. This process involves taking electron-carrying molecules (NADH and FADH2) harnessed from the nutrient resources along the pathways of glycolysis, fatty acid beta-oxidation, and the TCA cycle. Electron transfer from the NADH and FADH2 molecules onto complexes 1 and 2, respectively, of the electron transport chain, when excessive, leads to electron leakage and binding to molecules of oxygen resulting in the formation of superoxides. Superoxides and other reactive and free radical oxidative species promote oxidative stress that disturbs redox balance leading to oxidative modification of nucleic acids, lipids (such as of cell membranes), and proteins, hence disrupting the healthy structure and function of the cell. Importantly, this includes causing mitochondrial dysfunction, which is a fundamental cause of insulin resistance (see Chapter 8). Furthermore, there is a bidirectional feedforward self-amplification of the process of

mitochondrial dysfunction and insulin resistance whereby this reverberating circuit upregulates the level of oxidative stress and damaging effects of redox disturbance of both the mitochondria and other organelles and molecular components of the cell. This pernicious cascade occurs when nutrient caloric intake exceeds energy expenditure and/or energy demands exceed the capacity for mitochondrial production of ATP. Moreover, in the context of unremitting excessive caloric intake, relative to energy expenditure or relative to the capacity of mitochondria to accommodate the energy transformation from nutrient molecules to the biological currency of ATP, the further oxidation of nutrients is prevented and instead is diverted to storage within the cell. This may occur, for example, by the re-esterification of fatty acids and glycerol that enter the hepatocyte, into triacylglycerol that is stored and accumulates within the cytoplasm. Additionally, the acetyl CoA molecules

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FIGURE 5.24  Metabolic signals resulting from chronic overnutrition. *CHO = carbohydrate; FA = fatty acid; PI3K = phosphatidylinositol-3 kinase; mTOR = mammalian target of rapamycin; ATP = adenosine triphosphate; Mt = mitochondria; IR = insulin resistance; ACC = acetyl CoA carboxylase; ER = endoplasmic reticulum; GCK = glucokinase; Ox Phos = oxidative phosphorylation; TG = triglyceride; pgm = per glucose molecule.

that derive from fatty acids or glucose exit the mitochondria, and under the influence of insulin signaling, the rate-limiting enzyme acetyl CoA carboxylase (ACC) begins the process of fatty acid synthesis with the production of malonyl CoA. This represents de novo lipogenesis. Following synthesis, three fatty acids combine with glycerol to produce triacylglycerol,

or triglyceride. The accumulation of triglycerides within the cytoplasm of the hepatocyte evolves into hepatic steatosis, whether due to the re-esterification of fatty acids and glycerol, or to the process of de novo lipogenesis (Figure 5.22). Hepatic steatosis highlights the anatomical hallmark of insulin resistance. Furthermore, very low-density lipoprotein

Calorie Restriction and Metabolism (VLDL) is produced from these triglyceride droplets with the addition of Apolipoprotein B. Hepatic steatosis represents lipid accumulation that exceeds the storage capacity of the hepatocyte. This results in the secretion of VLDL into the circulation at supraphysiological levels. Thus, tantamount to hepatic steatosis representing the anatomical hallmark of insulin resistance, elevated VLDL circulating levels underscore a lipocentric criterion of insulin resistance. These levels are represented by a fasting triglyceride greater than 90 mg/dL or a nonfasting triglyceride greater than 170 mg/dL. In fact, a practical diagnostic triumvirate of insulin resistance may be proposed to include 1) elevated triglyceride (fasting triglyceride greater than 90; non-fasting triglyceride greater than 170); 2) ultrasound evidence of hepatic steatosis; 3) elevated serum C-peptide levels. Just as insulin signaling upregulates the rate-limiting enzyme ACC to promote de novo lipogenesis, it also promotes the anabolic process of protein synthesis in the endoplasmic reticulum. Protein synthesis is mediated through the signaling cascade of PI3K/Akt/mTOR. Continued nutrient excess along with accompanying endogenous hyperinsulinemia ultimately drives the ER stress response, exceeding the protein folding capacity of the cell. This unfolded protein response (UPR) results in inflammation and insulin resistance. The insulin resistance protects the cell at multiple levels from insulin signaling, including trapping glucose inside the cell by the actions of glucokinase, the mTOR pathway that promotes protein synthesis, and the upregulation of the rate-limiting enzyme ACC for de novo lipogenesis. Nonetheless, while insulin resistance may be an acutely protective adaptation in the allostatic response of an organism, it chronically drives responses of allostatic overload when overnutrition and the associated metabolic signals are unremitting. In this setting, insulin resistance and hyperinsulinemia promote metabolic inflexibility and loss of the synchronous nature of circadian physiology and result in progressive obesity. Consequently, accelerated biological aging and the susceptibility to chronic diseases of aging ensue (Figure 5.25).

5.8 Take-Home Messages • Excess or poor calorie intake accelerates aging and chronic diseases of aging by promoting oxidative and inflammatory stress. • Calorie restriction, time-restricted feeding, and intermittent fasting prevent inflammation and free radical stress by switching from the energy-inefficient classical mode of metabolism to the more energy-efficient quantum mode and, thus, prolonging lifespan. • Typically, we metabolize carbohydrates and sugars from our diet to provide us with energy in the form of ATP, however, under situations of prolonged fasting (or nutrient scarcity) we have evolved to utilize alternate substrates, such as fat stores, as “backup” fuel sources. • Prolonged fasting promotes ketogenesis and a state of ketosis, which can lead to weight loss and enhanced cognitive function.

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FIGURE 5.25  Insulin resistance and hyperinsulinemia promote metabolic inflexibility in conjunction with the loss of circadian synchronization. This leads to obesity and the accelerated pace of aging ultimately resulting in chronic diseases of aging. *AD = Alzheimer’s disease; CVD = cardiovascular disease; T2D = type 2 diabetes.

• The notion of hormesis should be considered in the context of diet and exercise. Hormesis refers to the idea that there is an ideal amount of something that will support healthy physiological conditions. Too little or too much can be damaging. An optimal amount will be vitalizing, not harmful. • Homeostasis means resistance to change, while allostasis means stability through change. Allostatic load represents the physiological cost of exposure to chronic stress. While acute stress can be adaptive and protective, prolonged stress can be pathogenic. This shift from adaptive to maladaptive stress is termed allostatic overload and leads to chronic disease states. • Molecular energy sensors such as AMPK and SIRT1 are activated by external factors such as fasting, calorie restriction, and exercise. Under these conditions, they stimulate ATP-producing pathways and inhibit ATP-consuming pathways to maintain homeostasis. • AMPK and SIRT1 activate PGC1α, which induces mitochondria biogenesis, and FOXO, which induces cell stress resistance programs of DNA repair, autophagy, cell differentiation, antioxidant systems, and apoptosis. These resistance programs are designed to protect against redox stress in a circadian fashion. • Insulin inhibits the transcription of FOXO. Under healthy circadian cycling, insulin levels are high during daylight feeding hours to induce rapid utilization of glucose to produce ATP and inhibit FOXO from promoting transcription of insulin resistance genes. During nighttime fasting hours, insulin levels decrease allowing for FOXO transcription and the activation of cell resistance programs.

222 • Under pathological conditions where circadian cycling has been disrupted, such as conditions of insulin resistance or hyperinsulinemia, FOXO transcription is continually suppressed, leading to chronic diseases such as obesity, cancer, cardiovascular disease, and Alzheimer’s disease. • Insulin also inhibits GSK3, activating glycogen synthesis occurring primarily in metabolic tissues such as skeletal muscles and the liver under healthy conditions. Thus, during daylight feeding hours, insulin’s inactivation of GSK allows for the utilization of nutrients for cell replication and anabolism. • Under circumstances of insulin resistance and hyperinsulinemia, insulin levels remain high even during nighttime fasting hours and continuously inhibit GSK3. This can result in enhanced cell replication of many tissues leading to inflammation, disruptions in redox homeostasis, and cancer. • Insulin also activates mTOR, which is the master regulator of energy-requiring physiological processes. Under healthy circumstances, during daytime feeding hours mTOR promotes anabolism processes of cell growth and proliferation and inhibits cell stress resistance programs. • Circadian regulation of energy storage and utilization is optimally synchronized to the metabolic anticipation of energy supply and demand. When this synchrony is broken, such as in the case of nocturnal eating, an overburdening of the mitochondria occurs leading to redox damage and mitochondrial dysfunction, and ultimately metabolic disease. • Chronic overconsumption leads to insulin resistance and metabolic inflexibility, which can be defined as the inability of skeletal muscle to shift between lipid and carbohydrate fuel sources for oxidation to produce energy in the form of ATP. Metabolic inflexibility also refers to the loss of healthy circadian insulin secretory patterns. • Chronic overnutrition also results in an overflow of the lipid stored in adipose tissue. This is due to insulin resistance and the fact that dietary intake no longer induces insulin secretion to suppress adipose tissue lipolysis. Glycerol and free fatty acids then enter circulation and are deposited as ectopic fat in tissues not designed for fat storage such as the liver, pancreas, myocardium, skeletal muscle, and brain.

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223 41. R. S. Seymour, S. E. Angove, E. P. Snelling, P. Cassey, Scaling of cerebral blood perfusion in primates and marsupials. Journal of Experimental Biology 218(16), 2631–2640 (2015). 42. K. Milton, The critical role played by animal source foods in human (homo) evolution. The Journal of Nutrition 133(11), 3886S–3892S (2003). 43. A. Gibbons, The evolution of diet. National Geographic Magazine (2014) https://www.nationalgeographic.com/ foodfeatures/evolution-of-diet/. 44. H. K. Akturk, A. Rewers, S. K. Garg, SGLT inhibition: A possible adjunctive treatment for type 1 diabetes. Current Opinion in Endocrinology, Diabetes and Obesity 25(4), 246–250 (2018). 45. D. Patoulias, K. Imprialos, K. Stavropoulos, V. Athyros, M. Doumas, SGLT-2 inhibitors in type 1 diabetes mellitus: A comprehensive review of the literature. Current Clinical Pharmacology 13(4), 261–272 (2019). 46. M. Earle, B. Ault, C. Bonney, Euglycemic diabetic ketoacidosis in concurrent very low-carbohydrate diet and sodiumglucose transporter-2 inhibitor use: A case report. Clinical Practice and Cases in Emergency Medicine 4(2), 185–188 (2020). 47. P. Rojas-Morales, J. Pedraza-Chaverri, E. Tapia, Ketone bodies, stress response, and redox homeostasis. Redox Biology 29, 101395 (2020). 48. S. Y. Foo et  al., Vascular effects of a low-carbohydrate high-protein diet. Proceedings of the National Academy of Sciences of the United States of America 106(36), 15418– 15423 (2009). 49. R. B. Kostogrys et  al., Characterisation of atherogenic effects of low carbohydrate, high protein diet (LCHP) in apoE/LDLR−/− mice. The Journal of Nutrition, Health and Aging 19(7), 710–718 (2015). 50. R. B. Kostogrys et  al., Low carbohydrate, high protein diet promotes atherosclerosis in apolipoprotein E/lowdensity lipoprotein receptor double knockout mice (apoE/ LDLR−/−). Atherosclerosis 223(2), 327–331 (2012). 51. P. J. Cox et  al., Nutritional ketosis alters fuel preference and thereby endurance performance in athletes. Cell Metabolism 24(2), 256–268 (2016). 52. A. S. Brickman, S. G. Massry, J. W. Coburn, Changes in serum and urinary calcium during treatment with hydrochlorothiazide: Studies on mechanisms. Journal of Clinical Investigation 51(4), 945–954 (1972). 53. J. E. Galgani, C. Moro, E. Ravussin, Metabolic flexibility and insulin resistance. American Journal of Physiology. Endocrinology and Metabolism 295(5), E1009–E1017 (2008). 54. D. Gnocchi, M. Pedrelli, E. Hurt-Camejo, P. Parini, Lipids around the clock: Focus on circadian rhythms and lipid metabolism. Biology 4(1), 104–132 (2015).

6 The Microbiota in Symbiotic Entanglement with Human Metabolism

Abbreviations AAA ACC ACTH AKT AMP AMPK ANGPTL4 ATP BCAA BCFA BDNF BMAL1 BMI CD4 CNS CoA CPT1 CR CRH CV DAMP DNA EDGF ENS EPI FIAF FMO FMT FOXP3 FXR GABA GALT GBA GERD GF GI GLP(1/2) GLUT4 HAT HDAC HPA IBD IBS

aromatic amino acid acetyl-CoA carboxylase adrenocorticotropic hormone protein kinase B (PKB) adenosine monophosphate AMP-activated protein kinase angiopoietin-like 4 adenosine triphosphate branched-chain amino acid branched-chain fatty acid brain-derived neurotrophic factor brain and muscle ARNT-like 1 body mass index cluster of differentiation 4 central nervous system co-activator carnitine palmitoyltransferase 1 calorie restriction corticotropin-releasing hormone cardiovascular danger-associated molecular pattern deoxyribonucleic acid epidermal derived growth factor enteric nervous system exocrine pancreatic insufficiency fasting-induced adipose factor flavin monooxygenase fecal microbiota transplantation Forkhead box protein P3 farnesoid X receptor gamma aminobutyric acid gut-associate lymphoid tissue gut-brain axis gastroesophageal reflux disease germ-free gastrointestinal glucagon-like peptide 1/2 glucose transporter 4 histone acetyltransferase histone deacetylase hypothalamic–pituitary–adrenal inflammatory bowel disease irritable bowel syndrome

DOI: 10.1201/9781003149897-6

Ig IGF1 IL ILC IRS-1 LCFAs LDL LPL LPS MAPK mRNA mTOR NAD NADH NAFLD NF-κB NFIL3 NPAS2 NSAID NT PAMP PGC1α PI3K PPAR PPD PRR PSA PYY Ras RNA RORγt rRNA SCFA SCN SFB SGLT1 SIBO SSRI TCA cycle TLR TMA TMAO TNFα

immunoglobulin insulin-like growth factor 1 interleukin innate lymphoid cell insulin receptor substrate 1 long chain fatty acids low-density lipoprotein lipoprotein lipase lipopolysaccharide (endotoxin) mitogen-activated protein kinase messenger RNA mechanistic target of rapamycin nicotinamide dinucleotide nicotinamide dinucleotide hydride non-alcoholic fatty liver disease nuclear factor kappa-light-chain-enhancer of activated B cells nuclear factor interleukin 3 neuronal PAS domain protein 2 non-steroidal anti-inflammatory drugs neurotransmitter pathogen-associated molecular pattern peroxisome proliferator-activated receptor gamma coactivator phosphoinositide 3-kinase peroxisome proliferator-activated receptor 1-phenyl-1 2-propanedione pattern recognition receptor polysaccharide A peptide YY superfamily of rat sarcoma proteins ribonucleic acid retinoid-related orphan receptor gamma t ribosomal RNA short-chain fatty acid suprachiasmatic nucleus segmented filamentous bacteria sodium-dependent glucose transporter 1 small intestinal bacterial overgrowth selective serotonin reuptake inhibitor tricarboxylic acid cycle Toll-like receptor trimethylamine trimethylamine N-oxide tumor necrosis factor α

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226 Treg tRNA T2D, T2DM UCP ZO-1

Metabolism and Medicine regulatory T cell transfer RNA type 2 diabetes mellitus uncoupling protein zonula occludens-1

Chapter Overview A greatly underappreciated aspect of human health is the crucial role played by the microbes with whom we share our bodies and upon whom we are unequivocally dependent. While the collection of microbes, or microbiota, is composed of bacteria, archaebacteria, eukaryotic microbes (including fungi), and viruses, this book focuses on the impacts of the bacterial members, the most thoroughly characterized and understood. Roughly 95% of the resident bacteria—that outnumber us cell to cell—live in cooperative guilds (functional ecosystems) on the surface of the colon (the large intestine). It is here that we have some of our most critical interactions with the outside world and offer a hospitable, responsive environment for the microbiota. Astoundingly, while bacteria populated the Earth roughly 4.2 billion years ago and the first Homo sapiens emerged nearly four billion years later, we speak the same language, using shared signaling molecules and receptors, supporting one another in our mutual quests for life. Humans have had no choice but to co-evolve with the bacteria, making our more complex human capabilities totally dependent on their presence. Indeed, the bacteria are not parasites or even visitors; they are inextricable components of the “supraorganism” that functions coherently and in an enhanced manner due to our synergistic mutualism, as was so aptly realized by Nobel laureate Joshua Lederberg. Indeed, the components of the healthy supraorganism sing to the tune of the same circadian rhythms, share the same diet (though humans generally get the first pickings), and experience the same physical and psychogenic stresses. While Hippocrates (460–370 BC) was convinced that “all diseases begin in the gut” and Antonie van Leewenhoek (in the 1680s) noted striking differences in microbes between oral and fecal samples as well as between healthy and diseased individuals, the importance of the gut microbiota regarding health was outweighed by the attention shifted toward getting rid of infectious agents (recognized as being microorganisms in the 20th century), knowing they could cause illness and even death. It has been a mere 10–20 years during which we are finally coming to appreciate that human health is critically dependent upon the health of our microbiota—for better and for worse. A major chapter in Volume 2 is devoted to this topic. Among the marvels of the microbiota that will be addressed therein are 1) its necessity in activating and training our innate and adaptive immune systems (some 70% of which resides in our gut), enabling them to differentiate between symbiotic bacteria vs. pathogenic bacteria and healthy human cells vs. cancer cells; 2) its role as a so-called “second brain” associated with its own enteric nervous system that communicates back and

forth with the same signaling molecules and neurotransmitters of the human brain; 3) its ability to elicit far-reaching transcriptional and epigenetic activity throughout the body; 4) its ability to turn dietary fibers indigestible to humans into indispensable vitamins, regulatory molecules, and other essential products; and 5) its balance of “healthy” versus “unhealthy” strains that has profound impacts on our health, mediating such modern—indeed, epidemic—ailments as obesity, type 2 diabetes, cardiovascular disease, a host of autoimmune diseases, a range of mental illnesses (e.g. depression, anxiety, ADD, ADHD, autism, and schizophrenia), Alzheimer’s and Parkinson’s diseases, irritable bowel syndrome, compromised liver and kidney function, and a variety of cancers. Like an endocrine organ, the impacts of the microbiota extend throughout the body and are unquestionably fundamental to our health (Figure 5.29). For the modern-day medical practitioner, the time has come to embrace the potential of the microbiota to address health in new ways. With urbanized lifestyle-driven shifts in our microbiota leading to reductions in the diversity and fraction of healthy bacterial strains in the gut, the onus is upon our medical practitioners to examine the spectrum of bacteria and bacterial metabolites that might be foundational to the panoply of related illnesses and consider restoring the gut with critically missing microbes from a repository of such microbes. Patient-specific restorations could be more effective than the standard use of medicines that often address symptoms rather than causes, or hurt the body’s immune system, for example. Metabolic or physiological fitness landscapes could be employed to great effect to identify appropriate precision restoration treatments that have the potential to reverse a wide range of the modern westernized metabolic- and inflammatory-related health epidemics. We refer the reader to a dedicated chapter in Volume 2 which presents a comprehensive discussion of the role of microbiota in maintaining good health (Figure 6.0).

FIGURE 6.0  An illustrative microbiota summary. An interwoven, bidirectional and self-amplifying web of parameters that affect microbial health.

Microbiota and Human Metabolism

6.1 The Microbiota and Human Liaison: Better Together 6.1.1 Overview and Importance of the Gut Microbiota The human body is host to trillions of microorganisms that are collectively referred to as the microbiota. This composite microbial ecosystem, built of bacteria, viruses, fungi, protists, and archaea, contains some of the most diverse and abundant life forms on the planet. It is increasingly recognized that the microbiota plays an essential role in shaping and sustaining human life. This chapter highlights the complex interplay that exists between humans and microbiota, with particular emphasis on the gut ecosystem, which has been estimated to comprise >98% of the total human microbiota. Among these gut inhabitants, bacteria are by far the most abundant and thoroughly characterized contributors to human health and physiology. Accordingly, this chapter will primarily draw from the literature base surrounding gut bacteria, though one would be remiss to neglect the impacts documented for viruses, fungi, protists, and Archaea. The microbiota is the composite microbial community occupying a given interface between an organism and its environment. The microbiome is the total gene pool of the microbiota. The metabolome is the collection of the metabolites produced by the microbiota.

6.1.2 The Relationship of the Gut Microbiota and the Human Host Virtually all forms of life on Earth have evolved in the presence of bacteria. Humans have benefited from a mutualistic relationship with bacteria for millennia, with our external surfaces, including the topologically exterior integumentary system (i.e. the skin) and microbe-accessible gastrointestinal system, believed to support roughly 1,000 species (50,000 strains) of bacteria. These numbers, undoubtedly goliath in their own right, still grossly under-represent the breadth of diversity that bacteria add to our metabolic repertoire. While humans are ~99.9% genetically identical to one another and ~85% identical to common mice, bacteria are so genetically divergent that only ~70% similarity is required for two to be considered the same species (1). Thus, it is insufficient to focus on the number of bacterial species or strains to fully grasp the extent of their variation. Bacteria play a critical role in the development of multiple organ systems, with some of the greatest influences noted in the gastrointestinal and immune systems. Some of the key physiological services provided by gut bacteria include 1) synthesis of vitamins, neurotransmitters, essential amino acids, and short-chain fatty acids, 2) modulation of gut epithelial gene expression, 3) transformation of bile acids, and 4) metabolism of drugs. In turn, humans provide bacteria with a temperature-controlled and moisturefilled environment with a continuous source of nutrients and other metabolic substrates.

227 While the bacteria within us only comprise about 1–2 kg of mass, they have been estimated to outnumber human cells in the body. For years it was accepted that the ratio of bacteria to human cells was approximately 10:1, but more recent estimates suggest that this figure is closer to 1.3:1 (2, 3). This likely remains quite approximate, but highlights the notion that gut bacteria are present in massive quantities. This holds true when comparing the composite, non-redundant gene pool of humans and the microbiome as well. Despite having a genome that is three orders of magnitude smaller, the microbiome contains an estimated 3.3 million genes compared to the 19,000 that comprise the human genome (4, 5) (Figure 6.1). This genetic diversity translates to a wide array of protein products with a far greater diversity of metabolic profiles than the human genome could ever manufacture. Humans and bacteria have co-evolved to share a biological vessel, and as such, our metabolism is not simply cooperative but inextricably inter-dependent for basic survival. This observation prompted Joshua Lederberg to formulate the notion of the “supraorganism”—a biological hybrid of sorts in which the “self” is viewed as the combination of both human and microbiota. Characterizing the interactions that occur between humans and microbiota offers a window to understand those aspects that are most crucial for maintaining the health of the supraorganism. One method of approaching this question is to observe how re-structuring microflora in vivo impacts various health and disease states. Fecal microbiota transplantation (FMT) is a novel, robust, and readily translational method of accomplishing this task. FMT has been utilized in some form or another since ancient Chinese medicine, but it wasn’t until 1684 that Antonie van Leewenhoek first described how fecal and oral microbes (“animalcules”) differ between healthy and diseased persons. More than 200 years later, immunologist Elie Mechnikov was awarded the Nobel Prize (1908) for illuminating how fecal toxins drive disease. During World War I, German physician Alfred Nissle uncovered the ability of microorganisms to antagonize other microbial pathogens,

FIGURE 6.1  Human and bacterial contributions to the supraorganism. Despite the fact that the human cell is larger and structurally more complex than the bacterial cell, the collective nature of the diverse microbiota tips the balance to being one in which there are more bacterial cells, more bacterial genes, and more bacterial metabolites in the host than those of the host. The genomic diversity of the microbiota, reflecting differing needs for adaptation for the different strains under varied conditions, is responsible for the enormous array of functional contributions made by the microbiota. The collective contributions made by the host and the microbiota are essential for the survival of both.

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demonstrating the concept of colonization resistance. However, it wasn’t until the 1940s that scientists began culturing microbes in the laboratory, rapidly accelerating our ability to characterize their physiological activity. Some twenty years later, scientists finally began drawing causal inferences about individual species by introducing them into gnotobiotic and germ-free test subjects (see highlight box). This approach was augmented by the introduction of sequence-based technology that allowed detection of organisms that previously could not be cultured. In 2004 and 2006, three landmark papers emerged from the laboratory of Jeffrey Gordon demonstrating how the transfer of gut microbiota from conventional mice to germ-free recipients was sufficient to increase adiposity due to enhanced energy harvest from otherwise indigestible food (6). This finding translated to FMT from obese mice, causing the germ-free recipients to develop obesity (7, 8). This finding was later recapitulated in studies utilizing FMT from mono- and dizygotic twins that were discordant for obesity (9). These findings, among others, thrust the microbiota into the mainstream consciousness and opened a dialogue regarding its role in health and disease. Gnotobiosis (from Greek roots gnostos "known" and bios "life") is the condition of having all lifeforms within an organism accounted for. Strictly speaking, any research subject with a well-characterized microbial composition would fit this definition; however, research paradigms typically seek to reduce the number of species present in order to minimize the number confounding variables. Thus, the term “gnotobiotic” is most commonly used when a research subject has a small number of known bacterial species comprising its microbiota. The term “gnotophoric” may be used when only one species is present. Germ-free (axenic) subjects technically meet criteria for gnotobiosis as well but are less commonly referred to by this terminology.

The aforementioned scientific advances, including next-generation sequencing, have profoundly transformed our ability to describe and characterize the microbiota. This success has inadvertently created a new challenge, however, in the analysis and management of the massive data pools that result from such techniques. Making sense of the estimated 3.3 million genes that comprise the microbiome is a daunting task, and grows exponentially more complex when considering how this translates to proteomics and metabolomics. Nonetheless, this data is critical to elucidate the origins and regulation of metabolties emerging from human and bacterial sources. Such evidence will bring us one step closer to discovering the bona fide causality data that will support the correlational evidence that has emerged from the findings of the last 15–20 years.

6.1.3 The Microbial Flora: Impacts and Implications of an Altered Microbiota Composition 6.1.3.1 The Microbiota Composition: A Bellwether of Health The Human Microbiome Project is a National Institutes of Health (NIH)-funded initiative with a primary objective of

elucidating the role of microbial flora in human health and disease. One of the prevailing findings that has emerged from this is that while virtually the entire phylogenetic tree of bacteria is carried by our bodies, there are four predominant phylogenetic groups that live symbiotically in the human gut— Bacteroidetes, Firmicutes, Proteobacteria, and Actinobacteria. Numerous factors influence the relative ratios of these phyla, including geography, diet, hygiene, genetics, and anatomical location, but a few general principles have been noted. Bacteroidetes and Firmicutes tend to account for >90% of the observed phenotypes, with Proteobacteria comprising 5–10% and Actinobacteria a lesser fraction (Figure 6.2). Other phyla are also present in trace numbers, including Cyanobacteria, Verrucomicrobia, and Fusobacteria. The most common genera include Bifidobacterium (phylum Actinobacter), Bacteroides (phylum Bacteroidetes), Clostridium (phylum Firmicutes), Streptococcus (phylum Firmicutes), Ruminococcus (phylum Firmicutes), Faecalibacterium (phylum Firmicutes), Lactobacillus (phylum Firmicutes), and Escherichia (phylum Proteobacteria) (10, 11). While these generalities allow us to describe the “typical” gut microbiota, it is not entirely clear which factors should be valued highest when considering the “healthy” gut microbiota. For instance, it has been shown that the microbiota of individuals in urban areas is significantly less diverse than those of their rural counterparts (13). Correlating with this reduced diversity is increases in inflammatory pathways and other downstream complications such as immune diseases, metabolic illnesses, and some cancers. However, even the microflora of non-diseased persons has been noted to differ in urban and rural settings, suggesting that the very definition of "healthy” may be dependent on geographic location. With few randomized, double-blinded clinical trials to turn to for reference, we currently rely on pre-clinical models to help guide our judgments about what this “healthy” microbiota might look like. Bacteroides species are the most abundant gut bacteria, comprising up to 30% of the mammalian gastrointestinal flora. These Gram-negative microbes are proficient digesters of carbohydrates and fiber, yielding short-chain fatty acids (SCFAs). Ridaura et al. demonstrated that Bacteroides species may influence lean/obese phenotypes in humans (9). When germ-free mice received FMT from discordant obese/lean human twins, the transmissible adiposity phenotype correlated negatively with microbial-driven fermentation of short-chain fatty acids and transformation of bile acids (with resultant down-regulation of host signaling via the farnesoid X receptor, FXR). In addition, adiposity correlated positively with circulating levels of branched-chain amino acids, which have been associated with insulin resistance and type 2 diabetes (14). Because mice are coprophagic (consume the fecal material of their colony members), the adiposity phenotype could be rescued by merely housing the obese cohort of mice with those colonized by the lean microbiota. This finding correlated positively with invasion of bacteria from the Bacteroidales subclass of Bacteroides. These findings were diet-dependent, requiring reduced consumption of saturated fats and increased consumption of fruits/vegetables. Clostridial species (of the phylum Firmicutes) are gram-positive anaerobes that make up a substantial portion of the total

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FIGURE 6.2  Taxonomy of the typical gut microbiota composition. Bacteroidetes and Firmicutes tend to account for > 90% of the observed phenotypes, with Proteobacteria comprising 5–10% and Actinobacteria a lesser fraction. Source: adapted from (12).

diversity of bacteria in the gut (15). Perhaps better known for their pathogenic varieties (e.g. Clostridium difficile, C. tetani, C. botulinum, and C. perfringens), the Clostridium genus is comprised of over 100 species that are highly abundant in the healthy human microbiota. Non-pathogenic Clostridia possess a significant level of anti-inflammatory activity and demonstrate reduced abundance in patients with inflammatory bowel disease (16). This effect has largely been attributed to fiber

metabolism, production of SCFAs (especially butyrate), and induction of regulatory T cells (17–19). However, many pathogenic and distinctly pro-inflammatory varieties of Clostridia exist as well. C. botulinum can produce botulinum toxin (Botox), which is exploited clinically for cosmetic and other purposes, but is also responsible for food-borne, wound, and intestinal botulism. C. tetani produces tetanospasmin (tetanus toxin), the astonishingly potent neurotoxin responsible

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for tetanus disease (lockjaw). C. difficile is an opportunistic pathogen that is typically suppressed by commensal bacteria but may thrive in settings when commensal bacteria are limited (e.g. antibiotic therapy). Overgrowth of this microbe is capable of causing severe diarrhea and the potentially fatal pseudomembranous colitis. C. perfringens may cause food poisoning, cellulitis, fasciitis, and gas gangrene. Lactobacillus species also fall within the phylum Firmicutes and are among the most extensively tested and commonly recommended probiotic agents. This topic will be discussed further in Section 6.3.4 (see Probiotics). Proteobacteria comprise a rather heterogenous phylum of gram-negative bacteria that includes a wide variety of pathogenic genera, including Escherichia, Shigella, Salmonella, Vibrio, Helicobacter and Yersinia. In the healthy gut microbiota, these bacteria comprise a small but significant fraction (5–10%) of the total bacterial abundance. Prudent restriction of these microbes to a minority population appears to be a prominent component of preventing disease. Indeed, proteobacteria bloom has been associated with numerous disease states, the vast majority of which involve inflammation as a fundamental component (20). This relationship is so consistent (among intra- and extra-intestinal diseases) that some have even proposed using proteobacteria as a biological indicator of dysbiosis (21). Because of the diversity of forms, Proteobacteria are named after the Greek god of the sea, Proteus, capable of assuming many different shapes.

Remarkably, in a world filled with great microbial diversity, the fact that the Bacteroidetes and Firmicutes phyla dominate suggests that their relative balance should be considered a general bellwether for wellness. One such example is that obese individuals are known to have reduced microbial diversity (22), with an increased ratio of Firmicutes to Bacteroidetes (7). In adult humans, a 20% shift in the bacterial population from Bacteroidetes to Firmicutes has been estimated to provide an additional 150 kilocalories of energy per day (23). This translates to roughly one pound of weight gain every 23 days. Firmicutes have been reported as distinctly proinflammatory and obesogenic, with Bacteroidetes counter-regulating these effects (24). The obesogenic basis of Firmicutes appears to be rooted in the increased production and absorption of short-chain fatty acids. However, proinflammatory and obesogenic characteristics should not necessarily be interpreted as unhealthy per se. Rather, the compositional balance of the symbiotic microbiota as control parameters is key to metabolic health. Layered on top of the variety of microbes seen across individuals, it is important to consider that different microbes appear to be able to provide complementary and compensatory genes which, in turn, provide functional redundancy. Turnbaugh et al. identified a set of genes, as opposed to bacterial species, that was common among monozygotic and dizygotic twin pairs concordant for obesity or leanness (25). They saw that extremely different species of bacteria could share similar metabolic functions and pathways, suggesting that the twins shared a “core microbiome” rather than a “core

microbiota”. This observation highlighted the importance of pursuing metabolomics beyond phylogenetic studies to best understand the relationship of host and microbiota. Similarly, a horizontal gene transfer from microbes from Japanese sushi was shown to provide seaweed-digesting enzymes valuable in the Japanese population (26). This is a nice illustration of microflora representing a significant source of metabolic variability in the host. With the need for strict microbial regulation being abundantly clear, one might wonder how the body can exert a meaningful influence on this domain. As will be addressed further in Section 6.2.3., the immune system not only tolerates indigenous flora but plays a key role in the active regulation of its composition and activity. Indeed, without an indigenous microbiota to which our immune system is tolerant, we would not survive. Selective pressures are imposed by both the immune system and the microbiota, with immune-derived influences commonly referred to as a “top-down force” (selecting for stable communities with functional redundancy) and microbiota-derived influences commonly referred to as a “bottom-up force” (selecting for adaptation to the niches occupied). In addition, the microbes themselves compete with pathogenic organisms for mucosal binding (colonization), with one such method being that of producing bacteriocins, proteinaceous or peptidic moieties that inhibit the growth of similar bacterial strains (27). As will be addressed in Section 6.3.4, bacteria are also capable of producing antibiotics that enable them to thrive and support the health of the host.

6.1.3.2 Microbiota-Mediated Inflammation A key characteristic of host interactions with the gut microbiota is the degree to which these interactions invoke inflammatory pathways. Inflammation is a critical control parameter of systemic phenomena (e.g. obesity and metabolic disease) and must be considered to define the role of the gut microbiota in morbidity and mortality. By this means, we can better understand how the microbiota contribute to our fitness landscape and create susceptibility states that render us vulnerable to disease. Not only would this identify key biomarkers for surveillance, but it would also reveal targets for therapeutic interventions to prevent susceptibilities before they even arise. This understanding would have a major influence on health maintenance strategies and allow clinical interventions much earlier in the course of disease. Obesity, insulin-resistance, and metabolic syndrome are all characterized by chronic low-grade inflammatory states. While the immune system evolved inflammatory mechanisms to combat foreign microbial invasion and assist wound healing, excessive or prolonged inflammation can actually be quite deleterious and generate disease in its own accord. It is generally accepted that the low-grade inflammation associated with obesity, insulin-resistance, and metabolic syndrome derives from inflammatory activation of adipose tissue. While this may derive from intrinsic sources, significant gut dysbiosis and cytokine activation has also been noted in these conditions and may contribute to the initiation or exacerbation of the inflammatory response in adipocytes. Regardless, the resultant breakdown of the evolutionary mechanisms that maintain

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Microbiota and Human Metabolism energy balance and homeostasis in adipocytes is rooted in inflammation and initiates after a certain threshold of lipid storage has been exceeded. As adipocytes hypertrophy, they ultimately outgrow their blood supply, become hypoxic, and require macrophage infiltration for processing of cellular debris. This effect is particularly prominent in visceral adipose tissue and changes the phenotype of macrophages from the less inflammatory M2 to the more inflammatory M1 subtype. This signature transformation marks a critical point of transition for the involved tissue and fosters an insatiable feedforward process for further inflammation and disease progression. Taken in context, systemic metabolic disease is thought to be propelled by the phenomena of metabolic bacteremia and endotoxemia. Lipopolysaccharide (LPS), also called endotoxin, is the major component of the outer membrane of gramnegative bacteria. LPS is classically recognized by the pattern recognition receptor (PRR) Toll-like receptor 4 (TLR4) on innate immune cells. When activated by LPS, TLR4 elicits a signal transduction mechanism that activates immune and inflammatory responses. In the absence of symbiotic metabolites that suppress the activity of pathogenic bacterial species, endotoxin can contribute pathoetiologically to breaches of the mucosal barrier that promote translocation of bacterial products from the gut lumen (11, 28–30). The phenomenon of metabolic endotoxemia is thus promoted by gram-negative bacteria and results in the subclinical passage of LPS into portal circulation. This most prominently occurs via paracellular leakage through weakened tight junctions but may also occur intracellularly (i.e. through enterocytes) as facilitated by lipoproteinaceous chylomicrons (11, 31). These chylomicrons typically serve to transport dietary lipids into the circulation but cannot discriminate which cargo is burdened by LPS. The disassembly of tight junction complexes is notably enhanced in the setting of a high-fat diet. Several putative mechanisms have been implicated in the pathophysiology of this process. First, the increase in lipid substrates also increases the formation of chylomicrons, enhancing the intracellular translocation of LPS discussed above. Second, a reduction in alkaline phosphatase activity reduces the cleavage of LPS in the intestinal lumen, increasing the total LPS burden in the gut. Finally, high-fat diets augment the abundance of gram-negative bacteria in the gut, reducing the expression of genes that encode for epithelial tight junction proteins, zonula occludens-1 (ZO-1, tight junction protein-1), and occludin. Further exacerbating this insult is the concomitant rise in inflammatory cytokines that disrupt epithelial function by independently compromising tight junction protein complexes and promoting apoptosis (32). With increasing destruction of tight junctions, the gut mucosal barrier eventually loses its ability to contain bacteria within the intestinal lumen. The resulting phenomenon, known as leaky gut syndrome, allows the microbiota to infiltrate the gut wall and enter the circulation. Amar et al. evaluated the prognostic value of metabolic bacteremia for the subsequent development of type 2 diabetes among 3,280 abdominally obese insulin-resistant individuals over nine years (33). They demonstrated that the Proteobacteria represented the vast majority of blood microbiota at baseline and that its concentration

rose among those who went on to develop type 2 diabetes. This increased abundance of bloodborne Proteobacteria likely contributes to the chronic low-grade inflammation observed in diseases of insulin-resistance. As discussed, inflammation appears to be a fundamental component of Proteobacteriarelated diseases (20). Both viable and dead bacteria activate cells of the innate immune system. Infiltration of the bacteria into adipose depots along the portal circulation leads to inflammation of the hypertrophied adipose tissue. This promotes local and systemic obesity and amplification of the pernicious gestalt of obesity, insulin resistance, metabolic syndrome, type 2 diabetes, and other manifestations of metabolic disease.

Contrasting the effects of gram-negative bacteria, Bifidobacterium species in the gut actually help to preserve mucosal tight junction integrity by promoting the production of glucagon-like peptide-2 (GLP-2) from intestinal L cells. GLP-2 drives the proliferation of cells in the intestinal villi responsible for crypt elongation, mediated by insulin-like growth factor 1 (IGF1) and the production of β catenin (34–36). β catenin is a protein component of the cell adhesion complex that is responsible for the cytoplasmic anchoring of cadherin. GLP-2 is also responsible for the production of other components of the tight junction, including ZO-1 and occludin (32). Another PRR, Toll-like receptor 2 (TLR2) helps maintain the integrity of intestinal tight junctions when activated. This occurs, at least in part, due to activation by the non-pathogenic gram-positive organisms that seed our intestinal tracts. This includes certain species of Lactobacillus, which are among the most thoroughly characterized probiotic agents. Lactobacillusdriven activation of TLR2 co-opts the insulin signaling pathway—phosphatidylinositol 3-kinase (PI3K)/ protein kinase B (PKB, AKT)—to prevent gram-negative species’ LPS-induced disassembly of paracellular tight junctions (37, 38). In addition to TLR2, crosstalk occurs between fatty acids of non-microbial origin and the PRRs of the innate immune system. Specifically, certain PRRs are activated by saturated fatty acids and inhibited by omega-3 polyunsaturated fatty acids (39). Investigators have demonstrated the effects of these fatty acids on the elaboration of cytokines and the inflammatory response coupled to the development of obesity and insulin resistance (40, 41). As speculated by Shen et al., in the absence of microbes, inflammation caused by saturated fatty acids is likely to potentiate the effects of metabolic endotoxemia (11). Not only does a high-fat diet promote the process of lipopolysaccharide (LPS) uptake from the gut lumen into the portal circulation, but the LPS and absorbed saturated fatty acids together in the circulation amplify the induced inflammatory state. A fascinating and far-reaching revelation that highlights how an altered microbiota composition modifies health comes from the work of Alyssio Fasano. Fasano demonstrated that the protein zonulin modulates tight junction permeability in a wide range of gut inflammatory diseases (42). This includes a number of conditions that have been correlated with an

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altered microbiota, including the gluten allergy-induced celiac disease, non-celiac gluten sensitivity, type 1 and 2 diabetes mellitus, insulin-resistant states of hepatic steatosis, obesity, polycystic ovarian syndrome, coronary artery disease, inflammatory bowel diseases, asthma, multiple sclerosis and other neurodegenerative disorders, primary brain tumors (particularly gliomas), other cancers (including non-Hodgkin’s lymphoma), and autism spectrum disorder (43–45). Certainly, a broad spectrum of pathophysiology, however in each case there is inappropriate trafficking of intact proteins and partially digested peptides, with abrogation of antigenic tolerance. This results in the destructive disassembly of the tight junction complexes that otherwise serve as the glue between epithelial cells, separating the toxic environment of the gut lumen from the internal milieu of the body. Under typical physiological conditions, antigenic trafficking occurs in most, but not all, cases via a transcellular mechanism involving endocytosis and lysosomal degradation associated with immune tolerance to these antigens. Trafficking occurs at tight junctions, which act like biological gatekeepers, physiologically dynamic and intricately regulated. Pathogen-secreted enterotoxins and gliadin (the protein in grains that forms gluten when combined with water) similarly promote the release of zonulin after interacting with the apical surface of epithelial cells. Zonulin induces the phosphorylation-dependent activation of epidermal derived growth factor (EDGF) in epithelial cell membranes which, in turn, transduces signals through the Ras/mitogen-activated protein kinase (MAPK) pathway that results in the disassembly of tight junctions downstream. In the body, both gluten and enterotoxins also promote pro-inflammatory cytokine release from macrophages, contributing to disease pathogenesis. Pathological inflammatory responses are indeed part and parcel of multiple chronic disease states. These may be derived from or enhanced by an antecedent factor contributing to a chronic psychogenic stress response. The notion that the mind is an important influencing factor of physiology can also be reciprocally stated in the sense that physical stress reduces the threshold for perceiving or coping with psychogenic stressors. Whether stress originates from a primarily organic or psychological source, the result is a reduction in the counter-regulatory control mechanisms of the immune system. It is crucial to recognize that stress responses of both types are inextricably connected and a paragon example of a positive feedback relationship. It should come as no surprise that perturbations also have a profound impact on gut microbiota composition. The gene products of gut microbes allow production of vitamins, transcription factors and co-activators, and neurotransmitters that are critical mood regulation. It should be no surprise that dysbiosis has been linked with pervasive maladies well beyond the limits of the gastrointestinal system. As discussed in Chapter 4, the status of the microbiota is also inextricable from inflammation and redox stress, which further cascades into a loss of the cell’s free energy state and an imbalance of acid-base chemistry. In a real and remarkable sense, the microbes, their gene pools, and their proteins and other metabolic products are fundamentally a part of who we are, being a critical function and determinant of our physical and mental health.

6.1.4 Genetics In contrast to what one might expect, Zhang et  al. reported that host genetics in mice account for only 12% of the variance in the gut microbial population (with diet accounting for 57%) (46). In humans, genotype and microbiome data from 1,046 healthy, genetically unrelated individuals from different ancestral origins but similar or shared living environments, led Rothschild et al. to report that the dominant factor impacting the composition of the flora was environmental (47). This was supported by a meta-analysis of twin studies performed by Goodrich et  al., collectively suggesting that host genetics play a relatively minor role in determining the structure of the gut microbial population. Nonetheless, the converse role of the gut microbiome in human health and evolution is proving to be markedly more intriguing (48). As alluded to, the gut microbiome contains an estimated 3.3 million non-redundant genes compared to the 19,000 that comprise the human genome (4, 5) (Figure 6.1). From the perspective of the composite supraorganism, the collective gene pool is almost entirely that of the microbiota. It is tantalizing to consider this in the context of ideas posed by Jack Tuszynski (addressed in Volume I) that the gut microbial flora may be in a transition state analogous to that of the endosymbiosis that resulted in the development of cell mitochondria. If such a hybridization were to occur, even on fractional scale, the composition of the collective gene pool would be quickly dominated by that of the microbiota. How this may manifest in terms of downstream translational expression remains unclear, but given the delicate balance of human physiological regulation, the impacts would likely be profound. One of the stunning elucidations of modern science is that the ancient Alphaproteobacteria became subsumed into eukaryotic cells and was ultimately transformed into mitochondria. The mitochondria, powerhouse organelles that they are, provide the metabolic machinery for oxidative metabolism, the manifestations of which made human evolution possible.

6.1.5 Epigenetic Systems Another key factor that imparts complexity and sophistication of the supraorganism is epigenetic regulation of gene expression. The noncoding regions of DNA represent the overwhelming majority of genetic material and are responsible for the repression of protein-coding genes. The environment induces epigenetic mechanisms that, in turn, mediate gene expression. Gut microbes have been noted to alter epigenetic homeostasis via their digestive products, such as metabolites and signaling molecules (reviewed in [49]). Investigations are ongoing to determine whether or not microbial enzymatic machinery interacts directly in modifying human DNA, histones, or other as yet unidentified targets that might influence genetic expression. The epigenetic chemical modifications discovered to date fall into three major categories: DNA methylation, histone modification, and modulation by non-coding RNA. Histone modification includes mechanisms such as acetylation, which

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Microbiota and Human Metabolism promotes transcription by pulling histones away from DNAcoding regions. Non-coding RNA primarily impacts regulation of gene expression at the transcriptional, post-transcriptional, and post-translational levels by silencing segments of DNA or RNA. The ramifications of these epigenetic changes are augmented by their transgenerational transmission, being preserved to some degree in offspring. Microbial methyltransferases in the gut catalyze the transfer of microbially-derived methyl (CH3) groups either to DNA (particularly cytosine residues) or to histone amino acids (e.g. lysine and arginine). In addition to transferring methyl groups, bacteria may add or remove acetyl groups to or from histones (50). Regulation of host gene expression through post-translational acetylation of amino acids in histone proteins typically occurs on lysine residues by histone acetyltransferases (HATs). Transcriptional activation and repression are generally achieved through the acetylation or deacetylation of specific lysine residues, respectively. Transcriptional gene repression can also occur through the process of biotinylation, in which biotin (vitamin B7) is attached to histone proteins. Biotin, like many other vitamins, can be synthesized by gut bacteria. Other bacterially synthesized vitamins include thiamin (vitamin B1), riboflavin (vitamin B2), niacin (vitamin B3), pantothenic acid (vitamin B5), pyridoxine (vitamin B6), folate (vitamin B9), cyanocobalamin (vitamin B12), and menaquinone (vitamin K2, converted from dietary phylloquinone, vitamin K1) (51–53). These socalled essential vitamins cannot be made endogenously by humans and, thus, must be acquired via dietary consumption or through biosynthesis by the gut microbiota. The inability to biotinylate histone proteins leads to dysregulated gene expression. Moreover, all of the microbially derived B vitamins appear to be important factors in the human epigenetic machinery, most prominently for donating methyl groups to DNA molecules (54, 55). This occurs primarily in concert with methyltransferases, which gut microbes also produce. Methyltransferases mainly act by attaching a methyl group to cytosine bases at DNA sites that are followed by a guanosine (CpG), resulting in gene silencing. A decrease in bioavailable methyl donors results in hypomethylation of certain genes, which can predispose one to conditions including obesity, cancer, and diabetes (56, 57). Hypermethylation of DNA can also lead to cancer by silencing specific tumor suppressor genes. Hypermethylation, as a driver in cancer onset, progression, and dissemination (58), is better understood than DNA hypomethylation. The metabolites produced by the gut-inhabiting microbiota influence epigenetics (59). For instance, bacterial non-coding RNAs can regulate host gene expression by binding to protein-coding regions of DNA, mRNA, or tRNA. Conversely, eukaryotic (host) non-coding RNA can regulate bacterial gene expression in an analogous way. Another key metabolite with a powerful role influencing epigenetics is that of the short-chain fatty acid, butyrate. Among the varied mechanisms of action of butyrate are many that involve epigenetic regulation of gene expression through the inhibition of histone deacetylase, undoubtedly with far reaching consequences (reviewed in [60]). These regulatory networks are examples within the emerging field of host-microbe interactions. These interactions

between the host and microbial flora that regulate one another’s gene expression speak for their coevolution and symbiotic nature. Thus, the normal versus disturbed microbiome appears to be mechanistically crucial to epigenetic regulation in human physiology and disease states. Conversely, a healthy host state will promote a salubrious microbiome composition, whereas disease states will promote dysbiosis and growth of opportunistic organisms associated with losses of beneficial organisms. This exciting field of research is anticipated to contribute profoundly to the abounding insights and therapeutic potential of medicine. Gene products of the gut microbiome include many essential vitamins, transcription factors, and coactivators of gene expression. The latter regulate the production of neurotransmitters that are important for mood regulation, including serotonin, dopamine, and gamma amino butyric acid (GABA). Thus, in a real and practical sense, the composite of these microbes (the microbiota) and their gene pool (the microbiome) are fundamentally a part of who we are. Their composition is a critical function (and determinant) of our physical and mental health.

6.1.6 The Ecology of the Microbiota and the Supraorganism Comparisons of bacterial populations from highly varied settings reveal that the diversity of bacteria in the vertebrate gut is extraordinarily high (61). This finding reflects the co-evolution of the microbiota and vertebrates that occurred over hundreds of millions of years. In addition, there is a great deal of cooperation among the bacteria themselves. These mutualistic relationships do not discriminate on the basis of taxonomy (e.g. at the phylum or species level), but instead formulate in functional groups called “guilds”. By working together, the members of a guild become metabolically related. Guilds come together to form communities, which themselves form larger ecosystems. Guild-level analyses have demonstrated correlations with a variety of host parameters, with some guilds even serving as predictors of clinical improvement (62, 63). Recent efforts have utilized statistical models to help identify “ecogroups” in humans and piglets via low frequency metabolic pathways, which may help identify critical drivers of community assembly and function (64). The immense depth of stratification built into the metabolic systems of the microbiota allow cooperation at multiple levels, from hyper-local to system-wide. The latter permits operations to synchronize at a very large scale and may help us understand how the microbiota serves as a virtual endocrine organ that collectively senses and influences physiology (reviewed in [65]). Thus, both the gut microbiota and the vertebrate host sense and respond to molecular signals from one another. This inter-connectivity allows the microbiota to interact with numerous host systems (e.g. the autonomic nervous system, neuroendocrine system, enteric nervous system, and immune system), which are extensively inter-connected themselves, allowing for large-scale physiological phenomena such

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FIGURE 6.3  Molecular conversations of the microbiota with key systems of the body. The gastrointestinal microbiota is a central component of the collection of body systems that interacts in concert to support function and health. These systems communicate with one another via the types of molecules exemplified.

as circadian rhythms (Figure 6.3). Both parties of the supraorganism are active in this communication, utilizing shared hormones, peptides, and neurotransmitters. In addition, the gut microbiota synthesizes short-chain fatty acids (see Section 6.3.4)., essential vitamins, and antibiotics, and also metabolizes primary bile acids to secondary bile acids that are mutually beneficial for the host (described in Section 6.3.3).. Importantly, insights into the orchestration of these biological processes offer the hope of a better understanding of the processes underlying health, disease, and aging and also augmenting the development of new predictive treatments.

6.2 The Supraorganism As discussed at the beginning of this chapter, our metabolic systems are inextricably dependent on our microbial companions for survival. The microbiota exerts a powerful influence over our bodily systems in much the same way that we regulate their composition and localization. While this revelation may seem to be unanticipated (even paradoxical perhaps), it is simply the inevitability of two highly complex biological systems being forced to share an organic vessel. While it can be easy to conceptualize the microbiota as an idle passenger, this could not be further from the truth. Our gut inhabitants are vigorous voyagers and have developed elaborate strategies to occupy nearly every ecological niche on the planet. Their ancestry greatly outstrips that of our own and would fare much better in the face of an existential crisis. The gut microbiota is a community of master survivors, constantly at odds with the environment and ever adapting to change. In their world, passive inaction would be a death sentence and quickly dissipate from the gene pool. As such, they are in constant search of an appropriate habitat and utilize many techniques to manipulate the environment in their favor. This means manipulating the human body itself, toward health or disease, to promote their

Metabolism and Medicine survival. With this in mind, one can appreciate the importance of maintaining a specific microbiota composition and understand why the body dedicates so many precious resources to achieve this goal. The microbiota lives at the interface of the host and the environment, with the most important junction being that of the gastrointestinal tract. Here, the host provides regular nutrition, moisture, and a rather stable growth environment for the microbiota. The microbiota, in return, aids in digestion of nutrients, development and functioning of the host immune system, fending off rival (including pathogenic) organisms, development and functioning of the brain (behavior), and synthesis of essential vitamins, neurotransmitters, and hormones. A normal, healthy microbiome interacts with a salutary diet to produce metabolites that favorably impact host physiology in a number of ways. Alternatively, an unhealthy diet and other factors predispose individuals to an abnormal microbiota that promotes disease. Dysbiosis (from Greek roots dys “bad” and bios “life”) is a maladaptive imbalance of microbial composition or localization within some environmental niche. Dysbiotic states are characterized by a relative under-abundance of the normally dominant species, with a simultaneous over-growth of other minority species. This compositional dysregulation often correlates with illness and may even play a causal role in the etiology and pathophysiology of many diseases.

The gut microbial composition can be perturbed by bioactive agents originating from sources that are exogenous (e.g. antibiotics and exogenous steroids) or endogenous (e.g. the generation of glucocorticoids from prolonged periods of stress) (66, 67). Additionally, birth by cesarean section and formula-feeding can disrupt the establishment of a healthy gut microbiota in newborns, predisposing them to risk factors for obesity and metabolic diseases later in life (68–73).

6.2.1 Co-Development: From Birth through Life The environment in utero is essentially sterile. Thus, under normal developmental conditions, mammalian infants begin their relationship with the microbiota during vaginal delivery. Within 20 minutes, vaginal microbes can be found harbored within newborns. Passage through the birth canal appears to be an integral step in this process as infants delivered by caesarian section are primarily colonized skin microbes (74). This early floral discrepancy can have major downstream consequences on gene expression, with cesarean newborns more likely to become overweight by three years of age (71). In addition, they are at higher risk for developing obesity, type 2 diabetes, and metabolic syndrome (75). Major differences have also been observed between breast- and bottle-fed infants. These two forms of nutrition demonstrate substantial compositional differences and diverge quite significantly in their impact on the microbiota. After all, formula is not a milk product, and breast milk has been biologically crafted over the course of millennia to contain an ideal balance of nutrients

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Microbiota and Human Metabolism for the developing newborn. This includes a mixture of oligosaccharides, antimicrobial agents, and immunomodulators that have been correlated with increased survival (reviewed in (76). Among these factors is the oligosaccharide “bifido factor” (as it was coined in 1954), which promotes the growth of Bifidobacterium bifidus. An individual’s intestinal microbiota continues to evolve over the course of development, most prominently during the first three years of life but also when prompted by major stressors. Environment serves a key regulatory role in this regard as evidenced by findings from Rothschild et  al., (47, 48). Genotype and microbiome data were compared from 1,046 healthy individuals with different ancestral origins but similar or shared living environments. Environmental factors such as common households, diet, and drugs accounted for greater than 20% of the variability seen among participants, while no significant similarity was noted among relatives that lacked a history of cohabitation. Other marked events with great impacts on the developing microbial ecology included the onset of breast feeding, the onset of formula or solid food consumption, latency to first fever, and latency to first antibiotics (74). As described in Section 6.3.4., antibiotics have a profound impact on microbial ecology, particularly at a young age. Numerous studies have shown that antibiotics and other medicines can produce significant changes in gene expression, fat accumulation, and the likelihood for developing certain metabolic diseases. Much of the research on this topic suggests that inadequate exposure of the immune system during early life yields intolerance of harmless antigens in adolescence and adulthood. The result of this is chronic immune activation that leads to a variety of chronic illnesses, including some forms of cancer. Human babies are colonized by environmental microorganisms, primarily from the mother’s vagina or skin during their passage through the birth canal and while breast feeding, respectively. Due to the highly oxidative environment in the gastrointestinal tract of the newborn, facultative anaerobic bacteria (e.g. proteobacteria) become the primary colonizers. These bacteria functionally reduce the oxygen concentration of the gut and subsequently promote the colonization of anaerobic microorganisms (e.g. Bacteroides, Actinobacteria, and Firmicutes). The composition of an infant’s gut microbiota is quite rudimentary and fluctuates significantly during the first year of life. Microbial signatures begin to stabilize and resemble the “adult state” around one to two years of age.

6.2.2 The Gastrointestinal Tract: Where Microbiota Meets Host The gut serves as the location for the first significant association of the microbiota with the host. As such, it is here that the immune system first detects microbes and determines if they are friends or foes. The enteric and autonomic nervous systems respond to immune surveillance signals and metabolites of both the host and microbes. The neuroendocrine system

senses and responds to the microbes via hormonal communication. If necessary, the hypothalamic-pituitary-adrenal (HPA) axis can be activated as well, all in accordance with the rhythms of the circadian system. The interactions of the gastrointestinal tract with the microbiota are critical to both the development and functioning of the host systems and the structure and functioning of the microbiota. The body’s systems and the microbiota are constantly sending and receiving signals. Thus, it is not surprising that disturbances in any of these bodily systems or in the microbiota will impact the other regardless of the source. Indeed, it can be extremely challenging to ascertain cause and effect relationships given the interactive nature of the systems and microbiota. Animal models and specialized in vitro systems offer the ability to manipulate specific components at will and help establish causation. In the intestines, the mucosal immune system has two primary tasks. First, it protects against microbial infection and translocation across the tissue barrier of the gut. The host intestinal epithelial cells are separated from the dense microbial communities by a mucous layer, comprised of interconnected sheets that form pores which exclude bacterial cells. Second, it facilitates nutrient absorption from the gastrointestinal lumen. The mucous layer provides lubricant that facilitates gastrointestinal transit, promoting microbial adhesion through lectins and glycosidase expressed by specific bacteria. Recent reports have shown that microorganisms have a major effect on both mucous thickness and composition. These studies represent one of the many examples of symbiosis or mutualism that occurs between humans and the gut microbiota.

6.2.3 The Microbiota and the Immune System: More Than Just Flagging Good versus Bad Two thirds of the immune system reside in the wall of the gastrointestinal tract (77). This commitment emphasizes the body’s priority for monitoring this fragile and potentially dangerous interface with the environment. The risks for toxicity come from all forms of xenobiotics (including drugs, allergens, and food additives), pathogenic microbes, and other enteric exposures. Microbes are one of the primary drivers of immune development. The innate immune system responds to pathogenassociated molecular patterns (PAMPs), antigenic molecules on the surface of pathogens that elicit the activation of proinflammatory signal cascades and the expansion/differentiation of regulatory T cells (Tregs) (17, 78, 79). When microbes cannot be locally contained, they may gain access to the circulation and incite a chronic systemic inflammatory response. In this context, inflammation is largely rooted in the gastrointestinal tract due to its considerable pathogenic burden (i.e. bacteria) and high density of immune tissue. Inflammation is a hallmark feature of many chronic diseases; such microbeinduced immune responses may contribute to the low-grade inflammation that characterizes obesity and type 2 diabetes. Indeed, subclinical endotoxicities in the portal circulation have been linked to hepatic insulin resistance and steatosis, which are classical indicators of systemic insulin resistance and type 2 diabetes (80).

236 In the healthy state, the immune system does an impressive job of distinguishing between self and non-self. The process of self-tolerance involves two steps, both of which minimize the potential for B and T lymphocytes to target host antigens. In the first process, known as central tolerance, the central lymphoid organs (e.g. bone marrow, thymus) provide signals that support lymphocyte maturation, eliminating most auto-reactive lymphocytes from the pool of early lymphocytes. In the second process, known as peripheral tolerance, the peripheral lymphoid organs (e.g. lymph nodes, spleen, and components of the mucosal immune system) capture pathogens and put them in close proximity with lymphocytes to promote maturation. The mature lymphocytes prevent auto-reactive lymphocytes from attacking self-antigens. With respect to the supraorganism, gastrointestinal flora are primarily restricted to the intestinal lumen and therefore isolated from immune cells. As a result, communication at the level of metabolites plays a significant role in training the immune system to be tolerant of bacteria that support healthy physiology. Rather than merely identifying symbiotic and pathogenic microbes based on antigens, the immune system responds according to the interactive nature of specific microbes with the host. This tailored approach permits the immune system to invoke strategic responses that regulate bacterial behavior (including damage to the host) and govern immune reactivity. In the intestinal lumen, the bacteria are physically and anatomically contained by the presence of intestinal epithelial cells, tight junctions, mucus, antimicrobial peptides and secretory immunoglobulin A (Figure 6.4). Rather than interacting with immune cells directly, the gut bacteria serve as immunomodulators. For instance, Bacteroides fragilis has a capsular

Metabolism and Medicine polysaccharide A (PSA) that can interact with Toll-like receptor to stimulate interleukin (IL)-10-producing cluster of differentiation four (CD4)+ Forkhead box protein P3 (FOXP3)+ Tregs in the colon. Studies in mice have demonstrated that this is required for intestinal colonization and is associated with prevention of colitis (18). B. fragilis has further been reported to modulate immune responses by producing glycosphingolipids that inhibit natural killer cell proliferation (81). Likewise, members of the Clostridium class (Firmicutes phylum) have been shown to prevent colitis by promoting differentiation and function of IL-10-producing CD4+ FOXP3+ Tregs in the colon (17). In addition, their production of short-chain fatty acids (SCFAs) has been shown to be responsible for promoting Treg immune suppressive function (82) and for suppressing the production of pro-inflammatory cytokines by dendritic cells while enhancing their ability to induce peripheral Treg differentiation (79). A small percentage of the bacteria of the gastrointestinal tract manage to penetrate the mucous layer and colonize the surface of the intestinal epithelial cells. This includes members of the Bacteroidetes and Firmicutes phyla, albeit at concentrations two to three logs lower than that of their luminal counterparts. One example is a Firmicutes member, segmented filamentous bacteria (SFB), which has been seen to elicit proinflammatory immune responses that have both protective and pathogenic features based on context (associated with pathogen immunity and autoimmunity) (84, 85). Symbiotic bacteria that manage to breach the intestinal barrier are generally phagocytosed within the lamina propria. Nonetheless, some are able to enter and colonize the gutassociate lymphoid tissues (GALT), including Peyer’s patches, lymphoid follicles, and mesenteric lymph nodes, where they

FIGURE 6.4  The anatomical locations of the gastrointestinal microbiota. The bacteria in the mammalian gastrointestinal tract are known to inhabit three locations: a) the lumen, b) the intestinal epithelium, and c) gut-associated lymphoid tissue. In healthy mammals, the vast majority of the symbiotic bacteria live in the intestinal lumen, away from physical contact with immune cells. Others are associated with the intestinal epithelium or, in a small percentage of cases, inhabit gut-associated lymphoid tissues, including the Peyer’s patches, lymphoid follicles, and mesenteric lymph nodes. Source: adapted from (83).

Microbiota and Human Metabolism live in relative isolation (86). However, when typical GALT inhabitants (e.g. Alcaligenes species) escape beyond GALT regions, they can induce intestinal IgA responses, activate IL-22-producing retinoid-related orphan receptor gamma t (RORγt)+ innate lymphoid cells, and elicit systemic inflammation with associated tissue pathology. While the story continues to unfold, a consistent observation has been that human and mouse microbiota can promote chronic inflammatory disease through dysbiosis and bacterial translocation. In this regard, it is important to bear in mind that even healthy bacteria can be pathogenic in certain contexts. Numerous factors, including viral infections, trauma, antibiotic use, and chronic exposure to allergens or inflammatory food components can disrupt the regulatory elements that govern dysbiosis and translocation. In the face of such acute decompensations, the traditionally commensal bacterial species can inflict serious tissue damage and invoke pro-inflammatory immune responses. The immune system does not simply distinguish bacteria as being healthy or pathogenic per se. Instead, it responds to and reciprocally impacts the balance of the structure and metabolic activity of the bacteria in the given milieu of the host, leading to tolerant or intolerant immune responses.

With a healthy gastrointestinal microbiota, bacteria will convert dietary fibers into short-chain fatty acids (SCFAs) that cross the intestinal epithelium into the mesenteric lymph nodes, where they induce regulatory T cells (Tregs) to inhibit inflammatory responses. Inversely, a paucity of SCFA-producing bacteria elicits pro-inflammatory responses in Tregs (Figure 6.5). In addition, dendritic cells and macrophages are antigen-presenting cells and possess long projection-containing pathogen

237 recognition receptors that sample the microbial flora along the mucosal surface of the gut lumen. When dendritic cells encounter pathogenic bacterial antigens, such as LPS, they present them to regulatory T cells, which induce an inflammatory response. Correspondingly, macrophages will capture the offending bacteria and transfer them into lysosomes for enzymatic degradation. As discussed, compositional deviations of the gut microbiota can promote disassembly of the epithelial tight junctions that normally isolate the toxic environment of the gastrointestinal tract from the rest of the body. Reductions of gut barrier-protecting bacteria and increases of sulfate-reducing pathogens both appear to contribute to the development of metabolic syndrome (46). Disrupting the integrity of the intestinal barrier recruits intestinal macrophages and promotes the amplification of innate immune system responses. This is further exacerbated by communication of the innate immune system with adaptive B and T cell lymphocytes that accumulate as Peyer’s patches in the gut wall. Interestingly, gut barrier function appears to degenerate naturally with age and is associated with the increased pro-inflammatory state that is characteristic of aging. Approximately 50 bacterial strains seem to play important roles regarding lifespan, with some extending and others reducing longevity (87). It is noteworthy that the diversity of an infant’s microbiota trains their developing immune system, metabolic systems, and even the nature of their tight junctions. As a result, it should not be surprising that adults who were born by C-section, fed formula, and/or given antibiotics in infancy demonstrate a dose-dependent increase in obesity, asthma, diabetes, celiac disease, allergies, multiple sclerosis, autism, and other ailments. These modern diseases are united by their underlying malfunctioning of immune and metabolic physiology.

FIGURE 6.5  Compromised tight junctions and the inflammatory response. A diet rich in fiber-containing produce enhances the production of SCFAs as microbes metabolize insoluble fibers. SCFAs serve as a substrate for numerous healthy metabolites and support the integrity of epithelial tight junctions. Dendritic cells of the immune system extend their arms to sample the mucosal surfaces of the gut lumen for pathogens and transmit this information to Tregs. In the presence of adequate SCFA production, Tregs produce inhibitors that block the induction of inflammatory responses from the immune system. In the relative absence of SCFAs or presence of bacteria producing endotoxin, dendritic cells send distress signals that reduce the anti-inflammatory actions of Tregs, enhancing the overall inflammatory response.

238 A consistent pattern that has been emerging, and that may underlie all of the chronic metabolic illnesses addressed throughout this book, is one in which microbial dysbiosis is driven primarily by intestinal inflammation. This dysbiosis is increasingly recognized as being a catalyst for the positive feedback loop that leads to increased gut epithelial permeability, enhanced pro-inflammatory immune responses, and reduced regulation of inflammatory activity (88). This triad has major implications on the chronic disease states that involve low-grade chronic inflammation, including obesity, insulin resistance, type 2 diabetes, cardiovascular disease, renal and liver diseases, and a host of neuropsychiatric disorders and cancers.

6.2.4 The Nervous System: Two Brains With the exception of the brain, the mammalian gastrointestinal tract is the only organ system with an autonomous nervous system, containing as many neurons in the small intestine as there are in the spinal cord (i.e. approximately 500 million). Affectionately referred to as the “second brain”, the neurons of the gut produce 90–95% of the body’s serotonin, along with every other class of neurotransmitter in the central nervous system. In addition to modulating gut motility/secretion, the enteric nervous system (ENS) plays a pivotal role in numerous extra-intestinal phenomena that are classically thought to be of central origin, including cognition, mood, behavior, and pain (89, 90). Our two nervous systems, though seemingly partitioned in space, share a profound reliance on the gut microbiota. With an impressively interactive choreography of biological activities occurring between microbes and their human hosts, both parties produce and respond to the metabolic

Metabolism and Medicine products of the other. Some of these products are common between the two, while others are uniquely provided by one. Figures 6.6 and 6.7 simplify this by highlighting some of the key metabolic currencies needed for proper functioning. The nervous system (consisting primarily of the brain, vagus nerve, and enteric nervous system), endocrine system (particularly the hypothalamic-pituitary-adrenal axis), bloodstream, and microbiota form a tightly knit and aptly named gut-brain axis (GBA). This complex collective interacts with the immune system and metabolic systems, as well as the body’s organs and limbs, providing a lifeline for functional healthy living. Several putative mechanisms have been proposed to explain how the microbiota modulates neural development, behavior, and mood (91–93). Gut bacteria produce a number of key metabolic substrates (e.g. tryptophan) that the host transforms to blood-brain barrier-permeable molecules like serotonin and SCFAs (e.g. acetate, propionate, and butyrate) (94, 95). This has been suggested to serve a neuromodulatory role in mood and cognition. The microbiota also produces acetylcholine, gamma aminobutyric acid (GABA), histamine, melatonin, and catecholamines, all of which are neuroactive and have critical implications in cognitive, behavioral, and neuromuscular function, among others. As such, dysbiosis of the gut microbiota has been linked to counter-regulatory neurotransmission (promoting depression and anxiety), impaired neurogenesis (hampering learning and memory), pain dysregulation, and neuroinflammation (leading to diseases like Alzheimer’s and Parkinson’s). Microbial dysregulation has been noted in the context of schizophrenia and autism spectrum disorder (89). In fact, it has been demonstrated with germ-free mice that regulation of repetitive behaviors and certain social behaviors, such as novelty preference and social motivation, is reliant on microbiota (95). There is promise in the utilization of

FIGURE 6.6  The microbiota-gut-brain axis. The microbiota, gastrointestinal system, and brain (as well as the nerves and blood stream that connect them) communicate and work together to provide the stimuli, hormones, and many metabolites needed to support health. This system interacts with the immune system and metabolic systems, as well as the body’s organs and limbs.

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increased inflammatory cytokines and their signaling pathways can deactivate the conversion of tryptophan to serotonin, depleting serotonin levels in the brain and promoting the development of depressive symptoms. Increased inflammatory markers can also disrupt the synthesis, reuptake, and release of serotonin, dopamine, norepinephrine, glutamate, GABA, and acetylcholine. Interestingly, GABA can reduce the release of inflammatory cytokines through inhibition of the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathway. Similarly, acetylcholine has been shown to reduce cytokine production in the periphery (98).

FIGURE 6.7  The microbiota-gut-brain axis. Ingested nutrients are metabolized by gut microbiota, leading to altered microbial composition and functionality. These gut microbes influence bile acid metabolism and produce metabolites such as SCFAs, neurotransmitters, neuromodulators, and toxins. These gut microbial metabolites interact with receptors in the enteroendocrine L cells and vagus nerve or by translocating through the intestinal epithelium into the peripheral circulation. Stimulation of intestinal L cells by bile acids or SCFAs releases the anorexigenic hormones PYY and GLP-1. It also modulates concentrations of peripheral hormones, such as leptin, ghrelin, and insulin. Gut-derived microbial toxins such as LPS can trigger an immune response. These pathways, highly regulated by the hypothalamus, cumulatively affect appetite and metabolism, ultimately affecting feeding behavior, feeding-related behaviors (e.g. cognition and impulsivity), and anxiety/depression. GABA, gamma aminobutyric acid; GLP, glucagon-like peptide; LDL, low-density lipoprotein; LPS, lipopolysaccharide; PYY, peptide YY; SCFAs, short-chain fatty acids.

psychobiotics (pre- and probiotics) to treat the microbiota of individuals belonging to these cohorts, with the goal of alleviating these and other downstream cognitive and psychomotor diseases (96). The connection between the gut microbiome and mood appears to be quite strong. Under homeostatic conditions, inflammatory cytokines play an essential role in neuroplasticity, neurogenesis, synaptic scaling, long-term potentiation, and learning and memory. However, excessive levels of inflammatory cytokines in the body have been associated with changes in cerebral cytokine levels, leading to changes in neurochemistry (neurotransmitter metabolism and function) that are associated with anxiety and depression (97). For example,

How does stress cause dysbiosis? When the sympathetic nervous system detects an acute stressor, the hypothalamic-pituitary-adrenal (HPA) axis is activated. The activated HPA axis causes a coordinated response across the body: catecholamine levels rise in the blood and tissues, glucocorticoids (such as cortisol) are synthesized and released from the adrenal cortex, blood sugar levels rise through gluconeogenesis, the immune (cytokine) system is suppressed, and the metabolism of fats and proteins is enhanced (99). Once the stressor is removed, auto-regulatory feedback pathways prevent overactivation of the stress response. However, when the stress response in chronically activated, the immune system becomes chronically suppressed by cortisol. At the same time, macrophages release a surge of pro-inflammatory cytokines (100). This immunocompromised system allows pathogenic microbes to overgrow while beneficial microbes dwindle. This change in bacterial ratios produces dysbiosis, leading to gastrointestinal infections and possibly changes in mental health.

Intestinal barrier function may be the bridge between stress, the immune system, and mental health. It has been postulated that stress increases intestinal permeability, allowing bacterial lipopolysaccharides to enter the bloodstream and activate an immune response. This inflammatory response spreads throughout the central nervous system (CNS), promoting the effects of neurotoxins while hindering beneficial neurotransmitters, thus impacting mental health (reviewed in [101]). Individuals with anxiety and depression generally have reduced microbial diversity and altered microbial metabolites, such as reduced SCFA production (crucial for healthy intestinal barrier function). Inadequate SCFA levels also compromise immune function and, ultimately, brain function (102). Further, stress-related psychiatric disorders, such as anxiety and depression, are associated with a microbiota-driven pro-inflammatory state, which can be observed as low-grade inflammation in the intestinal mucosa. The GBA is an emerging field with preliminary findings that sex hormones may regulate the gut microbiome, immune cells (including microglia), and stress. This may help explain the higher prevalence of anxiety and depression in women. Other early work suggests that administration of probiotics and prebiotics may improve intestinal barrier integrity, preventing lipopolysaccharide leaks from the intestines into the bloodstream, decreasing inflammation, and ultimately diminishing

240 the brain stress response. SCFAs and fecal transplants from healthy donors might also have the ability to improve intestinal barrier integrity, immune system activity, and vagal-nerve stimulation. Rigorous future research will be needed in this field to determine the therapeutic potential of targeting the GBA for depression and anxiety.

6.2.5 The Hypothalamic-Pituitary-Adrenal (HPA) Axis: A Lifeline in Times of Need When the body is exposed to stressors for more than a few minutes, the sympathetic nervous system releases epinephrine and norepinephrine. The elevated levels of norepinephrine stimulate the Hypothalamic-Pituitary-Adrenal (HPA) axis such that the hypothalamus secretes corticotropin-releasing hormone (CRH). In a cascade-like fashion, CRH stimulates the pituitary gland to release adrenocorticotropic hormone (ACTH), which in turn stimulates the adrenal glands to secrete cortisol and other glucocorticoids. This helps the body deal with sustained stressors (e.g. by increasing blood pressure and cardiac output, increasing circulating levels of blood glucose, and shutting down non-critical functions so that one can deal with the stressor. Eventually, high cortisol levels stimulate the hypothalamus and hippocampus to shut off the stress response in a negative feedback loop. As adaptive as the HPA axis is, excessive stimulation can nonetheless result in physical and psychiatric morbidity. Elevated cortisol levels have been linked to sequelae of immune suppression, including infection and cancer. Repetitive stimulation of the HPA axis may even increase the incidence of insulin resistance, type 2 diabetes, obesity, and cardiovascular disease. In addition, cortisol appears to impair memory and cognition, with high cortisol levels being associated with mood disorders like depression (103). The microbiota and HPA axis communicate and work together in a bidirectional manner. For example, not only does the establishment of the gut microbiota in early life appear to influence neuroendocrine stress responses (90, 104), but conversely stress appears to alter the composition of the gut microbiota and increase gastrointestinal barrier permeability (105–107). Studies have suggested that microbiota-derived peptidoglycan (a major constituent of most bacterial cell walls) has the ability to penetrate into the central nervous system, thereby activating cells of the innate immune system. This appears to have important implications on brain development and behavior (108). Likewise, LPS from gram-negative bacteria has been demonstrated to conditionally permeate the intestinal epithelium in the context of stress or a high-fat diet. The subsequent liberation of LPS from the gut has been tied to both immune and HPA axis activation (109). Fecal microbiota transplant from patients with depression can induce depression-like behavior in rodents (110). While it seems likely that depression could conversely lead to unhealthy balances of the gut microbiota, such studies remain in their infancy. The general consensus is that the microbiota–gut– brain axis is able to modulate central processes, in part, by manipulating the activity of the vagus nerve. This appears to be mediated by microbial metabolites and immune mediators

Metabolism and Medicine that alter neurotransmission via cytokine production, shortchain fatty acids (SCFAs), and microbial byproducts. This soup of mediators may also regulate activity of the HPA axis. Another possible mechanism of action of the GBA involves activating microglia in the blood brain barrier, which play critical roles in immune surveillance, synaptic pruning, and clearance of debris. Microglia are known to regulate the HPA axis, glucocorticoid release, and cytokine release (reviewed in [111]). Germ-free mice offer a chance to look for causality regarding dysbiosis and HPA axis abnormalities. Indeed, germ-free mice are characterized by often having increased reactivity of the HPA axis. Germ-free mice have been seen to have increased corticotropin-releasing factor (CRF) expression and elevated plasma ACTH and corticosterone levels in response to restraint stress (112, 113). Germ-free mice also show developmental deficits of the gastrointestinal tract (114). Consistent with germ-free mouse studies, several studies demonstrate increased corticosterone levels in response to antibioticinduced gut dysbiosis (summarized in [115]).

6.2.6 Impacts on Host Metabolism The impacts of the microbiota on host metabolism are profound and myriad. Metabolic phenotypes and profiles are modulated by interactions of gene products, diet, and symbiotic gut microorganisms that favorably or unfavorably influence responses to therapeutic interventions. Data-rich molecular signatures are providing valuable information toward a better understanding of microbial impacts on host metabolism. Interestingly, various members of the gut flora seem to be associated with specific metabolic profiles in the host. This was first demonstrated in humans by Li et al. (116) who introduced the concept of functional metagenomics, showing that changes in the abundance of one intestinal gut species, Fecalbacterium prausnitzii (one of the most abundant bacteria in the gut), were associated with differences in the concentration of eight urine metabolites. More recently, Llopis et  al. demonstrated that human gut microbiota samples transplanted into mice resulted in dramatic metabolic effects in the recipients (117). This was reflected in the metabolic profiles of their body fluids (urine and plasma) as well as in the metabolic profiles of organs (such as the liver). These differences correlated with changes in bile acids in the ileum and SCFAs in the cecum. The recipients of transplanted human microbiota showed a shift in bile acid composition (due to the inability of intestinal bacteria to deconjugate bile acid) and enhanced absorption of dietary fat. Alterations of plasma lipid profiles also correlated with the composition of the gut microflora. Indeed, the application of metabolomics (the systematic study of metabolites unique to each individual or sample) illustrates that different microflora generate different metabolic phenotypes. Using whole metagenome shotgun sequencing (as opposed to the more limiting 16S rRNA sequencing) on samples of blood and feces from 1,004 twins, Visconti et  al. were able to do a microbiome-wide association study, revealing that the majority of samples from unrelated individuals had metabolites derived from common metabolic pathways, whereas only half as many samples contained the same microbiota

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responsible for more selective shaping of the microbiota composition. As a result of microbial secretion of bile salt hydrolases in the small bowel, the taurine and glycine conjugates of bile acids are cleaved. Consequently, it is both the primary hepatic bile acids (cholic acid and chenodeoxycholic acid) and the secondary bile acids (deoxycholic acid and lithocholic acid) that are predominantly present in the colon (119, 120).

6.2.7 Co-Evolution: Commensalism and Beyond

FIGURE 6.8  Gut microbiota and metabolome composition. The pie charts compare the percentages of bacterial species with the percentages of bacterial metabolic pathways identified using whole metagenomic shotgun sequencing and a microbiome-wide association study with samples of blood and feces from 1,004 twins. They demonstrate that the functionality of the gut ecosystem is more highly conserved across a given population than the composition of species might suggest. Source: adapted from (118).

species (118) (Figure 6.8). In fact, over 90% of the microbes identified were associated with a vast proportion of the measured gut metabolites (>80%). This study revealed a degree of functional redundancy not previously appreciated. In another study, Smith et  al. examined mouse recipients of microbiota transplants from discordant Malawian infant twins with and without kwashiorkor malnutrition syndrome (82). The mice that received transplanted flora from the kwashiorkor twins demonstrated impaired growth and reduced weight gain compared to their normal twin counterparts. These mice also demonstrated disturbances in amino acid, carbohydrate, and Krebs cycle metabolism while fed a traditional Malawian diet. Their kwashiorkor malnutrition only resolved when they were switched to a protein-enriched diet, highlighting another key role of microbiota-derived metabolic impacts on the processing of nutrients and extraction of energy from the diet. Metabolic stratification of patients with type 2 diabetes and prediabetes could be based on bottom-up predictability models that determine etiologic failure points. These may result when an altered microbial flora disrupts the digestion and absorption of fats and fat-soluble vitamins via metabolism of hepatically derived conjugated bile acids and salts into deconjugated and dehydrogenated bile acids and salts (Figure 6.9). By reducing the conversion of conjugated bile salts to primary and secondary bile acids, an altered flora can cause unhealthy increases in fatty acid absorption. Since conjugated bile acids have antibiotic properties in the small intestinal lumen and are a major factor responsible for the paucity of micro-organisms in the small bowel. This can lead to further reductions of the downstream microbiota in the large intestine. In contrast, the free unconjugated primary bile acids in the large bowel are

The microbes inhabiting our body are exceptionally diverse and engage in a range of metabolic relationships that are equally, if not more, variable. Darwin’s survival of the fittest mantra applies to all organisms that seek their ecological niche, from the largest animals in the jungle to the smallest microbes that live within them. Competition (for resources, survival, mates, etc). is a universally applied and appreciated construct. The microbiota living with the human host are part and parcel of the unitary supraorganism. While classically regarded as “commensal” (benefiting one partner), a vast breadth of cooperation exists between humans and microbiota. For this reason, the terms “symbiotic” and “mutualistic” provide a more accurate description of these relationships. Figure 6.10. illustrates key aspects of these interactions, focusing on the health of the central nervous system, cardiovascular system, and gastrointestinal system. This should not be misinterpreted as comprehensive— the impacts of the gut microbiota extend to nearly every organ system, including the liver, kidneys, and pancreas, among others. This figure instead reflects that a healthy and diverse diet is essential to support the nutritional needs of the microbiota. This enables the production of SCFAs, neurotransmitters, cytokines, bile acids, and hormones. These products, in turn, interact with the brain, supporting healthy neurotransmission, neurogenesis, and neuroprotection. Both neural communications and transmission of metabolites via blood to the heart and other organs enable the various organs and systems to function properly. Such functioning is mutually beneficial and depends on the cooperation of the host and microbiota. The previously proposed ongoing evolution toward a merging of the human host and the inhabitant microbiota as a unified organism is analogous to the endosymbiosis that subsumed ancient bacteria into eukaryotic cells as mitochondria. The addition and mixing of genes resulted in two independent organisms becoming one, with some of the original prokaryotic genes becoming integrated into the nucleus. The microbiota is exceptionally diverse in terms of its ability to function under a great range of environmental, epigenetic, and genetic threats. The supraorganism would therefore benefit from a reduced need for mutational evolution to achieve resistance and greater resilience in the face of threats. In this case, at least in theory, longevity of the host lifespan would be maximized and infirmity minimized. Given the genetic and biochemical interplay among microbial agents in a given community, or guild, the biomic, genomic, and metabolomic diversity present is likely to reduce the need to evolve as the primary means to flourish and withstand existential threats.

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FIGURE 6.9  Bile acid metabolism by the host and the gut microbiota. Bile acids, initially synthesized in the liver, are further metabolized by the microbiota and can impact the composition and magnitude of the intestinal flora. This can enable the body to absorb unhealthy levels of fatty acids. Abnormal increases in fat absorption from the small bowel may promote hepatic steatosis, insulin resistance, and type 2 diabetes (121, 122).

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FIGURE 6.10  Far-reaching impacts of the gut microbiota on health and disease. The constant communication between the gut microbiota and the human host at the levels of molecules, pathways, cells, organs, and systems impacts virtually all metabolic processes. The well documented abilities of the microbiota to impact health and, conversely, the abilities of health and disease to impact the microbiota, illustrate the interwoven and interdependent nature of these relationships.

However, the above hypothetical evolutionary circumstance can only be described with the caveat that sufficient macronutrients and essential micronutrients are ingested while unhealthy environmental exposures are avoided. The scenario whereby nutrient prerequisites would not be required is the equivalent of a perpetual motion machine, such that biological thermodynamic entropy did not exist. In fact, if that were the case, not even would reproduction be required! Indeed, it would reflect Newton’s first law, that an object at rest remains at rest unless acted upon by an external force. The nutrients required are the fuel that, through energy transformation and the first law of thermodynamics, ultimately provide the force that gets a system moving.

6.3 Control and Order Parameters The factors contributing to human health and disease can be organized into two distinct categories based on their source with respect to a biological system. Extrinsic control parameters are factors external to the biological system that exert

some control or influence on said system. By contrast, intrinsic order parameters are internal properties of the biological system that determine its fundamental phenotype (i.e. physiological characteristics, behavior, etc). Under this framework, one can quickly discern that the microbiota does not fit exclusively into one category. It holds a unique position, topologically exterior to the epithelial surfaces (i.e. the gut and skin) but is more intimately engaged and directly interactive than most extrinsic parameters. It mediates several internal and external aspects of the human biological system and is itself modulated by intrinsic and extrinsic factors.

6.3.1 Extrinsic Control Parameters Human health and disease are impacted by extrinsic control parameters, many of which are shaped by lifestyle choices. The extrinsic control parameters can be divided into four general categories: diet, psychogenic factors, physical factors, and circadian behaviors. These can be envisioned as either fortifiers or stressors of the body, with the potential to enhance or degrade health, respectively.

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6.3.1.1 Diet

6.3.2 Intrinsic Order Parameters

The gut microbiota lies at the intersection of diet and metabolic health. The nutrient abundance, high surface area, and relatively stable environment of the gastrointestinal tract render it ideal for the growth of microorganisms (123). Diet is the major factor determining the microbiota composition and microbial metabolite production (124). (Impacts of diet on health are addressed further in Section 6.3.4).

Intrinsic order parameters are properties of the physiological system that determine its fundamental phenotype and are mediated by external control parameters. They can be stratified as primary, secondary, or higher order parameters depending on their relative position within the hierarchy of causality (i.e. with some parameters being “upstream” or “downstream” of others). Intrinsic order parameters primarily fall into three categories:

6.3.1.2 Psychogenic Factors Arguably the most underappreciated control parameter of human physiology and behavior is the emotional stress response. At face value, nerve roots from the brain and spinal cord infiltrate virtually every niche of the human body and are specifically designed to either gather information (afferent neurons) or exert physiological control (efferent neurons). Accordingly, the neurological and psychological status of an individual can have a profound influence on their general health. This carries both clinical and practical relevance, worthy of addressing one’s reservoir of life skills and experiences as meaningful extrinsic control parameters. In quantitative and qualitative terms, there is no stronger vitalizing force for psychological health than optimizing stress, and no greater threat to psychological well-being than devitalizing stress. (Impacts of psychogenic stress on health are addressed further in Chapter 2).

6.3.1.3 Physical Factors Another key control parameter is physical stress, which may result in either beneficial or maladaptive biological changes based on the quality and quantity of the stressor. Constructive physical stressors, such as aerobic or resistance exercises, can improve cardio-pulmonary health, boost bone density, promote weight loss, and prevent insulin resistance. On the other hand, destructive physical stressors, such as traumatic accidents or excessive exercise with inadequate rest/nutrition, can result in rapid tissue breakdown and even death. It cannot be overemphasized that our bodies thrive from healthy physical activity and suffer from insufficient or harmful activities. (Impacts of physical stress on health are addressed further in Chapter 2).

6.3.1.4 Circadian Behaviors The feeding–fasting, sleep–wake, and light–dark cycles represent the fourth fundamental pillar of the extrinsic control parameters. Each of these circadian cycles, and even cycles of social engagement, have evolved to be in sync with the periodicity of light/dark cycles created by the earth’s rotation around its own axis. While this notion is difficult to prove or disprove, it appears to be a fundamental example of evolution promoting selective advantages to living systems in terms of reproductive fitness. This resonates with Darwinian “survival of the fittest” models, as well as the fitness functions and landscapes as overarching models of health (impacts of circadian behaviors on health are addressed further in Chapter 4).

6.3.2.1 Hypothalamic-Pituitary-Adrenal (HPA) Axis One of the fundamental effects of the environment on the microbiome (including epigenetic mechanisms of disease risk) is that of eliciting a hypothalamic-pituitary-adrenal stress response. This drives a cortisol-induced immune suppression and overgrowth of pathogenic microbes with negative consequences on health. (Interactions of the HPA axis with the microbiota and impacts of the HPA endocrine axes on health are addressed further in Section 6.2.5).

6.3.2.2 Autonomic Branches of the Central Stress Response The autonomic nervous system, a subset of the peripheral nervous system, consists of 1) the sympathetic (“fight or flight”) nervous system (which activates the HPA axis in the case of prolonged stress, 2) the parasympathetic (“rest and digest”) nervous system, and 3) the enteric nervous system (ENS) of the gut. It is the autonomic branches of the central stress response that monitor and mediate the microbial-host interactions from the moment they meet. (Interactions of the HPA axis with the microbiota and impacts of the autonomic branches of the central stress response on health are addressed further in Section 6.2.4).

6.3.2.3 Immune Responses While active autonomic, hormonal, and immune responses are among the basic lifelines of any individual, their activation in a state of chronic stress leads to inflammation and immunocompromise. In sync with this, there are disturbances in the diversity and compositional constitution of the microbiota, impairing the metabolic state of the host. Not only does this condition weaken the host’s defenses against infection and some cancers, but it is at the very heart of the spectrum of illness on which this book focuses. (Impacts of the immune system on health are addressed further in Section 6.2.3).

6.3.3 The Microbiota as an Extrinsic Control Parameter and Intrinsic Order Parameter The microbiota serves as both an extrinsic control parameter that impacts the human biological system and an intrinsic order parameter that characterizes the host phenotype and is itself subject to regulation by external factors. Recognizing the microbiota from this perspective, however, demands a fundamental paradigm shift in the conceptualization of “host

Microbiota and Human Metabolism health”. Both human and microbiota serve as the organic source of intrinsic order parameters, and each is subject to modulation by extrinsic control parameters. While the microbiota serves as an external predictor of the human phenotype, so is the human an external predictor of the microbiota phenotype. The two are deeply interwoven and together subject to further modulation by other external factors. One can imagine this as a metaphorical body with four pillars (or legs), three arms, and a trunk (Figure 6.11). The four pillars are the key extrinsic control parameters (diet, psychogenic factors, physical factors, and circadian behaviors), while the three arms are the intrinsic order parameters (the HPA axis, autonomic branches of the central stress response, and immune responses). The trunk represents the gastrointestinal microbiota, which lies at the interface of the arms and legs—a hybrid of intrinsic and extrinsic. These external and internal parameters continuously impact and are impacted by one another through uninterrupted communications and responses. For this reason, human and microbiota frequently share a health status and are inter-dependent for the maintenance of homeostasis. Under this framework, the conceptualization of “host health” would be inadequate if the microbiota was excluded. The four pillars are highly interactive and function in parallel. The diet we ingest and the associated molecular trafficking within the gut lumen enable metabolic crosstalk at the

FIGURE 6.11  The organizing framework. The body of an organizing framework that provides a model for approaching a precision and personalized scale of medicine can be depicted with four pillars of external control parameters: 1) diet, 2) psychogenic factors, 3) physical factors, and 4) circadian behaviors; three arms of intrinsic order parameters: 1) hypothalamic-pituitary-hormonal endocrine axes, 2) autonomic branches of the central stress response, and 3) immune responses; and a trunk consisting of the microbiota, which provides essential support, connections, and instructions to the pillars and arms. Under this framework, the microbiota can be understood as a hybrid parameter, with both intrinsic and extrinsic qualities.

245 intestinal interface and beyond (e.g. the microbiota-gut-brain axis). Psychogenic factors (e.g. fear, reward), physical factors (e.g. exercise, trauma), and circadian behaviors all continuously modulate these processes and sculpt the way that the diet impacts clinical health. Each of these subgroups is deeply interwoven and even categorically overlapping, with fundamental connections to physiology and/or pathophysiology via their effects on the gut microbiota. As an external control parameter, the influence of an organism’s diet very much depends on the circadian phase in which it was consumed. The immune system interacts bidirectionally with the stress response and protects the homeostasis of vital organ systems. Responding to microbial invasion is a major component of this function. Likewise, redox potential (in parallel with free energy and acid-base balance) is foundational to circadian clock transcriptional regulation (see Chapter 4). This regulation includes circadian metabolism and physiology cycles such as feeding/ fasting, somnolence/wakefulness, and states of rest/activity. Disturbances of redox potential desynchronize chronophysiology, not only of the human host, but also of the intestinal microbiota. This occurs with respect to the feeding, metabolic, and physiological cycles that modulate the composition of intestinal microbes and the health of the host. Inadequate quantity or diversity of nutrition can directly impair microbial diversity and propagate pathogenicity. By comparison, invigorating stress (either psychogenic or physical) promotes a favorable influence on the intestinal microbiota, whereas toxic stress exerts a punitive effect. The inflammatory response, provoked by unfavorable alterations of the microbiota, further disturbs the redox balance and elicits the central stress response toward a self-exacerbating web of pathophysiology (see Chapter 2). This complex web of events and responses is orchestrated within the context of circadian rhythms at all levels of biology. Maintaining and establishing beneficial connections between microbiota and host is vital to their mutual health. Although the gastrointestinal microbiota has previously been studied from the perspective of inflammatory diseases, more recently it has become clear that the gut microbiota plays a central role in maintaining host health. By virtue of co-evolving throughout the entirety of human existence (125), the microbiota have critically influenced the adaptive tools that are required for human survival. The gut microbial population and its collective metabolic activity has been suggested by some to be the bioequivalent of an organ (126). The potential (biochemical) energy of the microbiota is immense and requires strict regulation. Figure 6.12. illustrates one example of how dysregulation can lead to the development of chronic disease. In this example, a breach of intestinal barrier integrity and subclinical endotoxemia represent primary order parameters that result from the extrinsic control parameter of intestinal dysbiosis. These events occur upstream of secondary order parameters such as insulin resistance in hepatic and visceral adipose tissue, redox disturbances, mitochondrial dysfunction, inflammatory responses, and hyperinsulinemia. These secondary order parameters, in turn, promote such higher order manifestations as obesity, hypertension, hepatic steatosis, dyslipidemia, hypercholesterolemia, hyperglycemia and type 2 diabetes, and a proinflammatory state. These factors

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FIGURE 6.12  The interplay of control and order parameters in the development of cardiovascular disease. Extrinsic control parameters such as low quality/excessive diet and insufficient exercise can lead to secondary control parameters such as disturbances in the small intestinal microbiota composition and diversity. The altered microbiota may then be responsible for the ultimate translocation of endotoxin into the portal circulation, which carries it to visceral adipose tissue and the liver. This manifests physiologically as secondary order parameters like increased inflammatory responses, redox disturbances, mitochondrial dysfunction in hepatic and visceral adipose tissue, and hyperinsulinemia. These parameters, in turn, modulate higher order properties, including obesity, hypertension, hepatic steatosis, dyslipidemia, hypercholesterolemia, hyperglycemia and type 2 diabetes, and a generalized pro-inflammatory state.

collectively generate susceptibility states for the development of cardiovascular disease. In reality, these different level order parameters interact with one another in feedforward selfamplifying loops to potentiate the evolution of chronic disease. While subclinical endotoxicosis was chosen to exemplify a primary order parameter in the context of this discussion, a more traditional perspective (e.g. Chapter 7) would consider the pathophysiology of insulin resistance, obesity, adipocyte hypertrophy, and ectopic fat deposits in non-subcutaneous adipose tissues. One’s view of control and order parameters as susceptibility states is likely to vary according to perspective. Obesity, for example, may be viewed as a primary order parameter in a traditional sense, with insulin resistance occurring in classical insulin-targeted metabolic tissues as a secondary order parameter. Alternatively, obesity as a component of metabolic syndrome may be viewed as a higher order parameter, downstream of insulin resistance, with subclinical endotoxemia as a primary order parameter. In this case, systemic

Metabolism and Medicine hyperinsulinemia accompanies insulin resistance, with a consequence of hyperinsulinemia in the hypothalamus being downregulation of insulin receptors, impaired insulin signaling and, thus, an increased threshold for satiety resulting in weight gain and obesity. It should be additionally appreciated that there is enormous complexity when considering integrated total body systems biology. The parameters of one model frequently interact with those of another, so that the sequence of parameters at the organism level is far from “clear cut”. Moreover, a hallmark of pathogenicity is instability generated by positive feedforward loops that might be detached from the stabilizing governance of negative feedback (e.g. insulin resistance propagating obesity, and vice versa). Nonetheless, it is encouraging to recognize that targeting the susceptibility states and secondary control parameters (e.g. intestinal dysbiosis) would actually prevent or even reverse the associated disease state. For example, bariatric surgery is sometimes capable of reversing the downstream order parameter type 2 diabetes. Interestingly, this improvement in—and sometimes reversal of—glycemic criteria for diabetes occurs prior to the onset of weight loss. Thus, obesity per se is insufficient to account for the total variance of the type 2 diabetes phenotype in cases that demonstrate improvement. One possible explanation for this residual variance may be related to the differences in gut microbiota that arise in the setting of bariatric surgery (127). These microbial alterations post-bariatric surgery have been noted to induce enteroendocrine L cells (most prominently located in the intestinal ileum) to release incretin hormones as microbiota interact with bile acids. Incretin hormone signaling systemically improves energy homeostasis, insulin sensitivity, pancreatic beta cell function, and possibly beta cell neogenesis. In addition to the beneficial independent effects of bariatric surgery on metabolic homeostasis and diabetes, the surgery also promotes a uniquely durable effect on obesity. Bariatric surgeries other than gastric banding remove the gastric fundus, which is the source of ghrelin, the only known orexigenic (i.e. appetite-stimulating) hormone. This contributes to the more enduring stability to bariatric surgical weight loss compared to lifestyle changes. Lifestyle changes alone (i.e. without surgery) are characteristically transient, with weight typically regained within two years of the initial lifestyle modifications. Weight loss due to lifestyle modification (but not surgical treatment) appears to amplify stress response systems, such as the HPA axis, with chronically elevated fasting morning cortisol levels contributing to the non-sustained weight loss (128). Chronically elevated cortisol levels suppress neurogenesis, while promoting hippocampal atrophy and reduced cognition (129). The cost to the body of long-term adaptation of stress exemplifies the concept of allostatic overload (130, 131). Accordingly, the allostatic overload associated with chronically elevated cortisol levels leads to the increased likelihood of mood, depression, and anxiety disorders (132). Thus, the high recidivism of obesity following lifestyle-mediated weight loss seems, at least in part, to be undermined by so-called “stress eating”. The inability to adhere to dietary control in these cases appears to occur to some extent independent of energy balance, hunger, or satiety. Rather, it is born from an emotionally unrequited desire for food that seems crucially

Microbiota and Human Metabolism linked to the stress response. This behavior is concomitant with an upregulated appetitive neural circuitry of the reward motivation component of the limbic system (encompassing the hippocampus and amygdala). Accordingly, memories attached to emotions drive the repetitive behavior for eating. In addition, the chronic stress response, mediated largely by hypercortisolemia, is associated with impaired executive function of the prefrontal cortex, which is designed to mediate emotions (133). This illustrates how the neural circuitry associated with stress-induced obesity serves as an “emotional nervous system”. Other mechanisms by which the chronic stress response contributes to weight gain are cortisol-induced adipogenesis and correlated lipogenesis that fills the adipocytes, as well as impaired satiety and increased hunger due to the counterregulatory effects of insulin resistance. It is likely that, at least in some cases, postsurgical recidivism of obesity is due to exaggerated stress response systems, especially corresponding to the HPA axis. Furthermore, it may be that successful postsurgical transition from the diabetic to the nondiabetic state and long-term weight loss are mirrored by (and perhaps mediated by) favorable alterations in the microbiota. An abnormal stress response rooted in the microbiota composition may impair a successful long-term phase transition that restores the healthy body weight set point. In this regard, it is unclear if the HPA system is an upstream order parameter relative to the microbiota. Although it may seem intuitively likely to be the other way around, particularly since dysbiosis itself activates the stress response, the HPA system may alter the microbiota composition, both directly as well as indirectly, via a disturbed diet. In a feedforward fashion, the abnormal microbiota, subsequently mediated by inflammatory cytokines, amplifies the stress response in a pernicious circuit. This observation has provided a powerful impetus for the study of microbiota and its relationships to bile acid metabolism and the intestinal endocrine system for understanding the high volume of data that one day can be translated from a bottom-up to a top-down strategy. In this scenario, control parameters would be interventional and non-empirically applied to an order parameter, or set of order parameters, safely and effectively.

6.3.4 Extrinsic Control Parameters and Targeted Interventions 6.3.4.1 Stress and The Microbiota Emotional stress can disrupt digestive functions. Microbiota composition changes in response to stressful situations and also modulates the stress response. Acute stress is critical for the body’s ability to react to threats and for competitive motivation; however, chronic stress is associated with various neuropsychiatric disease states such as anxiety and depression. Acute stress can cause bowel dysfunctions such as nausea, vomiting, abdominal pain, and alterations in bowel habits. Chronic stress is associated with gastrointestinal (GI) disease states such as irritable bowel syndrome (IBS), which can be exacerbated by, and cause reciprocal exacerbation of, neuropsychiatric states. In fact, depression has been associated with its own unique microbiota profile from onset to disease progression.

247 It is important to appreciate the intricate crosstalk between stress and microbial systems. Stress has direct effects on the GI tract including alterations in intestinal motility, mucosal transport, and gut barrier function. Those who experience chronic daily-life stressors are predisposed to GI diseases, such as the onset or exacerbation of IBS symptoms. Microbial responses in the gut that are induced by stress are primarily mediated by neuroimmune interactions (134). Bidirectional communication between the gut and brain has been extensively documented, giving rise to the aptly named gut-brain axis (GBA). The vagus nerve, endocrine system, and immune system have all been implicated in this network. Healthy GBA communications ensure proper maintenance and coordination of GI functions to support physiological processes while also facilitating the gut’s ability to affect mood, motivated behavior, and higher cognitive functions. Stress is also among the many factors that crucially influence microbial colonization following delivery. Maternal stress and altered microbiota are both linked to premature births and poor neurodevelopment. Early-life stress increases cortisol levels, increases the neuroimmune response, decreases noradrenaline levels in the brain, dysregulates brain-derived neurotrophic factor (BDNF, crucial for promoting neurogenesis) and enhances colonic secretory responses to norepinephrine. As a result, early-life stress reduces the composition and diversity of gut microbiota (135). Social stress, physical stress, and psychological stressors have similar negative impacts on the microbiota. Germ-free animals reared in sterile environments have exaggerated HPA-induced stress responses that can be reversed in early life with recolonization. The GI microbiota has recently emerged as a powerful facilitator of stress adaptation. Stress is linked to gut dysbiosis, suggesting that the microbiota mediate chronic stress responses. Microbial products intersect with host metabolism to yield important neurotransmitters and neuromodulators that can amplify or suppress the stress response. The body’s primary stress response system, the HPA axis, mediated by corticotropin-releasing factor (CRF), influences the microbiota through glucocorticoid and cortisol release. In fact, stress-induced CRF release can lead to bowel dysfunction by acting directly on the bowel itself and or indirectly via the CNS. Glucocorticoids can, in turn, induce non-neuronal catecholamine enzymes, which may amplify stress-signaling mechanisms that mimic chronic stress exposure. Prolonged stress exposure reduces SCFAs, which are critical in maintenance of gut and immune homeostasis. Chronic stress induces alterations in various neurotransmitter systems and affects the immune response, particularly cytokine expression, which can impair cognitive functions, such as memory, perception, and attention. Via the GBA, the gut microbiota has the ability to modulate neurotransmitters directly or through host biosynthesis pathways involving Toll-like receptors and heat-shock proteins. The first evidence that bacteria could direct, sense, and respond to neuroendocrine hormones dates back to 1929, but our understanding of the GBA is still in its infancy. Leveraging animal models and some preliminary human studies, bacteria have been shown to produce and/or catabolize neurotransmitters such as dopamine, norepinephrine, serotonin, l-glutamate,

248 and GABA. Other neurotransmitters that the microbiota has the potential to influence include acetylcholine, histamine, neuropeptides, steroids, and endocannabinoids. Dopamine (involved in reward-motivated behavior) and its precursor norepinephrine (involved in attention, memory, and cognition) increase the growth rate of pathologic bacteria, including Escherichia coli. In addition to growth rate, norepinephrine also increases the motility, biofilm formation, and virulence of bacteria, including Staphylococcus aureus. Further, several strains of bacteria have been shown to not only produce dopamine and norepinephrine, but also play a role in host biosynthesis/catabolism by reducing production of these catecholamines in the gut and brain. The general ability of the microbiota to influence catecholamine systems may be functionally important for modulating attention and rewardrelated behaviors, which are altered by stress. The microbiota also regulates serotonin synthesis in the gut, leading to the production of approximately 95% of the body’s serotonin. In the gut, serotonin is responsible for GI secretion, motility, and pain perception. In the brain, it modulates mood and cognition. A dysfunctional serotonergic system has been implicated in numerous GI and mood disorders. Indeed, selective serotonin reuptake inhibitors (SSRIs) are a mainstay of treatment for major depression, but are also effective in treating IBS and other GI disorders. Serotonin synthesis is dependent on the availability of tryptophan, an essential amino acid that must be supplied by the diet. Reduced tryptophan concentrations in plasma have been associated with clinical depression. Alteration of host serotonin levels appears to be mediated by secretion of small molecules (like SCFAs) that signal serotonin production via tryptophan expression. The gut microbiota can increase tryptophan metabolism and also decrease the amount available for serotonin synthesis, playing a crucial role in impacting serotonin concentrations. GABA is the primary inhibitory neurotransmitter in the CNS and has been linked to behavioral disorders, pain, sleep, and a multitude of GI functions (e.g. intestinal motility, gastric emptying, nociception, and acid secretion). GABA consumption occurs mainly through its conversion to succinate for entrance into the Krebs cycle, but bacteria have been noted to both produce and consume GABA. Both prokaryotes and eukaryotes synthesize GABA through the decarboxylation of glutamate (the primary excitatory neurotransmitter in the CNS), which is produced by several bacterial strains. The intestinal microbiota reduces circulating levels of GABA in the serum and gut, but not the brain. Lactobacillus rhamnosus JB-1, in particular, modulates cerebral GABAergic activity and reduces depressive- and anxiety-like behavior through the vagus nerve. Bacteria-mediated production of GABA has been noted to reduce visceral pain sensitivity in preclinical models. Diet-based intervention is likely to be one of the key means for mediating the relationship between stress and the microbiota. The gut microbiome composition is malleable and quick to respond to dietary changes. High-fat diets (particularly those rich in saturated-trans fats) reduce SCFA production, alter GI microbiota metabolism, increase gut inflammation, play a key role in the development of metabolic diseases, and increase risk for anxiety-like behaviors mediated by the gut microbiota. Since the HPA axis establishes crucial communication

Metabolism and Medicine between the gut and brain, HPA dysfunction may lead to GI dysfunction. Dietary interventions, such as a high-fiber diet, stimulate fiber fermentation and increase levels of SCFA producers, resulting in an overall increase in microbial byproducts, some of which have been shown to benefit cognitive performance (136). The ketogenic diet is characterized by high-fat intake (saturated and mono-polyunsaturated fats), adequate protein, and low-carbohydrate intake that together aim to restrict glycolysis and increase fatty acid oxidation to ketone bodies to produce a state of ketosis. As a result, glucose is replaced by ketone bodies as the primary energy source for the brain. This diet has neuroprotective effects, which may be mediated by ketone bodies (such as β-hydroxybutyrate) that inhibit the degradation of GABA, increasing its availability in the brain. The ketogenic diet also protects against oxidative stress and normalizes neuronal bioenergetics by stimulating mitochondrial biogenesis and stabilizing synaptic function (137). The ketogenic diet has proven to be a powerful tool for individuals with central diseases, such as Alzheimer’s, autism spectrum disorder, and glucose transporter 1 deficiency syndrome. It has also been noted to increase GABA levels in the cerebrospinal fluid of children with refractory epilepsy, which has been linked to symptomatic improvement. The gut microbiota may be responsible for modulating the selective metabolism of ketogenic amino acids and increasing brain GABA levels, both of which contribute to the beneficial effects of the ketogenic diet (138). Similar to the ketogenic diet, time-restricted diets (characterized by periods of fasting) and calorie-restricted diets (consisting of a 10–40% reduction in daily calorie intake without causing malnutrition) constitute other strategies for producing ketonemia (primarily acetoacetate and β-hydroxybutyrate). Establishing an eating pattern in which food intake is restricted to a chosen time window or setting can restore circadian rhythms that affect bacterial communities and lower the risk of disease. Calorie restriction has the ability to adjust the gut microbiota of obese patients to more closely resemble those of lean patients after long-term intervention. Calorie restriction impacts the gut microbiota by decreasing the rate of lipid biosynthesis and increasing the rate of fatty acid catabolism. It also increases the growth of some butyrate-producing microbial strains, which may have beneficial anti-inflammatory properties that decrease gut permeability. One key question in the field is whether treatments targeting the microbiota may have therapeutic benefits in stressrelated disorders. A better understanding of the mechanisms underlying stress modulation through the microbiota is needed, particularly regarding the gut-brain axis. As more is learned, prospects for restoring the microbiota through the use of dietary interventions (e.g. prebiotics and probiotics) and their effects on the stress response are likely to prove valuable. Prebiotic fermentation by the gut microbiota can produce SCFAs, providing an energy source and positively modulating microbiota composition. Probiotics can more directly restore and improve gut microbiota. Fecal transplantation might also be a useful tool to treat different effects of chronic stress, preventing the elevation of stress-induced cytokines. Stress can finally modulate the microbiota via the immunological route, particularly through proinflammatory cytokines.

Microbiota and Human Metabolism Stress and bacterial antigens can both elicit and increase an immune response, inducing cytokine release in the blood stream that influence regulatory brain areas, such as the hypothalamus. The intersection between stress, microbiota, and the immune system is covered further in Section 6.2.3.

6.3.4.2 Circadian Rhythms: Biological Blueprints for Host and Microbiota Activity Over the course of a day, the human gut microbiome fluctuates in terms of total abundance and the relative composition of different bacterial species. These oscillations have been estimated to regulate 20% of all metabolic functions performed by the microbiota (139). Metabolic pathways involved in energy metabolism and protein production dominate during the diurnal phase (daytime), whereas detoxification is favored during the nocturnal phase (nighttime). Similar circadian patterns of microbial composition have been observed in rodents, facilitating the study of the basic mechanisms involved in this process (139–141). The gut microbiota can be parsed into two distinct subgroups based on localization. Epithelial-associated communities line the superficial lining of the gut, while luminal communities remain in transit throughout the gut and only transiently interact with the epithelium. Based on their close proximity with host tissues, epithelial-associated bacteria are thought to have a greater impact on host biochemistry. Mouse studies have revealed that there is a ten-fold variation in the number of bacteria lining the gut wall over the course of a day (140). Human fecal matter, composed primarily of luminal bacteria, also demonstrates circadian oscillations in approximately 10% of bacterial species (139). These daily variations in the microbiota are hypothesized to be important for the metabolic health of the host. For example, jet lag in mice has been associated with a loss of rhythmic microbiota oscillations and a subsequent increase in fat accumulation (139). There is evidence that jet lag-induced changes in the human microbiome can also influence fat deposition, with fecal transplantation from jet lagged humans accelerating weight gain in mice consuming a high-fat diet (139). The changes in human microbiota induced by jet lag are characterized by a transient increase in Firmicutes bacteria that resolves within two weeks following a flight. Though a dysregulated microbiota can influence fat gain, specific details regarding how the dynamics of bacterial oscillations either support health or drive disease are not yet clear. Studies in mice are now beginning to reveal the external and internal inputs that drive daily rhythms in bacteria. Transgenic mouse models have revealed that the circadian clock system is essential for daily rhythms of gut bacteria (139). This appears to be related to a disruption of the typical feeding patterns that are coordinated by circadian networks. If feed-fasting rhythms are re-established experimentally, then bacterial oscillations can be restored (140). Even wildtype mice demonstrate abnormal bacterial oscillations with manipulation of feeding times, demonstrating that the primary driver of this phenomenon is related to consumption (139). The key signaling pathways important for regulation of microbiota oscillations in response to feed-fasting are

249 unknown; however, altered bacterial composition upon feeding may occur in part due to activities of the transcription factor neuronal PAS domain protein 2 (NPAS2) in the liver (142). Other central clock-influenced outputs, such as control of melatonin secretion from the pineal gland (143), may also play a role in affecting bacterial function in the gut. Certain bacterial species isolated from the human gut show 24-hour rhythms in response to melatonin (144). In addition, glucocorticoid signaling, driven by the central clock in the suprachiasmatic nucleus together with the adrenal gland, may regulate composition of the microbiota (145). Of note, glucocorticoid signaling and feed-fasting rhythms are both controlled in part by behavioral choices in humans, leading to the hypothesis that conscious control of certain behaviors/activities may regulate bacterial oscillations in the human gut. In addition, mouse studies have also pointed toward a direct effect of light exposure on oscillation of the gut microbiome (145), indicating that properly controlled light cycles may be important for optimization of daily microbiota functions. Lastly, the immune cells present in the human gut are also highly likely to regulate daily microbiota function. Innate lymphoid cells (ILCs) regulate the response to pathogens and play a critical role in gut homeostasis (146). The local circadian clock present in innate lymphoid cells of mice have been shown to regulate microbiota composition (141). The circadian clock protein brain and muscle ARNT-like 1 (BMAL1) endows local lymphoid cells with the ability to influence daily oscillation of bacteria. In part, this may take place through regulation of the number of ILCs (141). The role of oscillations of the microbiome on pathogenesis is still poorly defined, but it is clear that the microbiota responds to circadian cues along with their hosts (Figure 6.13). Maintaining a healthy feeding-fasting cycle with a minimum of 12 hours fasting daily has been shown to be safe for healthy persons and those with type 2 diabetes (147). These conditions likely support the rhythmic oscillations of the human

FIGURE 6.13  Regulation of gut microbiome composition and dynamics by external and internal inputs. Oscillations of the gut microbiome, represented by a sinusoidal wave, are affected by externally derived inputs such as light, feeding, and stress. The local circadian clocks in innate lymphoid cells (ILCs) play a key role in driving oscillations of the microbiome.

250 microbiome (139). The clinically relevant effects of such timerestricted feeding are likely to be driven, at least in part, by the microbiota. Adhering to these defined feeding rhythms, while avoiding a high-fat diet, is likely to be one the strongest predictors of a healthy microbiota. The influence of the gut microbiota is far reaching, with studies of circadian function demonstrating a significant influence on the liver parenchyma (140). Investigations of hepatic metabolism in mice suggest that even the pharmacokinetics of acetaminophen oscillate in a circadian manner(148). In this context, acetaminophen-induced liver toxicity was noted to be worse in the early active phase versus the early rest phase (140, 148). The microbiota has been implicated as a key determinant in this process. Further, eradication of the bacterial microbiota using antibiotics appears to prevent acetaminophen toxicity (140, 149). In another investigation, the necrosis observed upon acetaminophen toxicity is worsened by the bacterial metabolite 1-phenyl-1,2-propanedione (PPD) (149). While the field of chronopharmacology has established that the timing of drug dosing can drastically influence the efficacy of various compounds in humans, the role of the microbiota in regulating drug action in this regard remains to be determined(150). Early studies in antibiotic-treated or germ-free mice also suggest that the microbiota is required for circadian clock gene expression in the gut, liver, and brain (151–153). However, more recent reports have contradicted these early findings, demonstrating that the microbiota does not affect circadian clock gene expression dramatically (140, 154, 155). This may suggest that the interactions of gut microbiota with circadian rhythms is context specific. Indeed, some of the metabolites produced by the microbiota, such as SCFAs, have shown potential to affect circadian clock function in the liver (154). In addition, 10–40% of the daily rhythmic gene expression of the gut, liver, and white adipose tissue is reportedly dependent on the microbiota (140, 155). The microbiota is suggested to achieve these effects through activation of transcription factors in target tissues (156, 157). Therefore, these microbiota-host interactions may represent promising targets for future drug development. For example, the microbiota signals to the gut epithelium through the circadian transcription factor nuclear factor interleukin 3 (NFIL3) (157). This interaction is important for the control of lipid metabolism in the gut and, if perturbed, alters the composition of the body. The role of the gut microbiota in driving circadian metabolic function in the brain remains under-substantiated; however, one of the main gene classes that demonstrates abnormal oscillation in the liver upon antibiotic treatment of mice is central to the development of Parkinson’s Disease (140). In support of this, oscillation of metabolites in the blood are abolished in germ-free mice, suggesting that the microbiota has a widespread influence on circadian function in the host (140). Concentrations of several sex-specific hormones have been reported to be dependent on microbiota as well (155). Indeed, germ-free male mice exhibit feminization with regard to their sex-specific circadian gene expression, while germfree females are masculinized (155). Factors present in the serum are thought to underlie this change (155).

Metabolism and Medicine

6.3.4.3 Diet: Where It All Begins 6.3.4.3.1 Dietary Intake Sets the Stage for the Microbes That Will Flourish Changes in dietary intake can have a profound impact on the gut microbial composition owing to the metabolic capabilities of various microbial communities. When Ley et al. placed people on fat-restricted or carbohydrate-restricted diets, their levels of Bacteroides rose as their weight decreased (7). This demonstrated that diet impacts early signatures of obeseassociate and lean-associated microbial communities. Ley et  al. did an analysis with 60 mammalian species, including humans, and in each case the microbial community structures shifted with respect to changes in diet (158). Turnbaugh et al. also noted marked changes in the microbiota of humans that paralleled changes in diet (159). In particular, they observed that a high-fat/high-carbohydrate diet, designed to mimic the diet most commonly consumed in Western cultures, leads to significant shifts in the two major phyla of the distal gut microbiota of mice. Specifically, they observed a reduction in the prevalence of Bacteroidetes with an increase of Firmicutes. These shifts were evidenced rather promptly, with changes noted in mice within a single day and in humans within one to two days (159–161). In mice, it was found that diet can contribute to greater than half (57%) of the structure of the gut microbial population (124). This impact on the microbiota is nearly five times greater than the observed 12% contribution attributable to genetic variations of the host. Dietary changes, such as adding 30 grams of dietary fiber per day or switching to or from a high-fiber/low-fat diet to or from a low-fiber/high-fat diet, have been shown to readily modulate the composition and function of the human gut microbiota. A dietary intervention, in which people eating a low-fiber/high-fat diet were switched to eating a high-fiber/low-fat diet, led to increases in the microbial diversity and gene content of the microbiota of those individuals who started with a low microbiota diversity and gene content (161). The association of enhanced richness of the gut microbiota diversity with improved metabolic health is strongly supported in the literature. One’s diet has a profound impact on the characteristics of one’s microbiota. Significant changes in diet can be observed to produce significant variations in gut bacterial composition within one to two days.

It came as a breakthrough in 2004 when Bäckhed et al. demonstrated that germ-free mice are actually protected, relative to conventional mice, against the obesity that arises from consumption of a high-fat/high-carbohydrate diet (162). When the germ-free mice were transplanted with gut microbiota samples from the conventionally raised mice, they developed increases in adiposity. This phenomenon was shown to be driven by a microbial suppression of expression of fasting-induced adipose factor (FIAF, also known as angiopoietin-like 4, ANGPTL4), a circulating lipoprotein lipase inhibitor. Suppression of FIAF, in turn, suppresses expression of the peroxisomal proliferatoractivated receptor coactivator (PGC)-1α along with enzymes

251

Microbiota and Human Metabolism involved in fatty acid oxidation, promoting the observed increases in adiposity (163). In alignment with the study of Bäckhed et  al., Turnbaugh et  al. observed weight gain when genetically wild-type lean germ-free mice were transplanted with gut microbiota from obese mice (6, 8). (The diet provided to these mice was not described). Comparably, fecal transplants from severely stunted or underweight children to germfree mice who subsequently lost weight further established a causal relationship between the gut microbiota and the nourishment phenotype (164). In a corroborating study involving transferring gut microbiota from human twins to mice, controlling for human host genetics, obesity was observed in association not only with phylum-level differences in the bacteria present, but also reduced microbial diversity and differences in the metabolic pathways being used (9, 159). This led Turnbaugh et  al. to conclude that there is an identifiable “core microbiome” of shared microbial genes observed at the functional level (159). While the co-variation seen was comparable for monozygotic vs. dizygotic twins, there were marked variations comparing lean versus obese twins, representing significant physiological deviations between such twins. In another twist, Fei and Zhao reported that lean germfree wild-type mice transplanted with the lipopolysaccharide endotoxin-producing bacterial pathogen, Enterobacter cloacae B29, from the microbiota of an obese human with metabolic syndrome went on to develop obesity as well as metabolic syndrome (165). This study revealed that both a high-fat diet and the presence of the endotoxin-producing B29 pathogen were necessary and sufficient to induce these unhealthy phenotypes. The powerful impacts of the gut microbiota on obesity were shown to be linked to roles in which they influenced the harvesting, use, and storage of energy obtained from the diet. Thus, obese mice were better able to harvest energy from foods than their lean counterparts (6, 8, 159). This energy-harvesting efficiency, particularly of otherwise indigestible food, as well as marked changes in the microbiota itself, can explain the observed increases in weight. Similarly, obese humans also appear to experience an enhanced ability to harvest energy from foodstuffs along with increased lipogenesis compared to their lean counterparts (8). The personalized response to dietary composition (PREDICT 1) study examined postprandial triglyceride, glucose, and insulin levels following standardized meals in twin and non-relative healthy adults. The aim of this study was to use such measurements to predict responses to dietary composition in a personalized and precisely individualized way in strategic effort to prevent chronic disease. Components analyzed included 1) baseline characteristics such as age, sex, and circulating lipids and glucose, 2) genetic factors examining single nucleotide polymorphisms (SNPs) using genome-wide association studies (GWAS), 3) gut microbiota composition by using 16S rRNA high-throughput sequencing from the stool, 4) meal composition, 5) habitual diet, and 6) circadian behavior and physical activity. On day one all metabolic parameters were measured for each participant to establish individual baselines.

Subsequently, from days 2–14 all the postprandial metabolic parameters including blood glucose, lipids, and insulin were measured. Results indicated that there is a large amount of inter-individual variability in circulating triglyceride and glucose levels after feeding. It was observed that among these factors, gut microbiota composition had the most influence in creating inter-individual variability in postprandial plasma lipid and blood glucose levels. This suggests that microbiota may play a key role in regulating whole-body glucose and lipid homeostasis. On this basis, the researchers developed a machine-learning model in an attempt to establish the relationship between circulating triglycerides/ glucose and food intake. Overall, this study suggests that lifestyle metabolic diseases could be managed by developing a personalized diet by utilizing this model.

Despite the rapid dynamics linking diet to microbiota composition, long-term dietary habits dominate in determining a number of critical health impacts as a function of the gut microbiota (166). A key example is seen with L-carnitine, an amino acid derivative in red meat and other foods commonly consumed in a Western diet (Table 6.1). Carnitine normally facilitates the transport of palmitate fatty acids into cell mitochondria for fatty acid oxidation (167). Healthy adults and children do not require dietary carnitine intake, as sufficient levels can be synthesized de novo from the amino acids lysine and methionine. High concentrations of carnitine can be pathological in humans, as gut microbes metabolize it to trimethylamine (TMA) (168) (Figure 6.14). The TMA produced in the intestines by the microbiota is absorbed by the gut into the blood stream and taken to the liver where it is enzymatically cleaved by flavin monooxygenases (FMOs) to trimethylamine N-oxide (TMAO), a uremic toxin. Notably, some gut bacteria have been shown to impact the conversion and retroversion of TMA and TMAO, including the families Peptostreptococcaceae and Clostridiaceae (phylum Firmicutes) and members of the Enterobacteriaceae family (169). Carnitine has been shown to promote atherosclerosis in mice due to reductions of reverse cholesterol transport and bile acid TABLE 6.1 Carnitine and Choline Concentrations in Some Commonly Eaten Foods Food Beef steak, cooked, 4 ounces Ground beef, cooked, 4 ounces Codfish, cooked, 4 ounces Chicken breast, cooked, 4 ounces Milk, whole or 1%, 1 cup Cheese, cheddar, 2 ounces Egg, 1 large

Milligrams carnitine

Milligrams choline (% daily value)

56–162 87–99 4–7 3–5 8 2

129 (28%) 96 (17%) 125 (17%) 96 (17%) 43 (11%) 147 (27%)

Source: from National Institutes of Health, Strengthening Knowledge and Understanding of Dietary Supplements.

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FIGURE 6.14  The impact of dietary carnitine and choline on metabolic disease. Dietary carnitine and choline are converted into trimethylamine (TMA) by some of the bacteria of the intestinal microbiota. The liver flavin monooxygenases (FMOs) convert TMA to trimethylamine N-oxide (TMAO), which is a risk factor for numerous diseases.

synthesis (168). Among the 2,595 human participants that underwent elective cardiac evaluation in this study, there was a dosedependent relationship between TMAO levels, plasma carnitine concentrations, and overall risk for cardiovascular diseases (including coronary and peripheral artery diseases). Indeed, TMAO has been linked to a number of chronic disease states, including metabolic disorder, insulin resistance, obesity, type 2 diabetes, renal diseases, neuropsychiatric disorders (e.g. seizures, depression), and cancers (e.g. hepatocellular, colorectal, oral, and prostate) (170). These findings are difficult to interpret, however, in the context of studies involving another intermediary for microbiota-dependent TMA production known as betaine. Unlike carnitine and choline, betaine has not been associated with the aforementioned disease states. In fact, it appears to be protective with regard to obesity, diabetes, cancer, and Alzheimer’s disease (summarized in [62, 171]). These findings seem difficult to reconcile, but certainly warrant further investigation. Regardless, the flavin-containing monooxygenases (FMOs) that metabolize carnitine, phosphatidylcholine, and their derivatives should be considered in future research paradigms. As intrinsic control parameters, FMOs represent a promising target for pharmaceutical development. One possible confounder for investigations of TMA precursors is that not all gut microbes are proficient TMA producers. Foods rich in phosphatidylcholine (meat, cheese, seafood and eggs) and L-carnitine (primarily meat) may vary considerably in their health burden based on the TMA production efficiency of the host microbiota. Individuals with a low rate of TMA conversion would be relatively protected from the toxic influence of phosphatidylcholine and L-carnitine consumption. It is critical to appreciate that these effects are highly individualized, but generally depends on the complexity of the host’s microbial ecology. Indeed, dietary diversity is known to portend gut microbial diversity, which enhances the resilience of the gut microbiome to compositional changes induced by fluctuations in diet. A healthy gut microbial ecosystem with a rich genomic diversity benefits from stability in the face of transient dietary indiscretions. In contrast, an unhealthy microbial ecosystem with limited diversity, characterized by dysbiosis, is likely to be more responsive to even short-term dietary improvements, with greater potential to become a more diverse ecosystem.

6.3.4.3.2 Short-Chain Fatty Acids Unlike human digestive enzymes, microbial digestive enzymes can degrade dietary fiber to short-chain fatty acids (SCFAs) and monosaccharides, providing the host with 9 kilocalories or 4 kilocalories per gram, respectively. As will be described in this section, the SCFAs serve as important energy sources for supporting the gut microbiota and host intestinal epithelial cells. Their roles are myriad, supporting the health and functioning of the intestinal epithelium, promoting mucus production, providing anti-inflammatory benefits, protecting against dietary-induced obesity, supporting mitochondrial function, increasing fatty acid oxidation, inhibiting fat accumulation, and modulating neurotransmission. The most common SCFAs derived from bacterial fermentation of dietary fiber and resistant starches are the two-carbon acetate, three-carbon butyrate, and four-carbon propionate, each with different effects on metabolism. Butyrate is particularly important in providing energy for colonic epithelial cells and maintaining the integrity of the gut epithelial barrier, preventing metabolic endotoxemia (172, 173). In contrast, acetate and propionate enter the portal circulation and are carried to the liver. Propionate appears to promote hepatic glycogenesis and gluconeogenesis, whereas acetate serves as a substrate for cholesterol synthesis (172, 173). Furthermore, acetate is the most abundant and inherently obesogenic of the microbial fatty acid metabolites. Not only does it serve as a building block substrate for the synthesis of cholesterol in the liver, but also for long-chain fatty acids and lipids stored in the liver and adipose tissue. Moreover, the presence of excess hepatic fat (i.e. steatosis) and visceral adiposity are sine qua non features of insulin resistance. The overload of triglycerides in the liver, coupled to the influx of fatty acids from unsuppressed visceral adipose tissue lipolysis, drives the characteristic atherogenic dyslipidemia of insulin resistance. SCFAs may also beneficially impact body weight by influencing energy expenditure. In one study, obese mice given oral administration of butyrate demonstrated a reduction of body weight, which may be related to an increase in energy expenditure and lipid oxidation (128). This effect was associated with an upregulation of genes involved in thermogenesis such as peroxisome proliferator-activated receptor-gamma co-activator (PPARGC) 1A (encoding PGC1α) and uncoupling protein 1 (UCP1) in brown adipose tissue. Furthermore, intragastric

Microbiota and Human Metabolism and oral SCFA administration in mice with a high-fat diet decreased total body fat content and hepatic fat accumulation (31, 174). This finding is concomitant with augmented expression of the thermogenesis-related proteins acetyl-CoA oxidase, carnitine palmitoyltransferase I, and UCP2 in the liver and adipose tissue (31, 174). These animal studies provide important evidence for SCFA-induced upregulation of genes related to thermogenesis and lipid oxidation, resulting in the impediment of weight gain and adiposity. However, the significance and role of uncoupling processes and/or adipose tissue browning to energy homeostasis and control of body weight in humans remains elusive. In vivo data in humans show that acute infusions of acetate or SCFA mixtures of acetate, propionate, and butyrate in the distal colon increased fasting lipid oxidation and resting energy expenditure in overweight or obese volunteers (175, 176). Interestingly, a recent in vivo study in healthy men showed that acute oral propionate administration elevated resting energy expenditure and fasting lipid oxidation independent of insulin and glucose levels and sympathetic nervous system activity (32). Additional human intervention studies are necessary to explore whether these SCFA-induced improvements in oxidative metabolism translate into long-term benefits in weight control (118). These SCFAs also affect lipid oxidation capacity in skeletal muscle and improve adipose tissue metabolism by decreasing lipid overflow and intramuscular lipid accumulation and attenuating supply of pro-inflammatory cytokines to the skeletal muscle, thus preventing the development of insulin resistance. Beneficial metabolic effects of butyrate have been seen with a number of transcriptional regulation mechanisms. One such impact involves inhibition of histone deacetylases (HDACs) via butyrate-response elements (177). HDAC inhibition modulates the expression of genes involved in cell proliferation, which is believed to reduce the development of colon cancer (177). Butyrate also contributes to the expression of the key transcriptional coactivator, peroxisome proliferator-activated receptor-gamma coactivator 1α (PGC1α), a regulator of cellular energy metabolism in skeletal muscle and brown muscle tissue, whereby it enhances mitochondrial biogenesis and function, including fatty acid oxidation (177). Butter is one the largest dietary sources of butyrate. The numerous benefits of butyrate summarized in this section accompany the unfortunate falsehood, even in the medical community, that butter is intrinsically “bad”. Ironically, many US hospitals have taken to replacing butter on patient meal trays with margarine that contains high levels of trans fat. This cultural rejection of butter highlights one of the challenges of changing long-held perceptions and practices, both for the individual consumer and the medical community. Changing the “modus operandi” of problem solving is an enormous task in research and clinical medicine. This book’s proposed framework invokes a physics-based model that uses control and order parameters to inform healthy practices and is intended to address the needed change.

Another proposed favorable metabolic effect of SCFAs, not limited to butyrate, is their enhancement of the secretion of

253 the enteroendocrine hormones, glucagon-like peptide-1 (GLP1) and peptide YY (PYY) (178–180). These hormones, along with the gut peptide ghrelin, regulate energy homeostasis by imparting a satiety effect in the brain involving the hypothalamus, brain stem, and other reward/motivation circuits (181, 182). In the case of PYY, this effect is imparted by inhibiting gut motility, allowing for maximal energy harvest from oral nutrition. Thus, it should not be surprising that studies in PYY knockout mice demonstrate increased intestinal transit rates, and thereby reduced dietary energy harvest (183). Soliman et al. reported that butyrate stimulated the release of leptin, a hunger-suppressing hormone, from human adipocytes, leading to inhibition of food intake and increasing energy expenditure, accounting for another hormone-mediated mechanism for SCFA appetite regulation and metabolic health (184). Lin et  al. reported that the SCFAs acetate, butyrate, and propionate protected mice on high-fat diets from obesity and insulin resistance by enhancing gut secretion of hormones GLP-1 and PYY (185). Similarly, Arora et al. showed that propionate may have the same effects in humans (186). Together, these data speak to a potential clinical role of prebiotic precursors of SCFAs as substrates for promoting metabolic health. In apparent contrast to their roles in increasing satiety, SCFAs have been seen to promote the transfer of energy to their hosts. When microbes colonize the guts of germ-free mice, they induce the expression of sodium-dependent glucose transporter 1 (SGLT1) in the small intestine, which increases glucose absorption and the density of capillaries beneath the villous epithelium, increasing nutrient absorption (187, 188). Thereafter, SCFAs are more avidly absorbed by colonocytes, further contributing to the transfer of energy to the host from otherwise non-digestible dietary fiber. However, SCFAs produced by bacterial fermentation function as more than energy substrates, and, on balance, appear to promote metabolic health and prevent weight gain by eliciting increased satiety and decreased dietary intake (32, 189–191). It has become clear that there are numerous factors that contribute to the obesogenicity of microbiota. Shen et  al. provide a review of the data supporting contributory mechanisms pertaining to the various stages involved, including food intake, energy harvest, energy expenditure, and fat storage (11). Elevated levels of SCFAs have been observed in obese mice, suggesting that increased absorption and energy harvest of SCFAs are likely to contribute to obesity (6). Additionally, it has been shown that the microbial flora of wild-type mice reduces expression of host fasting-induced adipocyte factor (FIAF), an inhibitor of lipoprotein lipase (LPL) in the intestinal epithelium and a promoter of triglyceride storage, thereby leading to increased susceptibility to diet-induced obesity (163). In contrast, germ-free mice display elevated levels of FIAF and intestinal LPL activity, providing protection against obesity (163). This underscores a relationship of gut microbiota with hepatic steatosis (accumulation of fat in the liver), an anatomical hallmark of insulin resistance and a precursor to type 2 diabetes and obesity. Microbial inhibition of FIAF expression as a fundamental etiology of insulin resistance is rooted in the interference of FIAF-derived induction of the transcriptional cofactor, proliferator activated receptor coactivator (PGC1α). In simple

254 terms, PGC1α is necessary for mitochondrial biogenesis in many tissues, including in the classical metabolic tissues (i.e. skeletal muscle, liver, adipose tissue). A hallmark of insulin resistance is impairment of the mitochondrial oxidative phosphorylation mode of energy production and overreliance on the much less efficient cytosolic pathway of glycolysis. The consequent reduction of lipid oxidation leads to the accumulation of fat in metabolic tissues and in skeletal muscle via accumulation of intramyocellular lipid droplets, thereby interfering with insulin signaling. This, in turn, leads to impaired glucose tolerance, the earliest glycemic perturbation. In adipose tissue, the excess fat stores and associated hypertrophy of the adipocytes are additional signature characteristics of insulin resistance. In the brain, most notably in the arcuate nucleus of the hypothalamus, insulin resistance results in impaired satiety with hyperphagia and correlates with the insulin resistance in skeletal muscle. Accordingly, excess dietary intake appears to be a compensatory mechanism for the intracellular energy deprivation present in skeletal muscle. However, inhibition of FIAF in adipocytes, reduced mitochondrial biogenesis, and insulin-stimulated increased LPL activity (relative to the degree of insulin resistance) all serve to drive the excess energy toward storing lipid in adipocytes. The teleological role of FIAF in starvation is to block the storage of energy fat depots, instead prioritizing energy for work-related processes elsewhere in the body, consistent with the induction of PGC1α and subsequent mitochondrial biogenesis that drives efficient production of adenosine triphosphate (ATP). Notably, PGC1α in the liver paradoxically promotes increased gluconeogenesis and hepatic glucose output, consistent with the role of FIAF in starvation. Chronic inhibition of FIAF leads to the loss of the energy power plants of cells and associated impaired bioenergetics. This is the upstream etiopathogenesis of insulin resistance. Mitochondrial dysfunction has been identified as a root cause of insulin resistance, while insulin resistance reciprocally promotes mitochondrial dysfunction in a pernicious feedforward cycle. Pyruvate dehydrogenase is notably stimulated by insulin, catalyzing the decarboxylation of pyruvate in mitochondria to promote oxidative energy production. Another important part of the discussion regarding PGC1α that parallels the activity of FIAF involves adenosine monophosphate (AMP)-activated protein kinase (AMPK). Under healthy conditions, AMPK is another up-regulator of PGC1α and, thus, an indirect promoter of mitochondrial biogenesis. AMPK acts as an energy sensor and a metabolic regulator of various bodily tissues, including the brain, liver, and skeletal muscle. This, in part, drives the production of energy required in skeletal muscle for doing exercise. It underlies the ability of metformin in the liver to improve mitochondrial biogenesis, fatty acid oxidation, and insulin sensitivity. AMPK is activated when the intracellular ratio of AMP:ATP or NAD:NADH is increased, corresponding to states of energy depletion as a result of metabolic stress (e.g. exercise or hypoglycemia). It follows that AMPK activation promotes the availability of energy by driving catabolic pathways such as glucose transport and fatty acid oxidation while inhibiting anabolic pathways of lipogenesis, glycogenesis, and protein synthesis. AMPK interfaces with insulin signaling to promote these functions, for

Metabolism and Medicine example, by enhancing the insulin receptor substrate 1 (IRS1)/PI3K/AKT pathway involved with translocating the glucose transporter 4 (GLUT4) molecule to the cell membrane and inhibiting the mechanistic target of rapamycin (mTOR) insulin signaling pathway of protein synthesis (192, 193). AMPK stimulates fatty acid oxidation by phosphorylating the enzyme acetyl-CoA carboxylase (ACC) that is thereby inhibited from converting acetyl-CoA to malonyl-CoA, the rate-limiting step of fatty acid synthesis. Fatty acid synthesis normally occurs in the liver and in adipose tissue. This, in turn, stimulates the rate-limiting enzyme carnitine palmitoyltransferase 1 (CPT1) that carries palmitate fatty acids into the mitochondria for oxidation-derived production of ATP. Importantly, a disturbed composition of gut microbiota interferes with the activation of AMPK. Thus, this elaborate design is abrogated by pathogenic gut microbiota that promote obesity and insulin resistance (163), interfering with adaptive responses to metabolic stress and the ability to provide energy production when it is needed. The greater the level of obesity, mediated by an increasing low-grade proinflammatory milieu of circulating inflammatory cytokines and metabolic endotoxemia (11), the greater the provocation of the neuroendocrine and autonomic nervous system branches of the stress response (130). The stress response, in turn: 1) slows intestinal transit time, 2) disturbs the gut microbiota composition to one that is more obesogenic (via increased energy harvest), 3) provokes increased circulating proinflammatory responses to the gut (e.g. TLR4 activation) (innate immune system release of cytokines IL-1, IL-6, and tumor necrosis factor α (TNFα) with concurrent disassembly of endothelial cell tight junctions and release of endotoxin into the portal circulation), and 4) increases insulin resistance (as a result of the inflammatory cytokines, hypercortisolemia, induction of sympathetic nervous system elements of the inflammatory response, and further suppression of FIAF). All of these effects significantly contribute to obesogenicity in a pernicious feedforward fashion. Nonetheless, the specific contribution of the Firmicutes:Bacteroidetes ratio and the impact of other microbial species on obesogenicity remains unclear. Indeed, this fervent area of research holds promise for defining the susceptibility states and order parameters of obesity that drive the vicious feedforward cycle of insulin resistance. Disturbances in the microbiota composition, which may promote increased energy harvest and fat storage, also provoke insulin resistance. A hallmark feature of insulin resistance is impaired satiety and a subsequent increase in ingestive behaviors. Consequently, a disturbed microbiota may initiate an escalating cascade of physiological events that promote obesity and metabolic disease.

Ley et  al. showed that weight loss in human participants correlates with changes in the microbiota (61). Increases in Bacteroidetes and decreases in Firmicutes correlated with weight loss but not the caloric reduction or the type of diet consumed. While the ratio of Bacteroidetes:Firmicutes, or their independent contributions to the microbiota composition, are not consistently associated with weight loss across studies, it remains possible that the microbiota is a key determinant

255

Microbiota and Human Metabolism of weight loss and weight set points, which may explain the variation in weight loss among individuals with similar diets.

to underlie the connection of diet and predisposing conditions to the development of metabolic disease.

Many patients are disquieted by their inability to lose weight or by weight loss results that inadequately realize their expectations based on the extent of calorie restriction. In the clinical setting, it is not uncommon for these patients to request a thyroid evaluation. It is a faulty premise that an underactive thyroid gland (“thyroid condition”) is synonymous with “weight condition”, but this misconception nonetheless has deep cultural roots that span many generations.

Gut microbial diversity, which varies between individuals, appears to be the strongest and most consistent marker of metabolic health.

The relationship of the Firmicutes:Bacteroidetes ratio to weight loss interestingly appears to be largely independent of energy extraction of dietary components and unrelated to the energy-harvesting capacity of the microbiota (194). This could be explained by the observation that different species of microbial symbionts across individual hosts are capable of providing the same metabolic functions. A conclusive elucidation of these mechanisms may lead to direct translation into medical practice via a top-down application of precision medicine for metabolic disease. This is likely to be a subject of robust and exciting research for decades to come. Given that fatty acids (including SCFAs) are important sources of energy harvesting, it is seemingly paradoxical that opportunistic microbes appear to produce fewer SCFAs. Examples of this include Staphylococcus aureus (phylum Firmcutes), several species of Clostridia (phylum Firmicutes), Mycoplasma (class Mollicutes), and several Proteobacteria species (e.g. E. coli) that reduce sulfate and serve as a source of endotoxin (11). The sulfate-reducing bacteria reduce sulfate (SO42-) to sulfite (SO32-) then sulfide (H2S), with a characteristic foul odor that is reminiscent of rotten eggs. This reduction generates energy while expelling sulfide as waste. In a sense, these organisms “breathe” sulfate, rather than oxygen, in a form of anaerobic respiration. These bacteria are generally harmful because the sulfite moiety interacts with periodontal tissues and the intestinal mucosa as a reactive oxygen species, leading to inflammation-related breakdown of the tissue barriers. A characteristic behavior of opportunistic organisms, whether prokaryotic or eukaryotic, is that they take advantage of nutrient surplus and reproduce exponentially. This dynamic interaction highlights an important perspective of how dietary excess is detrimental to health. Overabundance of pathogenic organisms displaces healthy microorganisms, leading to intestinal dysbiosis. In the example of Staph. aureus, Collado et al. reported an overabundance in overweight and obese pregnant women (195). Kalliomaki et al. likewise demonstrated that an overabundance in infants is a reliable predictor of obesity later in childhood (29). Intriguingly, women who gained excessive weight during pregnancy were also several-fold more likely to have obese offspring than obese women who do not gain excessive weight. This effect is epigenetically linked and extends to subsequent generations (196). Hence, disturbances in gut microbiota, including elevated populations of opportunistic pathogens and certain epigenetic modifications, appear

Coincident with the abnormally high levels of opportunistic microbial organisms that are characteristic of intestinal dysbiosis in obesity and type 2 diabetes is a reduction of SCFA-producing organisms. Although the Firmicutes Faecalibacterium prausnitzii may promote obesity with certain dietary substrates (presumably due to energy harvesting), this organism has typically been shown to be reduced in the setting of obesity and type 2 diabetes. Importantly, this bacterium also imparts salutary effects on the host by secreting metabolites that block NF-κB, thus exerting systemic antiinflammatory effects that lower circulating pro-inflammatory cytokines (116, 197). A large-scale microbiome analysis indeed concluded that the hallmark features of gut dysbiosis in patients with type 2 diabetes included an increase of opportunistic organisms, increase of sulfate reducing capacity, and decrease of SCFA-producing microbes (5, 11, 29, 158, 176, 194, 195, 197, 198). This is supported by the identification by Zhao et al. that SCFA-producing bacteria alleviate type 2 diabetes (thereby restoring a mutualistic relationship with the host) and diminish the production of metabolically detrimental compounds (62). This exemplifies the need to assess the overall balance of metabolic functions provided by the bacterial species present under a given set of conditions.

6.3.4.3.3 Proteolytic Fermentation The microbiota in the distal colon is dedicated to harvesting energy from the fermentation of residual peptides and proteins. Proteolytic fermentation also yields SCFAs, though the contribution of this mechanism to the total SCFAs in the distal colon remains unclear. In contrast to carbohydrate fermentation, protein and peptide fermentation yields a diverse range of metabolites, including 1) the branched-chain fatty acids (BCFAs) isobutyrate, 2-methylbutyrate, and isovalerate derived from fermentation of branched-chain amino acids (BCAAs); and 2) phenolic and indolic compounds derived from microbial fermentation of aromatic amino acids (AAAs) and gaseous products such as hydrogen, methane, carbon dioxide, and hydrogen sulfide (199). The majority of these compounds have been deemed toxic and have damaging effects on colonic and metabolic health (62, 199, 200). In addition, microbial proteolysis can yield three (3) BCAAs and AAAs, which can be further metabolized by microbial cross-feeding (i.e. nutritional interdependence of microbial species) (200, 201). Disruptions in these cross-feeding pathways augments absorption of these amino acids, disturbs gut integrity, and leads to insulin resistance (200–202). Several studies in pigs and humans (199, 203, 204) demonstrated that increased availability of dietary proteins and diminished availability of fermentable fibers leads to increased proteolytic fermentation in the colon. At least some protein fermentative strains of the gut microbiota might be involved in facilitating pro-inflammatory

256 responses and non-alcoholic fatty liver disease (NAFLD) progression (114). Specifically, in rodents fed with a high protein diet, the hydrogen sulfide, ammonia, and phenolic compounds produced have been seen to be connected with damaging effects on gut epithelial health and gut permeability (205, 206). Therefore, these proteolytic metabolites might indirectly contribute to NAFLD progression via increased translocation of toxic compounds to the liver. An interesting study that utilized a gnotobiotic mouse model demonstrated a possible direct link between products of microbial protein fermentation and NAFLD (207). Mice fed a high-fat diet developed hepatic macrovesicular steatosis after colonization with microbiota of diabetic mice, whereas control mice that were treated with microbiota of normoglycemic mice only developed low-level steatosis. In comparison with control subjects, mice with macrovesicular steatosis had increased concentrations of the BCFAs, isovalerate and isobutyrate, derived from the microbial fermentation of BCAAs. In addition, these mice also developed insulin resistance (207). Another microbial metabolite derived from proteolytic fermentation of L-tryptophan by the microbial enzyme tryptophanase is indole, which has been shown to decrease gut inflammation and prevent gut barrier dysfunction (208, 209). In a mouse experiment, acute orally administered indole improved lipopolysaccharide-induced upregulation of proinflammatory cytokines and downregulated key proteins of the NF-κB pathway in the liver (210). A metagenome analysis by Hoyles et al. was combined with an analysis of the hepatic transcriptome and plasma and urine metabolomes in women with morbid obesity but no history of type 2 diabetes mellitus (211). This study indicated that the status of steatosis was associated with decreased gut microbial gene richness and dysregulation of microbial AAA and BCAA metabolism. Using a rodent model and human hepatocytes, this study identified microbial-derived phenylacetic acid (a product of phenylalanine catabolism) as a contributor to steatosis progression. Phenylacetic acid might play a role in increased hepatic lipid accumulation via a synergetic increase in BCAA utilization in the Krebs cycle. These observations further indicate that proteolytic fermentation products might play a role in the development of hepatic steatosis. However, it should be noted that this study also identified other dysbiosis-associated factors, including lipopolysaccharide and trimethylamine N-oxide, as being important contributors to hepatic steatosis. Hydrogen sulfide is a major byproduct of protein fermentation. Studies in animal models suggest that increased hydrogen sulfide production adversely affects pancreatic islet function, thereby leading to the development of type 2 diabetes (212, 213). In addition, hydrogen sulfide stimulates gluconeogenesis and glycogenolysis while decreasing glucose utilization and glycogen storage in rodent hepatocyte models. This collectively reflects impairments in glucose homeostasis (214). Another metabolite specifically originating from proteolytic fermentation by gut microorganisms is p-cresol, which is converted to p-cresyl sulfate by the host. In mice, administration of p-cresyl sulfate for 4 weeks increases ectopic fat accumulation in the liver and muscles and triggers peripheral insulin resistance (215). Several studies demonstrated that the gut microbiome from insulin-resistant individuals show increased

Metabolism and Medicine BCAA biosynthesis potential (largely driven by Prevotella copri and Bacteroides vulgatus) but a reduced potential for BCAA uptake and catabolism (202). These observations indicate that the microbiome contributes to increased peripheral BCAA concentrations and insulin resistance. Overall, hydrogen sulfide, p-cresol, phenolic compounds, and BCAAs derived from proteolytic fermentation appear to be involved in the progression of insulin resistance.

6.3.4.3.4 Prebiotics Prebiotics represent a valuable opportunity for improving metabolic health by targeting imbalances of the gastrointestinal microbiota. Prebiotics are dietary substrates, typically non-digestible fibers, that nourish probiotic gut microbes. Bifidobacterium and Lactobacillus, in particular, are capable of fermenting these otherwise non-digestible polysaccharides or resistant starches into short-chain fatty acids (SCFAs) (216). Overall, data on prebiotic treatment point to an effect reducing appetite and increasing satiety, consistent with improvements in insulin sensitivity. Mechanistically, this appears to be mediated by an increase in secretion of the gut Peptide YY (PYY) and a decrease in the secretion of hormone appetite stimulator, ghrelin (32, 217). Additionally, prebiotic enhancement of Bifidobacterium strains improves metabolic function by controlling inflammation in obesity through mechanisms involving a glucagon-like peptide 2 (GLP-2)-mediated reduction in gut permeability. An impressive finding with obese premenopausal females consuming a syrup of prebiotics from yacon roots was that of increased satiety accompanied by a striking 15 kilogram of weight loss (on average) as well as a 50% reduction in fasting insulin levels and a 30% drop in low-density lipoprotein (LDL) cholesterol (218). Comparable studies have similarly shown reductions of body weight, though more modestly so. It should be noted that in contrast to the benefits of prebiotics, there are perplexing misconceptions that guide hospital dietary policy to include the routine use of skim milk and saccharine sugar for inpatient meals. Skim milk has a higher glycemic index than low fat and whole milk, which elevates blood glucose levels. In the case of saccharine, Barbara Corkey’s research that led to her receipt of the Banting Award (2013) showed that not only are sugar substitutes diabetogenic, but saccharine is the most so (at doses not unusual for humans to consume). Prebiotics are dietary substrates, typically nondigestible fibers, that promote the growth of beneficial microorganisms in the gut. Probiotics are a consumable form of the microorganisms themselves, which need to be taken routinely to support a healthy gut microbiota composition (219). Antibiotics, on the other hand, reduce microbial diversity by eliminating subsets of bacterial populations. These insalubrious changes to the microbiota can promote antibiotic resistance in the remaining populations via horizontal gene maintenance and transfer (220).

6.3.4.3.5 Alcohol Chronic alcohol consumption may disturb gut microbiota by increasing the Proteobacteria:Bacteroidetes ratio. This, in

Microbiota and Human Metabolism turn, results in a corresponding increase in endotoxins known to be cofactors in certain forms of alcoholic liver disease (221). Bacterial lipopolysaccharide endotoxins released into the portal circulation may serve as one class of proinflammatory cofactors for the development of liver disease and neurological complications in 20–30% of alcoholics (222). Additionally, endotoxins may prime monocytes in alcoholics to produce cytokines and oxidant molecules following endotoxin exposure (223). The dysbiotic gut microbiota of alcoholics further predisposes these individuals to obesity, insulin resistance, and type 2 diabetes.

6.3.4.3.5 Antibiotics and Other Xenobiotics Given that virtually all forms of life have co-evolved in association with bacteria, it is not surprising that disruptions of the microbial equilibrium often have dramatic manifestations. This is particularly stark in cases where entire strains or species become extinct. For example, microbial diversity has been noted to steadily decrease with increasing urbanization (224). There are many factors that contribute to this phenomenon, not the least of which is an increase in antibiotic use. Martin Blaser, the director of the Center for Advanced Biotechnology and Medicine (CABM) at Rutgers University, is one of the foremost experts on this topic and has argued that antibiotics are the single most important factor for this decrease.

257 With the industrialization of farming, livestock have been increasingly exposed to antibiotics as a means of increasing feed efficiency and weight gain. From a business perspective, this serves to improve product yields and increase profit margins; however, antibiotics radically alter the microbiota of the recipients and select for antibiotic-resistant strains of bacteria that can spread resistance to other animals and humans via horizontal gene transfer (Figure 6.15). Antibiotic-resistance gene transfer renders consumers vulnerable if they become infected with bacteria that will not be responsive to the particular antibiotic involved. While the practice of fattening livestock with antibiotics has been banned in China, the European Union, and the United States, many other countries have continued using this practice. In addition, farmers around the globe use antibiotics prophylactically at birth to combat issues associated with factory farming, such as stress from crowding and abrupt weaning practices that lead to altered microbiota and unnatural patterns of bacterial exposure. While the numbers are unreliable, it is clear that the vast majority of antibiotics are consumed by the animal husbandry industry. The overuse of antibiotics by humans is also a matter of concern. In the United States, the average baby/toddler takes 2.7 courses of antibiotics in the first three years of life. In Pakistan and Bangladesh, this is increased to ten courses in the first year of life. Multiple studies have demonstrated that even a single dose of antibiotics is enough to leave long-lasting impacts,

FIGURE 6.15  Antibiotic use in livestock alters the composition and diversity of the microbiota. Treating livestock with antibiotics to increase feed efficiency and weight gain or prophylactically minimize illness associated with factory farming leads to unhealthy outcomes for both the livestock and consumers. The livestock become overweight and unhealthy from antibiotic-driven dysbiosis and demonstrate antibiotic-resistant bacterial species. In turn, the excreted bacteria and antibiotics get passed along to humans via consumption of crops grown on contaminated soil or via handling of animals and uncooked meat.

258 particularly if given during a critical developmental period. In many countries, all babies born in hospitals are given prophylactic ophthalmic antibiotics. Dethlefsen and Relman reported that structural changes to the microbiota were induced by antibiotics and that these changes did not revert back to normal, even one year after the perturbations took place (225). In addition, usage of the broadspectrum antibiotic ciprofloxacin led to reduced diversity of the microbiota when measured three to four days post-treatment. Significant resilience could be seen approximately oneweek post-antibiotic treatment, but structural changes to the microbiota did not revert back to normal even one year after the perturbations took place and some species were extinct entirely (as determined using deep sequencing) (226, 227). Cho et al. demonstrated that even sub-therapeutic doses of antibiotics altered early-life murine metabolic homeostasis (228). Significant changes were observed in the metabolism of carbohydrates to SCFAs, impacting fatty acid metabolism, lipid metabolism, lipogenesis, lipid transport to the periphery, and the percentage of body fat. When Hviid et al. worked with children in Denmark, they observed that the more antibiotics a child took, the more likely they were to develop inflammatory bowel disease (229). Cox et al. reported that female mice given low-dose penicillin plus a high-fat diet exhibited significant shifts in their microbiota and were seen to have long-lasting metabolic effects, including maintaining twice the fat mass of their counterparts (even after the microbiota ostensibly renormalized) (230). The antibiotics perturbed gene expression as much as ten-fold for certain pathways, including pathways involved with feeding and immune regulation. The same perturbations were seen with post-treatment fecal transfers to germ-free mice, suggesting that the microbiota changes, and not the antibiotics per se, were responsible for the long-term changes in fat mass.

6.3.4.3.6 The 4Rs An emerging mode for the treatment of dysbiosis, or small intestinal bacterial overgrowth (SIBO), is embodied by a therapeutic approach referred to as the “4Rs”, which stands for 1) Remove, 2) Replace, 3) Reinoculate, and 4) Repair. The wide spectrum of manifestations for gut dysbiosis that need to be addressed by the 4Rs include skin changes (e.g. eczema, seborrhea, Rosacea, and pruritis), GI symptoms (e.g. bloating, diarrhea, and constipation), hair loss, disturbed sleep, and unintentional weight changes. This approach is at the very core of the clinical toolbox for practitioners in the disciplines of Naturopathy and Functional Medicine. It should not be overlooked that all interventions in healthcare carry some degree of risk and should be guided by the same risk/benefit assessment that guides allopathic decision making. The 4Rs entail the following:

1) Remove. Insofar as possible, one is encouraged to remove processed foods (e.g. those containing artificial colorings and flavorings, emulsifiers, and preservatives); common dietary allergens and sensitizers (e.g. whole wheat and whole grains, alcohol, caffeine, dairy, eggs, soy, peanuts, and corn); non-steroidal

Metabolism and Medicine anti-inflammatory drugs (NSAIDs); toxins; and noncommensal/non-symbiotic microbiota (which can be promoted by courses of antibiotics or anti-fungals). 2) Replace. Significant relief can be provided by replacement, or more precisely restoration, of deficiencies that hinder adequate digestion and absorption. Gastric secretions contain mucus, hydrochloric acid (HCl), water, and pepsin (which digests proteins and stimulates the HCl pump). While a typical assumption is that too much acid in the stomach causes dysbiosis, it is not atypical that the true culprit is an insufficiency of acid production. Thus, Betaine HCl is advocated as a supplemental source of HCl, which plays a major role in the pathophysiology of gastroesophageal reflux disease (GERD) along with a relaxed lower esophageal sphincter. Impaired gastric secretory function can be ameliorated by pepsin replacement, and pancreatic enzyme insufficiency, which is commonly associated with poor digestion, can often benefit from pancreatic enzyme replacement therapy. Causes of impaired gastric secretions include aging, chronic stress (some of which may be agerelated), and imbalances of vitamin and mineral cofactors (e.g. B vitamins and zinc). It is worth stating that essential cofactors are necessary for mitochondrial function and therefore connected to the pace of aging. Exocrine pancreatic insufficiency (EPI) is associated with symptoms of diarrhea/steatorrhea, bloating, gas, and abdominal pain. EPI due to chronic pancreatitis appears to have a relationship with SIBO, and it is likely that other causes of EPI do as well (e.g. aging, types 1 and 2 diabetes, cystic fibrosis, pancreatic hemochromatosis, and pancreatic tumors). EPI is a cause of gallbladder dysfunction and is also associated with gastric exocrine dysfunction. Taken together, SIBO is a feature of a plethora of common gastrointestinal disorders with a basis for therapeutic replacements. 3) Reinoculate. There has been growing interest in making use of the health-benefiting potential of prebiotics and probiotics, presumably by generating a healthier balance of the gut flora. Some of the more promising prebiotics include Jerusalem artichokes, asparagus, inulin, carrots, and bananas, often accompanied by fiber in general. Some of the common sources of probiotics are fermented products (e.g. kombucha, dairy products, vegetables) and Acidophilus gasseri. Unhealthy exposures have been shown to actually deplete many of the species of the gut microbiota, making it necessary to reinoculate these species exogenously. Some of the exposures that appear to deplete various gut bacteria include caesarean childbirths, a high-fat (Western) diet, and urban living, among others. While reinoculation remains an imprecise science, it may still prove to be of utility. It is the goal of many contemporary scientists and practitioners to reach a point when one can specifically identify

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prebiotic and microbial insufficiencies (much like with diet- and digestion-related insufficiencies) and reinoculate with the missing species or supplements. 4) Repair. A number of approaches focused on repairing an unhealthy gut (i.e. restoring the integrity of the gut wall and reducing inflammation) have proven helpful to sufferers. One such approach involves feeding the gut with healthy sources of omega-3 and omega-6 fatty acids (e.g. cashews, almonds, macadamias, flaxseeds, and oils from olives, sunflowers, and certain fish), vitamins B5 and D, glutamine, and zinc. In addition, inflammation can be at least partially repaired, so as to support a healthier gut, with butyrate (a SCFA), curcumin, and quercetin. A number of mindful activities have also proven themselves capable of reducing dysbiosis or SIBO, such as meditation, mindful eating, enjoying the company of others, and engaging in activities that provide a sense of purpose.

6.3.4.3.7 Exercise as a Modulator of the Microbiota The specialties of sports medicine and exercise medicine have recently recognized the significance of the gut microbiota. These fields highlight that healthy microbiota compositional and functional characteristics may be the result of not only optimized nutrition but of long-term physical conditioning as well. In this regard, there is evidence that physical activity in childhood and adolescence promotes a greater diversity of microbiota and correspondingly favorable psychological and metabolic health profiles (231). Cumulative evidence suggests that exercise can improve whole-body energy metabolism, intestinal peristalsis, and immunological functions. Additionally, exercise can maintain the dynamic balance of the gut mucosal immune system and expand the number of SCFA producers. A recent study involving 16S ribosomal DNA sequencing of stool samples from a group of marathon runners observed that the bacterial genus Veilllonella, which converts lactate into acetate and propionate, was increased in a post-marathon cohort compared to pre-marathon controls. Additionally, microbiota transplantation of Veillonella from marathon runners into mice led to increases in running times on treadmills. Furthermore, the microbiota of professional athletes displays greater diversity and improved metabolic capacity as compared to that of sedentary subjects. Similarly, rodents receiving exercise training exhibit favorable modifications in the composition of gut microbiota, including increased Firmicutes and Proteobacteria, but reduced Bacteroidetes. These studies indicate that exercise increases the gut microbial diversity, particularly the prevalence of bacterial species associated with improved metabolic health. These relationships are mediated by the effect of gut microbes on the immune system, neurodevelopment, and behavior (89). Accordingly, the fitness or free energy landscape of an individual in the field of exercise physiology can be assessed by factors that include the composition of the microbiota. The free energy landscape is relevant not only to assessing modifiable risk factors of disease, but also to maximizing physical performance in the arena of sports medicine. There is

a reported association of specific bacterial groups differentiating obese individuals according to the degree of their weight loss on calorie-restricted diets accompanied by increased physical activity (198). Individuals who start with higher bacterial counts of Bacteroides fragilis, Bifidobacterium catenulatum and Clostridium leptum, and lower counts of Clostridium coccoides, Bifidobacterium breve, Bifidobacterium bifidum, and Lactobacillus, experience the most weight loss. Additionally, the ratios of Bacteroides fragilis:Lactobacillus and Bifidobacterium:Clostridium coccoides correlated with the amount of weight loss (198). These data suggest that the interactions between the gut microbiota and body weight may be sensitive to intervening lifestyle changes, including exercise, to varying degrees based on the composition of the individual’s microbiota (198). Of note, the group of Ronald Evans at the Salk Institute has been working on developing a pharmacological agent to enable immobilized individuals to derive some of the benefits otherwise derived from exercising. Recognizing that a metabolic attribute of endurance athletes is that of burning fat in preference to carbohydrates in muscle cells, the group set out to develop agonists of the peroxisome proliferator-activated receptor delta (PPARδ), a key nuclear receptor that regulates fatty acid metabolism in muscle. In doing so, they have created a functional ligand mimetic, GW501516, that can activate PPARδ and enhance fatty acid burning without promoting carbohydrate burning. This development begs the question of whether or not inducing this exercise-like metabolic impact with GW501516, controlled for diet and activity, will lead to changes in the microbiota of those tested.

6.3.4.3.8 Probiotics The insights gleaned in recent years on the mechanisms of microbial dysbiosis, including disruption in endothelial cell barrier function, systemic inflammation, and effects on metabolism (including obesity and insulin resistance) have begun to translate into novel metabolic therapies. One approach, espoused in the naturopathic health community for decades, has been that of supplementing with probiotics, live bacteria found in fermented foods that are being explored as novel metabolic therapies to confer health benefits. This practice has been legitimately denounced by mainstream medicine because of the lack of large-scale randomized placebo-controlled trials supporting it as well as the proprietary nature of promoting particular brands. However, fervent increasing interest and vigorous scientific research catalyzing the field of intestinal microbiota and meta-genomics medicine have led to impressive cumulative evidence that supports the role of the gut microbiota as an “organ” that fundamentally regulates metabolic health and can be cultivated, so to speak, to promote health. In general, probiotics and prebiotics appear most beneficial for two general types of disease states: 1) obesity and associated metabolic states of insulin resistance (e.g. metabolic syndrome and type 2 diabetes), and 2) inflammatory bowel disease. This is said in light of observations that probiotics do not generally appear to colonize the gut, although some individuals appear to be permissive to colonization in a strain-specific manner (232). Nonetheless, it is possible that probiotics

260 function while they are “passing through”, particularly given that transient changes in gene expression are seen during the course of taking probiotics. Bifidobacterium and Lactobacillus strains are among the most thoroughly characterized probiotic agents, with a preponderance of evidence demonstrating a protective role in types 1 and 2 diabetes, Crohn’s disease, and ulcerative colitis (reviewed in [233]). These two bacterial strains are administered as probiotics and often touted as the healthy components of consumables like Greek yogurt and kombucha Bifidobacterium is a Gram-positive, anaerobic bacterial genus of the phylum Actinobacteria, found in the human mouth and gastrointestinal tract (234, 235). They are commonly associated with the large intestine and may be of clinical utility in the treatment of inflammatory bowel disease, particularly ulcerative colitis (reviewed in [236]). In association with Lactobacilli, they are also helpful in preventing or reducing the severity of acute diarrhea in children, and may be useful in antibiotic-associated diarrhea (237). Lactobacillus, a genus within the phylum Firmicutes, contains at least two strains that have been shown to be clinically useful for people with irritable bowel syndrome, Lactobacillus GG and Lactobacillus plantarum 299v (238–240). While Lactobacillus has been associated with the progression of dental caries, it has been suggested to populate sites on teeth that prevent the colonization of pathogenic Streptococcus species (241–243), thereby minimizing the incidence and progression of caries. In addition, Lactobacilli are believed to be capable of neutralizing oxidative stress, with Lactobacillus acidophilus being found to have antioxidant properties (244, 245). Pre-clinical studies suggest that certain strains of both Bifidobacterium and Lactobacillus endogenously promote metabolic health in a fashion that is protective against obesity, insulin resistance, and type 2 diabetes (11, 80, 246–249). The mechanisms underlying these observations appear to be manyfold. (1) Certain strains of Bifidobacteria and Lactobacilli inhibit the adherence of pathogenic microbes to gut epithelial cells, promoting mucosal barrier integrity and function (largely via SCFAs like butyrate) (31, 33, 80, 250). (2) The SCFAs are essential nutrients that serve as an energy source for the gut epithelial lining and promote barrier integrity (see Section 6.3.4). (3) At least some strains of Lactobacilli exert salutary effects on the enteric nervous system (ENS) of the gut (251). It is noteworthy that this component of the nervous system innervates both the Auerbach’s (myenteric) plexus in the intestinal wall, regulating gut motility, and the Meissner’s plexus, including axon terminals on the epithelial cells within the submucosal layer of the lamina propria that regulates the structure of the luminal surface, glandular secretions, electrolyte and water transport, and local blood flow. Inflammatory processes in the gut wall disturb the properties of enteric neurons and, as a result, cause gut dysmotility. This presumably impairs epithelial functions, including nutrient transport, absorption, mucus secretion, and epithelial barrier integrity (252). Probiotic lactic acid-producing bacteria, Lactobacillus and Bifidobacterium, have been shown to reduce the proinflammatory profile in patients with enteric neuropathy and improve gastrointestinal symptoms and neuropsychological impairment (253). In part, the reduction of inflammatory-induced autonomic enteric

Metabolism and Medicine neuropathy by lactic acid-producing microbes is facilitated by the role of the SCFAs that they produce, preserving the integrity of the epithelial barrier. (4) Some strains of Lactobacilli and Bifidobacteria reduce the growth of opportunistic proinflammatory pathogens by competing for nutrient sources. (5) Probiotic Lactobacillus strains have been shown to promote weight loss related to reductions of white adipose tissue (192, 254). (6) Probiotic Bifidobacteria strains have been demonstrated to reduce intestinal endotoxin (255), lower serum triglycerides and hepatic lipid deposition, and (stain-specifically) promote weight loss (256). (7) The commercial probiotic VSL #3, which contains strains of both Bifidobacteria and Lactobacillus, has exhibited attenuation effects on insulin resistance and hepatosteatosis, accompanied by immune system up-regulation of hepatic natural killer T cells (133). Faecalibacterium prausnitzii (phylum Firmicutes) is another organism important to intestinal and immune system health because of its production of SCFAs through the fermentation of dietary fiber. It normally represents 3–10% of bacteria in the intestine (257–259); however, lower than normal levels are correlated with Crohn’s disease(260, 261), type 2 diabetes (5, 197, 214), bipolar disorder (262), and major depressive disorder (263, 264). The microbial population of Proteobacteria in the human gut produces a wide range of products that include watersoluble B vitamins (reviewed in (265, 266)), the fat-soluble vitamin K, carbohydrate-fermenting enzymes, SCFAs, secondary bile acids metabolized from host primary bile acids, lipopolysaccharides (LPS), trimethylamines (TMAs), and other metabolites (122, 267–269). These microbial products may enter the human blood stream and contribute to energy flux and metabolic regulation. While the relative proportions of the major phyla of the gut microbiota may or may not differ between obese and lean individuals, the genetic and functional profiles reflect that different phyla can provide complementary bacterial strains as well as complementary functional roles (270). Meta-analyses have demonstrated that microbial communities were not predictive of differences between lean and obese individuals; however, the authors note that this could be a function of the limitations of the replicon-based analyses used or their sensitivity (271). The same study was able to selectively distinguish individuals with inflammatory bowel disease versus healthy controls. In contrast, Armougom et al. observed elevated levels of Lactobacillus populations in obese individuals compared to an increase in Methanobrevibacter smithii in patients with anorexia (272). Methanobrevibacter smithii are the predominant Archaea in the human gut, distinct from the Bacteria and Eukarya domains (273, 274). M. smithii indirectly plays an important role in efficient digestion of complex sugars by converting the end products of bacterial fermentation (H2 and CO2) into methane. This shift in bacterial fermentation to more oxidized end products is responsible for a reduced energy caloric value extracted from the baseline low-calorie diet of patients with anorexia. This contrasts with the microbiota of lean, nonanorexic individuals with a baseline low-calorie nutritional intake. The genome of M. smithii has been sequenced and may be a target for the treatment of obesity by reducing the energy harvesting from consumption of dietary polysaccharides.

261

Microbiota and Human Metabolism The gut microbiota appears to contribute independently and differentially in the otherwise typically intertwined metabolic disturbances of type 2 diabetes and obesity. The ratio of Bacteroidetes to Firmicutes in the diabetes populations has been reported to correlate inversely with the level observed with obesity using body mass index (BMI) as the parameter (275). Thus, instead of displaying the higher Firmicutes to Bacteroidetes ratios that are typical of obesity, patients with diabetes showed the reverse pattern. Additionally, among overweight patients with type 2 diabetes, several groups exhibited reduced levels of Firmicutes, while populations of Bacteroidetes and Proteobacteria were proportionately higher, with elevated Bacteroidetes being associated with worsened glucose tolerance (275, 276). Given that the genus Lactobacillus of the Firmicutes phylum, which is commonly conceptualized as a healthy component of microbiota, in fact represents a heterogenous group, it may be that some members contribute to inflammation in diabetic individuals, promoting both worsening glucose tolerance and obesity (176, 275). The authors showed that at least some strains of Bifidobacteria of the gram-positive Actinobacteria phylum are protective in mouse models of diabetes against gram-negative microbial LPS production and endotoxemia associated with potent stimulators of inflammation. Accordingly, Bifidobacteria correlated with reduced endotoxemia, decreased pro-inflammatory cytokines in plasma and adipose tissue, and improved glucose tolerance. The authors proposed that the prevalence of gramnegative organisms in the microbiota belonging to the phyla Bacteroidetes and Proteobacteria explain the differences in microbiota between diabetic and non-diabetic individuals. Furthermore, this may explain discrepancies in the pattern of relative microbiota composition in obesity in the context of diabetes versus non-diabetes (24). Investigators have also recently turned attention to the healthy symbiotic microbes mediating the so-called microbiota-gut-brain axis, which appears to provide powerful neuropsychological benefits. Microbial dysbiosis has been linked to intense stress responses, anxiety, and depression, and can be countered by the synthesis and secretion of certain neuropeptides and neurotransmitters into circulation, including GABA, serotonin, and dopamine. While it may be that either the dysbiosis or the extreme stress responses, anxiety, or depression are etiologically causal, it could be that a new avenue of relieving such responses would be to consume microbes as probiotics that are able to modulate the neuropsychological pathways engaged by pharmaceuticals like Valium (in the case of a GABA deficit) or Zoloft (in the case of a serotonin deficit). In the case of dopamine, probiotics could theoretically provide a stimulant-like effect that is energizing and contributes to the sense of wellbeing that motivates reward-seeking behavior. Notably, while dopamine is an important neurotransmitter that has salutary and even stress-reducing effects at physiological levels, overproduction may exacerbate the stress response and could be coupled to reward-seeking addictive behavior. It is worth re-emphasizing the inseparable and fundamental role of the prolonged abnormal stress response, involving the neuroendocrine and autonomic nervous systems and the emotional components underlying all chronic disease states, independent of whether it is primarily organic or psychogenic in nature.

The next vista in developing appropriate probiotic therapies for individual needs will require a determination of strainspecific deficiencies and/or metabolite-specific deficiencies that can be addressed with appropriate strains. Such a tactic will allow for personalize treatments that will serve the individual far better than promoting consumption of undefined mixes of bacteria, some of which could be detrimental. The greater the microbial diversity, the greater the diversity of communications with the host. A mutualistic relationship of these communications favors optimal health.

Regarding the safety and efficacy profiles of probiotics, it is important to keep in mind that research is still in early stages when it comes to identifying the strains and enzymes that most strongly portend the associated health benefits. One must consider that not all strains of Bifidobacteria and Lactobacillus will prove to be beneficial. While the overwhelming majority of probiotics studied have been deemed safe, caution is needed for individuals who are immunocompromised or have compromised gut barriers or serious illnesses. Such individuals are more prone to experience maladies such as sepsis, fungemia, and gastrointestinal ischemia (reviewed in [277]). Furthermore, while the gut microbiota is characterized by various guilds (see Section 6.1.6) that fight off newcomers wishing to colonize their precious real estate, a large influx of probiotics could conceivably compromise the ecological balance, at least temporarily if not long-term. Indeed, this sentiment is exemplified by the rather perplexing observation that probiotics interfere with re-normalization of the microbiota post-antibiotic treatment (232). This is in notable contrast to observations that autologous fecal microbiome transplantation enhanced recovery. In the not-too-distant future, we will be in a better position to consider which strains will be most beneficial for a given individual at a given time and by a given means.

6.3.4.3.9 Fecal Microbiota Transplants An increasing body of evidence indicates that gut microbiotahost interactions play a critical role in the pathogenesis of type 2 diabetes and insulin resistance via various mechanisms, including enhanced gut permeability, low-grade variations in the production of SCFAs and BCAAs, and dysregulation of bile acid metabolism. Recent studies have shown that fecal microbiota transplantation (FMT), using feces from humans following strenuous exercise, improves glucose metabolism, insulin sensitivity, intestinal homeostasis, and metabolic health in obese mouse recipients. Numerous microbial species, such as Alistipes putredinis, Ruminococcus gnavus, and Alistipes shahii reveal similar trends. Moreover, obese mice receiving FMT from humans post-exercise display an increased abundance of beneficial metabolites, such as SCFAs. FMT from healthy humans into patients with metabolic syndrome have also been seen to increase microbial diversity and improve insulin sensitivity as well as glycemic control (278). Conversely, another report has shown that FMT from obese humans to healthy mice increases the adipose mass and reduces SCFA concentrations in the cecum (8). These studies suggest that FMT in

262 humans may improve insulin resistance, glucose homeostasis, and the diabetic phenotype. Apart from diabetes, FMT has been used to treat Clostridium difficile-associated diarrhea (CDAD) and inflammatory bowel diseases (IBD). However, the use of FMT in clinical treatment still faces many difficulties, such as health status, lifestyle, age, the number of donors, the transplantation procedure, ethical concerns, health complications, and a number of long-term potential risks. While complications from fecal microbiota transplants are extremely rare, it should be noted that deleterious bacterial infections have been seen in a small number of recipients. In addition, a pooled source of fecal matter from healthy volunteers could lack a recipient’s missing microbe(s). For these reasons, Maria Gloria Dominguez-Bello of Rutgers University is spearheading efforts to establish a microbial vault—a repository of bacterial strains collected from individuals of different ages living in unurbanized settings across the globe. This effort could conceivably lead to the prospect of being able to provide a targeted “transplant” corresponding to one’s personal set of deficiencies. This could more or less replace fecal microbiota transplantations with an approach that is more individualized and patient focused.

6.3.5 Intrinsic Order Parameters through the Lens of the Innate Immune System Toll-like receptors (TLRs) are components expressed on the surface of antigen-presenting dendritic cells and macrophages of the innate immune system. They serve as the sensors of pathogen-associated molecular patterns (PAMPs) on pathogenic microbes and the danger-associated molecular patterns (DAMPs) on toxicants. PAMPs and DAMPs are recognized by pattern recognition receptors (PRRs) on antigen-presenting cells, with the greatest activity occurring along the epithelial surface of the gastrointestinal tract. While TLR4 is the best understood, there are numerous TLRs, each sharing the capacity to sense microbes with pathogenic potential, triggering immune responses with the induction of inflammatory signaling that promotes the transcription of pro-inflammatory cytokines. The latter are centrally mediated by the transcription factor nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB). NF-κB has a DNA-binding domain within the promoter region of genes responsible for transcription of pro-inflammatory cytokines. Toll-like receptor 5 (TLR5) specifically detects bacterial flagellin. It was found that TLR5 knockout mice (i.e. mice with dysfunctional or missing TLR5 genes) become hyperphagic and develop morbidities related to obesity and insulin resistance, including the hypertension and dyslipidemia components of metabolic syndrome (279). Furthermore, these features are not all the consequence of hyperphagia and obesity but, rather, effects that independently cause insulin resistance despite the fact that insulin resistance, obesity, and impaired satiety are inseparably intertwined. Vijay-Kumar et  al. reported an additional and separate mechanism contributing to obesity, independent of energy harvesting (279). Given TLR5’s key role in the innate immune response of recognizing bacterial flagellin and initiating an NF-κB-mediated cascade of immune responses, TLR5

Metabolism and Medicine knockout mice were seen to acquire the obese phenotype, without concomitant differences in energy harvesting. Instead, it appeared that alterations in the microbial communities of the TLR5 knockout mice were increasing feeding behaviors. In addition, Vijay-Kumar et al. showed that while TLR5 knockout mice with restricted food intake did not become obese, they did develop insulin resistance (279). This data is consistent with the notion that TLR activation by PAMPs at the gut epithelial surface is critical for maintaining immune tolerance and gut microbial homeostasis, supporting the postulation that a healthy microbiota evolves with and serves as part of the host’s immune system (280). In the case illustrated, the innate immune system serves dual functions in its interactions with the gut microbiota that includes not only host defense, but also its coupling to the regulation of energy balance and insulin sensitivity. Thus, members of a microbiota characterized by alterations in bacterial composition can tilt the balance, so to speak, and promote metabolic dysregulation that correlates with immune system overactivity (i.e. inflammation). In such cases, the energy extracted from food fails to be translated into the work of maintaining healthy metabolic homeostasis, including postprandial satiety, normal insulin secretion, and insulin sensitivity. Chronic inflammation and oxidative stress disrupt the integrity of information systems, perpetuating and amplifying the loss of energy as heat. This diverts metabolic energy away from tasks that maintain the structural and functional integrity of the system.

SCFAs have been demonstrated to cross-react with the LPS receptor TLR4. This thereby induces insulin resistance and associated increases in adiposity via intracellular signaling of innate immune cells and adipocytes that promote the expression of pro-inflammatory cytokines (40). In contrast, the intestinal microbial-derived SCFA butyrate induces favorable metabolic effects that reduce obesity and improve insulin sensitivity and glucose tolerance in type 2 diabetes. Such effects are mediated by enhanced mitochondrial fatty acid oxidation in addition to intestinal gluconeogenesis and prevention of metabolic endotoxemia (281).

6.3.6 Integration of Bottom-Up and Top-Down Order and Control Parameters The translocation of bacteria from the gut lumen into the blood and adipose tissue is associated with hepatic inflammation and metabolic diseases such as obesity, insulin resistance, and type 2 diabetes (33). Bifidobacteria and Lactobacilli have been seen to reduce mucosal adherence of a number of pathogenic gram-negative bacteria, thereby ameliorating tissue inflammation and manifestations of insulin resistance and type 2 diabetes (282). Thus, control of bacterial translocation and gut mucosal adherence may represent promising therapeutic strategies for protecting against chronic inflammation, insulin resistance, obesity-associated diabetes, and cardiovascular disease.

Microbiota and Human Metabolism Such strategies may eschew a requirement for polypharmacy and increase the related costs, not only in direct fiscal terms but also in unpredictable toxicities associated with the nonlinearity of a bottom-up approach in complex biological systems (as described in Volume I, Section 4.3). This is of core significance and reflects the value of using interdisciplinary perspectives, such as those utilized by the physics and medical communities, to solve biological challenges. The notion of the fitness/free energy landscape can be considered in the context of designating susceptibility and disease states along with their primary and secondary order parameters. In this context, predisposing conditions would be secondary order parameters with extrinsic control parameters leading to the development of these conditions. Two distinct paradigms of therapeutic development are generally recognized: a “bottom-up” approach and a “top-down” approach. A bottom-up approach begins with fine-scale or granular observations and progresses toward more generalizable endpoints. It is based on an analysis of the molecular biomarkers of a pathological condition, which could, for example, be over-expressed or under-expressed proteins or enzymes. They can then be quantified in terms of deviation from the baseline, which may be linked to the severity of disease. Proper identification of a therapeutic target at a molecular level in the context of the proposed methodology would define the primary order parameter. The next step would be development of a pharmaceutical agent that either inhibits or activates the target based on the desired outcome. Optimizing the dosing and scheduling of the selected agent would lead to the observation and quantification of the patient’s physiological parameters and, ideally, alleviate the symptoms of the underlying condition. In contrast, a top-down approach begins with generalized (often symptomatic or behavioral) observations and proceeds toward molecular endpoints. In the context of the physiological fitness landscape, it would begin with mapping a patient’s health status based on a series of stress tests, with the objective

263 of determining the organism-level response to external stimuli. This could include control parameters such as physical exertion, blood oxygen saturation, temperature variation, etc. This would then be followed by the use of a knowledge base coupled with artificial intelligence algorithms to guide the patient’s recovery pathway via behavioral and pharmaceutical interventions that are not necessarily tailored to a molecularlevel analysis of the patient’s disease state. While both methods fundamentally rely on empiricism, the bottom-up approach is based on molecular medicine while the top-down approach is based on heuristics. It should be stressed that the two approaches are not in conflict with each other and in many cases may indeed be of complementary value. A schematic illustration of the two approaches is given in Figure 6.16. A crucial distinction between treatment strategies that target extrinsic control parameters, versus intrinsic order parameters, is that the former involves a top-down approach while the latter involves a bottom-up approach. Control parameters are, by definition, external to the biological system, so manipulations are thereby applied at an organism-wide level with effects that percolate down to the molecular level. Such top-down interventions (e.g. pharmaceutical treatments, lifestyle changes, dietary adjustments) are founded on the basic premise that they produce the desired outcome. While effective, the molecular pathways involved (if identified) are typically myriad and exceptionally complex. Such a non-specific approach does little to expand the basic understanding of the disease construct. Still, it can be incredibly useful when the entity in question is mechanistically complex and/or poorly characterized. Top-down interventions fundamentally rely on symptomatology, restricting disease monitoring to symptom severity and precluding quantification when the disease parameters are sub-threshold to manifest symptoms. Further, pharmaceutical interventions are generally non-specific and often produce undesirable side effects related to off-target pharmacological effects.

FIGURE 6.16  Bottom-up and top-down approaches to treatment. A bottom-up approach begins with fine-scale or granular observations and progresses toward more generalizable endpoints. A top-down approach begins with generalized (often symptomatic or behavioral) observations and proceeds toward molecular endpoints. While both methods fundamentally rely on empiricism, the bottom-up approach is based on molecular medicine while the top-down approach is based on heuristics.

264 In contrast, order parameters are internal properties of the biological system that typically function at a molecular, cellular, or tissue level. Interventions at this scale traditionally begin with identifying a molecule or pathway of interest that is pharmacologically characterized and pharmaceutically targeted. This requires a fundamental knowledge of disease pathophysiology, and may not be possible if the disease itself is mechanistically complex and/or poorly characterized. When possible, however, it allows for increased specificity and quantifiability of the therapeutic approach, reducing side effects when the pharmaceutical agent is appropriately specific. It further promotes disease monitoring, with the goal of returning the order parameters to the values that are characteristic of the healthy state. This is particularly pertinent when the values are sub-threshold for external manifestations (i.e. symptoms), and may inform the clinician of the best time and/or quantity of further treatments. By taking complementary bottom-up and a top-down approaches toward developing personalized treatment plans, one can benefit from the power of amassing “big data” from clinical observations, developing a personalized physiological fitness landscape, and subjecting these data to artificial intelligence algorithms for pattern identification and the development of robust treatment strategies. By quantifying a patient’s myriad intrinsic order parameters, which result from interactions with extrinsic control parameters (e.g. disturbed diet, physical activity, stressors, and circadian behaviors), a clinician can identify the therapeutic interventions with the best odds of recovery. This requires a depth of knowledge regarding the predictive factors that contribute to the disease phenotype at the both the population and individual levels, including genetic, epigenetic, metabolomic, proteomic, and lipomic profiles, among others. The intervention may be something that modifies the interpretation of stress, activation of the stress response, improvement of circadian behaviors, or reversal of dietary patterns, any of which may restore the diversity and composition of the microbiota. As discussed, the implications of doing so are profound and include improvements in systemic inflammatory responses, redox conditions, acid/base equilibrium, and free energy stress—many of the foundational parameters of disease. Modulating the milieu in which a pathological condition functions fundamentally modifies the nature of the condition itself. In much the way that a toxic environment catalyzes a phase transition of biological order parameters from a healthy to a diseased state, restoring the environment offers the potential to reinstate homeostatic balance. These concepts are central to the discipline of complexity medicine and fall within the assimilating domains of physics and biology. A maximally steep valley within the fitness landscape, representing a response to a physiological parameter or set of parameters, is maximally stable. The free energy that maintains this stability is maximal at the mountaintop and can be utilized for doing work. Systems utilize free energy to accomplish the work required to maintain the physiological parameters of the steady state. The interactions between parameters in the steady state can also exist in a mode of symmetry provided that sufficient free energy can be translated into work. The metabolic efficiency

Metabolism and Medicine of the system is thus a function of free energy conversion and inversely correlates with the amount lost as unusable heat. The presence of acute stress (organic or psychogenic) can decompensate these systems and force them to engage modes of energy production that are less efficient though more readily available (e.g. glycolysis). While not ideal, this prevents the system from decompensating further into a state with sustained pathological ramifications. As long as these supplemental pathways are only required briefly, the human body can rapidly restore its dynamic equilibrium and reinstate homeostasis. It is during prolonged periods of stress, when the body’s energy-producing systems are unable to meet the metabolic demands of the tissues, that irreversible changes occur and chronic disease results. This issue of metabolic efficiency is highly context specific. For example, a high intensity stress response in the skeletal muscle is much better able to recover from a period of glycolytic metabolism because it cycles very rapidly. Additionally, oxidative phosphorylation has the capacity to render glycolysis more efficient than fatty acid oxidation based on the amount of ATP produced for the quantity of O2 consumed. This reduces the overall burden of redox stress and preserves the coupling of cytosolic and mitochondrial bioenergetic pathways. Indeed, mitochondrial dysfunction results from pathological redox reactions and defines the fundamental basis of chronic disease. Metabolic efficiency can also be described in terms of the pathways utilized. This underscores the notion that oxidative phosphorylation produces a nearly twenty-fold greater yield of usable energy than the substrate-level phosphorylation that occurs with glycolysis. The physiological system with maximal metabolic efficiency in terms of the complexity of interactions is one that occurs not only constrained by oxidative phosphorylation as the mode of energy production, but correlated in the sense of quantum metabolism (see Chapter 2). This higher efficiency, quantum mode of energy production is characterized by the allometric scaling laws of physiology, while the less efficient glycolytic mode of energy production is described by the isometric scaling laws of classical metabolism. An intriguing analogy can be made here with Einstein’s special relativity, which demonstrates that time can be constrained or dilated as a result of movement at high speeds. At the ultimate limit of this relationship (i.e. the speed of light), time becomes infinitely dilated and grinds to a halt. With regard to the natural course of senescence, chronic disease serves to accelerate biological aging. Inversely, a phase transition that prevents or reverses an inflammatory or chronic disease state has the potential to dilate biological time. Crucially, if one changes the environment associated with a pathological condition, one can change the pathological condition itself, effectively slowing the pace of aging. While an unhealthy environment may catalyze a phase transition from the order parameters of a healthy biological system to those of a disease state, the restoration of a healthy environment offers the potential to reverse these deleterious effects. Manipulating the control parameters extrinsic to the human being offers provocative potential, but may not be possible in all cases. Indeed, the disease state may be advanced beyond a threshold of recovery and become irreversibly damaged (Figure 6.17).

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FIGURE 6.17  Schematic representation of the change in the fitness landscape caused by diet as an external control parameter. Note the presence of allostatic overload and its role in causing irreversible changes in the state of metabolic health.

The application of translational medicine “from bench to bedside” will require an intense commitment and collaboration among researchers to address the individual needs of precision medicine in the fields of obesity, type 2 diabetes, and related metabolic disease states. The basic constructs of fitness landscapes that define susceptibility and disease states and the constructs of control and order parameters (both primary and secondary) are crucial frameworks for differentiating which parameters are causal and which are merely correlational or coincidental. This could generate a revolution of sorts with regard to the modus operandi of clinical medicine, but would require the effort of the Endocrine Society, American College of Clinical Endocrinology, Obesity Society, and other relevant organizations worldwide Many unanswered questions remain regarding the translational approaches that will convert information on the gut microbiota into clinical paradigms of care. This is a paragon example of why interdisciplinary assimilation of basic and applied science is critical in both the clinical arena and the laboratory (32). Multispecialty and interdisciplinary assimilation is paramount to establish this exciting field, including hormonal endocrinology, microbiology, gastroenterology, immunology, and computational biology.

6.3.7 New Prospects With new techniques for determining and analyzing microbiota structure, function, and interactions, we are heading toward an era with a great depth of understanding about the interactions between the host and microbiota. This includes the role of the microbiota in the mechanisms of various diseases, such as liver diseases, bacterial infection, cancer, psychiatric diseases, and metabolic diseases. Studies exploring the metabolic consequences of microbial fermentation indicate that dietary fiber may be an incredibly robust strategy to prevent metabolic diseases, such as obesity-linked diabetes and non-alcoholic fatty liver disease.

One of the remaining challenges is that it has only been possible to culture approximately half of the bacterial species identified by 16S rDNA high-throughput sequencing (283). New technologies are making advances in this arena, paving the road toward an enhanced characterization of microbiotahost interactions. Among these is a method of simulating gastrointestinal tract conditions using reactor-grown microbial communities to identify single cells that produce metabolites of interest (284). Another technology, dubbed the “gut-ona-chip” system, serves as an in vitro cell-based model that mimics the properties of the human gut. It is populated with defined microbial symbionts and has incredible potential to transform into a platform for drug discovery (285). A third technological advancement involves colonic or intestinal stem cell construction, consisting of an in vitro system for growing three-dimensional organoid epithelial structures from colonic or intestinal stem cells along with various types of differentiated cells (286). Immense developments have been made, not only in classifying, isolating, and culturing members of the gastrointestinal microbiota, but also in the creation of valuable new genetic tools (e.g. whole-genome sequencing) and novel genetic models. Guo et al. have been pioneering methods for knocking out individual bacterial species and specific genes from the gut microbiota to characterize their role in the scheme of host biology (287). Combining these approaches for additional studies in the future will vastly increase our understanding of the molecules involved in the homeostatic communications between the gut microbiota and the host. Coupled appropriately with the numerous tools available for sequencing, identifying metabolites and their interactions with biological ligands, measuring biological activity, and preparing formulations of biologically active human/bacterial isolates, it becomes possible to envision a scenario in which the most important information can be readily assessed. This will enable clinicians to evaluate the host/microbiota system as it relates to the phenotype of the supraorganism (i.e. the patient) and promote better health outcomes via precision

266 medicine. As we head toward an era of personalized medicine, it is encouraging to note that much of our research enterprise has been dedicated to the understanding of the gut microbiota. Numerous industries are actively developing iterative approaches of sampling an individual’s gut microbes and their metabolic products. Coupled with the use of artificial intelligence to characterize one’s microbiota/microbiome/metabolome status, this has the potential to be profoundly robust for the development of an individualized fitness landscape. With sufficient time and data, such information has the potential to generate new insights into host-microbiota interactions and the development of new effective treatments.

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273 272. F. Armougom, M. Henry, B. Vialettes, D. Raccah, D. Raoult, Monitoring bacterial community of human gut microbiota reveals an increase in Lactobacillus in obese patients and methanogens in anorexic patients. PLOS ONE 4(9), e7125 (2009). 273. T. L. Miller, M. J. Wolin, Methanogens in human and animal intestinal tracts. Systematic and Applied Microbiology 7(2–3), 223–229 (1986). 274. P. B. Eckburg et  al., Diversity of the human intestinal microbial flora. Science 308(5728), 1635–1638 (2005). 275. N. Larsen et al., Gut microbiota in human adults with type 2 diabetes differs from non-diabetic adults. PLOS ONE 5(2), e9085 (2010). 276. A. Schwiertz et al., Microbiota and SCFA in lean and overweight healthy subjects. Obesity 18(1), 190–195 (2010). 277. S. Fijan, Microorganisms with claimed probiotic properties: An overview of recent literature. International Journal of Environmental Research and Public Health 11(5), 4745– 4767 (2014). 278. R. S. Kootte et al., Improvement of insulin sensitivity after lean donor feces in metabolic syndrome is driven by baseline intestinal microbiota composition. Cell Metabolism 26(4), 611-619.e616 (2017). 279. M. Vijay-Kumar et  al., Metabolic syndrome and altered gut microbiota in mice lacking toll-like receptor 5. Science 328(5975), 228–231 (2010). 280. N. Cerf-Bensussan, V. Gaboriau-Routhiau, The immune system and the gut microbiota: Friends or foes? Nature Reviews. Immunology 10(10), 735–744 (2010). 281. A. V. Hartstra, K. E. C. Bouter, F. Bäckhed, M. Nieuwdorp, Insights Into the role of the microbiome in obesity and type 2 diabetes. Diabetes Care 38(1), 159–165 (2014). 282. G. T. Macfarlane, J. H. Cummings, Probiotics, infection and immunity. Current Opinion in Infectious Diseases 15(5), 501–506 (2002). 283. J. W. Arnold, J. Roach, M. A. Azcarate-Peril, Emerging technologies for gut microbiome research. Trends in Microbiology 24(11), 887–901 (2016). 284. B. L. Wang et al., Microfluidic high-throughput culturing of single cells for selection based on extracellular metabolite production or consumption. Nature Biotechnology 32(5), 473–478 (2014). 285. H. J. Kim, D. Huh, G. Hamilton, D. E. Ingber, Human guton-a-chip inhabited by microbial flora that experiences intestinal peristalsis-like motions and flow. Lab on a Chip 12(12), 2165 (2012). 286. Z. Wang et al., Gut flora metabolism of phosphatidylcholine promotes cardiovascular disease. Nature 472(7341), 57–63 (2011). 287. Y. Guo et al., Commensal gut bacteria convert the immunosuppressant tacrolimus to less potent metabolites. Drug Metabolism and Disposition: The Biological Fate of Chemicals 47(3), 194–202 (2019).

7 The Role of Insulin Resistance in Metabolic Disease

Abbreviations ACC ALL ATGL ACTH AGE AgRP AD ADH apo B CaMKII ChREBP CVD CPT-1 CML CART CRH DNL DAG DHA DHAP DI ETC ER eNOS EGFR ERK FAO FGF-21 FGFR FOXO1 GLP-1 GCK G6Pase G-6-P GLUT4 Glu Gln GFAT GAPDH GH HDL HSL HIF1α IGF IGF-1

acetyl CoA carboxylase acute lymphoblastic leukemia adipose triglyceride lipase adrenocorticotropic hormone advanced glycation end-product agouti-related peptide Alzheimer’s disease antidiuretic hormone apolipoprotein B calcium-calmodulin kinase II carbohydrate response element binding protein cardiovascular disease carnitine palmitoyl transferase chronic myelogenous leukemia cocaine- and amphetamine-related transcript corticotropin releasing hormone de novo lipogenesis diacylglycerol dihydroxyacetone dihydroxyacetone phosphate disposition index electron transport chain endoplasmic reticulum endothelial nitric oxide synthase epidermal growth factor receptor extracellular signal-regulated protein kinases fatty acid oxidation fibroblast growth factor 21 fibroblast growth factor receptor Forkhead box protein 1 glucagon-like peptide-1 glucokinase glucose 6-phosphatase glucose-6-phosphate glucose transporter type 4 glutamic acid glutamine glutamine fructose-6-phosphate aminotransferase glyceraldehyde-3-P dehydrogenase growth hormone high-density lipoprotein hormone-sensitive lipase hypoxia inducible factor 2 alpha insulin-like growth factor insulin-like growth factor-1

DOI: 10.1201/9781003149897-7

GFBP IR IRS-1 ISGU IFNγ IL1-β IL-6 IMCL JAK LTP MRS mTOR MAP MAPK MGL MAO GLcNAc NPY NEFAs NFκB

insulin-like growth factor-binding protein insulin receptor insulin receptor substrate-1 insulin-stimulated glucose uptake interferon gamma interleukin 1 β interleukin 6 intramyocellular lipid Janus kinase long-term potentiation magnetic resonance spectroscopy mammalian target of rapamycin microtubule associated protein mitogen activated protein kinase monoacylglycerol lipase monoamine oxidase N-acetyl glucosamine neuropeptide Y non-esterified free fatty acids nuclear factor kappa-light-chain-enhancer of activated B cells oxLDL oxidation of polyunsaturated fatty acids on the surfaces of low-density lipoproteins O-GlcNAc O-linked N-acetylglucosamine PTH parathyroid hormone PPP pentose phosphate pathway PGC1α peroxisome proliferator activator gamma C1 alpha PI3K phosphatidylinositol-3 kinase PEP phosphoenolpyruvate PEPCK phosphoenolpyruvate carboxykinase PFK phosphofructokinase PDGFR platelet-derived growth factor receptor PARP Poly (ADP-ribose) polymerase POMC proopiomelanocortin Akt protein kinase B PKC protein kinase C PP2A protein phosphatase 2A PMF proton motive force PDH pyruvate dehydrogenase enzyme complex PDK pyruvate dehydrogenase kinase ROS reactive oxygen species RANK receptor activator of nuclear factor kappa-B RANKL receptor activator of nuclear factor kappa-B ligand RAGE receptor for AGEs TNFR receptor for tumor necrosis factor ɑ

275

276 RQ RXR SHBG S-1-P SREBP1c Th-1 TZD TAG TCA cycle TG TNF-ɑ NF-ɑ Upd VLDL

Metabolism and Medicine respiratory quotient retinoid X receptor sex hormone binding globulin sphingosine-1-phosphate sterol regulatory binding protein 1c T helper-1 thiazolidinedione triacylglycerol tricarboxylic acid cycle triglyceride tumor necrosis factor ɑ tumor necrosis factor ɑ uridine diphosphate glucose very low density lipoproteins

Chapter Overview Insulin resistance is a cardinal underlying mechanism in the pathogenesis of chronic disease states. In many cases, insulin resistance results from adaptive responses in efforts to promote survival under circumstances of scarce energy availability. Insulin signaling pathways typically induce mechanisms of cell survival and growth in the presence of required bioenergetic machinery such as healthy mitochondria. Although it is linked to metabolic disease, insulin resistance also plays a role in healthy physiology under conditions of periodic cyclicity such as the fasting/feeding circadian cycles seen in humans. Insulin resistance additionally results in an adaptation to cope with excess energy stores. Under these conditions, it serves as a protective mechanism for metabolic tissue and prevents these tissues from being exposed to the threat of increased energy influx. There are currently two predominant theories of the exact etiology of insulin resistance that debate whether it precedes or follows a state of hyperinsulinemia. Another less widely discussed theory involves the notion of subclinical endotoxicosis promoting inflammation, which ultimately leads to hyperinsulinemia and secondarily to insulin resistance. Each of these arguments is discussed in great detail in the chapter on insulin resistance. Insulin secretion and signaling are each under circadian regulation. Moreover, insulin signaling governs the timing of biological clock activity. This bidirectional relationship highlights the significance of food as the strongest external cue for peripheral clocks. The loss of circadian rhythm of daytime insulin sensitivity and secretion alternating with nocturnal insulin resistance is a primary driver and component in the pace of aging and in the pathogenicity of chronic diseases of aging. Furthermore, non-circadian insulin resistance is integrally linked to mitochondrial dysfunction. Consequently, there is a matrix of feedforward self-amplifying loops of redox and inflammatory stress that are intrinsic to the most basic elements of metabolic disease, which also include imbalances of energy and acid-base. The relationship of redox, energy, and acid-base parameters of metabolic homeostasis is highlighted by a strikingly tandem correlation between the Nernst (redox), Gibbs free energy, and Henderson-Hasselbalch (acid-base) equations.

The energy sensors AMPK and SIRT1 are primary metabolic regulators with a strong circadian influence. They connect energy-consuming and producing pathways (in the case of AMPK) and redox stress resistance programs (in the case of SIRT1) in an inextricably coupled fashion to biological clocks for the maintenance of metabolic homeostasis. Fundamental to the development of metabolic disease is the decoupling between the cytosolic glycolysis pathway that converts glucose to pyruvate and mitochondrial oxidative combustion (oxidative phosphorylation). This is especially important in tissues (such as skeletal and cardiac muscle, adipose tissue, and brain) where glucose metabolism is dependent on insulin signaling. This is specific to GLUT4-mediated translocation of glucose into the cell and the enzyme complex pyruvate dehydrogenase complex (PDC) catalyzed decarboxylation of pyruvate to acetyl-CoA in mitochondria prior to feeding into the TCA cycle. The term metabolic flexibility is classically reserved for the circadian “metabolic switch” that occurs in skeletal muscle at the transition of the fasting-feeding (nocturnal-daytime) cycle. Accordingly, fatty acid oxidation occurs during the nocturnal hours while glucose oxidation occurs during the day. The loss of circadian rhythm is therefore tantamount to the conversion from cyclical (healthy) to noncyclical chronic (unhealthy) insulin resistance. Metabolic flexibility is lost in the setting of mitochondrial dysfunction. Thus, there is a decoupling of mitochondria from cytosolic glucose bioenergetic metabolism. Accordingly, glucose combustion cannot be completed by the process of oxidative phosphorylation in the cells of any tissue where mitochondria are not functional. Thus, cells are inflexible in the sense of adaptability to changes in energy substrate availability, and the presence of ectopic lipid deposits ensures that fatty acid oxidation (FAO) outcompetes glucose oxidation. The significance of this inflexibility is rooted in the greater oxidative stress generated by FAO versus glucose oxidation. The exact mechanisms of this decoupling of these pathways are detailed in the chapter on insulin resistance. The perspective of mitochondrial function in the clinical approach to diabetes has been a crucial missing piece. There are currently a few drugs that may be used to help restore mitochondrial function in the treatment of diabetes and other metabolic disorders. One newly approved drug, 6j, targets the enzyme complex PDC and thus helps repair the coupling of glucose metabolism in the cytosolic glycolysis pathway to pyruvate with mitochondrial oxidative metabolism. Another drug, Imeglimin, targets nuclear hormone receptor (NRH) coactivator PGC1α to promote mitochondrial biogenesis. It is also relevant in the connection of insulin signaling and secretion to circadian biology and NHR biology. Chapters 3 and 4 are dedicated to NHR metabolic regulation and the biology of time, thus these drugs are highly relevant to the focus of these discussions. Chapter 7 is dedicated to these topics of insulin signaling and resistance. Insulin signaling is discussed from a genomics and molecular perspective to unveil relevant pathways critical to the pathogenesis of insulin resistance. On a more translational and clinical basis, insulin resistance is examined here in the contexts of cancer, type 2 diabetes, cardiovascular

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Insulin Resistance in Metabolic Disease

FIGURE 7.0  Insulin resistance and hyperinsulinemia lead to the pathogenesis of chronic diseases such as obesity, cardiovascular disease, type 2 diabetes, Alzheimer’s disease, cancer, and accelerated cognitive decline.

disease, obesity, neuroendocrinology, and Alzheimer’s disease (Figure 7.0).

7.1 Physiological Role of Insulin in Classical Insulin Targeted Tissues Whole-body energy homeostasis is regulated by the coordination between food intake and energy expenditure. It is well established that glucose and fatty acids are major sources of energy, therefore maintaining optimum glucose and lipid levels in the blood is critical for survival. Furthermore, cellular and systemic glucose metabolism is predominantly maintained by insulin and glucagon. For example, after feeding, glucose enters the blood through the gut and arrives at the pancreas. In the pancreas, glucose stimulates insulin secretion from pancreatic beta cells. Insulin is an endocrine hormone that circulates through the bloodstream and acts on peripheral tissues such as adipose tissue, skeletal muscle, and the liver. As a result, insulin increases glucose uptake in adipocytes (fat cells) and myocytes (muscle cells) and suppresses hepatic glucose production (gluconeogenesis). Simultaneously, insulin inhibits lipolysis (lipid metabolism) in white adipose tissue (WAT), which results in a decrease in free fatty release from WAT. Conversely, during fasting conditions, when blood glucose levels are low, glucagon is released from pancreatic alpha cells to maintain adequate blood glucose levels. Glucagon is another endocrine hormone, which elevates blood glucose levels by increasing hepatic glucose production through upregulation of gluconeogenesis and glycogenolysis. Additionally, decreased circulating insulin and increased glucagon levels during fasting conditions promote lipolysis in WAT and release free fatty acids into the bloodstream to provide energy substrate to other tissues such as the heart and skeletal muscles. Thus, insulin and glucagon act antagonistically with respect to one another in order to maintain whole-body energy homeostasis at cellular and systemic levels during feeding and fasting conditions.

7.2 Insulin Resistance under Healthy and Pathologic Conditions Insulin is fundamentally an anabolic hormone that promotes energy storage in response to nutrient intake. Insulin suppression of hepatic gluconeogenesis and stimulation of liver glucose uptake promotes hepatic glycogen synthesis. Though insulin’s roles in regulating glucose metabolism often take center stage, insulin has important roles in lipid metabolism suppressing adipose lipolysis, stimulating hepatic lipid synthesis, and inhibiting the liver’s conversion of lipids into ketones. In insulin-resistant states, the ability of insulin to promote energy storage is impaired. When peripheral tissues become insulin resistant, impaired glucose uptake contributes to post-prandial hyperglycemia (e.g. glucose intolerance). In many cases, the development of insulin resistance in the liver leads to uncontrolled hepatic glucose production which may be exacerbated by the increased flux of fatty acids and glycerol from insulin-resistant adipose tissue. These phenomena are key to the transition from the prolonged allostatic stress response to chronic disease states and have been the focus of numerous mechanistic studies. But, why do cells possess the mechanisms to become resistant to insulin? Energy availability is fundamental to survival. When energy sources become unavailable, insulin resistance can actually be a potential adaptation that promotes survival. Insulin resistance can prevent glucose utilization by peripheral tissues so that there is sufficient glucose available for brain metabolism. Insulin resistance also occurs during normal physiological processes, such as puberty, pregnancy, and physical/physiological stress, where it may help the body conserve energy. Following a periodic cycle, such as the feeding/fasting cycle in humans and the circannual cycle in hibernating bears or migratory birds, insulin resistance is a healthy event. Therefore, despite its negative association with metabolic disease, insulin resistance can play a significant role in the context of a healthy physiology.

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FIGURE 7.1  When healthy mitochondria are available, insulin signaling pathways promote cell growth and proliferation (mediated by mTOR), as well as stress resistance programs (mediated by FOXO). Conversely, when mitochondria are dysfunctional, cells become vulnerable to redox stress, which ultimately leads to a decrease in cell survival. *Akt = protein kinase B; FOXO = forkhead box protein class O; GSK3 = glycogen synthase kinase 3; mTOR = mechanistic target of rapamycin; IRS = Insulin receptor substrate; PI3K = phosphoinositide 3-kinase.

Insulin signaling pathways promote cell survival, growth and replication, when nutrient availability is balanced with the capacity of bioenergetic machinery, i.e. healthy mitochondria. When an imbalance arises, various stress pathways are activated. An integral part of this response is the inhibition of insulin signaling pathways. Significant work has been done regarding insulin’s suppression of FOXO1, a transcription factor that regulates hepatic gluconeogenesis (a process of glucose synthesis from non-carbohydrates), and GSK3, a kinase that regulates glycogenesis (a process of glycogen synthesis from glucose). In insulin-resistant states, decreased insulin signaling lifts the inhibition that was on FOXO1 and GSK3 allowing them to activate gluconeogenesis and impair glycogen synthesis respectively. Though other mechanisms may contribute (e.g. altered composition of gut microbiota and disruptions to the synchronization of circadian cycles), insulin resistance can be considered as the major mediator of metabolic stress responses (Figure 7.1).

7.3 Historical Context of Insulin Resistance The modern perspective of the pathogenesis of type 2 diabetes dates back to a series of papers published in The Lancet by Himsworth in 1939. This view posited that the ineffective action, or insensitivity, of insulin may be responsible for many cases of diabetes (1–4). At the time, this was a radical departure from the widespread acceptance that all diabetes was the consequence of absolute insulin deficiency. It was not until 1959 that Yalow and Berson described a method for measuring endogenous insulin (5), which subsequently led to the finding that individuals with insulin insensitive adult-onset diabetes typically had higher than normal circulating levels of insulin (6).

Metabolism and Medicine

Ralph DeFronzo, MD (Used with permission).

In 1979, Ralph DeFronzo and colleagues described the euglycemic insulin clamp technique that quantifies insulin sensitivity. This procedure assessed insulin-mediated glucose disposal by the simultaneous infusion of constant rates of insulin with a varying rate of glucose infusion to maintain the euglycemia (euglycemic-hyperinsulinemic clamp) (7). The extent of insulin insensitivity, or resistance, thus parallels the rate of glucose delivery. DeFronzo received the Lilly Award from the American Diabetes Association in 1987 for his contributions narrowing in on the hallmark feature of insulin resistance in type 2 diabetes. His award lecture titled “The triumvirate: β-cell, muscle, liver: a collusion responsible for NIDDM”, described his seminal work recognizing defects of insulin signaling in two primary tissues, skeletal muscle, and the liver. In addition, he described a third core defect in the pancreatic beta cell, impairing the insulin secretory response to peripheral tissue insulin resistance, which must be present in order to progress from glucose intolerance to frank diabetes (8). See Sidebar 7.1 for a note about β-cells.

SIDEBAR 7.1: DEFRONZO’S CAUTION ON SULFONYLUREAS DeFronzo emphasized that people with advanced glucose intolerance show an 80% reduction in pancreatic β-cell function. β-cell exhaustion can be present prior to the onset of diabetes. For that reason, it is important to use diabetes medications with beta cell-preserving effects, and to avoid diabetes medications that promote beta cell failure, such as sulfonylureas. DeFronzo further argued that treating type 2 diabetes is more than simple glycemic lowering; a successful treatment must also use insulinsensitizing agents with anti-atherogenic properties. Obesity has been recognized as a component of the insulininsensitive adult form of diabetes, going back to Himsworth in 1939. Specifically, central abdominal fat is a risk factor for

Insulin Resistance in Metabolic Disease type 2 diabetes. In 1968, Salans and colleagues showed that fat cell hypertrophy is responsible for impaired insulin sensitivity and carbohydrate tolerance (9). In 1983, Krotkiewski and others made the connection between regional distribution of central abdominal fat topography and adverse effects of lipid and glucose metabolism, with corresponding risk of type 2 diabetes (10). To add to these findings, Weyer and colleagues investigated abdominal subcutaneous adipocytes in Pima Indians. They concluded that subcutaneous adipocyte size in the abdomen, rather than overall adiposity, better predicted type 2 diabetes (11). In the past decades, many other groups have since confirmed the relationship between adipocyte size, insulin resistance, and type 2 diabetes. Overgrown adipocytes with impaired perfusion become dysfunctional, leading to hypoxia and inflammation (12–14). Interestingly, these changes can be identified before the development of insulin resistance (15). The future of medicine might be able to use sensitive measurements of hypoxia and inflammation as predictors of impending insulin resistance, so that patients can be alerted that they are on the path toward developing type 2 diabetes.

7.3.1 History of Syndrome X

Gerald Reaven, MD (1928–2018) (Figure 1 from Kim, Sun H., and Fahim Abbasi. “Myths about insulin resistance: tribute to Gerald Reaven.” Endocrinology and Metabolism 34, no. 1 (2019): 47–52. Used with permission).

In 1988, Gerald Reaven introduced the term Syndrome “X” in his Banting Award presentation. The “X” was to indicate the unknown mechanism that modulates the relationship between insulin resistance and coronary artery disease (16). Insulin resistance is more than a hallmark of type 2 diabetes, but a predictor of several metabolic and cardiovascular diseases. Syndrome “X”, Reaven emphasized, occurred when insulin resistance with compensatory hyperinsulinemia led to increased risk of dyslipidemia (elevated hepatic very lowdensity lipoprotein [VLDL] secretion, high circulating triglyceride levels, exaggerated postprandial hyperlipidemia, and low circulating high-density lipoprotein [HDL]), dysglycemia

279 (glucose intolerance and impaired fasting glucose), and hypertension. The first support for Reaven’s hypothesis about Syndrome X came from hypertension studies where it was found that the treatment of hypertension failed to protect many individuals from cardiovascular disease (17–22). Later evidence for Reaven’s hypothesis about Syndrome X came when DeFronzo and Ferrannini in 1991 found a direct correlation between the severity of insulin resistance and hypertension (23). In their experiments, DeFronzo and Ferrannini used radiolabeled glucose and the euglycemic insulin clamp. They localized the site of insulin resistance to the muscle, which showed impaired insulin-mediated glucose uptake and oxidative bioenergetics. The mechanism by which insulin resistance caused hypertension was proposed to be any of a number of pathogenic events. Some of these pathogenic events include compensatory hyperinsulinemia-induced endothelial dysfunction (24), renal retention of sodium (25), sympathetic nervous system overactivity with impaired sympatho-vagal balance (26), and smooth muscle proliferation and fibromuscular hypertrophy in arteriolar walls (27–29). Hypertension due to insulin resistance/hyperinsulinemia implicates additional pathology related to the increased wall thickness of arterioles (due to smooth muscle mitogenesis, intimal hyperplasia, and fibromuscular hypertrophy), increased neurohumoral (sympathetic) tone, renal salt retention, and atherogenic dyslipidemia, which together exert greater potentiation of cardiovascular disease than hypertension alone imposing increased shearing force. Hypertension alone is a risk factor for cardiovascular diseases, but hypertension caused by insulin resistance (with compensatory hyperinsulinemia) contributes to greater risks of cardiovascular disease or even death. Hyperinsulinemia promotes the hepatic synthesis of VLDL (30–32). VLDL particles undergo aggressive remodeling, leading to atherogenic dyslipidemia. In addition to synthesizing more triglycerides, high circulating insulin encourages greater uptake of cholesterol into vascular smooth muscle cells of arterioles. It’s been demonstrated that insulin resistance can cause hypertension by activating MAPK signaling and reducing PI3K activity. MAPK induces overexpression of the potent vasoconstrictor endothelin-1 in vascular endothelial cells (33–35). Typically, endothelin-1 is countered by the vasodilatory actions of nitric oxide (NO). However, when the PI3K pathway is inhibited, there is less NO synthesized (36). To make matters worse, lipotoxicity in insulin-resistant vascular endothelial cells increases reactive oxygen species (ROS), which decimate the low levels of NO present (37). Adding insult to injury, MAPK has inflammatory effects. Glucose toxicity in uncontrolled diabetes has similar proinflammatory effects in endothelial cells (38, 39). Together, these mechanisms lead to endothelial cell dysfunction. Over the decades since Reaven’s historic Banting Award presentation of Syndrome X, it has become increasingly apparent that the cardiovascular dysfunction of Syndrome X is just the beginning. Insulin resistance and hyperinsulinemia have since been linked to procoagulant and proinflammatory states, with elevations in plasminogen activator inhibitor-1 (PAI-1); fibrinogen and c-reactive protein (CRP); and disturbed uric acid metabolism and clearance. Both cause high blood levels of uric acid; ovarian hyperandrogenism (testosterone production); central obesity; polycystic ovarian syndrome (PCOS);

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FIGURE 7.2  Insulin resistance and compensatory hyperinsulinemia can cause systemic damage. More than a simple metabolic disease, insulin resistance is implicated in everything from cardiovascular disease to cancer to organ damage to neurological changes. Source: adapted from (40). *PCOS: polycystic ovarian syndrome; NAFLD: non-alcoholic fatty liver disease.

obstructive sleep apnea; hepatic nonalcoholic steatosis; many gastrointestinal and reproductive tumors; Alzheimer’s disease; and non-Alzheimer’s disease dementias (Figure 7.2).

7.3.2 Insulin Resistance Has Many Effects on the Body The majority of research on insulin signaling has historically focused on the conventional metabolic effects on glucose and lipids. However, dysfunctional insulin signaling has also been linked to early onset of several chronic diseases of aging. This suggests that insulin signaling has many other actions throughout the body. In fact, there are an estimated 1700 insulin signaling pathways! We do not know all of the pathways involved in insulin signaling yet, but from what we can tell, the pathways are intertwined and have non-linear actions on other signaling pathways. The resulting effects of insulin on a tissue type are highly nuanced. DeFronzo in 2009 delivered his Banting Lecture “From the Triumvirate to the Ominous Octet: A New Paradigm for the Treatment of Type 2 Diabetes” (41). This was yet another seminal contribution to the field of type 2 diabetes research. The presentation highlighted five new tissue defects (besides the original core pathophysiological triumvirate that were the basis of his Lilly lecture 21 years earlier). The five new defects were: overactive adipose tissue lipolysis, pancreatic alpha cell hypersecretion of glucagon, renal tubule hyperabsorption of glucose, impaired postprandial secretion of (or resistance to) intestinal incretins, as well as insulin resistance in the brain. Neural tissue demonstrates divergent responses to the setting of systemic insulin resistance and hyperinsulinemia. While hyperinsulinemia drives increased neural sympathetic tone, in 2000 Kahn and colleagues showed it was reduced insulin

Metabolism and Medicine action in the hypothalamus that is responsible for impaired satiety, weight gain, and infertility, with reduced spermatogenesis and ovulation (42). Another effect of insulin resistance and hyperinsulinemia is cancer. In 1832, pancreatic cancer was the first case of a malignancy reported in the setting of diabetes (43). In 1910, a South African epidemiologist was widely criticized and rejected for proposing that diabetes increases the risk of many types of cancers (44). In the mid-1950s, a preeminent pathologist from the University of Minnesota casually stated that the concurrence of diabetes and pancreatic cancer was “well known”. He went on to remark that he questioned whether this under-recognized relationship was casual or causal (45). Large observational studies have helped support the connection between obesity and cancer, especially in women. The relationship between obesity and cancer started to gain traction in the 1960s, when more information about molecular pathophysiology became available. In 1966, an epidemiological publication about uterine cancer recognized the link to obesity; the authors suggested that aromatase induced estrogen synthesis in adipose tissue, which promoted cancer progression (46). In the present day, endometrial cancer is known to have strongly positive relationships with both diabetes and obesity. A large Women’s Health Initiative Observational Study between 1993 and 2000 identified a strong correlation between obesity and breast cancer in post-menopausal women (47). More evidence for the connection between cancer and obesity came in 2003, when Calle observed cancer mortality in 900,000 US adults prospectively 1982–1998. The findings showed a positive correlation of obesity with many cancers: renal cell, cervical, endometrial, ovarian, breast, prostate, gallbladder, colorectal, gastric, esophageal, hepatocellular, non-Hodgkin’s lymphoma, and multiple myeloma (48). This increase in cancer mortality is largely driven by increased cancer incidence (49); however, several studies have also shown that obesity at diagnosis of cancer contributes to a worse outcome (50–52).

SIDEBAR 7.2: IMPACT OF OBESITY AND HYPERINSULINEMIA ON CANCER RISK Obesity and type 2 diabetes often coexist, creating challenges when trying to determine which factor is driving cancer risk. Epidemiological studies suggest that obesity and diabetes (type 1 and type 2) are both independent risk factors for cancer, and that the combination can further increase cancer risk. Obesity increases cancer risk. Obese individuals have higher rates of cancer than lean individuals. For example, obesity imparts ~30% increase in endometrial cancer, ~30% increase in breast cancer, ~40% increase in pancreatic cancer (exact rates vary with the study), ~50% increase in colorectal cancer, over 100% increase in hepatic carcinoma (43). Mechanisms driving cancer risk can develop in the obese state, often long before the onset of type 2 diabetes. Diabetes increases cancer risk. Cancer rates are higher in diabetic populations (43). Individuals with type 1 diabetes (who typically have a lean build) have

Insulin Resistance in Metabolic Disease higher rates of endometrial cancer, and moderate positive relationships to cervical, bladder, and nonmelanoma skin cancers. The incidence of leukemia, stomach, papillary thyroid, and glioblastoma multiforme malignancies were mildly increased in type 1 diabetics compared to the non-diabetic population (53). Obesity + Type 2 Diabetes greatly increases cancer risk. When obese individuals also have insulinresistant type 2 diabetes, their rates of gastrointestinal, urological, and reproductive cancers skyrocket. Hyperglycemia foments existing cancers by providing fuel to cancer cells. Hyperglycemia also creates a state of inflammation and redox stress that promotes oncogenic mutations. Not surprisingly, type 2 diabetes is linked with a higher risk of many malignancies, including hepatobiliary tract, esophageal, gastric, colorectal, renal cell, breast, squamous cell oropharyngeal carcinoma, and endometrial cancers (54–61). In the case of pancreatic cancer, type 2 diabetes and smoking are the only two consistent shown risk factors, with the link to obesity showing mixed findings (62). These observations suggest that impairment in insulin signaling creates added cancer risk, on top of obesity-related cancer risk. As scientists, we know that correlation does not equal causation. Obesity, insulin resistance/hyperinsulinemia, diabetes, and cancer risk are intertwined, making it difficult to determine which factors actually drive increased cancer rates in patients (see Sidebar 7.2). In the 1990s, it was discovered that insulin-like growth factor (IGF) signaling played a key role in adipose tissue biology (63, 64). Scientists started developing an integrative model of the interactions of systemic insulin resistance with hyperinsulinemia, type 2 diabetes, estrogens, inflammatory cytokines, hyperlipidemia, hyperglycemia, obesity, tumorigenesis, and cancer cell proliferation. In 1995, LeRoith and colleagues showed a positive relationship between IGF and cancer (65, 66). In 2011 Gallagher and LeRoith reviewed the correlation between endogenous hyperinsulinemia, its upregulating effects on IGF-1, and their combined influence on cancer (67). Derek LeRoith’s group in 2010 performed some of the original research that provided solid evidence for a causeand-effect relationship between hyperinsulinemia and cancer. In one experiment, LeRoith’s group used a beta-3 adrenergic receptor agonist (a drug that stimulates lipolysis in brown adipose tissue), which reduced hyperinsulinemia and simultaneously reduced cancer cell expansion (68). In another experiment, the group blocked the activation of insulin receptors and IGF-1 receptors. Without a working feedback mechanism in place, the body’s production of insulin shot up three-fold (69). However, with insulin receptors and IGF-1 receptors blocked, mammary tumor cell growth was also blocked (70). In yet another experiment by the LeRoith group, genetically engineered mice with an abnormal version

281 of the human IGF-1 receptor had accelerated breast cancer growth, which was blocked with IGF-1 receptor inhibitors (71). These studies strongly suggest that insulin and IGF signaling are key factors in the insulin-resistant state that contribute to cancer. Also, in 2010, Stephen Hurstings’s group published some of the mechanistic work linking insulin and IGF-1 to cancer cell growth (72, 73). Insulin and IGF-1 stimulated receptors signaling through IRS-mediated pathways PI3K/Akt/mTOR and RAS/MAPK which in turn promote cancer gene transcription leading to increased cancer cell proliferation and/or survival (prevents apoptosis), and increased tumor angiogenesis (Figure 7.3). Between 2012 and 2016, LeRoith’s group (and others) published many reviews of the interwoven metabolic abnormalities at the interface of obesity, diabetes, metabolic syndrome, and cancer (74–76). Obesity is a key feature that drives cancer cell initiation and progression for several reasons. Obesity drives systemic insulin resistance, which leads to elevated fasting and postprandial hyperglycemia. In 1970, Chick and Like demonstrated that this dysglycemia promotes a compensatory increase in pancreatic insulin secretion, leading to circulating hyperinsulinemia (77). While hyperinsulinemia leads to downregulation of insulin receptors in otherwise healthy tissues, Mulligan and

FIGURE 7.3  Peripheral insulin resistance is typically accompanied by high levels of circulating insulin and bioavailable insulin-like growth factor 1 (IGF-1) in addition to a high ratio of leptin to adiponectin released from adipocytes. Insulin and free IGF-1 bind tyrosine kinase receptors (TKRs) on the surface of cell membranes. TKRs include insulin receptors (IRs), IGF-1 receptors (IGF-1R), IR/IGF-1R heterodimers as well as epidermal growth factor receptor (EGFR). These receptors in turn signal through two major pathways, the metabolic pathway (IRS/PI3K/ Akt/mTOR) and the mitogenic pathway (IRS/RAS/RAF/MAPK), which together promote cancer cell growth, replication, and survival, in addition to promoting angiogenesis in tumors. The proinflammatory effect of leptin and the relative absence of the anti-inflammatory effect of adiponectin promote signaling through the JAK-STAT/NFkB pathway to synergistically amplify these effects. *IGF-1 = insulin-like growth factor 1; TRK = tyrosine kinase receptor; IR = insulin receptor; IGF-1R = insulin-like growth factor 1 receptor; EGFR = epidermal growth factor receptor; IRS = insulin receptor substrate; PI3K = phosphatidylinositol-3 kinase; Akt = protein kinase B; mTOR = mammalian target of rapamycin.

282 colleagues reported in 2007 that this downregulation does not occur in mammary tumors, underscoring the pathogenicity of hyperinsulinemia on cancer cell growth (78). Together, hyperinsulinemia and hyperglycemia promote tumor cell replication. Endogenous insulin levels have been associated with the progression, recurrence, and mortality of various cancers (43). In addition to the direct effects of insulin on cancer cells, hyperinsulinemia can promote cancer indirectly through the growth hormone axis. In the setting of insulin resistance and coexisting hyperinsulinemia, hyperinsulinemia drives higher expression of growth hormone (GH) receptors in the liver. Consequently, GH induces IGF-1 production. Hyperinsulinemia also reduces the expression of insulin-like growth factor-binding proteins 1 and 2 (IGF-BP1/2) which typically binds to IGF-1 and 2. The result is more unbound IGF-1/2, promoting tumor cell growth (79). While obesity is strongly linked to insulin resistance, it can also contribute to cancer risk in other ways. Adipose tissue has aromatase activity, which converts androgens into estrogen. Estrogen is a known contributor to several cancers, and increased adiposity can lead to increased estrogen levels, particularly in postmenopausal women. Other adipokines, such as leptin and resistin may also play roles in cancer. See Figure 7.4 for an illustration of the interactions between insulin resistance, adipose tissue, the liver, and estrogen.

7.3.3 Spotlight on C. Ronald Kahn and Critical Nodes in the Insulin Signaling Pathway

C. Ronald Kahn. Source: photo by Joslin Diabetes Center; sent to the author personally by Joslin Diabetes Center, CC BY-SA 3.0.

Any historical perspective on insulin signaling pathways must highlight the work of C. Ronald Kahn. The Kahn Lab has made several breakthroughs in the basic science of insulin action, insulin resistance, adipose deposits, diabetes, and metabolic syndromes. The group uses genetic engineering techniques in mice and induction of pluripotent stem cells in humans. In 1982, the Kahn Lab demonstrated that the stimulated insulin receptor (IR) is an autophosphorylating tyrosine kinase (80, 81). Later, the group identified insulin receptor substrate-1 (IRS-1) as a principal node in the insulin signaling pathway (Figure 7.5) (82).

Metabolism and Medicine

FIGURE 7.4  Insulin resistance has many effects on the body. Pancreatic dysfunction raises both insulin levels and glucose levels. Insulin resistance in the liver increases glucose production. However, insulin resistance in muscle cells prevents the muscles from taking up excess glucose, resulting in hyperglycemia. Other effects of insulin resistance include increasing inflammatory cytokines (IL-6, IL1-β, TNF-ɑ), which lead to cell damage and tumor growth. Insulin resistance can also reduce the liver’s production of SHBG, resulting in higher levels of free estrogen, another contributor to tumor growth. At the same time, the liver’s production of triglycerides (TG) increases, and HDL levels decrease. IGF-1 increases, and GFBP 1 and 2, a protein that modulates IGF-1, decreases. Source: adapted from (76). * GFBP 1 and 2 = insulin-like growth factor-binding protein 1 and 2; HDL = high-density lipoprotein; IGF-1 = insulin-like growth factor-1; IL1-β = interleukin 1 β; IL-6 = interleukin 6; SHBG = sex hormone binding globulin; TG = triglyceride; TNF-ɑ = tumor necrosis factor ɑ.

Subsequently, Kahn’s group identified phosphatidylinositol-3 kinase (PI3K) as another key node in the insulin signaling pathway. When insulin or insulin-like growth factor-1 (IGF-1) binds to the IR, the activated IR induces IRS-1 signaling, which, in turn, activates phosphoinositide 3-kinase (PI3K) (83). PI3K signaling occurs in classical insulin target tissues. Activated PI3K generates membranebound PIP3, which activates PDK-1. Subsequently, PDK-1 phosphorylates and activates Akt (84). Akt mediates metabolic actions of PI3K signaling pathways include: lipid and glycogen synthesis, glucose uptake and utilization, and other effects (85). Yet another node in the insulin signaling pathway is the Ras-Raf-mitogen activated protein kinase (MAPK) pathway. MAPK signaling has important roles in cell regulation and mitogenesis. When overactivated, MAPK signaling is responsible for tumorigenesis (86). MAPK signaling may also induce inflammatory effects in insulin-targeting tissues (87). Kahn’s group further revealed distinct signaling pathways in classical (skeletal muscle, adipose, and liver) and in non-classical (vascular endothelial cells, pancreatic beta cells, and brain) insulin-targeting tissues (88). Kahn’s group demonstrated the importance of insulin signaling in the brain on cognition and mood. Mice with inactivated insulin and IGF-1 receptors in the amygdala and hippocampus show increased anxiety-like behavior, altered spatial memory, and reduced glucose tolerance (90). Astrocytes, in particular,

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FIGURE 7.5  A summary of the findings of the Kahn Lab. The Kahn Lab proposed three major nodes in the insulin signaling pathway. Node 1: IRS1,2,3,4. Node 2: PI3K. Node 3: Akt 1, 2, 3. Each node has many downstream effects on health. Source: adapted from (89). *Akt = protein kinase B; ERK1,2 = extracellular signal-regulated protein kinases 1 and 2; IGF-1 = insulin-like growth factor 1; IGF1R = receptor for insulin-like growth factor 1; IRS = insulin receptor substrate-1; PDK 1, 2 = pyruvate dehydrogenase kinase 1 and 2; PI 3-kinase = phosphoinositide 3-kinase; PIP3 = phosphatidylinositol (3,4,5)-trisphosphate; TNF-ɑ = tumor necrosis factor ɑ. TNFR = receptor for tumor necrosis factor ɑ.

are a direct target of insulin, and knocking out the insulin receptor specifically in these cells leads to similar behavior abnormalities including depression- and anxiety-like signs (91). Specific deletion of the insulin receptor in the mouse brain leads to brain mitochondrial dysfunction, increased ROS, and anxiety and depression-like behaviors, further supporting the effect of impaired insulin signaling in behavior changes and cognitive decline. Kahn’s work has also pointed to the effects of sugar consumption on hepatic insulin resistance. Mice who received a high-fat diet supplemented with fructose were more obese, showed liver enlargement, and had less tolerance for glucose compared to fructose supplementation alone and compared to a high-fat diet supplemented with glucose. Compared to a high-fat diet, fructose seems to be more strongly responsible for generating inflammation and reactive oxygen species (ROS) in the liver and increasing the enzymes involved in de novo lipogenesis (DNL) (92, 93). Finally, Kahn’s group showed that the insulin receptor is critical for the maintenance of brown and white adipose tissue (94, 95). Abolishing insulin signaling specifically in adipocytes leads to transient insulin resistance, fatty liver, high blood sugar, and high blood insulin. Glucose and insulin levels return to normal with the proliferation and differentiation of preadipocytes into brown and white adipocytes, confirming the highly plastic nature of adipose tissue (96). Kahn and colleagues have made remarkable strides over the past four decades, and it is exciting to think about the advances the group will make in the future.

7.3.4 Spotlight on Gerald Shulman

Gerald Schulman, MD, PhD, MACP, MACE, FRCP (Used with permission).

As with many leading physician-scientists, Gerald Shulman’s contributions arose from early observations. In Shulman’s case,

284 these observations began in boyhood when he accompanied his father, Herschel Shulman, on evening house-calls or diabetes summer camps. In medical school, his studies focused on the roles of insulin and glucagon in regulating hepatic glucose and glycogen metabolism (97–99). Shulman pioneered the use of magnetic resonance spectroscopy (MRS) to quantify key metabolites non-invasively in vivo. MRS allowed Shulman’s lab to quantify changes in intracellular glucose, glycogen, triglycerides, and other metabolites in human subjects. Together with other advanced analytical techniques (i.e. GC/MS and LC/MS/MS), they measured in vivo substrate fluxes and key tissue metabolites with increasingly greater precision and developed our current understanding of the mechanisms for lipid-induced insulin resistance. The group began by examining the “Randle Hypothesis” or the “glucose-fatty acid cycle” (100). This model attempted to account for an observation that incubation of rat heart and diaphragm muscle preparations with fatty acids increased intracellular glucose-6-phosphate (G-6-P) and glucose, and glycogen concentrations, respectively. The model supposed that fatty acids impaired glycolysis due to the accumulation of the metabolic intermediates from lipid oxidation. The Shulman lab used MRS to explore this model in young, lean but insulin-resistant offspring of patients with type 2 diabetes. While there was an inverse correlation between plasma fatty acid concentrations and insulin sensitivity, the association between intramyocellular lipid (IMCL), assessed non-invasively with 1H MRS, and insulin resistance was even stronger (101, 102). 13C and 31P MRS were used to non-invasively measure insulin-stimulated changes in muscle glycogen and intramyocellular G-6-P in both patients with T2DM and in non-diabetic first-degree relatives of patients with T2DM. When measured by 13C MRS, the rate of glucose and insulin-stimulated muscle glycogen synthesis was more than 50% lower in the diabetic subjects than in the control subjects (103) and associated with lower muscle G-6-P concentrations (104). Moreover, insulin and glucose-stimulated G-6-P and glycogen concentrations were decreased in lean, normoglycemic first-degree relatives of T2DM (105). In contrast to the Randle hypothesis, these data suggested that the defect in insulin-stimulated glucose utilization was at the level of glucose transport and/or phosphorylation and was present prior to the onset of the T2DM. The same defects could be induced with a lipid infusion in healthy subjects (106). Further, to quantify changes intramyocellular glucose, the Shulman lab developed a novel 13C MRS method to non-invasively assess intramyocellular glucose concentrations and reported that this was decreased under high plasma fatty acids, implying that lipid-induced muscle insulin resistance impaired insulin-stimulated glucose transport activity and not glucose phosphorylation (107). They studied subjects with T2DM with the same 13C MRS method and found that these subjects also had defects in glucose transport (108). These seminal observations firmly linked intracellular lipid accumulation to impaired insulin-stimulated muscle glucose transport and provided the needed clinical correlate to in vitro studies demonstrating impairments in insulin-stimulated GLUT4 translocation and impaired cellular glucose uptake (109). Intracellular lipid accumulation in skeletal muscle and liver is associated with insulin resistance. These “ectopic sites’’ for lipid accumulation were probed to identify the lipid species responsible for impairing insulin signaling. Of the array of bioactive lipids that were plausible candidates, diacylglycerols emerged as leading contenders. These lipid species were consistently elevated

Metabolism and Medicine in insulin-resistant tissues. They are also activators of a family of kinases that are capable of interfering with insulin signaling: the “novel” protein kinase C (PKC) isoforms (i.e., δ, ε, η and θ). Studies in rodents and humans demonstrated activation of PKCθ in insulin-resistant skeletal muscle (110, 111) and PKCε in insulinresistant livers (112). The most recent studies from the Shulman lab have provided a greater resolution to this model. The current data shows that it’s the accumulation of the lipogenic sn-1,2-diacylglycerols in the plasma membranes of key tissues that activates nPKC’s, specifically PKCε in liver and white adipose tissue (113, 114). PKCε then phosphorylates the insulin receptor molecule at a specific residue (T1160) near a critical tyrosine site (Y1162) (115). This proximal defect in insulin signaling prevents insulin from activating the array of intracellular actions that coordinate energy storage. The Shulman group has also explored the reasons underlying ectopic lipid accumulation. While multiple etiologies likely exist, a broad model considers the imbalance between lipid delivery and oxidative capacity. The studies in the young, lean, insulin-resistant individuals demonstrated a decreased capacity for mitochondrial oxidation (116, 117). Similar changes were seen in aged patients with insulin resistance (118). This defect in skeletal muscle oxidation could lead to muscle insulin resistance and glucose tolerance, providing the carbohydrate substrate to drive hepatic lipogenesis and promote hepatic steatosis (117) but can be improved with exercise (119). Patients with congenital lipodystrophies lack fat tissue, are hypoleptinemic and hyperphagic leading to marked lipid accumulation in the liver and severe insulin resistance; both can be reversed with leptin therapy (120). In South Asians, polymorphisms in ApoC3 may impede peripheral clearance of lipid-laden chylomicron by adipose tissue, redistributing lipids to the liver and promoting insulin resistance (121). Weight loss can be beneficial in many groups. The negative calorie balance allows a reduction in ectopic lipid accumulation and improvements in insulin sensitivity (122). But, this is hard to achieve for most patients without surgery. As of this writing, the Shulman lab has been developing mitochondrial-targeted therapies, optimizing uncoupling agents to promote hepatic lipid oxidation, reduce sn-1,2-diacylglycerol accumulation and improve insulin sensitivity (123, 124).

7.3.5 Spotlight on Philipp Scherer’s Work on Ceramides and Inflammation

Philipp E. Scherer, PhD, Professor and Director, Touchstone Diabetes Center, University of Texas Southwestern Medical Center, Dallas (Used with permission).

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Insulin Resistance in Metabolic Disease The work of Philipp Scherer and colleagues has focused on adiponectin, a hormone derived from adipose tissue, which his group discovered in 1995 (125). This was the second adipokine to be discovered, following the discovery of leptin in 1994 (126). Adipose tissue became recognized as the most prodigious endocrine “organ” with powerful regulatory effects on metabolic homeostasis and health. The acknowledgment of the prominent role of adipose tissue precipitated an intense interest in adipose physiology coupled with the identification of many more adipokines over the following decades. Scherer’s work has beautifully illustrated the importance of healthy adipose tissue, and how dysfunction can lead to insulin resistance and diabetes. As obesity develops, healthy expansion of adipose tissue can preserve insulin sensitivity and metabolic health; it is only when adipose tissue becomes hypoxic, inflamed, and unable to efficiently store the excess lipid that insulin resistance and metabolic syndrome develop. Lipids begin to accumulate outside of adipose tissue, known as ectopic fat. Ectopic fat deposits in tissues such as the liver, skeletal and cardiac muscle, pancreas, and the brain, are a major cause of inflammation as well as mitochondrial dysfunction and lost synchronization of circadian insulin signaling within and between these organs and their systems. Scherer elegantly demonstrated this concept by overexpressing adiponectin in a leptin-deficient mouse (127). The resulting mouse was massively obese (upwards of 100 grams!), with expanded white adipose tissue made up of small and non-inflamed adipocytes. The mouse was metabolically healthy, with healthy lipid profiles, clean livers, and high insulin sensitivity, thus proving that healthy expansion of adipose tissue can completely prevent the metabolic dysfunction often associated with obesity. In 2005, Scherer developed the “ATTAC” mouse (apoptosis through targeted activation of caspase 8); this groundbreaking model allows researchers to selectively knock out specific cell types in a mouse any time during its development (128). Using this model, Scherer’s group made the FAT-ATTAC mouse, which can be depleted of white adipose tissue with an intraperitoneal injection of an FK1012 analog (129). Without healthy adipose tissue, the FAT-ATTAC mouse develops glucose intolerance and insulin resistance, making this an important model to tease apart the effects of adipose tissue. Of note, the ATTAC mouse has been used to selectively knock out several other cell types, including beta cells, podocytes, and senescent cells (130–132). Around 2011, Scherer’s work expanded to focus on the interaction of adipokines and lipid species with metabolic disease processes, systemic and tissue-specific lipotoxicity, inflammation, and insulin resistance (133, 134). Of particular interest was how these processes contributed to the pathogenesis of type 2 diabetes, cancer, and neurodegenerative and cardiovascular diseases (135, 136). Scherer, however, became most interested in the structurally and functionally robust class of a lipid species known as sphingolipids and their notable backbones comprising a ceramide subgroup (137, 138). Sphingolipids, including ceramides, have diverse and crucial physiological duties in the cell. One of their functions is to act as signaling molecules for cell cycle regulation. They also serve as key structural components of cell membranes and are inextricably linked to the overall function of the cell and its mitochondria (139). Despite their beneficial effects, ceramides can also be deleterious to the structures and functions

of many cell types. For example, high ceramide levels within ectopic fat deposits appear to lie at the center of chronic disease pathogenesis in most cases (140, 141). In 2017, Phil Scherer’s group made another groundbreaking discovery: fat cells produce uridine (142). Uridine is one of the eight major nucleosides that make up our genetic code. While circulating uridine levels are controlled by the liver in the fed state, during fasting, Scherer showed that adipocytes are uridine’s primary source. Further, this uridine release is a key regulator of the drop in body temperature that occurs with fasting, as a compensatory response to conserve energy. Thus, Phil Scherer has been at the leading edge of our understanding of adipose tissue health and disease.

7.3.6 Ceramides, Ectopic Lipids, and ROS In the case of liver steatosis, fatty acids pour into the liver as a result of chronically unsuppressed lipolysis of visceral adipose tissue. It has been proposed that ectopic fat accumulation in the liver increases the levels of fatty acid metabolites such as diacylglycerols (DAGs) (143–145). DAGs can activate protein kinase C isoforms, including PKCε/ PKCθ, which reduce PI3K activation and downstream insulin signaling, indicating that activation of this pathway may be central to the development of insulin resistance (Section 7.4.1.4). Overwhelming the liver with fat also leads to packaging and unloading small dense LDL particles and VLDL TG particles into the circulation, which, together with lipid remodeling and the resulting low HDL and small HDL particle size, represents the atherogenic dyslipidemia of insulin resistance. It should be emphasized that ceramide is not inherently bad, but when levels become excessive, it contributes to the loss of metabolic homeostasis in tissues, thus defining pathology. It’s important to underscore the idea that all parameters and regulators of redox, energy, and acid-base homeostasis have a bell-shaped curve. This is the idea of hormesis: The midrange of a given metabolic regulator is optimal, while too little or too much may have pernicious effects. The many hierarchical scales of parameters and regulators of whole-body metabolic homeostasis illustrate the organizational complexity of biological systems and the essential need to understand health and disease in the context of whole systems rather than silos. Ceramide and its regulation provide a nice example of this. Hence, it follows that balanced levels of ceramide promote adaptive physiology by inducing programs of resistance to cell redox stress, such as mitophagy to remove dysfunctional mitochondria or even induce apoptosis if a cell is damaged beyond repair. Consider unhealthy levels of adiposity: too little, such as in lipodystrophy, or too much compromise metabolic health by disturbing the physiological regulation of ceramide. In these contexts, optimal adiponectin levels (among many other adipokines) are disturbed, along with its ability to maintain the proper balance of ceramide and its anti-apoptotic metabolite, sphingosine-1-phosphate (S-1-P), which otherwise mediates the insulin-sensitizing, anti-diabetogenic, anti-inflammatory, cardio- and neuro-protective properties. However, optimal adiponectin-induced ceramidase activity is cell-type dependent with a higher ratio of ceramide to S-1-P serving as a lipid tumor suppressor to limit cancer cell replication by interfering with the cell cycle, or by inducing cell apoptosis (146).

286 Fibroblast growth factor 21 (FGF-21), a member of the FGF super family found naturally in significant levels in raspberries, is released from the liver in response to prolonged fasting, and from skeletal muscle following insulin stimulation (147). It triggers the release of adiponectin from adipose tissue, which is responsible for its glucose-lowering, insulinsensitizing, and anti-inflammatory effects. As described in the above discussion, much of these adiponectin effects are the result of its actions on ceramide. Intriguingly, the only class of diabetes drug therapy known as “true insulin sensitizers”, the thiazolidinedione PPARɣ agonists, act by the induction of FGF-21 (134, 148, 149). Taken together, FGF-21 exemplifies another layer or hierarchical regulatory scale for maintaining metabolic homeostasis, as well as an effective therapeutic target for potentially restoring homeostasis when things go awry. Adiponectin increases fatty acid oxidation by mechanisms that include promoting PPARɑ pathways (150, 151). Activated PPARɑ drives the transcription of enzymes involved in mitochondrial oxidative metabolism. Adiponectin also upregulates AMPK activity, which by inactivating phosphorylation of acetyl CoA carboxylase (ACC), the resulting reduction of malonyl CoA synthesis disinhibits carnitine palmitoyl transferase (CPT-1), thus driving fatty acid oxidation (152, 153). AMPK also promotes mitochondrial biogenesis by activating phosphorylation of PGC1 alpha, which in turn increases fatty acid oxidation longer term (154). Additionally, adiponectin prevents ceramide lipotoxicity mediated degradation of mitochondrial bioenergetics

7.3.7 Chronic Diseases of Aging as Manifestations of Insulin Resistance The greater share of total fat storage capacity in the body is determined by the number of subcutaneous adipocytes, which are larger than visceral adipocytes. Subcutaneous adipocytes derive from the mesenchyme, while visceral adipocytes derive from myeloid bone marrow progenitor cells (155). When fat cells become engorged by lipid accumulation, the cell’s blood supply required for functional needs is exceeded. The resulting adipocyte hypertrophy leads to hypoxia and the induction of hypoxia-inducible factor 2 alpha (HIF1α) (156), causing local and systemic inflammatory responses. Locally, insulin signaling is disrupted within the adipocyte, leading to exaggerated lipolysis and spilling of non-esterified free fatty acids and glycerol into the bloodstream. Hyperlipidemia results in the ectopic seeding of fat in organs such as the pancreas. Pancreatic steatosis, or fatty pancreas, promotes beta cell impairment and insulinopenia (inadequate insulin secretion) relative to the degree of insulin resistance in skeletal muscle, hepatic, and adipose tissues. The consequent hyperglycemia (high blood glucose) may progress to diabetes in addition to contributing to de novo lipogenesis in the liver, worsening hepatic steatosis (fatty liver), and atherogenic dyslipidemia (elevated LDL and triglycerides, reduced HDL) (157). Other tissues where ectopic fat can seed include skeletal muscle, and others unequipped to serve as lipid storing depots, such as the heart and the brain. Obesity is an established risk factor for Alzheimer’s disease and ectopic fat plays a role in this association. Just as Scherer’s

Metabolism and Medicine work connects ectopic fat and ceramide accumulation with insulin signaling in various organs, ectopic fat accumulation in the brain reduces insulin signaling and accelerates cognitive decline. Accumulation of certain types of lipids, such as ceramides, has been shown to cause brain mitochondrial dysfunction. Ceramide and diacylglycerol-induced inflammatory cascades prototypically inhibit insulin signaling. Lipids stored ectopically are a source of excess mitochondrial fatty acid oxidation. This is associated with an overburdened electron transport system that leads to redox stress and excess generation of ROS in mitochondria. The proximity of ROS to the molecular structures of this energy-producing organelle makes it particularly vulnerable to the harmful effects of said redox stress. Mitochondria become dysfunctional and exacerbate a feedforward reduction in their capacity to oxidize fatty acids, resulting in even higher and more toxic levels of ROS. The brain’s high demand for energy makes it vulnerable to the accumulation of dysfunctional mitochondria, which is associated with neurodegenerative disorders including Alzheimer’s disease (see Chapter 9, Section 9.3.6). Defective mitochondria generate ROS, which can eventually lead to neuronal death (158–160). Mitophagy, a form of autophagy, serves to preserve the nervous system’s physiology, and can drive the pathogenesis of Alzheimer’s and other neurodegenerative diseases when it fails (161, 162). The energy deficit and excess ROS generated by dysfunctional mitochondria promote insulin resistance in the brain, and ultimately amyloid beta accumulation and clinical signs of Alzheimer’s (163–166). Obesity, mitochondrial dysfunction, insulin resistance, hyperinsulinemia and/or diabetes can also lead to the initiation and proliferation of cancer. The setting of insulin resistance in classic insulin target tissues, particularly skeletal muscle, and subsequent hyperinsulinemia, can promote mitogenic and inflammatory pathways within non-classical insulin target tissues, such as epithelial, endothelial, and myocardial cells, as well as the gastrointestinal tract, the reproductive systems, the kidneys, the thyroid, and neurons and glia in the brain (167). While insulin does not directly transform cells, hyperinsulinemia does drive mitogenic pathways of cell proliferation, as well as inflammatory pathways leading to redox stress and potentially cancer cell initiation. For example, the transcription factor nuclear factor kappa-light-chain-enhancer of activated B cells (NFκB) and ROS bidirectionally upregulate one another in a feedforward fashion. Consequently, redox stress is generated within the cell that can oxidatively modify molecular components of the cell. Modifications can be made to DNA causing mutations (oncogenic or other) in genes that govern cell growth and differentiation (Ras-Raf-MAPK pathways). ROS, particularly peroxide (H2O2), diffuses across the mitochondrial membrane into the cytoplasm and inhibits several downstream glycolysis pathway enzymes. This creates a bottleneck when it comes to synthesizing proximal glycolytic intermediates which leads to their buildup and ultimately to inflammation, redox stress, and mitochondrial dysfunction. Further, the excess glycolysis intermediaries act as building blocks for cancer cell replication. This is the basis for Michael Brownlee’s 2005 hypothesis (see detailed discussion in Chapter 1, Section 1.11.2). We suggest that hyperlipidemia, in addition

Insulin Resistance in Metabolic Disease to hyperglycemia, could be another feature of the Brownlee Hypothesis, which may be intertwined with “The Warburg effect”, a metabolic adaptation of cancer cells that allows them to outcompete native cells for nutrient resources. Further, it may be proposed that dysfunctional metabolic dynamics of the Brownlee hypothesis are applicable to all chronic diseases of aging, potentially in some cases synergistically with the Warburg effect in the same cells. This may particularly be the case in chronic disease states associated with abnormal cell replication, such as hypertrophic cardiomyopathy and proliferation retinopathy. Several parallel, offshoot pathways of the glycolysis pathway contribute to cardiomyopathy, as they likely do for most chronic diseases of aging. These include the hexosamine pathway with the production of N-acetyl glucosamine (GLcNAc), which can bind contractile myofilaments, and impair contractile function. In concert, the protein kinase C and the advanced glycation end-product (AGE) pathways promote self-amplifying cascades of inflammatory and bidirectionally associated redox stress responsible for oxidative modifications of cell structural components (Figure 7.6). Furthermore, hyperglycemia with glucose accessing the cell via non-insulin-dependent transporters, potentiates glycolysis activity and the parallel pathways starting from proximal intermediates of this central pathway. The building blocks of cell replication derive largely from the pentose phosphate pathway (PPP; for nucleotide and lipid synthesis) and serine mediated

287 one-carbon metabolism pathways (for nucleotide and amino acid synthesis; Figure 7.7). Taken together, these pathways lead to the dysfunctional manifestations of both diastolic and systolic cardiomyopathy. Diabetic cardiomyopathy appears to involve a progression from what is initially cardiac myocyte replication and myocardium hypertrophy with fibrosis and diastolic dysfunction, to later-stage cardiac dilation and systolic failure. Ceramides, specifically those of the long-chain variety, appear to further promote lipotoxic myocardial dysfunction by targeting mitochondria (Figure 7.8) (168). Adaptive mitophagy (mitochondrial degradation through autophagy), and apoptosis in some cases when cell redox damage is extensive, are both protective against the acceleration of myocardial dysfunction. However, when lipotoxic damage is substantial and progressive, even the initial safeguarding responses of mitophagy and apoptosis themselves contribute to the later stages of systolic heart failure. Furthermore, the cause and effect relationship of ceramides to vascular (particularly cardiovascular) disease has explosive implications such that ceramides as a biomarker could be the ‘new cholesterol’ that can be used to predict disease risk (169). In fact, total and LDL cholesterol, insulin resistance, visceral adiposity, and incidence of type 2 diabetes, cardiovascular disease (CVD) and major CVD events were robustly correlated with blood ceramide levels (170–173). Plasma ceramides transported in LDL particles promote atherogenesis by encouraging the uptake and infiltration

FIGURE 7.6  Brownlee’s Unifying Hypothesis depicts the results of hyperglycemia-induced increases in ROS generation in the mitochondria along the electron transport system that inhibits the activity of glyceraldehyde-3-P dehydrogenase (GAPDH), resulting in the bottlenecking of the glycolysis pathway intermediates leading to the activation of non-energy producing pathways. Increasing glyceraldehyde-3-P activates AGE and PKC pathways, while an increase in fructose-6 phosphate enhances the hexosamine pathway. In addition, there is an increase in pyruvate conversion to lactate, and an impaired conversion of pyruvate to acetyl-CoA in the mitochondria, resulting in an increase in fatty acid oxidation. *AGEs = advanced glycation end products; CoA = coenzyme A; DAG = diacylglycerol; ETC = electron transport chain; FAO = fatty acid oxidation; GADPH = glyceraldehyde 3-phosphate dehydrogenase; GFAT = glutamine fructose-6-phosphate aminotransferase; GLcNAc = N-Acetylglucosamine; Glu = glutamic acid; Gln = glutamine; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; NFκB = nuclear factor kappa-light-chain-enhancer of activated B cells; PARP = Poly (ADP-ribose) polymerase; PDC = pyruvate dehydrogenase kinase; PFK = phosphofructokinase; PKC = protein kinase C; ROS = reactive oxygen species; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle); Upd = uridine diphosphate glucose.

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FIGURE 7.7  Insulin resistance and mitochondrial dysfunction are inextricably related through a self-amplifying feedback loop. This leads to the development of chronic diseases of aging through the mechanisms of both the Warburg effect and the Unifying Hypothesis Extension. The Warburg effect describes Increased glycolysis that results in an increase in the PPP as well as in one-carbon metabolism. Both of these pathways lead to the biosynthesis of the building blocks required for cell replication. The Unifying Hypothesis describes an increase in ROS that inhibits glycolysis pathway enzymes, creating a bottleneck resulting in upstream intermediates that activate non-energy producing pathways. In addition, the increase in ROS inhibits the PDC and hence the conversion of pyruvate to acetyl-CoA required for coupling the glycolysis pathway to the TCA Cycle, thus resulting in an increase in fatty acid oxidation and dysfunctional mitochondria. Collectively, these mechanisms contribute to the development of chronic diseases of aging. *CoA = coenzyme A; FAO = fatty acid oxidation; PDC = pyruvate dehydrogenase kinase; PPP = pentose phosphate pathway; ROS = reactive oxygen species; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

of LDL into the subendothelial space of the vasculature. Ceramides within LDL of atherosclerotic plaques are present in quantities up to 50-fold higher compared to circulating LDL (174). Further, under the influence of ceramides, LDL content within atheromatous plaque increases 50-fold (175). The inflammatory cytokine TNF-alpha has long been known to have an important role in promoting atherogenesis. Modur and colleagues demonstrated that TNF-alpha promotes de novo synthesis of ceramide within vascular endothelial cells (176). Others have shown ceramide accumulation within these cells occurs via TNF-alpha-mediated enzymatic cleavage of ceramide from a larger sphingomyelin lipid molecule. The inherently proinflammatory nature of ceramides promote ROS and thus the formation of oxidized LDL within atherosclerotic lesions. With high levels of ROS and ceramides in vascular endothelial and smooth muscles cells, the physiological balance of vascular tone mediated by such regulators as nitric oxide, prostacyclin, thromboxane A2, endothelial 1 and angiotensin 1, becomes interrupted and endothelial dysfunction ensues (177–180). The proinflammatory, insulin resistance, diabetogenic effects, and other lipotoxic properties of intracellular ceramide impose a major toll on metabolic homeostasis.

Excessive ceramide can promote mitochondrial dysfunctionmediated apoptosis in the heart to pathogenetically underpin cardiomyopathy, as well as insulinopenia, diabetes, Alzheimer’s disease, and Parkinson’s disease. Furthermore, ceramides independently exacerbate the risk of major cardiac events such as fatal and non-fatal heart attacks, sudden death, and stroke by promoting platelet activation and endothelial dysfunction, the latter by impairing nitric oxide-mediated physiological vasodilation. Moreover, Meeusen and colleagues have developed a ceramide cardiovascular risk stratification score independent of traditional risk factors (181). It has been suggested that an important link to the therapeutic benefit of statins to non-fatal heart attacks and stroke is their effect on ceramide-mediated oxidative and inflammatory stress (182, 183). A range of ceramide lowering strategies, such as targeting ceramide double bonds that reduce insulin resistance and hyperinsulinemia-mediated hepatic steatosis, and other intervening therapies have been shown to improve additional insulin resistance and hyperinsulinemia manifestations of metabolic syndromes and atherogenesis (184–189). Hypercholesterolemia (high cholesterol) is itself not considered a risk factor for stroke, however, statin therapy, a treatment for high cholesterol, has been shown to reduce stroke risk by roughly 35% because of the anti-inflammatory and antioxidative properties of statins (190, 191).

Insulin Resistance in Metabolic Disease

FIGURE 7.8  Role of ceramides in heart disease. More than a type of fat, ceramides can act as signaling molecules with deleterious consequences for health. Source: adapted from (181). *LDL = low-density lipoprotein; MACE = major adverse cardiac and cerebrovascular events.

As described throughout the chapters of this book, the inextricable intertwining of disturbed redox homeostasis, inflammation, and impaired bioenergetics, appear to be fundamentally linked to the chronic diseases of aging, including cardiovascular disease, dementias, and cancers. Moreover, these manifestations of advanced and often premature biological aging are largely mediated by pathogenic control parameters of a chronic exaggerated stress response, and dis-synchronous circadian metabolism and physiology within and between tissues. All of these factors are also inseparably entangled. The states of abnormal redox, free energy, and human biology cause diseases of aging. Diseases of aging form their own selfamplifying feedforward webs of pathogenicity.

7.4 Foundational Concepts of Insulin Resistance 7.4.1 Insulin Resistance and Metabolic Flexibility 7.4.1.1 Clinical Tools: The Respiratory Quotient Mitochondria play a key role in balancing nutrient availability with nutrient metabolism. Importantly, healthy mitochondria show flexibility in response to environmental changes. These organelles are also able to adapt to cycling changes in fuel sources (fat and/or glucose) within a circadian rhythm. Respiratory quotient (RQ), the ratio of CO2 production to O2 consumption reflects the substrates utilized by cells and can serve clinically to assess the level of mitochondrial flexibility. Under healthy conditions, RQ ranges from 0.7 to 1.0. Changes in the ratio reflect mitochondria adapting to different fuel sources. For example, oxidation of fats results in a lower value, while glucose oxidation results in a higher value (reflecting the fact that carbohydrates contain oxygen which contributes to carbon dioxide formation, while fatty acids do not). Therefore dynamic changes in RQ acts as a whole-body parameter that reflects the ability of mitochondria to adapt

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FIGURE 7.9  Under healthy conditions, cyclical insulin resistance is adaptive and promotes FOXO-mediated stress resistance programs as well as energy and redox homeostasis. Under pathologic conditions of insulin resistance, a lack of insulin causes FOXO to be constitutively activated leading to an increase in hepatic glucose output, decreased glucose uptake in the liver, and decreased insulin secretion from the pancreas. *FOXO = forkhead box protein; IR = insulin resistance.

to changes in nutrient intake. Under conditions of increased energy expenditure or reduced caloric intake, RQ values are lower as metabolic tissues such as skeletal muscle, myocardium (heart muscle), and the liver utilize fat as an energy source. Glucose is conserved for the brain, as this organ is less able to adapt to utilizing fat as an energy source. Adipose tissue lipolysis (metabolism of lipids) promotes fatty acid availability to the body when resources are scarce. This metabolic orchestra is synchronized and directed by numerous factors, including hormonal signals, neural innervations, and the oscillating circadian biological clocks within metabolic tissues. Modern perspectives on metabolic flexibility can be defined as the capacity of the body to adopt or respond depending on changes in metabolic conditions, activity, and energy demand. Classical perspectives though referred to just skeletal muscle and its ability to nimbly switch to carbohydrate from lipid oxidation as the fuel source for ATP at the transition of the fasting to the feeding phase. Per the modern definition, adaptable fuel sourcing in all flexible metabolic tissues is mediated by insulin and FOXO signaling (Figure 7.9). In metabolically flexible individuals, meals can elicit wide swings in RQ with relatively minimal changes in insulin secretion to maintain normal blood glucose concentrations (euglycemia). With a pathological transition to noncyclical insulin resistance, these rhythms become desynchronized and metabolism becomes inflexible (Figure 7.9). In fact, a hallmark feature of pathological insulin resistance and type 2 diabetes is the loss of adaptive metabolic flexibility. The degree of insulin resistance is reflected by variation in insulin’s response to carbohydrate intake. Additionally, mitochondrial damage can accrue with time, constraining oxidative capacity. As a result, mitochondrial engines are unable to appropriately adjust to changes in nutrient source in the setting of insulin resistance.

290 Galgani and colleagues proposed that RQ can be used to assess the impairment of metabolic flexibility in insulin-resistant muscle tissue when it transitions from carbohydrate to lipid oxidation overnight or when the body is introduced to a high-fat diet (192). As such, RQ has been shown to correlate with the loss of insulin sensitivity and metabolic flexibility that leads to impaired fatty acid oxidation. Insulin resistance therefore represents the impaired ability to upregulate fatty acid oxidation during a transition from feeding to fasting. This results in the buildup of IMCL, particularly ceramides and diacylglycerols (Figure 7.10).

7.4.1.2 Dyssynchronous Insulin Signaling and the Loss of Metabolic Flexibility Impaired insulin signaling impacts numerous cellular metabolic processes such as glucose uptake and regulation of FOXO transcription factors. As insulin resistance worsens, crosstalk between tissues becomes impaired. In the setting of healthy insulin signaling, the liver is normally capable of storing nutrients in the forms of glycogen and triglycerides during the daily cycle’s feeding phase (prandial insulin-sensitive phase). Alternatively, during the fasting phase of the daily cycle, the liver releases lipoprotein in the form of VLDL-triglyceride, and glucose releases via glycogenolysis and gluconeogenesis. Pancreatic insulin secretion patterns and peripheral sensitivity to insulin are also coordinately regulated during the feeding and fasting phases. Feeding and fasting cycle regulation of nutrient output from the liver and insulin secretion from the pancreas allows for the constant availability of nutrients for use by the brain and peripheral tissues independent of the circadian cycle phase, and the presence or absence of extrinsic resource availability.

FIGURE 7.10  The bidirectional relationship between insulin resistance and mitochondrial dysfunction causes a decrease in lipid oxidation. This, in turn, increases the RQ, leads to the accumulation of ectopic fat (fat stored away from adipose stores) and ultimately a buildup of ceramides and diacylglycerol. *ATP = adenosine triphosphate; RQ = respiratory quotient.

Metabolism and Medicine When the body is in a state of chronic insulin resistance, rescue programs for cell redox damage that typically occur during the daily cycle’s sleep phase become impaired. This along with the system’s additional loss of various forms of adaptive flexibility causes disturbances in the temporal balance between redox and metabolic homeostasis such as disrupted regulation of glucose and lipid output from the liver. Compensatory hyperinsulinemia ensues which may further stimulate hepatic lipogenesis and adipose hypertrophy with the spillover of non-esterified fatty acids into the bloodstream (193). Consequently, excessive accumulation of ectopic lipids in tissues systemically leads to cellular dysfunction mediated by redox and inflammatory stress, which ultimately promotes the pathogenesis of insulin resistance and chronic disease (194). And, in some individuals, a propensity of islet dysfunction leads to declines in insulin secretion that then bring about hyperglycemia and diabetes.

7.4.1.3 The Development of Pathogenic Hyperinsulinemia and Insulin Resistance The molecular pathways that underpin the transition of insulin resistance to impaired glucose tolerance and type 2 diabetes continue to be debated. There is some agreement however regarding the notion that fasting hyperinsulinemia, followed by fasting hyperglycemia, accompanying insulin resistance is the initial phase of type 2 diabetes. This is followed by earlyphase postprandial (post-meal) hyperglycemia and then fasting hyperglycemia. Insulin resistance develops before the onset of hyperglycemia in most cases. In one model, the accumulation of bioactive lipid species in ectopic sites (i.e. skeletal muscle, liver), impair insulin signaling. The body responds with hyperinsulinemia. Compensatory hyperinsulinemia in these early stages also acts to prevent fasting hyperglycemia, even in the setting of exaggerated hepatic glucose output. At the same time, hepatic lipogenesis promotes overall lipid accumulation. This occurs because the activity of the enzyme glucokinase (GCK, glucose sensor in pancreatic beta cells) is upregulated to promote systemic glucose uptake, while the activity of glucose 6-phosphatase (G6Pase), which produces free glucose from glucose-6-phosphate, is suppressed due to compensatory hyperinsulinemia of the insulin-resistant liver. In addition, peripheral insulin resistance can increase postprandial glucose delivery to the liver. This increased glucose influx acts as both a substrate and molecular regulator of hepatic de novo lipogenesis via transcription of carbohydrate response element binding protein (ChREBP). In addition, in insulin-resistant liver, there appears to be continued activation of sterol regulatory binding protein 1c (SREBP1c), which also promotes hepatic lipogenesis. The underlying mechanism of how SREBP1c activity is maintained in an insulin-resistant liver remains unclear and some have proposed that this paradox can be explained by bifurcations in insulin signaling. As stated, postprandial hyperglycemia occurs prior to the onset of fasting hyperglycemia. This early phase in the evolution of insulin resistance to type 2 diabetes coincides with a beta cell defect as a result of the decline in glucokinase activity and is controlled by FOXO transcription factors tightly regulated

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Insulin Resistance in Metabolic Disease by insulin signaling through the PI3K/Akt pathway. Insulin acts through this pathway via a feedback loop to inhibit FOXO, which prevents insulin transcription, consequently reducing insulin secretion from the beta cell. This beta cell defect diminishes postprandial insulin secretion, which especially in the context of peripheral insulin resistance leads to glucose intolerance, the signature biochemical hallmark of prediabetes (195). Alternatively, some would prefer a different explanation for the evolution of hyperglycemia from the insulin-resistant state. Insulin resistance alone does not generally cause diabetes. Many patients who are insulin resistant are able to maintain euglycemia, albeit at the expense of compensatory hyperinsulinemia. The hyperinsulinemia can presumably overcome defective insulin signaling to still activate downstream pathways (i.e., Akt2 and FOXO). However, some patients are predisposed to beta cell failure, likely due to a combination of factors, including genetics and age. Richard Bergman’s group contributed greatly to our quantitative understanding of wholebody insulin physiology. Trained as an engineer, Bergman developed a mathematical model (the “Minimal Model”) that quantified insulin sensitivity and beta cell function from an intravenous glucose tolerance test. This allowed researchers to quantify these parameters in one quick test, as opposed to performing two separate glucose clamps. Measurement of these two parameters at the same time allowed researchers for the first time to compare them simultaneously, and in larger numbers of animals and subjects due to the ease and lower expense. Bergman went on to quantitatively describe the relationship between these two parameters as the disposition index—defined as the product of beta cell function and insulin sensitivity. The disposition index (DI) may remain constant in healthy individuals as they traverse various physiological stages of life (illness, pregnancy, growth, fasting), but some patients and populations at risk for diabetes can have lower DI. Insults to beta cell function, as well as genetic predisposition, lead to a decline in DI, which then predicts diabetes. In those patients, the fall in insulin secretion leads to postprandial and eventually fasting hyperglycemia (195). Tom Buchanan’s group showed in a high-risk population—women with previous gestational diabetes—that those who go on to develop type 2 diabetes show a progressive decline in their disposition index (196). However, treatment with an insulin sensitizing drug prevented that decline in DI and the development of diabetes. As organizational precision of the body declines with age, desynchronization of insulin secretion with fasting/feeding and sleep/wake cycles can result in pathogenic insulin resistance. Insulin resistance loses its periodic circadian rhythm and becomes associated with relative postprandial insulinopenia and fasting hyperinsulinemia. Moreover, desynchronized insulin secretory and peripheral sensitivity patterns promote dyssynchrony among endogenous molecular clock-controlled output genes which causes downstream metabolic dysfunction. This compromised temporal organization across all of these factors is mediated by impaired bioenergetics of ATP production and limited availability of Gibbs free energy (the infrared energy released from the bonds of ATP) that accompanies redox stress. Departure from a healthy dietary and consistent circadian lifestyle promotes obesity and insulin resistance, and makes

the individual more susceptible to premature aging and chronic diseases. These metabolic responses are accelerated in response to reduced resource availability and engage members of the thyroid and steroid nuclear receptor superfamily that couple metabolic output with molecular clocks. Nuclear receptors as discussed in great detail in Chapter 3 should be recognized not only in the context of systemic hormone signaling but as mediators of energy and stress resistance in the cell. These endogenous molecular timepieces are a stunning evolutionary design for the temporal organization of metabolic physiology and behavior of living systems.

7.4.1.4 Ectopic Lipid Accumulation and Insulin Resistance Under normal physiological conditions, fatty acids are transported in triglyceride-rich lipoprotein particles such as chylomicrons and very low density lipoproteins (VLDL). Chylomicrons are exogenous lipids derived from the gut, whereas VLDLs are endogenous lipids originating from the liver. During fed conditions, chylomicrons distribute triglyceride to various tissue such as adipose, skeletal muscle, and heart by interacting with the enzyme lipoprotein lipase (present in capillary beds, i.e., extracellular), which catalyzes triglycerides into free fatty acids and glycerol. As a result, these tissues take up free fatty acids (197). Skeletal muscle and heart use these fatty acids as an energy substrate. In contrast, adipocytes reesterify these FFA into triglycerides, which are packaged into lipid droplets. During fasting states, when blood glucose and insulin levels fall, adipocytes are stimulated by noradrenaline/glucagon to activate intracellular lipases such as hormone-sensitive lipase (HSL), adipose triglyceride lipase (ATGL), and monoacylglycerol lipase (MGL). These release free fatty acids from stored triglycerides into the blood for use as an energy substrate by the heart, skeletal muscle, and brown adipose tissue (198). In the liver, these fatty acids can be oxidized to produce energy or packaged into lipoprotein particles and secreted in the form of VLDL- triacylglycerol (TAG). Obesity is often associated with the dysfunction of adipose tissue. The ability of adipose tissue to store lipids varies, dependent on sex, age, fitness, and genetics, among other factors. When this capacity is exceeded, the overflow of free fatty acid from adipose tissue into ectopic tissues, such as the liver and skeletal muscle (ectopic lipid accumulation), leads to insulin resistance in the liver and muscle (199). The relation between adipose tissue dysfunction and insulin resistance in peripheral tissue and the liver has been considerably studied, but the mechanism is not well established. However, it has been proposed that elevated intracellular (liver and muscle) fatty acid increases the levels of fatty acid metabolites such as diacylglycerols (DAGs) (143–145) and ceramide (149, 200). DAGs are known activators of protein kinase C isoforms. The “novel” family of PKCs can be activated by DAGs, but unlike the classical isoforms do not require a concomitant calcium signal. Numerous studies have shown that novel protein kinases such as protein kinase Cε (PKCε) in the liver and PKCθ in the muscle are activated in insulin-resistant states. Subsequently, PKCε/ PKCθ impairs insulin signaling pathways, possibly leading to serine/threonine phosphorylation

292 of insulin receptor substrates 1 and 2 in skeletal muscle and threonine phosphorylation of the insulin receptor in the liver (201). Recent studies have also shown that an increase in DAG in white adipose tissue can also promote PKCε activation and impair adipose insulin signaling. Thus, DAG-mediated nPKC activation may be a core pathway for the development of insulin resistance. Impaired insulin signaling then dampens the downstream kinase cascade, i.e. PI(3) kinase-mediated and Akt phosphorylation. Consequently, translocation of glucose transporter from the cytoplasm to the plasma membrane and glucose uptake is reduced in the tissue(s). In an alternate model, ceramides have been implicated in the pathogenesis of insulin resistance. Ceramides may cause insulin resistance by blocking Akt phosphorylation by two mechanisms: 1) ceramide stimulates protein phosphatase 2A (PP2A), which dephosphorylates Akt; 2) ceramide inhibits translocation of Akt through PKCζ. The inhibition of Akt phosphorylation leads to decreased translocation of glucose transporter type 4 (GLUT4) from the cytoplasm to the plasma membrane and hence reduced uptake of glucose (149, 202).

7.4.2 The Role of Free Radicals and Oxidative Stress in Insulin Resistance Reactive oxygen species and reactive nitrogen species, or free radicals of oxygen- and nitrogen-containing molecules, can cause oxidative and nitrosative stress respectively. Depending on the levels of each, plus the physiological condition, it is possible for these species to have either healthy or pathological effects (hormesis). As such, low to moderate levels of free radicals under regulated conditions promote healthy physiological effects, whereas excessive and uncontrolled levels of free radicals promote chronic disease and accelerated aging sometimes associated with metabolic disturbances, insulin resistance, and diabetes (Figure 7.11).

FIGURE 7.11  At low or moderate levels, free radicals or reactive oxygen/nitrogen species exert beneficial effects on health by promoting cellular responses and immune function. High levels of free radicals generate oxidative stress, a pathogenic process that promotes disease.

Metabolism and Medicine

SIDEBAR 7.3: SOURCES OF FREE RADICALS There are both endogenous and exogenous sources of free radicals. Exogenous sources include pharmaceutical drugs, hormone metabolites (notably estrogen metabolites), industrial chemicals, chemicals in cigarettes, dietary processing, agriculture, and radiation. The largest source of endogenous free radicals and most relevant to chronic disease are mitochondrial-generated reactive oxygen species. NAD(P)H oxidase is a membrane-associated enzyme that catalyzes the production of superoxide through a one-electron transfer from NAD(P)H or NADH to molecular oxygen as the electron acceptor. NAD(P)H oxidases are a family of enzymes that play a vital role in host defense against invading bacteria and hence are present in innate immune cells such as neutrophils and macrophages. However, NAD(P)H oxidases also play a critical role in redox signaling and mediate diverse functions in the body. These enzymes are present in virtually all tissues and cell types. They have an important role in cell growth and apoptosis, angiogenesis, regulation of the extracellular matrix, and thyroid hormone biosynthesis to name a few. An important molecular mechanism underlying the pathophysiology of oxidative stress that leads to chronic disease states of aging associated with insulin resistance and diabetes is the nonenzymatic glycation of lipids and proteins. Exposure to sugars causes the glycation of lipids at phospholipid groups and proteins at lysine/arginine amino acid groups. Both cases lead to the creation of advanced glycation products (AGEs). Soluble, circulating protein AGEs or AGEs formed on collagen in extracellular space bind to the receptor for AGEs (RAGE) on endothelial cells of blood vessels, peroneal cells, epithelial cells of the gut or reproductive tract, cardiomyocytes, pancreatic beta cells, adipocytes, and immune cells. RAGE’s promote the signal transduction of AGE’s which trigger inflammatory responses and cellular dysfunction. Another pathophysiological basis of oxidative stress in insulin resistance and diabetes involves methylglyoxal, the major product of glycoxidation (autoxidation of glucose). Methylglyoxal, a protein glycating compound, binds to promoter regions and response elements of genes and contributes to DNA glycation. This is important as DNA glycation is the specific mechanism underlying oxidative and nitrosative stress that results in gene activation or inactivation. This in turn may result in cancer via the induction of oncogenes or silencing of apoptosis-inhibiting antioncogenes. Methylglyoxal can also form AGEs and significantly, has been associated with many of the same disease states linked to RAGEs, including atherosclerosis, central nervous system diseases, cancers, diabetes, obesity, epigenetic disorders, and accelerated aging. Glucose oxidation may also occur by the polyol pathway mediated by the aldose reductase enzyme that converts glucose to sorbitol and subsequently sorbitol to fructose. Fructose 3-carbon metabolites, most notably dihydroxyacetone (DHA) that are further converted to 3-deoxyglucosone can also form AGEs. Reactive oxygen species that result from these various mechanisms culminate into the manifestation of disease.

Insulin Resistance in Metabolic Disease Insulin resistance is associated with atherosclerosis and cardiovascular disease so it is useful to consider how reactive oxygen species can play a role in this pathophysiology (203). Reactive oxygen species promote endothelial cell dysfunction by inhibiting endothelial nitric oxide synthase (eNOS) and nitric oxide (NO)-mediated vasodilatation (204). This results in hypertension. Additionally, oxidative stress drives the oxidation of polyunsaturated fatty acids on the surfaces of low density lipoproteins (oxLDL). These reactive species also drive the oxidation of surface polyunsaturated fatty acids on apoproteins which are small dense LDL particles associated with insulin resistance. Notably, LDL, in addition to being modified by oxidation, may also be modified by glycation and acetylation. Modified LDL particles are more easily taken up into the subintimal space of blood vessels (the space immediately below the endothelial cells), particularly in the regions where blood vessels curve or branch. Inside the subintimal space, LDL particles are further oxidized and then taken up inside macrophages within the vascular wall. Lipid uptake within the macrophages results in foam cell formation, which is the beginning of the process of atherogenesis (fatty plaque formation in arteries). When macrophages reach their limit of lipid storage capacity and go beyond it, they rupture, releasing digested lipid into the subintimal space of the vessel wall. This massively amplifies and accelerates the inflammatory and atherogenic processes. Thus, ROS, which are increased in the insulin-resistant state, contribute to further insulin resistance and mediate many of the negative consequences of metabolic syndrome.

7.4.3 Implications of Insulin Resistance across Different Tissues of the Body Different tissues are affected by insulin resistance in different ways. Additionally, the ways systemic consequences to insulin resistance manifest directly relate to the level of insulin resistance. In the setting of hyperinsulinemia, for example, metabolic tissues that are highly insulin resistant like skeletal muscle, liver, and adipose, will be affected differently than tissues that are sensitive to insulin. Hyperinsulinemia can also promote crosstalk with other signaling pathways, and depending on the tissue, different signaling cascades may be co-opted. For example, this occurs in the breast under conditions of hyperinsulinemia where these mechanisms of crosstalk can provide therapeutic opportunities. Specifically, blockade of estrogen receptors diminishes hyperinsulinemiainduced effects that trigger mitosis (mitogenic) which would have otherwise occurred alongside insulin signaling pathways PI3K/Akt and Ras/MAPK. Hyperinsulinemia affects insulinsensitive non-metabolic tissues by promoting inflammation and redox stress, in part driven by stress of the endoplasmic reticulum. Unfortunately, the pathogenesis of total body insulin resistance in specific tissues is not completely understood, but it may be a heterogeneous process that depends on multiple individual factors. Insulin resistance also typically occurs in the pancreas as well as in areas in the brain. For example, the arcuate nucleus in the hypothalamus can become insulin resistant, leading to impaired satiety - an independent contributor to

293 obesity. Metabolic dysfunction occurring in the hippocampus links to accelerated cognitive decline as well as Alzheimer’s disease in individuals with underlying insulin resistance and type 2 diabetes. How insulin-resistant states develop in different tissues throughout the body as a whole is an area of ongoing research. Discoveries have the potential to improve the treatment of chronic diseases that are a consequence of insulin resistance. Skeletal muscle insulin resistance is due to a defect in glycogen synthesis consequential to impaired insulin-stimulated glucose uptake (ISGU). Although it remains a subject of debate, Shulman and colleagues showed that diacylglycerol DAG as a result of intramyocellular lipid accumulation accounts for the disturbance in ISGU, mediated by the insulinantagonistic effects of protein kinase C (PKC) theta (205). Consistent with the notion that insulin resistance-mediated type 2 diabetes is a metabolic disease of aging, a 70-year-old has roughly a 35% reduction in skeletal muscle mitochondrial oxidative metabolism compared to a 20-year-old. Accordingly, ectopic IMCL accumulation can occur even in the absence of obesity and associated spillover of fat from adipose tissue storage depots (118). Furthermore, lean adolescents with both parents who are insulin resistant, have themselves a 100% incidence of being insulin resistant with a demonstrated reduction in mitochondrial oxidative metabolism and presumably with IMCL deposits (116). Furthermore, it has been shown that genetic variants in enzymes that code for fatty acid oxidation in humans have shown a high incidence of insulin resistance and diabetes (206). Knockout mice models of the homolog of these genes caused severe insulin resistance in skeletal muscle and liver with associated IMCL deposits as well as DAG in both tissues (207). Secondarily, Peterson and others demonstrated that those individuals in the top quartile of normal glucose tolerance maintained euglycemia with a cost of hyperinsulinemia (208). This compensatory response in turn becomes a pathogenic driver of de novo lipogenesis in the liver. It follows that hepatic de novo lipogenesis and steatosis is a hallmark of insulin resistance. It is potentiated by the concurrence of hyperinsulinemia and hyperglycemia that evolves following the development of glucose intolerance. The progression of hepatic fat accumulation is responsible for triggering inflammatory liver injury accompanying transaminitis, which is now the most common etiology of cirrhosis and can lead to hepatic carcinoma. Moreover, once a threshold of lipid buildup in the liver is reached, the synthesis of triglyceride and VLDL particles and release into the circulation is accelerated. This process is responsible for the ensuing atherogenic lipid profile, mediated by remodeling of the VLDL particles, characterized by low HDL as well as elevated small dense LDL particles. Another related feature of insulin resistance-mediated dyslipidemia is exaggerated adipose tissue lipolysis. The high influx of fatty acids pouring into the liver from the portal circulation inhibits the degradation of apoB molecules. Thus, a greater content of apoB is integrated into the synthesized hepatic VLDL particles, representing an explanatory basis for the ultimate production of the apoB rich atherogenic small dense LDL particles (209). Perseghin and colleagues showed that 45 minutes of leg exercise reverses the impaired ISGU in skeletal muscle and

294 restores glycogen synthesis (210), while Rabøl demonstrated that the same duration of leg exercise increases hepatic glycogen synthesis as well as reduces DNL (119). Gluconeogenesis, is regulated by various mechanisms including insulin inhibitory actions on the transcription of key gluconeogenic enzymes phosphoenolpyruvate (PEPCK) and glucose-6-phosphatase (G-6-Pase), which are upregulated by insulin-antagonistic effects of counterregulatory hormones glucagon, cortisol, and growth hormone as well as circulating epinephrine. Precursor substrate molecules such as glycerol, feeding into the gluconeogenesis pathway are derived largely from lipolysis of visceral adipose tissue. However, it is the recently elucidated pharmacotherapeutic mechanisms of metformin-induced reductions in hepatic gluconeogenesis that provide the greatest and broadest implications to future physiological discovery. Madiraju and colleagues demonstrated that redox disturbance is the basis for the rapid rate of gluconeogenesis, and, by increasing redox in the liver metformin, inhibits gluconeogenesis (211, 212). A discussion of the basic scientific principles of redox, and its inextricable link to energy balance as a foundational component of overall metabolic homeostasis, can be found in Chapter 1 Sections 1.7.5–1.7.7. Madirajuet showed that metformin increases redox by inhibiting the conversion of lactate to pyruvate as well as of glycerol-3-phosphate in the liver to dihydroxyacetone phosphate (DHAP). This seminal discovery of metformin’s actions is described in Chapter 1 Section 1.7.6 to exemplify a clinical application of redox principles to medicine. Petersen and others showed that in the state of type 2 diabetes, there is a hyperbolic benefit of reduced fat in the liver with resulting improvement in fasting hyperglycemia and an increase in total body oxidative bioenergetics achievable by a relatively modest 10% weight loss (122). Kim and others showed that rodents in the absence of adiposity, and hence no capacity to store fat, ironically manifest the same hepatic and skeletal muscle insulin resistance seen in obese states of humans and rodents (205). Shulman demonstrated that transplantation of adipose tissue in these mammals improves insulin-stimulated glucose uptake in muscle and hepatic insulin sensitivity (205, 213). Humans with genetic states of lipoatrophy and leptin deficiency are analogous to these rodent models because there is no place to store fat other than in ectopic tissues such as skeletal muscle and the liver. This in turn causes and exacerbates insulin resistance in these tissues and is often associated with type 2 diabetes. Leptin treatment of these individuals, which reduces hyperphagia, restores insulin sensitivity in these tissues (120). Taken together, this work underscores why thiazolidinedione drugs, despite their storied history, improve the fundamental defects of skeletal muscle and liver insulin resistance by increasing subcutaneous adipocyte tissue storage capacity and changing the topography of fat deposition. Thiazolidinedione agents along with metformin are now recommended firstline drug therapy for the treatment of type 2 diabetes. Gerald Shulman described in his 2018 Banting lecture, based on the lipocentric pathogenesis of insulin resistance and diabetes, that targeting an upregulation of fatty acid mitochondrial oxidation would be another ideal pharmacotherapeutic approach.

Metabolism and Medicine

FIGURE 7.12  Hepatic mitochondrial uncoupling improves liver lipid and glucose metabolism and insulin sensitivity. Source: adapted from (214). *VLDL = very low density lipoprotein.

Such drugs are currently in the pipeline of research and development that work by promoting the uncoupling of fatty acid oxidation to ATP production in the liver (Figure 7.12). This approach increases the burning of acetyl CoA, rather than allowing the alternate pathway of gluconeogenesis, following delivery of excess fatty acids and glycerol to the liver due to exaggerated adipose tissue lipolysis in states of insulin resistance. Additionally, it prevents the formation of DAG and subsequent activation of PKC epsilon in the liver, thus promoting glycogenesis rather than glycogenolysis. The reduction in glycogenolysis and gluconeogenesis helps to normalize fasting hyperglycemia, as well as the superimposed component of relatively uninhibited hepatic glucose output by meals (201). Shulman concluded his 2018 Banting discussion by emphasizing that in addition to the glycemic benefits of increasing hepatic fatty acid oxidation, its effect on reducing hepatic steatosis has robust implications for improving atherogenic dyslipidemia as well as a range of liver diseases.

7.4.4 The Relationship between Mitochondrial Dysfunction and Insulin Resistance Mitochondria play a crucial role in balancing substrate oxidation with nutrient availability. Defects in mitochondrial function can cause various metabolic abnormalities (see Chapter 9, Section 8.3 for detailed explanation). In the context of metabolic and chronic diseases of aging, the molecular link between insulin signaling and mitochondrial function has only recently been described. It lies in insulin’s inhibition of FOXO1, a process indirectly responsible for degrading electron transport chain (ETC) structural stability and function. FOXO1 is a transcription factor that induces the expression of hundreds of proteins including heme oxygenase 1, an enzyme that breaks down heme, a necessary cofactor that maintains the stability and function of ETC components. This essential component of mitochondrial function promotes higher concentrations of NAD+, and hence the appropriate NAD+/NADH ratio. Because NAD+ is a necessary cofactor for the mitochondrial

Insulin Resistance in Metabolic Disease enzyme acyl CoA dehydrogenase, when it is present at higher concentrations, fatty acid oxidation is enhanced. NAD+ is also a cofactor of SIRT1 and aids in the activation of peroxisome proliferator activator gamma C1 alpha (PGC1α), which in turn promotes the expression of genes driving mitochondrial biogenesis (see Chapter 1 Figure 1.20). In the setting of insulin resistance, FOXO1 is uninhibited and hyperactive, ultimately impairing the stability and function of the ETC, NAD+, fatty acid oxidation, and mitochondrial biogenesis. Another link between insulin signaling and mitochondrial function is found in the mitochondrial generation of ROS. At moderate levels and in addition to adaptively stimulating the uncoupling of proteins for the production of heat (physiological thermogenesis), ROS enhances insulin sensitivity by upregulating insulin receptor tyrosine autophosphorylation. High levels of mitochondrial ROS impairs insulin sensitivity, providing another example of hormesis. Insulin resistance can also drive mitochondrial dysfunction. Since insulin is known to be a strong regulator of biological clock function, insulin resistance often occurs with impaired circadian patterns of insulin secretion. Dysfunctional timing of insulin signaling leads to disruptions in the synchronization of transcriptional regulator activation. This occurs with PGC1α, a transcriptional coactivator necessary for inducing mitochondrial biogenesis as mentioned. Mitochondrial dysfunction itself can further impair the ability of insulin to promote oxidative mitochondrial bioenergetics. Insulin resistance therefore represents a susceptibility state to both mitochondrial dysfunction and metabolic and chronic diseases. Furthermore, mitochondrial dysfunction with aging decreases oxidative capacity, leading to an imbalance between nutrient availability and substrate utilization which ultimately could favor ectopic lipid accumulation. This could also be associated with the activation of ER stress pathways. As mitochondrial bioenergetic capacity declines, there is an associated increase in unfolded proteins. Dysfunctional mitochondria have a reduced ability to maintain the metabolic demands of normal protein folding and are thus burdened by endoplasmic reticulum (ER) stress (the organelle in which protein folding takes place). ER stress and the accumulation of unfolded proteins follow to initiate the unfolded protein response which activates branches of inflammatory (NFκB and JNK) and oxidative stress pathways that all work to aggressively promote insulin resistance (Figure 7.13). Mitochondrial dysfunction thus represents an impaired capacity to transform available energy substrates into the biological currency of ATP in a manner sufficient to maintain cellular homeostasis. The unfolded protein response that results from the accumulation of unfolded proteins may be considered adaptive in the sense that it inhibits the driving force for insulin signaling to generate further biosynthetic growth as this demand exceeds the bioenergetic capacity of the cell. Conversely, many do not interpret the unfolded protein response as adaptive. Rather, mitochondrial dysfunction w/ aging decreases oxidative capacity, leading to an imbalance between nutrient availability and substrate utilization which ultimately could favor ectopic lipid accumulation. Certainly, this could also be associated with the activation of ER stress pathways.

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FIGURE 7.13  ER stress induces the unfolded protein response, which activates NFκB, JNK, and oxidative stress pathways ultimately resulting in insulin resistance. *ER = endoplasmic reticulum; JNK = c-Jun N-terminal kinases; NFκB =nuclear factor kappa-light-chain-enhancer of activated B cells; UPR = unfolded protein response.

Some degree of mitochondrial dysfunction is present in most individuals who are predisposed to insulin resistance. Mitochondrial dysfunction will fundamentally decrease bioenergetic metabolism, altering the balance between substrate availability and oxidative capacity. The interconnections between mitochondrial dysfunction and insulin resistance are complex and varied. Mitochondrial function and insulin signaling are also influenced by numerous hormonal, neural, circadian, and metabolic inputs, creating a challenging landscape for study. Progress in this area will require the development of new techniques to actually quantify mitochondrial function. While whole-body calorimetry is helpful to quantify RQ, it is insensitive to subtle changes that may underpin metabolic disease. And while advanced techniques such as magnetic resonance spectroscopy and stable isotopic methods can provide more precision, these are not scalable for large clinical studies. Finally, “omic”-type data will require new analytical tools and computer models to compile these multiple ordinates into a relatable physiological model. Though the challenges are daunting, these future developments could provide a deeper understanding of the fundamental connections. The implication of the relationships discussed in the above paragraphs emphasizes the fundamental connection between mitochondrial function and bioenergetics with insulin signaling. The dysfunction of mitochondria sits at the crossroads of metabolic and chronic diseases as a function of bioenergetic capacity impairment. The influential introduction to the concept of insulin resistance was recognized by Gerald Reaven’s 1988 Banting Medal for Scientific Achievement Award (16). This highlighted the role of insulin resistance as a major pathophysiological basis for type 2 diabetes and other metabolic syndromes, plus cardiovascular disease. Ralph Defronzo is another giant and pioneer in the field who over decades has helped establish insulin resistance as a fundamental player

296 in metabolic and cardiovascular disease (41, 203, 215–217). Moreover, insulin resistance (and associated hyperinsulinemia) is increasingly being recognized to play a role in the pathogenesis of accelerated cognitive decline, Alzheimer’s disease, and cancers of reproductive and gastrointestinal tissues. The intertwined relationship of insulin resistance and mitochondrial dysfunction implicates a likely fundamental and bidirectional cornerstone of metabolic and chronic diseases of aging.

7.4.5 Control Parameters of Insulin Signaling Control parameters (extrinsic to the body) and upstream order parameters (intrinsic to the body) represent possible stressors that may promote chronic disease. Diurnal circadian patterns of insulin secretion, peripheral sensitivity and signaling is characteristic of healthy physiology. Chronic non cyclical insulin resistance is therefore an upstream order parameter for chronic disease states of aging and contributes to an accelerated pace of aging itself. In addition, there is typically an interacting set of control parameters that are also of clinical importance. These include 1) stress-provoking events and the perceived stress response; 2) diet; 3) circadian behaviors; and 4) the gut microbiota that regulate metabolic physiology and behavior (Figure 7.14). Unhealthy extrinsic control parameters disturb intrinsic bodily order parameters of physiology and promote mitochondrial dysfunction and non-circadian insulin resistance in insulin-responsive metabolic tissues. As will be

FIGURE 7.14  Control parameters involved in insulin signaling. Extrinsic control parameters such as stress, disturbed quantity or quality of food intake, disruptions in circadian behaviors, and/or sleep cycle can all lead to intrinsic order parameters of insulin resistance and obesity. Insulin resistance and obesity then become intrinsic control parameters that result in the intrinsic order parameters of chronic diseases such as cancer, cardiovascular disease, and diabetes.

Metabolism and Medicine explained below, this leads to hyperinsulinemia and systemic redox disturbances and inflammatory responses, representing upstream order parameters responsible for virtually all chronic diseases of aging. Such chronic diseases include cardiovascular disease, cancers, and Alzheimer’s disease, which should be considered metabolic sequelae to a matrix of order parameters of which insulin resistance is central. The insulin resistance may involve the diseased tissue itself, such as in the case of AD or cardiomyopathy. Alternatively, in the case of vascular disease or cancer, the insulin resistance lies outside the diseased tissue itself, present in the classic insulin-responsive metabolic tissues, skeletal muscle, the liver, and adipose tissue.

7.4.5.1 Insulin Resistance and Alzheimer’s Disease The major portion of glucose uptake in the brain of humans and rodents is independent of insulin. Glucose uptake in most neurons is through the GLUT3 transporter and in glial and brain endothelial cells via the GLUT1 transporter. GLUT1/ GLUT3-mediated glucose uptake is insulin-independent, and thus insulin is not needed for glucose uptake in most brain cells. However, studies have reported glucose transport expression and activity with the insulin-sensitive GLUT4 in the nuclei of several key memory, cognitive and emotional centers of the brain (218, 219).

7.4.5.2 Insulin Resistance and Cardiovascular Disease In the US, coronary heart disease is a major cause of death in adults with diabetes. Insulin resistance, while not the primary cause, is a major contributor to atherosclerosis (cardiovascular disease, CVD). The major cause of atherosclerosis is cholesterol, specifically LDL cholesterol. Several studies have also suggested that triglyceride could be responsible for atherosclerosis progression. During hyperlipidemic conditions, LDL-C particles easily enter the arterial wall (intima), and subsequent oxidative modifications in components of LDL (Oxidized-LDL [Ox-LDL]) such as lipid and apolipoprotein B (apo B) cause dysfunction of endothelial cells. As a result, endothelial cells recruit monocytes, which differentiate into macrophages. Here, macrophages engulf ox-LDL and transform into a foamlike structure called atherosclerotic plaque. Plaque formation leads to a reduced cross-sectional area of the arterial channel as well as irregularities and shape deformations that contribute to increased blood pressure and introduce turbulence into the blood flow. Despite the strong mechanistic and epidemiologic connections, there are clearly components of CVD that are independent of insulin resistance. Among adult type 1 diabetics without insulin resistance, heart disease is at least twice as common in patients with diabetes (220). Hyperinsulinemia may not increase the risk of fatal CVD in elderly men or women without diabetes (221). Insulin resistance has also been shown in one study to not be associated with CVD in women (222). Nonetheless, the balance of data increasingly does show that the dysfunction of mitochondria is causally associated with the development of insulin resistance.

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7.4.6 The Role of Insulin Signaling Dysregulation in Cancer

leukemia (CML), as well as a high-risk subset of acute lymphoblastic leukemia (ALL). ABL-specific tyrosine kinase inhibitors have been remarkably successful in treating these diseases that previously had a 100% fatality rate. mTOR is downstream from the classical insulin signaling cascade (insulin receptor → IRS → PI3K) and its dysregulation is responsible for the abnormal cell growth and proliferation for many cancers including glioblastoma and renal cell cancers, the latter not uncommonly seen in diabetes type 2. Finally, receptor and non-receptor tyrosine kinases play an important role in the formation of new blood vessels that feed tumor cell transformation at the in situ tumor stage. They also contribute to the progression of cancer by ultimately inducing the expression of genes that promotes cell proliferation, migration, differentiation, and inhibition of apoptosis. These functions are mediated by two fundamental signaling cascades: PI3K → Akt → mTOR and Ras → Raf → MAPK (see Figure 7.3).

Genetics can predispose individuals to pathological insulin resistance. It has been shown that lean, active adolescents with pathologically insulin resistant parents have mitochondria that are subtly dysfunctional such that fatty acid oxidation is impaired (116). In these cases, mitochondria are likely overburdened by the electron transport chain’s high requirement for fatty acids. This results in electron leakage and the formation of reactive oxygen species that can lead to further mitochondrial dysfunction, skeletal muscle insulin resistance, hyperinsulinemia, and dysregulation of insulin receptor function. Dysregulation of insulin receptors, mentioned previously to be a result of mitochondrial dysfunction, can have serious effects on the health of an individual including the development of cancer. While there has been significant attention paid to resultant hypertension, dyslipidemia, obesity, and cardiovascular disease as metabolic consequences of insulin resistance, cancer is an additional consequence that mustn’t be left out. One prominent link between insulin dysfunction and cancer involves dysregulation of tyrosine kinases. There are receptor and non-receptor tyrosine kinases. The receptor variety are transmembrane cell surface receptors and enzymatic kinases that phosphorylate tyrosine residues on substrates like epidermal growth factor receptor (EGFR), platelet-derived growth factor receptor (PDGFR), fibroblast growth factor receptor (FGFR), and the insulin receptor. Activation of receptor tyrosine kinase by insulin, IGF-1, and other growth factors leads to phosphorylation of select tyrosine residues on itself (autophosphorylation), as well as other target cytoplasmic proteins using ATP. Non-receptor tyrosine kinases include Janus kinase (JAK), Abelson tyrosine kinase (ABL kinase), and mammalian target of rapamycin (mTOR). Multifactorial mechanisms link tyrosine kinase to cancer onset, but two specific signaling pathways are of particular importance to this pathophysiology: JAK, ABL, and mTOR. Both happen to occur at the expense of more conventional metabolic signaling pathways that promote glucose uptake and lipid and glycogen synthesis. JAK is activated by various cytokines like IL-6 and hormones like leptin, growth hormone, and prolactin. IL-6 directly promotes cancer development, and elevations of IL-6 have been shown to be a poor prognostic factor in numerous cancer types (223). JAK functions to stimulate a variety of cell types but is critically important for immune cells and hematopoietic cells (blood stem cells). Dysregulation of JAK can have serious effects; overexpression promotes certain autoimmune diseases such as myeloproliferative disorders and rheumatoid arthritis. Immune suppressive therapy using inhibitors of JAKs are being developed to treat autoimmune disease and lymphoproliferative malignancies, multiple myeloma, and solid tumors (for example prostate cancer) (224–227). Dysregulation of ABL kinase is also notably harmful. The Philadelphia chromosome was the first chromosomal translocation identified in a cancer (228), and was shown to be the causal driver of leukemia (229). This translocation between chromosomes 9 and 22 creates a BCR-ABL fusion protein, leading to the unrestrained activity of ABL that is responsible for the malignant transformation of chronic myelogenous

7.5 Bioenergetics and the Basis for the Development of Insulin Resistance Most eukaryotic cells use glucose as a primary source of energy. A definite amount of glucose is needed for cells’ functioning; however, elevated glucose levels in plasma can be toxic and exhibit harmful effects. Metabolism of glucose in all tissues is tightly regulated in a coordinated manner, both at cellular as well as systemic levels. At the physiological level, glucose metabolism is regulated by the endocrine action of polypeptide hormones, such as insulin and glucagon. At the cellular level, it is regulated by energy sensors, including AMPK, sirtuins, and mTOR pathways. Defects in any of these pathways can lead to the deregulation of glucose metabolism and eventually result in the development of diabetes. Cellular bioenergetics play a crucial role in maintaining systemic glucose homeostasis. Excess glucose present in the circulation needs to be utilized to prevent harmful secondary effects (i.e., the generation of advanced glycation end products and subsequently ROS production). Mitochondria play a critical role not only in cellular bioenergetics, but also in maintaining systemic metabolic homeostasis. It is of critical importance for clinicians to understand the biochemical basis of energy flow through systems and how the breakdown of this complex chain of events can contribute to the pathogenesis of insulin resistance and chronic diseases of aging.

7.5.1 Cellular Bioenergetics under Normal Physiological Conditions Systemic glucose metabolism homeostasis is tightly controlled in healthy individuals through highly coordinated interplay between all organs. Under conditions of elevated blood glucose after the meal, pancreatic β cells increase glucose uptake and its metabolism to generate ATP through oxidative phosphorylation. The resulting elevated ATP/ADP ratio works as an important signal responsible for the secretion of insulin by β cells (230, 231). Consequently, insulin instructs metabolic organs to respond to the elevated blood glucose to restore and

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maintain optimum blood glucose concentration. It is a critical process to maintain the optimum concentration of blood glucose as both hypoglycemia and hyperglycemia can cause medical complications. Insulin not only promotes glucose uptake in target tissues, but also regulates mitochondrial function. Insulin increases mitochondrial oxidative capacity, mitochondrial biogenesis, and coupling efficiency of oxidative phosphorylation (232, 233). Importantly, bioenergetics of muscles are mainly regulated by the energy demand, in a way that ATP supply adapts promptly to any change in ATP turnover. Thus, the effect of insulin on the oxidation of glucose may be the indirect consequence of anabolic changes. Different dietary nutrients are broken down into their simplest form, such as glucose or fatty acids, which eventually converge in the mitochondria where these compounds have reducing power in the form of NADH or FADH2. These reducing powers fuel oxidative phosphorylation in the mitochondria to generate ATP. Under the condition of low energy demand, instead of generating ATP, mitochondrial carbons are diverted to provide building blocks for anabolic processes. Mitochondria are critical for the homeostasis of nutrient metabolism and therefore, any defect in mitochondrial function may lead to the emergence of metabolic disorders. The process of metabolism of various nutrient substrates is explained in Chapter 8, Section 8.3.4.

potentials of the ETS electron carriers progressively increase (become more positive) from Complex I to Complex IV, and the terminal electron acceptor O2 has the highest reduction potential in the respiratory chain (Complex I < Coenzyme Q < Complex III < Cytochrome C < Complex IV < O2). This is the reason for the unidirectional flow of electrons from Complex I to O2. The difference in reduction potential between the complexes in the respiratory chain is sufficient enough to drive the transport of protons (H+) from the mitochondrial matrix to the inner membrane space. This creates an electrochemical gradient across the inner membrane resulting from both the concentration and the electrical potential difference (also known as membrane potential) across the membrane. The electrochemical gradient creates a proton motive force (PMF). The energy generated from the proton motive force is used for the synthesis of ATP by another complex called ATP synthase (Complex V). Important characteristics of the respiratory system are that: 1) the transfer of electrons through the ETS occurs spontaneously, and 2) electron flow is tightly coupled with the pumping of protons into the inner membrane space. These two processes typically do not take place without the other under normal conditions. See Chapter 1, Section 1.6 and Chapter 9, Section 9.3 for the detailed discussion of cellular metabolism and bioenergetics.

7.5.2 The Role of Mitochondria in Cellular Bioenergetics

7.5.3 Mitochondrial Function and Insulin Resistance

Nutrients in the form of glucose or fatty acids are metabolized in cells via different pathways such as glycolysis, the TCA cycle, and β-oxidation (in the case of fatty acids). This generates reducing equivalents in the form of NADH and FADH2, which are eventually involved in electron transfer reactions in mitochondria through the electron transport system (ETS) to generate ATP. This process is called oxidative phosphorylation. In 1961, Dr. Peter Mitchell conceptualized the famous chemiosmotic theory of ATP synthesis in mitochondria, for which he received the Nobel Prize in chemistry in 1978. His chemiosmotic theory of oxidative phosphorylation accounts for the coupling of the proton (H+) and electron transfer through the inner mitochondrial membrane to the phosphorylation of ADP to form ATP. The mitochondrial ETS consists of five different multimeric protein complexes that are embedded within the inner mitochondrial membranes. The electrons from NADH and FADH2 flow through a series of electron carriers in the chain of complexes and, ultimately, to molecular oxygen (O2). Every electron carrier in the ETS represents a redox pair, which has a characteristic reduction potential. A redox pair is defined as a species capable of existing both in an oxidized or reduced state. “Reduction potential” denotes the tendency of the oxidized substrate to accept an electron. Reduction potential is of utmost importance in governing the direction and flow of the electrons through the ETS. For example, a negative reduction potential signifies that a reduced substrate (e.g., NADH or FADH2) has a greater tendency to lose electrons. In comparison, the positive reduction potential denotes a higher tendency to accept electrons by the substrate (e.g., O2). The reduction

Under the condition of low energy demand, mitochondria are not involved in ATP synthesis; instead, they facilitate anabolic processes such as lipid and amino acid biosynthesis by providing the necessary building blocks (234). Chronic overnutrition has been shown to lead to mitochondrial dysfunction and insulin resistance. Nutrient mismanagement causes the accumulation of lipid intermediates such as diacylglycerol (DAG) or ceramide and ROS in muscle. These intermediates are harmful for cellular function and significantly affect mitochondrial ETS function, eventually causing mitochondrial dysfunction. Therefore, mitochondria play a crucial role in maintaining a well-balanced nutrient metabolism and homeostasis of systemic metabolism. Mitochondria are now considered a key player in the emergence of altered ROS homeostasis and myocellular lipid metabolism in the setting of diseases like obesity and diabetes. There are different theories regarding mitochondrial dysfunction and insulin resistance; the most current and accepted theory is explained below (see Chapter 8, Section 8.3.3). In 1963, British biochemist Sir Philip John Randle proposed that non-esterified free fatty acids (NEFAs) inhibit glucose catabolism at several key enzymatic steps, pyruvate dehydrogenase, phosphofructokinase, and hexokinase. This impaired glucose utilization manifests as lower insulin sensitivity in muscle (235). However, more recent studies from Dr. Gerald Shulman and colleagues challenged the “Randle paradigm” (143, 236). Their studies revealed that insulin-stimulated glucose disposal in diabetic patients is restricted by glucose uptake, not glucose utilization. That is the primary defect in insulin-resistant tissue is one in which insulin is unable to

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Insulin Resistance in Metabolic Disease promote glucose transport from the bloodstream into insulinsensitive tissues. This forms the basis of the hypothesis that lipid signaling molecules such as DAG and ceramide inhibit the insulin-stimulated GLUT4 translocation (143, 237, 238). According to this model of muscle insulin resistance, mitochondrial dysfunction is the leading cause of the accumulation of these lipid intermediates, as it prevents β-oxidation of the excess NEFAs and promotes the accumulation of DAGs under the condition of overnutrition or obesity. This concept is supported by experimental evidence from human and animal studies, which suggests that insulin resistance is linked with decreased mitochondrial size, diminished activity of mitochondrial enzymes, and decreased fatty acid oxidation (239–241). Moreover, rates of substrate oxidation and mitochondrial ATP synthesis are comparably lower in individuals with insulin resistance (242–244). Importantly, it has also been observed that type 2 diabetic patients exhibit low mitochondrial respiration (245, 246). The concept of oxidative capacity is again supported by other studies demonstrating that muscles of individuals fed with a high-fat diet, or in the muscle of insulin-resistant subjects, there is a profound downregulation of oxidative phosphorylation genes downstream of PGC1α (247– 249). Though the concept of oxidative capacity in the context of insulin resistance is experimentally supported, it is not universally accepted. It is still unclear whether mitochondrial dysfunction is a cause or a consequence of insulin resistance. We have discussed this issue in Chapter 8, Section 8.3.3.

7.5.4 Pyruvate Dehydrogenase Enzyme Complex May Be the Key to Fighting Insulin Resistance A critical feature in insulin resistance and type 2 diabetes is metabolic inflexibility. Healthy individuals can flexibly utilize fatty acids for energy during fasting or low glucose availability, and can switch to using glucose when available. However, type 2 diabetics do not have this degree of metabolic flexibility; they cannot easily switch from fatty acid oxidation to glucose oxidation (250). Pyruvate dehydrogenase enzyme complex (PDH) plays a crucial role in metabolic flexibility, so dysregulation of PDH could be a contributing factor to insulin resistance. Several medications that counter the effects of type 2 diabetes converge on PDH.

7.5.4.1 Role of PDH in Energy Production and Insulin Resistance Muscles use glycogen for energy. The force of muscle contraction degrades glycogen, generating pyruvate. Skeletal muscle also takes up circulating glucose. Pyruvate may either be reduced to lactate in the cytosol or oxidized in mitochondria by PDH, producing acetyl-CoA. Oxidation of pyruvate occurs by the irreversible biochemical reaction:

Pyruvate + CoASH + NAD + ® Acetyl-CoA + NADH + CO2

(7.1)

Oxidation of pyruvate by PDH is a significant factor in wholebody glucose homeostasis - it is the step where carbohydrates

are transformed into energy. PDH is a key enzyme and is an important target for the regulatory signaling pathways. Flux through PDH determines the fate of oxidative glucose metabolism. The activity of PDH is regulated by phosphorylation and dephosphorylation processes mediated by various kinases. It is important to note that the inactive, phosphorylated form of pyruvate dehydrogenase enzyme complex is a hallmark of insulin resistance. Forkhead box protein 1 (FOXO1) is a transcription factor. Under insulin-sensitive conditions, FOXO1 is inhibited by the IRS-1/PI3K/Akt pathway. When there is insulin resistance, FOXO1 binds to and stimulates the promoter region of the enzyme PDK, causing PDK to be produced (251). PDK phosphorylates PDH, which turns off PDH. Through a sequential chain of events, FOXO1 makes the cell lose its ability to use pyruvate as a fuel source. Blocking FOXO1 sounds like a compelling therapeutic target for reversing insulin resistance and type 2 diabetes. Statins are a class of drugs that act on PDK (the PDK4 isomer, to be exact). Statins activate the FOXO1 transcription factor, which binds to the promoter region of the gene for PDK4. PDK4 is upregulated, producing phosphorylation-mediated inhibition of PDH. Remember, PDK has a feedback mechanism in place where high levels of PDK deactivate PDK. This feedback mechanism allows PDH to become disinhibited. Therefore, PDH is left “on” and can use pyruvate as fuel. In a subset of patients treated with statins, statins activate muscle atrophy genes (proteasomal and lysosomalmediated protein breakdown of muscles) (252). Autoimmune statin myopathy decreases mitochondrial ATP production. Theoretically, exercise should reliably reduce statin-induced myopathy, but biological reactions are highly complex and non-linear. Sometimes, resistance exercise can increase statininduced myopathy. Patients generally recover from statin myopathy two to three months after stopping statins.

SIDEBAR 7.4: EXERCISE CAN MAKE YOU STORE FAT Resistance exercise helps keep mitochondria healthy. The force of the contraction increases calcium availability in the muscle. Calcium improves insulin sensitivity, which enhances the oxidation of carbohydrates. Resistance exercise also builds up pyruvate and enhances PDH activity, improving carbohydrate metabolism. PDH decarboxylates pyruvate, producing acetyl-CoA, which enters the TCA cycle. Acetyl-CoA and the reduced form of coenzyme A (CoASH) exist in equilibrium as redox pairs. The ratio of acetyl-CoA : CoASH is regulated by carnitine. Some of the acetyl-CoA produced during resistance exercise is stolen by carnitine: carnitine snatches the acetyl root from acetyl-CoA, forming acetyl-carnitine. By breaking down acetyl-CoA, carnitine forces a higher ratio of CoASH. CoASH is a necessary reagent in the TCA cycle (253). When carnitine combines with the acetyl group of acetyl-CoA, carnitine is unable to work as a fatty acid carrier. Instead of carrying the fatty acid palmitate from the cytoplasm into the mitochondria, palmitate accumulates

300 in the cytoplasm. In this setting, the increased oxidation of carbohydrates results in the accumulation of lipids in the cytoplasm of cells not specialized to store fat. Ectopic fat like this is a source of lipotoxicity, with the potential to promote insulin resistance and mitochondrial injury (193).

SIDEBAR 7.5: EXERCISE IN A BOTTLE Resistance exercise improves muscle insulin sensitivity. Nothing can replace exercise, but that does not stop people from finding alternatives. Drugs are in development to mimic the beneficial effects of exercise on diabetes. One of the experimental therapeutics, dichloroacetate (DCA), inhibits PDK. DCA is effective at improving insulin sensitivity. However, there are concerns about the longterm toxicity of DCA. Carnitine supplements might be a way to reduce competition for CoASH between fat and carbohydrate oxidation in myocytes (254), though more testing is needed. Increasing carnitine levels also appears to improve muscle insulin sensitivity, at the cost of nausea, vomiting, diarrhea, and a “fishy body odor”.

7.5.4.2 Yin and Yang of Glyceroneogenesis in Patients with Insulin Resistance Glycerol is the backbone of triglycerides, high-energy molecules that are stored in fat cells. Glyceroneogenesis is the process of synthesizing glycerol, which occurs primarily in liver and adipose tissue. Glyceroneogenesis also modulates fatty acid release during insulin-resistant states (high-fat diet, sepsis, inflammation, or fasting with insulinopenia). In such settings, metabolism is shifted away from glucose oxidation in favor of fatty acid oxidation. In adipose tissue, when pyruvate

Metabolism and Medicine is unable to be converted to acetyl CoA due to PDK inhibition of PDH, it cannot undergo oxidative phosphorylation. Instead, pyruvate is carboxylated in adipocytes by pyruvate carboxylase, forming oxaloacetate. Oxaloacetate can enter the TCA to form citrate, or can be converted to phosphoenolpyruvate (PEP) by PEP carboxykinase (PEPCK). PEP can then undergo a series of reactions to form glycogen, glucose, or glycerol. Glyceroneogenesis occurs when pyruvate goes through a series of reactions to become glycerol. Conversion of PEP to intermediaries is the rate-limiting step of glyceroneogenesis (Figure 7.15). While glyceroneogenesis is adaptive at physiological levels, it increases susceptibility to metabolic disorders at high levels. One problem with excess glyceroneogenesis is that it stunts energy production. For example, glycolysis generates lactic acid in peripheral tissues that can circulate back to the liver. At the liver, lactic acid enters the Cori Cycle, which is involved in the process of gluconeogenesis. Gluconeogenesis puts glucose into the circulation, a way of bringing glucose to peripheral tissues. However, when glyceroneogenesis is activated, lactate is diverted away from the Cori Cycle, less gluconeogenesis occurs, and the stolen lactic acid becomes inaccessible and is instead hoarded as triglycerides in adipose tissue. In addition to stunting energy production, these inaccessible, hoarded triglycerides cause systemic problems, both during storage and during release. Over-filled fat cells outgrow their blood supply, causing hypoxia, inflammation, insulin resistance, reduced mitochondrial biogenesis, and impairment of mitochondrial function. Nutrient oxidation becomes inefficient in these overstuffed fat cells; the ratio of oxygen consumption to ATP production is too high, meaning that oxygen is being wasted as ROS. Pathologically high levels of ROS, in turn, enhance systemic inflammation, insulin resistance, and mitochondrial dysfunction (234). Excess production and storage of triglycerides cause systemic hyperinsulinemia.

FIGURE 7.15  During fasting conditions, glyceroneogenesis modulates the release of fatty acids. Triglycerides stored in fat cells release fatty acids and glycerol through the process of lipolysis. The release of fatty acids is limited due to an increase in glyceroneogenesis and the re-esterification of glycerol-3-phosphate. Almost all of the glycerol is released, though remains unphosphorylated. Source: adapted from (255). *–P or P– = phosphate group; PEPCK = phospho-enolpyruvate carboxykinase.

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Insulin Resistance in Metabolic Disease Complementarily, excess release of stored triglycerides can cause insulin resistance. During fasting, triglycerides stored in fat cells undergo lipolysis. Lipolysis converts stored triglycerides into fatty acids and glycerol. Roughly 40% of the fatty acids generated from lipolysis, and 100% of the unphosphorylated glycerol, are released into the circulation (Figure 7.15), where they travel to other tissues to serve as an energy substrate. Lipolysis goes into overdrive during inflammation, insulin resistance, hepatic steatosis, sepsis, and ectopic fat accumulation (muscles, islet cells, brain). Circulating fatty acids become chronically elevated, which can lead to systemic insulin resistance and type 2 diabetes. These examples demonstrate that glyceroneogenesis and insulin resistance share a chicken-or-the-egg relationship. The mechanism of insulin resistance-mediated glyceroneogenesis involves regulation of PDH. PDK phosphorylates PDH, which inactivates PDH. This is countered by insulin, which stimulates the dephosphorylation of inactivated PDH (through the enzyme PDH phosphatase). During insulin resistance, insulin loses its ability to stimulate PDH phosphatase, keeping phosphorylated PDH inactive. With PDH inactive, pyruvate and lactate build up, unable to enter the TCA cycle, and are instead diverted to glyceroneogenesis (256). We know that stimulating glyceroneogenesis can cause insulin resistance, and that blocking glyceroneogenesis can cause type 2 diabetes (see Sidebar 7.6). Glyceroneogenesis must be in a delicate balance with glycolysis and lipolysis. It may seem counter-intuitive, but in some cases, facilitating glyceroneogenesis can help reverse insulin resistance by preventing and reversing ectopic fat deposits. Left untreated, ectopic fat deposits in muscle cells promote disruption of the IRS-1/PI3K/ Akt insulin signaling pathway (238, 257). Combating ectopic fat storage can help rebalance insulin signaling pathways. Therapeutics that target peroxisome proliferator-activated receptor gamma (PPARγ, a.k.a. glitazone receptor) promote glyceroneogenesis. PPARγ is a nuclear receptor that regulates lipid storage. When activated, PPARγ and the retinoid X receptor (RXR) heterodimerize, then bind to the promoter region of genes that control insulin sensitivity (adiponectin, components of the insulin signaling cascade). The proposed mechanism by which PPARγ agonists enhance glyceroneogenesis has to do with promoting the transcription of phosphoenolpyruvate carboxykinase (PEPCK). PEPCK is the rate-limiting step during the process of glyceroneogenesis, so upregulation of PEPCK helps increase the throughput of this relatively slow step (258). Ultimately, gene regulation by PPARγ improves hyperlipidemia and hypercholesterolemia and diminishes intramyocellular lipid droplets. PPARγ agonists reduce ectopic fat deposits by enhancing fatty acid oxidation and reducing cholesterol biosynthesis. Another effect of PPARγ agonists, including members of the thiazolidinedione class (TZDs), is upregulation of PDK4. As we know, increased PDK4 causes phosphorylation and deactivation of PDH, producing increased circulating free fatty acids. At the same time, PPARγ agonists combat the excess circulating free fatty acids by enhancing glyceroneogenesis: fatty acids become esterified, producing glycerol, the backbone of triglycerides. Triglycerides buildup in subcutaneous adipose tissue and visceral adipose tissue, but not in skeletal

muscle or the liver. Tissue specificity is the key here - accumulation of fat in “typical” locations is better for patients than ectopic fat accumulation. PPARγ therapy should be a consideration for patients with steatohepatitis, hepatic fibrosis, and early hepatic cirrhosis related to hepatic steatosis. PPARγ agonists have known direct effects on PDK4, but some of PPARγ agonists’ other mechanisms of action are indirect on PDK4, or possibly PDK4-independent. For example, a popular theory of how PPARγ agonists upregulate PDK4 involves transrepression (inhibition of FOXO1 through protein-protein interactions) rather than traditional signaling. Long-chain acetyl CoAs may need to be present in order for PPARγ agonist-mediated repression of FOXO1 to occur (Constantin-Teodosiu personal communication). In another example, PPARγ agonists can have PDK-independent effects on hepatic glucose. Drugs that target PPARγ can lower hepatic glucose by increasing glycolysis, the pentose phosphate pathway, and hepatic fatty acid synthesis (259). Furthermore, Bouskila and colleagues have shown that PPARγ agonist upregulates adiponectin secretion (260). Since adiponectin is known to increase the insulin sensitivity, PPARγ may regulate whole-body glucose homeostasis partly via adiponectin release. Future research into PPARγ agonists will certainly reveal more mechanisms of action underlying their beneficial effects. PPARγ agonists are not completely safe; stimulation of PPARγ produces downstream inhibition of PI3K/Akt activation, ultimately impairing insulin signaling. However, the complex interactions PPARγ agonists have on inhibition and disinhibition of signaling pathways leads to a net effect of improved insulin sensitivity. It is important to note that PPARγ agonists have mixed effects on insulin sensitivity in heterogeneous populations (261). In a sense, this is a reciprocal process to an effect of PPAR agonist drugs, in one case favoring carbohydrate oxidation, and the other fatty acid oxidation (194). Elegant studies have shown that adipocytes’ specific deletion of PPARγ in the rodent leads to impaired glucose homeostasis, insulin resistance, and fatty liver (262). Furthermore, activation of PPARγ through its agonist thiazolidinediones (TZDs) improves adipocytes’ function, whole-body lipid and glucose metabolism, insulin sensitivity, and vascular structure and function. While TZDs are used as antidiabetic agents, they do have some undesirable effects such as weight gain, heart failure, and bone loss (263).

SIDEBAR 7.6: STATIN THERAPY CAN PROMOTE OR INHIBIT GLYCERONEOGENESIS Statins can suppress or increase glyceroneogenesis. While it sounds beneficial to block the production of glycerol, without a way to neatly pack up excess fatty acids, fatty acids are released from adipocytes into the circulation. As described previously, adipose tissue is the best home for lipid storage, and when this is impaired, lipids accumulate in other tissues. While tissues may respond by increasing fatty acid oxidation and mitochondrial biogenesis, these processes can only compensate so much. The liver

302 gorges on these excess fatty acids but inactivation of glyceroneogenesis means that triglycerides released by the liver will not get packed away for storage in adipose tissue. The liver gets fatter and fatter, resulting in. hepatic steatosis (fatty liver disease) and insulin resistance (217). At the same time, excess nonesterified fatty acids in the circulation are taken up by skeletal muscle, which becomes insulin-resistant (195). Excess fatty acid uptake by pancreatic beta cells can impair their ability to synthesize and secrete insulin, as well. Lipid droplets can even accumulate in the brain, possibly impairing cognition (hippocampus) or satiety (arcuate nucleus of the hypothalamus). In addition to potentially impairing these organs, statin-mediated inhibition of glyceroneogenesis can cause type 2 diabetes. Fortunately, statins more often increase glyceroneogenesis (258).

7.6 Insulin Signaling and the Link to Cancer 7.6.1 The Role of Insulin Resistance and Mitochondrial Dysfunction in the Pathogenesis of Cancer Endogenous hyperinsulinemia with insulin resistance is now recognized to be a risk factor for cancer. In addition, there is concern that exogenous insulin may have a cause-effect relationship with cancer as well. Moreover, a number of control parameters in the pathogenesis of insulin resistance and hyperinsulinemia have both independent and synergistic effects on cancer. Risk factors for insulin resistance and hyperinsulinemia share a large overlap with those for cancer, including genetic susceptibility, visceral obesity, mitochondrial dysfunction, food additives, high dietary saturated fat, high glycemic load (high quantity of foods with an elevated glycemic index), high caloric intake (by overloading mitochondrial capacity) and subclinical endotoxemia (due to altered microbiota composition). Insulin resistance promotes inflammation and the formation of reactive oxygen species which can modify DNA and induce carcinogenic tumors. Buildup of reactive oxygen species along with the mitochondrial electron transport chain induces activation of NFkB, which amplifies the risk of DNA damage and drives aerobic glycolysis due to destruction of the mitochondria by the process of mitophagy. Also described below, obesity and insulin resistance/hyperinsulinemia and directly promote cancer. Thus, the interwoven fabric of obesity, insulin resistance/hyperinsulinemia, and inflammation provides a foundational control parameter for many cancers. As a result of the increased efficiency of cancer cells to upregulate glycolytic metabolism to serve the bioenergetic needs of cell replication, a phenomenon referred to as the Warburg effect, subclinical cancer cells are allowed to outcompete host cells for available resources. Furthermore, in the setting of insulin resistance and hyperinsulinemia, which is integrally associated with mitochondrial dysfunction, the upregulation of insulin signaling in cancer cells promotes cell survival, growth, and replication. Insulin-stimulated signaling

Metabolism and Medicine of Akt or protein kinase B (PKB) promotes cell survival by inhibiting various pro-apoptotic pathways. For example, insulin-stimulated Akt, largely through the PI3K-Akt-mTOR complex1 (mTORC1) pathway, promotes cell growth. Additionally, Akt-stimulated cell cycling pathways promote cell division in concert with MAPK/ERK-stimulated cell survival, proliferation, and angiogenesis (Figure 7.16). The presence of hyperinsulinemia provides extracellular stimulation that links cancer cells to the Warburg effect (see Chapter 9, Section 9.2.2–9.2.4), largely underpinned by the PI3K-Akt-mTOR pathway and other Akt-mediated signaling. However, cancer cells often exhibit an independence of extracellular signals like insulin. The presence of amplification (multiple copies of DNA segments) or activating mutations of protooncogenes, e.g. RAS, FAF, PI3K, Akt, or MYC, or inactivating mutations of tumor suppressor genes, e.g. of PTEN (phosphatase and tensin homolog), provide activation of these growth factor pathways with metabolic independence from growth factor stimulation. Thus, in the case of oncogenic signals, less extracellular stimulation by insulin or other tyrosine kinase receptor-mediated growth signals is required to drive the clinical state of cancer. Despite the overlapping effects of IGF-1 and insulin, their qualitative effects on visceral adipose tissue are discordant. In the case of hyperinsulinemia and insulin resistance, visceral adipose tissue is increased, whereas IGF-1 signaling results in decreased visceral adipose tissue mass. Visceral adiposity is strongly correlated to metabolic syndrome and cancer, and likely further contributes to the cancer-promoting effects of hyperinsulinemia. This is likely to be mediated by increased systemic inflammatory cytokines and other factors generated by the adipose tissue that bind to and activate receptor tyrosine kinases. Additionally, aromatase activity in adipose tissue converts androgens to estrogens. Estrogens mediated by

FIGURE 7.16  Insulin signaling in cancer cells promotes cell survival, cell growth, and cellular replication. Increased insulin signaling through the Akt/PKB pathway inhibits pro-apoptotic factors, resulting in increased cellular survival. Insulin signaling through the PI3K pathway results in the activation of mTORC1, increasing cellular growth. Insulin signaling through the ERK/MAPK pathway upregulates cellular replication. *Akt = protein kinase B; ERK/MAPK = extracellular signalregulated kinase/mitogen-activated protein kinase; mTORC1 = mechanistic target of rapamycin complex 1; PI3K = phosphoinositide 3-kinases; PKB = protein kinase B.

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Insulin Resistance in Metabolic Disease cell membrane estrogen receptors co-opt intracellular insulin signaling pathways that activate MAPK and mTOR signaling. As we have discussed, excess glyceroneogenesis promotes insulin resistance. Insulin resistance, in turn, indirectly promotes cancer. Insulin resistance in classic insulin target tissues results in hyperinsulinemia, which can have ramifications for other tissues throughout the body. Hyperinsulinemia could be a contributing factor to cancer in the gastrointestinal, genitourinary, and reproductive systems (see Sidebar 7.7 for information about interactions with hyperinsulinemia and estrogen).

SIDEBAR 7.7: INTERPLAY BETWEEN ESTROGEN AND INSULIN ON CANCER Insulin resistance and high estrogen levels increase the risk of female reproductive system cancers. Why? The reason may be related to crosstalk between estrogen and insulin signaling, converging on MAPK pathways. At physiological levels, estrogen receptors modulate the expression of genes involved in insulin sensitivity and glucose uptake. At pathologically high levels, estrogen is associated with cancer of estrogen-responsive organs (especially the mammary glands and female reproductive tract). Obese patients may have higher levels of estrogen than lean patients because adipose tissue produces estrogen. Obese patients are at higher risk hyperinsulinemia, which increases cancer risk. Therefore, female obese patients with hyperinsulinemia and pathologically high estrogen levels are at a much higher risk of breast cancer and reproductive tract cancers (ovarian, uterine, vaginal, cervical cancers) than lean patients.

7.6.2 Insulin Signaling, Cancer, and Bioinformatics, Defining Simple Rules There are over 1800 post-receptor insulin signaling pathways. In the absence of simplifying and distilling enormous complexity into a manageable few clinically relevant interactions, much of our mechanistic understanding of these signaling pathways would be devoid of meaning. A framework of simple rules or interactions between components of a system that underlie systems biology is determined by computational simulations. Computer-generated statistical anomalies of a given disease state focus attention on mechanistic study to drill down and better understand that particular rule. Hence, the “simple rules”, or interactions that describe emergent nonlinear processes of a system, may be at the individual level of each rule understood mechanistically. Components of the MAPK pathway may be statistical anomalies to a set of rules that define normal tissue differentiation. These in turn become the targets for understanding mechanistically how dysregulated cancer cell proliferation occurs in response to insulin signaling, as well as allow the identification of the underlying MAPK oncogenes that promoted the original transformation of the cell. Because of the incredible complexity, mechanistic insight of the Ras-Raf-MAPK pathway or of Ras-PI3K-mTOR pathway will need to be understood in the context of computer analyzed simple rules that are positively or negatively associated with disease susceptibility. This will

help clarify unexpected clinical interventional effects (e.g. secondary malignancies with BRAF therapy for thyroid cancers such as melanoma) and improve the predictability of response to targeted therapy. An overactive PDK may be the statistical anomaly to the set of rules that define metabolic insulin sensitivity in a given tissue. The PDK enzyme isomer therefore is the identified mechanistic target to be studied. Insulin resistance results in impaired IRS-1/PI3K/Akt signaling and resultant FOXO1 transcription factor binding at the mitochondrial gene promoter region of PDK. Simultaneously, overactive PDK is potentially an independent cause of insulin resistance due to reduced methylation of this promoter region. Oxidative stress, in turn, is often responsible for disturbed epigenetic effects in methylation patterns mediated by pulling the histone away from the gene. Intervention may target the oxidative stress (the insulin resistance and the cause of the insulin resistance), the cause of the oxidative stress and the overactive PDK itself. The aberrant activity of this enzyme isomer in hippocampal neurons of the brain involved in a form of Alzheimer’s disease, or of hepatocytes underpinning cirrhosis, promoted the discovery of its link to insulin resistance. A MAP kinase activation was found as a statistical anomaly (aberrant activity) by computer bioinformatics simulations, mechanistic insights, and correlations, found using the bioinformatics approach is capable of determining for example an estrogen receptor-mediated activation of the MAP kinase by co-opting the post-receptor insulin signaling. This has the potential, as a top-down approach, to translate to specific therapeutic targets of an individual at the bedside. For example, an insulinresistant, type 2 diabetic, obese individual who co-presents with breast cancer and a MAP kinase activation could be given a specific treatment regimen. Obesity-related insulin resistance is mediated by nonesterified fatty acids and inflammatory cytokines, which result in the activation of intracellular kinases such as protein kinase Cs that impair the proximal part of the insulin signaling network responsible for glucose homeostasis in insulin target metabolic tissues (264). Insulin resistance is typically restricted to the metabolic pathway most relevant in the classical metabolic tissues of the liver, skeletal muscle, and adipose. Conversely, insulin resistance and hyperinsulinemia are associated with overexpression of IR-A isoform as well as enhanced hybrid receptor formation between insulin receptor and IGF-1 receptor that has increased binding affinity for IGFs. Insulin resistance and hyperinsulinemia upregulate growth hormone receptors, which drive IGF-1 production. Insulin also increases the bioavailability of IGF-1 through the down regulation of IGF binding protein-1 (IGFBP1) and IGF binding protein-2 (IGFBP2), which inhibit IGF-1 actions (265).

7.7 Accelerated Cognitive Decline, Alzheimer’s Disease, and Insulin Resistance There is evidence for a bidirectional relationship between accelerated cognitive decline and Alzheimer’s disease with insulin resistance and diabetes type 2.

304 Between the ages of 60 and 74, the age range when accelerated cognitive decline and Alzheimer’s disease incidence precipitously increases, an estimated 67% of the United States population is diabetic or pre-diabetic. The cerebral cortex and hippocampus, two regions of the brain that are highly sensitive to insulin, require both glucose and insulin for high level cognitive functions such as learning and memory consolidation.

7.7.1 Effects of Insulin Resistance on Microtubule Dynamics Microtubules are proposed to be the molecular substrate whereby consciousness is encoded in neurons and is rooted in quantum behavior (see Volume 1 Chapter 3, Section 3.24 “Brain’s Processing Power: How Many Flops and How Many Watts?”). Accordingly, microtubule disassembly results in impaired cognitive status. Tau is a microtubule-stabilizing protein belonging to a class of microtubule-associated proteins (MAPs), which is inactivated by phosphorylation. Abnormal phosphorylation of Tau is associated with Alzheimer’s disease (266). Importantly, insulin resistance is associated with hyperphosphorylation of tau at serine/threonine residues, which leads to the disassembly of the microtubules (267). Healthy insulin signaling generally inhibits tau phosphorylation of tau, and in fact indues with another posttranslational modification of serine/threonine residues of tau protein: O-linked N-acetylglucosamine (O-GlcNAc) (268). This is of clinical interest, as increasing levels of O-GlcNAc has been shown to inhibit the pathologic hyperphosphorylation of tau induced by insulin resistance or other factors (Figure 7.17) (269).

Metabolism and Medicine

7.7.2 Impaired Insulin Signaling, Neurofibrillary Tangles, and Amyloid Plaques Neurofibrillary tangles of tau proteins, one characteristic of Alzheimer’s disease, may represent a different process, or a later, more advanced stage of the same process. That is, mild cognitive dysfunction may or may not evolve into Alzheimer’s disease, depending on the degree of insulin resistance and probably more importantly, the genetic predisposition (such as indicated by the APOEε allele). The other distinguishing pathological finding of Alzheimer’s disease is the presence of soluble amyloid beta neuronal plaques. The bidirectional factors of soluble amyloid beta and insulin resistance in the pathogenesis of accelerated cognitive decline and Alzheimer’s disease have not been definitively elucidated but appear to involve heterogeneous processes. It seems that the role of impaired insulin signaling is fundamental as is mitochondrial dysfunction-induced oxidative stress, inflammation, and impaired bioenergetics, and ultimately compromised synaptogenesis, synaptic plasticity, and consonantly reduced memory and cognition. Amyloid beta and insulin may compete for the insulin receptor, though insulin signaling appears to downregulate the binding of soluble amyloid beta oligomers. Soluble amyloid beta oligomers impair synaptic function due to competitive binding for insulin receptors. Downregulation of plasma membrane insulin receptor activation is a fundamental mechanism sensitive to calcium-calmodulin kinase II (CaMKII) that reduces synaptic spines. This mechanism blocks the potassium channel and hyperpolarizes the neuron to make it less likely to fire. That is, soluble amyloid beta causes reduced insulin signaling cascades, which result in impaired synaptic plasticity (270). Soluble amyloid beta intraneural accumulation appears to be mediated by endosomes (i.e. endocytic uptake of soluble amyloid beta) (271). Mitochondrial amyloid beta also may be an initial contributor in the pathological cascade leading to neuronal dysfunction (272).

7.7.3 Brain Glucose Metabolism and Alzheimer’s Disease

FIGURE 7.17  Insulin resistance is associated with abnormal hyperphosphorylation of tau protein, which leads to disassembly of microtubules and functionally results in accelerated cognitive decline, memory loss, and Alzheimer’s disease. Conversely, healthy levels of insulin signaling are associated with high levels of O-GlcNAc, which inhibits aberrant tau phosphorylation, maintains microtubule stability, and results in normal cognitive aging processes. *O-GlcNAc = O-linked N-acetylglucosamine.

There is enormous clinical and experimental evidence showing reduced brain glucose metabolism and transport as well as impaired metabolic signaling in the progression of Alzheimer’s disease (273). There is still insufficient elucidation of isoforms of different classes of glucose transporter families expressed in the brain. The Rotterdam Study showed that abnormal insulin signaling (i.e. insulin resistance) in the brain results in synaptic failure and impaired learning and memory decline (274). Insulin resistance and mitochondrial dysfunction are bidirectionally correlated with resultant disturbed bioenergetics. Most consumed glucose is used to maintain synaptic function and resting neuron potentials, which are compromised in the setting of insulin resistance and mitochondrial dysfunction. Impaired insulin signaling (IRS-1 > PI3K > Akt/PKB) is associated with upregulation of pyruvate dehydrogenase kinases (PDKs) driving inactivated phosphorylation of pyruvate dehydrogenase enzyme complex. This inhibits the entrance of pyruvate into the mitochondria from the cytosol where glycolytic metabolism of glucose is initiated. Isoforms

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Insulin Resistance in Metabolic Disease of PDK differ depending on the tissue. PDKs are linked to the development of several neurological disorders, including Alzheimer’s disease. This is consonant with the intertwined relationship of insulin resistance with Alzheimer’s disease discussed above. Alzheimer’s disease along with reduced pyruvate dehydrogenase activity and associated mitochondrial glucose oxidation corresponds to increased PDK2 in the hippocampal formation and the cerebral cortex. PDK2 is also upregulated in glioblastoma, consistent with impaired mitochondrial function in the Warburg effect in cancer. Teleologically, hypothalamic upregulation of PDK4 is considered to reflect an attempt to conserve energy during food deprivation. Insulin resistance in today’s modern world of energy surplus is not adaptive in this context. When available resources are scarce, the speed of energy production takes priority over efficiency. Food acquisition and energy expenditure are more typically required in rapid spurts.

7.7.4 Therapeutic Strategies for Treatment Based on mechanistic insights of Alzheimer’s disease and accelerated cognitive decline, as well as other neurodegenerative and psychiatric disorders (not discussed), a few novel therapeutic strategies deserve mention. Inhaled intranasal insulin that allows enhanced delivery of insulin into the brain. This appears to be useful for accelerated cognitive decline, Alzheimer’s disease, anxiety, depression and Parkinson’s disease in the setting of insulin resistance, to prevent the full manifestations of these pathologic states if used early (275– 277). The indirect insulin-sensitizing agent metformin and the glucagon-like peptide-1 (GLP-1) agonist liraglutide upregulate insulin receptor substrate –1 activation and insulin signaling (278–283). It is through the insulin signaling pathway that they act to reduce oligomeric amyloid beta neuritic plaque load and microglial activation (and hence inflammatory response), and increase neurogenesis, long-term potentiation (LTP), memory, and cognition in Alzheimer’s disease rodent models (284). The monoamine oxidase (MAO) A and B inhibitors also appear to offer potentially promising therapeutic advantages to the prevention and treatment of Alzheimer’s disease, Parkinson’s disease, as well as anxiety and depression disorders. MAOs sit just outside the outer mitochondrial membrane and increase the oxidative clearance of dopamine. The elevated reactive oxygen species that result from reduced insulin signaling and mitochondrial dysfunction promote the activation of MAOs that contribute to these diseases. In general, the utilization of early clinical and biochemical markers of insulin resistance and mitochondrial dysfunction may provide remarkable benefit when coupled to the routine use of fitness or free energy landscapes employing cascades of control and order parameters which are powerful tools in medicine, both research and bedside.

7.7.5 Bioenergetics, PDK, and Alzheimer’s Disease Insulin resistance and type 2 diabetes are associated with increased PDK in the hippocampus (a brain region for memory). If hippocampal PDK accelerates cognitive decline in early Alzheimer’s disease, then hippocampus-specific PDK

inhibitors would be a compelling target. PDK inhibitors are in the pharmaceutical pipeline of development and may prove useful for patients with metabolic inflexibility with insulin resistance and type 2 diabetes that have an impaired ability to suppress pyruvate dehydrogenase kinase enzyme activity. Individualized therapy in the near future is expected to be able to match the tissue-specific benefits of the particular PDK inhibitor, as well as other therapeutic interventions, with the manifestations of an individual patient so as to achieve the highest benefit to risk ratio. This will be made possible with future generations of electronic medical records, for example, the IBM Watson model, as well as the field of Quantitative Biomedicine. Dichloroacetate and lipoic acid are currently available agents that generally suppress PDK, although they are weak inhibitors, and in the former case may be toxic. Resistive exercise training, particularly in conjunction with novel approaches for enhancing carnitine availability to skeletal myocytes, appears promising for improving muscle insulin resistance. It should be emphasized that molecular insights into biology are highly complex and nonlinear.

7.8 Integrated Systems Biology Approach to Human Health and Disease The integrated complex relationships between seemingly disparate organ systems are increasingly recognized as being of critical importance. Again, it points to the deeply entangled nature of the subsystems of biology that evolved with exquisitely eloquent feedback systems for the purpose of providing robustness and resilience of autonomous living systems as a whole. Resilience is the capacity to maintain allostasis and homeostasis under adverse external conditions. Robustness helps to maintain resilience.

Robustness theory, which emerged from the control systems of engineering, has to do with feedback regulation of the system in the setting of adverse external conditions. The greater the number of interactions and redundancies in the system, the finer tuning of the feedback regulations. This has a lot to do with redundancies in the systems, which are built-in for the purpose of safety and stability. A great example of systems that were not expected to be integrated until only a few years ago is that of bone metabolism, insulin signaling, and total body energy homeostasis. In the model of a physiological fitness landscape, this unveils the curtain to a host of model relationships that provide clinical fodder for physicians practicing an art of medicine that sits on top of the science. The physiological fitness landscape fundamentally is a free energy metabolic landscape of connections between the systems. New perspectives of looking at these relationships in terms of primary and secondary order parameters and control parameters frame this physiological fitness landscape and provide an excellent clinical model that is keenly adaptable to highly individualized patient care.

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7.8.1 Osteocalcin and Insulin Signaling Osteocalcin is the predominant protein of the bone matrix, excluding collagen. There are recent provocative data showing an endocrine role of osteocalcin on whole-body energy homeostasis and metabolic function, with the implications that deficient or abnormal osteocalcin production from bone results in metabolic disease states of insulin resistance, type 2 diabetes, obesity, and hypogonadism (285–287). Vitamin D increases osteocalcin and has traditionally been considered the primary driver of bone formation. However, it appears it may act only indirectly to promote bone formation and mineralization mediated by the osteoblast. Vitamin D works in concert with parathyroid hormone (PTH) to mobilize calcium from bone. This concerted action of vitamin D3 (calcitriol; 1,25 (OH2) vitamin D) and PTH appears to be one of the most potent inducers of osteoclastic bone resorption. This occurs through stimulated expression of the apoptosis regulator gene receptor activator of nuclear factor kappa-B ligand (RANKL), a ligand on the osteoblast, and interaction with receptor activator of nuclear factor kappa-B (RANK), a receptor on the osteoclast (288). RANKL is referred to as osteoclast differentiation factor. This physiology was exploited by the drug teriparatide that increases bone mass by driving osteoblastic bone formation over osteoclastic bone resorption. Osteocalcin has been shown to have a number of interactions underpinning its integrated relationship on affecting whole-body energy homeostasis. These effects include: 1) an indirect insulin secretory action on the pancreatic beta cells; 2) enhanced release of GLP-1 from the enteroendocrine cells of the distal small intestine; 3) enhanced adiponectin levels in the circulation; and 4) enhanced insulin sensitivity in muscle. Notably, vitamin D, by binding to the vitamin D receptor with subsequent binding to the osteocalcin response element promotes transcription of osteocalcin. Intriguingly, while it is not surprising that this effect increases bone density and mineralization, it also enhances insulin secretion and sensitivity. Vitamin D deficiency is thus a susceptibility state for insulin resistance, type 2 diabetes, obesity in addition to osteoporosis.

SIDEBAR 7.8: VITAMIN D SUPPLEMENT AS A TREATMENT Recent research has examined the use of vitamin D supplementation in the treatment and management of pathologies such as insulin resistance, type 2 diabetes, obesity, and osteoporosis. For example, research from Kanazawa and colleagues suggests that intermittent injection and oral administration of osteocalcin may be useful for the treatment of type 2 diabetes, obesity and in the prevention of metabolic disease in insulin-resistant states (289). Further, Pittas and others have shown that serum osteocalcin concentration inversely correlated with serum markers of insulin resistance, glucose intolerance, inflammation as well as measures of adiposity (290). Studies from Lee have also demonstrated that skeletal osteocalcin profoundly affects insulin sensitivity, glucose tolerance, and fat metabolism (291, 292).

Metabolism and Medicine Osteocalcin is a well-accepted marker of bone osteoblastic activity. Under-carboxylated osteocalcin is a marker of hip fracture risk in elderly males (293). While there is no clinical evidence yet that pharmacologic agents that increase circulating osteocalcin levels, for example, teriparatide, improves metabolic health, this likely speaks to biological complexity and still unidentified mediators and regulating factors.

7.8.2 Adiponectin, Leptin, and Insulin Signaling Adiponectin is an important adipokine that regulates insulin sensitivity and has an important role in mediating the systemic metabolic effects of osteocalcin. Adiponectin and leptin are the two most abundant and well-studied adipokines. They both exert favorable effects on energy expenditure and homeostasis shared in part by upregulating AMPK. Leptin signals centrally in the brain to suppress appetite as well as directly on skeletal muscle to increase insulin-like growth factor binding 2 (IGFBP2) expression. Increased IGFBP-2 binds IGF-1, reducing its free and bioavailable concentrations; this in turn will reduce gluconeogenesis and hepatic glucose output, enhance muscle insulin sensitivity, and promote net bone resorption (265). Apart from energy storage, adipose tissue acts as an endocrine organ that secretes several cytokines (adipokines). Adipocytes communicate with skeletal muscle and liver through adipose-derived adipokines such as adiponectin and leptin to maintain whole-body energy homeostasis (294). A dysregulation of adipokine secretion leads to the development of metabolic diseases. Adiponectin is a large complex protein molecule and because of its complexity, researchers have developed small molecule adiponectin receptor agonists or “adiponectin mimetics” as a therapeutic approach. It has recently been observed in mice that treatment with the adiponectin receptor agonist AdipoRon or the adiponectin mimetic GTDF considerably improves glucose intolerance, insulin sensitivity, and whole-body metabolism (295, 296). Furthermore, by promoting insulin sensitivity of skeletal muscle and hence increased muscle mass, the shared embryological origin of skeletal muscle and bone and the integrated function of these two tissues remain parallel throughout life. Indeed, a signature morbidity of senescence is sarcopenia and associated osteoporosis in both men and women. The effect of leptin on bone is further partly explained by suppression of the gene that codes for osteocalcin, which is mediated by leptin’s effect on sympathetic tone. Nonetheless, there is a magnificent beauty of nature’s evolutionary design, which is not always intuitive, and due to the complexity of interactions, it is not surprising that answers to this and many other questions in the scientific realm of biology and medicine are not known. This again highlights the notion that the practice of medicine is an art that sits on top of the science. Leptin interacts with the immune system, predominantly by activating monocytes and T cells, setting in motion a chain of interactions (297). For example, leptin activates the monocyte to release interleukin 1, interleukin 6 and TNFα, which in turn activates naive T cells, stimulating their release of IL-2 and interferon gamma (IFNγ), and their differentiation into

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Insulin Resistance in Metabolic Disease effector T helper-1 (Th-1) cells. IL2 and interferon gamma further act on the activated monocyte to promote further cytokine release. It has also been shown that leptin and IL-6 share the signaling pathways of JAK–STAT, PI3K, and MAPK (297). In addition to the obesogenic and associated proinflammatory effects in settings of hypoleptinemia and leptin resistance/ hyperleptinemia, leptin signaling can be either inflammatory or anti-inflammatory, which are context and cell dependent. While leptin-induced IGFBP-2 expression discussed above promotes skeletal muscle insulin sensitivity and reduces visceral adipose tissue fat accumulation, in macrophages leptin drives a feedforward loop of proinflammatory cytokine production. In the former setting, the natural consequence of reduced visceral adiposity is less macrophage infiltration. Conversely, increasing levels of visceral adipose tissue and fat result in the expression of inflammatory cytokines IL-1, IL-6, and TNF-alpha by the adipose tissue infiltrating macrophages induced by leptin. This in turn bidirectionally perpetuates the loop and sustains the chronic inflammatory state of obesity by upregulating the transcription of leptin in the adipocyte (298). The relationship between leptin, immune system function, and inflammation is however highly complex and nuanced. Leptin enhances insulin release by directly promoting the first phase of insulin release, mediated by pancreatic-specific leptin receptors. However, leptin also exerts modulatory effects on insulin secretion via the sympathetic nervous system. It is unclear how these two opposing actions have teleological significance.

7.8.2.1 Leptin and Circadian Insulin Signaling Leptin regulates the circadian rhythm of the hypothalamicpituitary-adrenal, gonadal and thyroidal axes to optimally calibrate energy availability to metabolic demands. Leptin plays an important role in the sleep-wake cycle and the circadian rhythm of insulin and fasting glucose (299, 300). Alternatively, leptin co-opts insulin signaling through a variety of pathways, such as JAK-STAT, ERK1/2, PI3K, and AMPK, which are context and cell dependent, hence serving as a secondary order parameter protective against metabolic sequelae of insulin resistance. It preserves insulin signaling in the face of counter-regulatory factors (301, 302). As an aside, leptin signaling occurs primarily through the pathways of JAK–STAT, ERK1/2, PI3K, and AMPK. It follows, for example, a disturbed sleepwake cycle is a secondary order parameter of both leptin resistance and insulin resistance, as well as glucose intolerance, obesity, and other downstream metabolic disease states of insulin resistance. This further highlights the feedforward relationship between leptin resistance and insulin resistance, which is a self-propagating destructive cycle. Leptin exerts a satiety effect through regulation of neuropeptides, by signaling through the leptin receptor, found on neurons in the arcuate nucleus in the hypothalamus. NPY (neuropeptide Y) and AgRP (agouti-related peptide) are orexigenic neuropeptides; leptin signaling inhibits NPY/AgRP by co-opting the insulin PI3/Akt signaling pathway (303). Similarly, leptin signaling activates satiety-inducing neuropeptides POMC (pro-opiomelanocortin) and CART (cocaineand amphetamine-related transcript), which subsequently

FIGURE 7.18  Leptin signaling causes the brain to receive a “fullness” signal when eating. Obesity can cause leptin resistance, making it harder to know when one is full, and when to stop eating. This creates a feedforward cycle of obesity and leptin resistance. Source: adapted from (306). *AGRP = agouti-related peptide; CART = cocaine- and amphetaminerelated transcript; MCH = melanin-concentrating hormone; NPY = neuropeptide Y; ORX = orexin; POMC = proopiomelanocortin.

act largely on neurons in the paraventricular nucleus of the hypothalamus (Figure 7.18) (304, 305). Overall, leptin acts to reduce food intake. During leptin resistance seen in states of obesity, the positive energy balance is further potentiated. Perhaps independently of leptin’s effect on the circadian rhythm of the hypothalamic pituitary adrenal, gonadal and thyroid axes are additional effects on neuroendocrine function. Moreover, the hypothalamic pituitary growth hormone axis is also regulated by leptin (307). It follows that leptin resistance is associated with a blunted growth hormone response (308, 309). Leptin has a complex effect on the hypothalamic pituitary adrenal axis. Leptin acts directly on the adrenal gland to inhibit cortisol release from adrenocortical cells (310, 311). However, centrally leptin opposes cortisol feedback suppression of CRH in the hypothalamic paraventricular nucleus, mediated by endocannabinoid biosynthesis and release. Thus, leptin disinhibits the feedback suppression of CRH by cortisol, potentiating the CRH driven stress response. Accordingly, leptin resistance attenuates the cortisol stress response. This relationship is interesting because while leptin resistance promotes obesity, insulin resistance and metabolic disease states downstream of these secondary order parameters, it counterbalances the toxic metabolic effects of the prolonged HPA stress response. Therefore, leptin resistance in a clinical scenario can be expected to contribute to these clinical common manifestations and presentations. Understanding this helps a clinical reassurance that treating the common upstream causal parameters to insulin resistance and resultant leptin deficiency can avoid anxiety perhaps and needless workup for other causes.

7.9 Symmetry, Neuroendocrinology, and Insulin Resistance The discussion of symmetry and symmetry breaking in biology and pathobiology may importantly be considered in the context of control and order parameters, especially as it pertains to the opportunities that abound interventionally in medicine. A central and perhaps paragon system in biology

308 to look at is the neuroendocrine response to stress. As discussed in other chapters, this central neuroendocrine axis may be extended to psycho-neuroendocrine response, the psychoneuroendocrine-immune response, and even the psych​o-neu​ roend​ocrin​e-imm​une-g​astro​intes​tinal​ response to stress. Each of the components of these axes contributes at a fundamental level to the pathogenesis of disease states. At this juncture, we will focus on the psychogenic neuroendocrine stress response as both physiologically adaptive and pathologically maladaptive, highlighting in each case the role of symmetries and the identification of order and control parameters.

7.9.1 Order and Control Parameters in Insulin Resistance The relationship of order to control parameters in biological systems is helpful to be understood from the perspective of symmetries and asymmetries to appreciate the nonlinear nature and complexity of these systems, as well as their relationship to health and disease. The reader is referred to a detailed exposition of these general physical concepts and their relevance to biology in Volume 1, especially in the “Roadmap to Future Medicine” chapter. In general, the response to stress represents symmetry breaking with the formation of new symmetries made possible by a high degree of freedom, robustness, and resilience, and external perturbations provided by allostatic responses. These healthy allostatic changes maintain physiological homeostasis at the organismic level. While these changes create new symmetries at the expense of breaking the old, the new symmetries should be recognized as asymmetries relative to the now broken baseline symmetries. Symmetries in this context refer to a new dynamic balance of a living system, which is adaptive and maintains the health of the organism. The loss in the ability to form new adaptive symmetries equates to a loss of robustness (redundancies) and flexibility of allostatic compensations, which together represent a loss of resilience to external perturbations to the system, the organism. In addition to considering the psycho-neuro-endocrine stress response in the context of symmetries and symmetry breaking as well as the identification of order and control parameters, this discussion will be oriented from the perspective of insulin signaling and the role of insulin resistance both physiologically and pathogenically. As abundantly elaborated on in Volume 1 of this book, symmetries represent invariant properties of the state of a physical or biological system. Physical systems are static (in thermodynamic equilibrium) by comparison to biological systems which are dynamic (out of thermodynamic equilibrium). Therefore, in physical systems symmetries are often manifested by invariance with respect to some spatial or temporal operation, e.g. rotations. In living systems symmetries can be found in their response to external influences, e.g. invariance of the human physiology to diurnal or seasonal cycles. A broken symmetry signifies a newly established lack of invariance. For example, the onset of a disease may manifest itself by disturbances in the sleep patterns of the person. Comparing the physiological state of the same person before and after the onset of the disease can identify the socalled order parameters. These are the parameters that changed

Metabolism and Medicine significantly as a result of the broken symmetry. An example of an order parameter could be the person’s cystolic blood pressure which could be correlated with sleep disturbances or other manifestations of the underlying disease. Finally, we can also introduce control parameters that are externally applied perturbations to the state of human physiology. There can be an infinite number of control parameters since literally every physical, chemical, psychological or other type of stressor affects our physiology. Specific examples of control parameters include nutrient disturbance or psychogenic stress. Considering nutrient disturbances and psychogenic stressors as control parameters per se does not differentiate these control parameters as healthy or unhealthy. A calorie-depleted diet acutely, for example, leads to a healthy stress response that promotes energy availability to tissues. Conversely, nutrient excess results in insulin resistance, as an attempt to prevent obesity. In the case of prolonged disturbance of these control parameters, the healthy adaptive stress response and the ability to form new symmetries serve as limiting factors, hence is the harbinger of disease. In the case of psychogenic stressors as control parameters, imagined stress when acute may be motivating; hence adaptive stressors activating the sympathetic nervous system and hypothalamic pituitary stress response may be lifesaving in the case of a real physical threat. However, psychogenic stressors are often pathologically prolonged in modern society, thus overextending the adaptive nature of the stress response as an order parameter and leading to pathology or disease. The notion of control parameters, which may take many forms, is exemplified here as either various nutrient disturbances or psychogenic stressors. Downstream order parameters are the components of the stress response, the sympathetic nervous system, and hypothalamic pituitary neuroendocrine responses. Notably, the psychogenic component of the psychoneuroendocrine stress response may be considered a control parameter, but is generally viewed as both a control and an order parameter because it is part of a feedforward process. These order parameters in turn become control parameters for further downstream effects. That is, the neuroendocrine stress responses become control parameters for the downstream effects of insulin resistance.

7.9.2 Insulin Resistance as a Chronic Control Parameter The manifestations of insulin resistance are designed to be adaptive in the acute setting. However, when the underlying control parameters are chronic, insulin resistance becomes the control parameter to the susceptibility for disease states within the landscape of the overall fitness or free energy of the organism. In this case, the chronic neuroendocrine stress response is the immediate control parameter with the more upstream parameters being in this example the nutrient disturbances or psychogenic stressors. The susceptibility for chronic disease state as the order parameters of insulin resistance being the control parameter, as well as the more upstream control parameters of the neuroendocrine stress responses and nutrient or psychogenic stressors, the susceptibility for disease state

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Insulin Resistance in Metabolic Disease now becomes the control parameter for downstream chronic disease such as accelerated cognitive decline and Alzheimer’s disease, cancers and cardiovascular disease. The further downstream we go in these schemata of control and order parameters, the less capable the system as an organism is of healthy resilience and allostasis to the external perturbations. With the continual breaking of old symmetries and forming of new symmetries, there becomes distinctly greater asymmetry from the prior order. Each of these identifiable control parameters becomes a target for intervention in medicine for treating the downstream pathological order parameters. The further upstream the intervention, the easier it is to change the trajectory to a healthy basin of attraction, which means a range of physiological parameter values that maintain the stability of the living system. Homeostasis which plays such an important role in human physiology is conceptually related to the dynamic stability of physical systems under perturbation. This means that over a finite range of parameter values the system under perturbation will return to its normal behavior when the perturbation is removed. This range of parameters is called the basin of attraction. A healthy person can undergo a strenuous exercise regimen to restore the physiological parameters to normal values within an hour or less of rest. A person suffering from cardiovascular disease subjected to the same level of physical stress may instead suffer a heart attack. This represents parameter values outside a healthy basin of attraction for this person. Consequently, even in the setting of a disease such as the chronic diseases just listed, there may be a reversible and an irreversible phase whereby interventions are unable to change the trajectory of the basin of attractions with each disease state to a healthy one. However, once a chronic disease manifests, what previously was considered irreversible may indeed lend itself to reversibility. It should be the aim in medicine to target upstream control parameters wherever possible. Nutrient disturbances as upstream control parameters may be in the form of three pathological patterns: nutrient depletion; energy excess; and dietary toxicants, the pollution of diet with greater than 80,000 processing chemicals introduced in the 1970s. Psychogenic stressors as control parameters may take many forms. Being the caretaker of a sick and elderly parent, or other loved one, ranks among one of the most stressful circumstances in life. Loss of physical health is also a significant psychogenic stressor; importantly, this relationship is bidirectional. Perceived stress worsens physical health, and mediated by inflammatory protein cytokines, physical health decline reduces the threshold for tolerance of external stressors. It is worthwhile in making the above distinctions of nutrient disturbances and psychogenic stressors as control parameters in order to discern them as targets of upstream interventions to prolonged and pathogenic order parameters of the neuro-endocrine stress responses which in turn, as described above, become control parameters for insulin resistance and subsequent disease states of insulin resistance including not only type 2 diabetes but chronic disease states of accelerated cognitive decline, Alzheimer’s disease, cardiovascular disease, and cancers should be recognized as metabolic disease states.

SIDEBAR 7.9: SYMMETRY AND SYMMETRY BREAKING A healthy human body is a perfect example of an exquisitely constructed and highly efficient biological system with built-in strategies for adaptability and survival under various forms of stress and environmental challenges. Its organizational perfection can be seen through spatiotemporal symmetries. Symmetries refer here to a dynamic balance of a living system, which is adaptive and maintains the health of the organism. Two main strategies in response to stress are: a) increased resilience, which maintains the state of symmetry, or b) symmetry breaking and establishing a new stable state with new symmetries. This adaptability is clearly seen in the mechanisms of homeostasis and allostasis, the former maintains symmetry while the latter may lead to new symmetries. Healthy allostatic changes maintain physiological homeostasis at the organismic level. A canonical example of maintaining symmetry when exposed to stress and making the system even more resilient than before is called hormesis. Somewhat paradoxically, some responses leading to pathologies, such as insulin resistance, can be viewed as manifesting adaptation by breaking old symmetries and finding new ones, which are better suited to the prevailing conditions. Moreover, type 2 diabetes can be seen as an adaptation, not just a pathology. The human body automatically optimizes its response by finding the highest fitness state achievable. Losing the ability to form new adaptive symmetries under stress represents a loss of robustness, flexibility of allostatic compensations, and hence resilience to external perturbations challenging the biological system. Aging and senescence gradually lead to a complete loss of adaptability when a biological system turns into its physical shadow incapable of entropy reduction and symmetry restoration enabled by metabolism, the essence of life.

SIDEBAR 7.10: SHOULD DIABETES TYPE 2 BE CONSIDERED AN ADAPTATION RATHER THAN A DISEASE? The human body is an exquisitely constructed biological system characterized by extremely robust adaptability. This adaptability can be clearly seen in the mechanisms of homeostasis and allostasis, which have been discussed in detail elsewhere in this volume. Some of the manifestations of this process of adaptation to externally generated stresses may appear paradoxical at first. One such example involves hormesis whereby a relatively limited amount of radiation damage to the tissue stimulates not only its repair but additional growth and improved stability. Below, we hypothesize that type 2 diabetes can also be viewed as an adaptation, not just a pathology. While the prevalence of diabetic adults in the US is an estimated 10.5% (American Diabetes Association, 2018) and 8.5% worldwide (World Health Organization, 2014), the

310 metabolic state of prediabetes in the US, measured by a fasting glucose or a hemoglobin A1c, is roughly 34.5% (Center for Disease Control and Prevention, 2013-2016). Notably, the condition of prediabetes and its significance are both under-recognized. Indeed, only ~15% of the population reported being told of the diagnosis, less than half of those with the condition (Center for Disease Control and Prevention, 2013–2016). Importantly, the state of prediabetes, characterized by insulin resistance and endogenous hyperinsulinemia, is a predisposing state for the major chronic diseases of aging, namely AD (312), cancer (313), and CVD (314). Within the perspective of the Physiological Fitness Landscape, we can envisage the state of prediabetes as a condition associated with declining metabolic fitness and hence altitude on the PFL topological terrain. Accordingly, it can be proposed that the conversion to type 2 diabetes due to a pancreatic beta cell defect represents an adaptation associated with breaking symmetry and forming a new symmetry as a complex adaptive system. The new stable symmetry state is portrayed by declining insulin secretion and hence promotes less atherogenesis, less cancer cell stimulated mitogenesis, and reduced brain insulin resistance mediated AD. Thus, it can be argued that the human body optimizes its response by calculating the highest fitness state under the prevailing constraints. This results in reduced hyperinsulinemia in the presence of diabetes, which provides greater protection against further declines in physiological/metabolic fitness (as a stability zone with a steeper slope) than would be the case in the absence of diabetes with greater hyperinsulinemia. It can, therefore, be concluded that the human body’s selection of the prediabetic state is a manifestation of its evolutionary adaptation and not its failure. Using colloquial language, this is a lesser of the possible evils which the PFL predicts emerge as stable states (valleys) within the given conditions of aging.

7.9.3 Stress as an Allostatic Response: Corticotropin Releasing Hormone and Growth Hormone as Antagonizers of Insulin Action Stress is any situation that may disturb the equilibrium of a living organism and its environment. This equilibrium is asymmetrical, an adaptive homeostasis of the organism in the setting of its environment. The responses of the organism to the stress are allostatic responses to maintain homeostasis. These allostatic neuroendocrine responses include various hormonal changes such as enhanced secretion of glucocorticoids, catecholamines, growth hormone, prolactin, and vasopressin. These stress responses are considered necessary for survival in the classical fight or flight setting to adaptively increase mobilization of energy sources, optimized immune function as well as wound healing. The neuroendocrine response to stress includes the secretion of corticotropin releasing hormone (CRH) from the paraventricular nucleus of the hypothalamus. This secretion of CRH is mediated by an integrated neurotransmitter stimulation of norepinephrine, serotonin, and

Metabolism and Medicine acetylcholine. CRH stimulates proopiomelanocortin (POMC) production in the anterior pituitary, which is further cleaved to endorphins (to control physical pain) and adrenocorticotropic hormone (ACTH; to promote the secretion of cortisol) necessary for the anticipated fight or flight response. Growth hormone is also increased during acute physical stress and antagonizes insulin signaling, hence promoting energy mobilization, allowing availability of energy sources to the body systemically. Interestingly, chronic psychological stress is not usually associated with a growth hormone response. Importantly, it should be highlighted that the purpose of the acute stress response is to promote the calibration of limited energy resources to the fight or flight response intended to keep the organism alive from an evolutionary perspective. Accordingly, it calibrates these resources away from energy-expensive processes such as reproduction. Fundamentally, the functions of cortisol and growth hormone antagonize insulin signaling which is important to the overall response of promoting glucose and fatty acid delivery to the brain, heart, and skeletal muscles allowing the appropriate preferred energy source to their respective tissues to optimize the fight or flight response. In addition to the hormonal component of the neuro-endocrine response, the catecholamine response is inextricably part of the fabric of this stress response. Catecholamines importantly contribute to nutrient delivery as well as other independent effects on sharpening cognition, sight, hearing, and other senses that put the body in a state of hair-trigger alert. Some of the effects of catecholamine that mediate the stress and hence fight or flight responses include hemodynamics such as activating the renin angiotensin aldosterone system promoting sodium retention from the kidney, the release of antidiuretic hormone (ADH) or vasopressin, promoting retention of free water, and increased cardiac output (both heart rate and ventricular force), all of which promote the adequate flow of blood carrying nutrients and oxygen to peripheral tissues. Catecholamines as neurotransmitters of the sympathetic nervous system reduce intestinal motility and increase cutaneous vasoconstriction. It promotes gluconeogenesis, the production of glucose from other nutrient precursors such as lactate, amino acids, and glycerol in a variety of tissues, most importantly the liver. Through beta receptors, catecholamines enhance bronchodilation for deep breathing, allowing oxygenation of tissues during this high metabolic demand state. Finally, it mediates behavioral activation as mentioned above to enhance cognition. The stress-induced catecholamine response to many, albeit not all, of these behaviors is mediated by its antagonism of insulin signaling and hence insulin action. This includes the increased hepatic glucose output not only from gluconeogenesis but also glycogenolysis, the breakdown of glycogen into glucose, as well as fatty acid output from adipose tissue due to enhanced lipolysis (as well as reduced lipogenesis). Skeletal muscle efficiently utilizes fatty acids in times of stress allowing the glucose to go to places like the brain that is not adept at using fatty acids as a fuel source. Also, in addition to the impairment of insulin signaling, catecholamines may directly suppress insulin secretion from the pancreatic beta cells.

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Insulin Resistance in Metabolic Disease Insulin is not only important for example in glucose transport into skeletal muscle, the suppression of glucose output from the liver, and the suppression of fatty acid released from adipose tissue, it also plays critical roles in promoting protein synthesis in cell growth, cell replication, inhibiting programmed cell death, (apoptosis), promoting vasodilation and inhibiting counter-regulatory gene expression such as due to cortisol and catecholamines, just to name a few.

7.9.4 Prolonged Stress Response Resulting in Allostatic Load An acute stress response is a deeply rooted evolutionary adaptation partially mediated by a state of insulin resistance, which represents a breaking of the symmetry and forming new symmetries. The stress response described to a modest extent above represents allostatic changes to mediate forming new adaptive symmetries. However, when the stress response is excessive or prolonged, a state of allostatic load ensues. In this state, the allostatic responsiveness exhibits a loss in the resilience of the body against the external perturbations that provoked the stress response, and hence the capacity to form new symmetries as a continuum of breaking old symmetries and maintaining organismic-wide homeostasis reaches its limitations. Beyond this threshold, dynamic reorganization of structural or functional information with the inextricable flow of energy through this information becomes impaired accompanying a rise in oxidative stress and changes in acid-base status. This corresponds to the loss of molecular fidelity, that is, loss of molecular function in tandem with the loss of energy available to do useful biological work or free energy, into heat and promoting entropy. This state of allostatic overload prior to the onset of chronic disease represents an order parameter of insulin resistance whereby the landscape of free energy and fitness represents a susceptibility state to chronic disease. This excessive or prolonged stress response may be rooted in epigenetic factors, that is, environmental exposures as well as genetic predispositions for abnormal perceptions of stress. It may also be rooted in the prolonged nature of psychogenic stress, whether real or imagined. Finally, it may be underpinned by unremitting physical stress such as diet or other physical exposures such as toxicant chemicals in the diet. Thus, these factors that promote the prolonged stress response themselves represent control parameters. In this case, the stress response represents an order parameter, and the subsequent insulin resistance that mediates the disease susceptibility state or state of allostatic overload becomes a more proximal control parameter.

7.9.5 Targeting Upstream Control Parameters to Treat Disease When control parameters are further upstream, they provide more effective targeting therapy to successfully change the trajectory into a healthy basin of attraction. Notably, chronic disease states that are consequences of insulin resistance such as cardiovascular disease, cancer, Alzheimer’s disease, or

even accelerated cognitive decline, represent metabolic disease states due to the inability of the body to mount further responses that break the existing symmetries and form new ones. For example, excessive cortisol signaling on hippocampal neurons that are responsible for the cognitive decline initially in short-term memory cannot be abrogated by further adjustments in endocrine and hormonal responses. That is, the elevated cortisol and resistance to insulin that provided the initial breaking of symmetry and adaptive response in the acute event of stress were no longer adaptive and further symmetry breaking and finding new solutions is not possible. In the case of cancer, the unregulated cell replication and growth as a consequence of the prolonged chronic insulinresistant state actually occurs in epithelial cell tissues such as the reproductive and gastrointestinal tracts; a consequence of excessive insulin signaling, and a casualty of the compensatory allostatic response of hyperinsulinemia that often occurs accompanying the metabolic tissue insulin resistance. In this case, the endogenous hyperinsulinemia represents a control parameter. Hence both molecular biology and traditional biochemistry will be important components to look at in their respective roles as order and control parameters in the overall schemata for this modeling approach for the prevention and treatment of these devastating metabolic chronic disease states. It is also worth mentioning that disturbed redox chemistry with pro-oxidative and proinflammatory states that mediate disease should be highlighted as important therapeutic targets and control parameters to these chronic diseases. However, it should also be recognized in the context of the overall picture whereby these control parameters are also order parameters but more upstream events. The problem with aggressively addressing molecules as therapeutic targets, such as NFkB or other proinflammatory cytokines or particular reactive oxygen species as control parameters, is that upstream stressors and control parameters remain unabated and ultimately generate their own allostatic repertoire that promotes the ultimate goal of the arrow of time in biological systems is the acceleration of senescence, disease and perpetuating the loss of molecular fidelity and in tandem the loss of heat for useful biological functions to entropy. The loss of biological complexity accompanying the decrease of free energy and the decline in the physiological fitness landscape is consistent with the notion that immunosuppressive therapy may be effective in treating an autoimmune disease. Such therapy often tips the scale away from the chronic autoimmune disease instead in the direction of promoting cancer.

7.10 Chapter Take-Home Messages • Insulin resistance occurs under both healthy and pathologic conditions. In healthy tissue insulin resistance is maintained under cyclical circadian patterns that are adaptive and maintain cell stress resilience programs. Conversely, insulin resistance becomes

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Metabolism and Medicine pathological when not following cyclical circadian patterns. Extrinsic control parameters of insulin resistance include periods of prolonged stress, diet quantity and quality, gut microbiota, and circadian synchronicity. The respiratory quotient (RQ) is a clinically useful tool to measure mitochondrial inflexibility, which is indicative of insulin-resistant states. Increased levels of reactive oxygen species (ROS) and advanced glycation end products (AGEs) generate inflammation and are associated with insulin resistance. Insulin resistance affects the different tissues of the body (i.e. metabolic, skeletal, cardiac, adipose tissues) in unique ways There is a bidirectional self-amplifying relationship between insulin resistance and mitochondrial dysfunction, where either can drive the other. Insulin resistance can contribute to the pathogenesis of cardiovascular disease, though cardiovascular disease can occur without insulin resistance. High levels of free radicals and oxidative stress are associated with insulin resistance, while low levels promote healthy physiological effects Insulin resistance (along with mitochondrial dysfunction) contributes to the pathogenesis of cancer via the Warburg effect. This effect can be described as the inability of native host cells to efficiently utilize available oxygen to meet their bioenergetic needs. Thus, cancer cells can outcompete them for available resources using glycolytic metabolism. Insulin resistance can also contribute to the pathogenesis of Alzheimer’s disease and accelerated cognitive decline by altering states of tau protein phosphorylation that affect microtubule dynamics. Altered states of tau protein can additionally lead to neurofibrillary tangles and amyloid plaques.

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8 Mitochondrial Function and Dysfunction and Insulin Resistance

Abbreviations ɑKG AMPK CO2 CACT CPT-1 CoA CoA-SH CoQ10 DAG e ETF ETFQO FAD FMN HMG HMG-CoA H+ LC LCFA MCD mTOR MCAD NAD+ NHR NRF OGT PPAR PFK PDH PDC ROS RET TFA TCA cycle Vit

ɑ-ketoglutarate AMP-activated protein kinase carbon dioxide carnitine-acylcarnitine translocase carnitine palmitoyltransferase 1 coenzyme A coenzyme A not attached to an acyl group coenzyme Q10 (also known as ubiquinone-10) diacylglycerol electron electron transferring flavo-protein ETF coenzyme Q dehydrogenase flavin adenine dinucleotide flavin mononucleotide 3-hydroxy-3-methylglutaryl 3-hydroxy-3-methylglutaryl-CoA hydrogen long-chain long-chain fatty acid malonyl CoA decarboxylase mechanistic target of rapamycin medium-chain acyl CoA dehydrogenase nicotinamide adenine dinucleotide nuclear hormone receptor nuclear respiratory factor O-linked N-acetyl glucosyl transferase peroxisome proliferator-activated receptor phosphofructokinase pyruvate dehydrogenase pyruvate dehydrogenase complex reactive oxygen species reverse electron transport transcription factor A tricarboxylic acid cycle vitamin

Chapter Overview This chapter is where we connect all the dots regarding the bioenergetics of metabolism. We detail the crucial function of mitochondria in health and discuss how the inextricable and bidirectional link between dysfunction of mitochondria and resistance to insulin contributes to chronic diseases of aging. We consider underlying and intertwined factors such as the stress response, circadian rhythms, gut microbiota, immune system response, and bioenergetics. DOI: 10.1201/9781003149897-8

The central ideas covered in this book are metabolic health, metabolic disease, the initiation of metabolic health and disease, and therapeutics aimed at slowing down, stopping, or even reversing metabolic dysfunction. Metabolic health is directly linked to the energy-producing organelles, mitochondria. Dysfunction of mitochondria is associated with insulin resistance and changes in VO2 max and VO2 submax. Skeletal muscle biopsy with cell mitochondrial stress testing can assessVO2 max and VO2 submax using rotenone and other electron transport chain inhibitors. In the sense that mitochondrial function and insulin signaling are inseparably intertwined, mitochondrial dysfunction is interwoven in the fabric of insulin resistance. Whether the presence of insulin resistance and mitochondrial dysfunction overlaps completely remains unclear. Comparable to “the chicken or the egg”, the question of which of these parameters came first in the pathogenic process is posed. We would argue that this bidirectional, feedforward relationship may be initiated by either mitochondrial dysfunction or insulin resistance, depending on patient-specific circumstances and genetic susceptibilities. On the one hand, it may be that all patients either develop insulin resistance as a cause, and subsequently an effect, of mitochondrial dysfunction, or it may be initially caused by mitochondrial dysfunction. In either case, if one accepts the premise that all chronic diseases of aging are rooted in mitochondrial bioenergetic compromise, then all individuals who eventually develop a chronic disease would also in parallel manifest underlying pathologies of insulin resistance and mitochondrial dysfunction. For counterarguments exploring the other sides of insulin resistance and dysfunctional mitochondria, see Sidebar 8.12.

8.1 Mitochondrial Dysfunction and Aging Mitochondrial energy production synchronizes all parts of the body, at all scales of biological and physiological organization. The process of effortless organizational synchrony can be illustrated by viewing a flock of starlings evading a predator falcon. The flock dynamically reconfigures and the falcon is unable to capture a single bird. This is analogous to how our body responds to stress: constantly readjusting to maintain homeostasis and allostasis. Reaching the critical threshold of allostatic overload is akin to the fragmentation of the flock and the capture of a starling. As we argue throughout this book, entropy and the heat of inflammation represent the deterioration of mitochondrial energy production systems, leading to the acceleration of aging. 323

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SIDEBAR 8.1: THE RATE OF LIVING HYPOTHESIS AND FREE RADICAL THEORY OF AGING The evolution of mitochondria has allowed eukaryotic organisms to come out of the oceans and adapt to life on land, equipped with the capacity for harnessing the high oxygen content of air to fulfill bioenergetic demands. However, this evolutionary splendor comes at the cost of the toxic damage induced by oxygen on the same tissues it fuels. The rate of living theory, first proposed in the 1900s by Max Rubner, argued that there is a fixed totality of oxygen that is consumed over a lifetime: the faster the metabolic rate, the quicker that oxygen is used up, and the shorter the lifespan. For example, smaller animals with higher metabolic rates (per gram of tissue) have shorter lifespans. That theory has been largely replaced by the free radical theory of aging, originally proposed in the 1950s by Denham Herman. This theory posits that oxidative stress imposed on the tissues of the body is mediated by metabolism-promoted reactive oxygen species and free radicals that oxidatively modify and damage tissues. The process of oxidative phosphorylation produces energy in the mitochondria but is also the major generator of these detrimental molecules. Microbiota, psychogenic stress, circadian behaviors, and diet (quantity, quality, and timing) all contribute to the free radical theory of aging. A connection between the rate of living hypothesis and the free radical theory of aging can be made: the greater the demands for oxidative metabolism production of ATP, the faster the metabolic rate, the higher the production of byproduct reactive oxygen species, and the greater the associated tissue damage. Metabolic rate is correlated with caloric consumption, energy expenditure, and production of reactive oxygen species (ROS) (1, 2). The quantum mode of energy production is maximally efficient, whereas the classical mode loses energy in the form of heat. During the classical mode of energy production, calorie restriction slows metabolic rate which reduces ATP production. In contrast, calorie restriction may promote a quantum mode of energy production by falling below the “takeover threshold”, thus increasing the efficiency of bioenergetic metabolism, and requiring less ATP production per unit body mass (see quantum metabolism, Chapter 2 Vol 1). A ~15% reduction in daily caloric intake translates to an average weight loss of 19 pounds over a two-year period, with a reduced energy expenditure of ~100 Kcal per day lower than expected based on body weight. This example illustrates how reducing caloric intake can cause beneficial metabolic adaptations.

8.1.1 Air Hunger as a Sign of Mitochondrial Dysfunction (Clinical, Introductory Level) Bioenergetics is at the core of metabolism. The loss of bioenergetic efficiency by mitochondrial dysfunction

Metabolism and Medicine accelerates the aging process and the onset of chronic diseases. Therefore, mitochondrial health determines bioenergetic efficiency. Mitochondria are organelles that transform energy within the cell into the universal biological currency of ATP. Ways of assessing mitochondrial health include muscle biopsies (to observe mitochondrial structure) and exercise stress tests (to observe VO2 max or VO2 submax). The air hunger (i.e., the sensation of not being able to breathe sufficient air) that accompanies overexertion during exercise stress tests drives increased respiration to provide mitochondria with sufficient oxygen to produce enough ATP to meet the exercise work demand. Clinical analysis of aerobic mitochondrial function during a stress test correlates with the volume of oxygen consumption. While VO2 max and VO2 submax do not indicate mitochondrial efficiency, they have predictive values for premature chronic disease and mortality. The air hunger (i.e. the sensation of not being able to breathe sufficient air) that accompanies overexertion during exercise stress tests drives increased respiration to provide mitochondria with sufficient oxygen to produce enough ATP to meet the exercise work demand. An ideal, yet theoretical method of assessing mitochondrial health, would be to perform a stress test and calculate the amount of oxygen consumed per unit of work performed. Accordingly, an optimal VO2 max or VO2 submax consists of a high amount of oxygen consumed, but a low ratio of oxygen per unit of work performed. This low ratio of oxygen: work would indicate greater efficiency of ATP production from oxidative metabolism. When aerobic capacity is poor, oxygen is wasted; it combines with electrons that are lost along the shuttle of the electron transport chain, forming an excess of toxic, reactive oxygen species. When air hunger occurs at a low threshold of work performed, mitochondrial capacity and efficiency of ATP production are impaired. This is the fundamental basis of redox disturbance that leads to mitochondrial dysfunction. Mitochondrial dysfunction is characteristic of aging and of chronic diseases caused by aging. Mitochondrial dysfunction can occur when redox stress causes modifications of mitochondrial chemistry or when the inner mitochondrial membrane has reduced electrical and chemical potentials. Some causes of these changes to mitochondria include insulin resistance, impaired antioxidant capacity, insufficient mineral and vitamin cofactors, insufficient metabolite transporters for mitochondrial processes, reduced electron carrier molecules, and nutritional excess. Therapeutic interventions for dysfunctional mitochondria include correcting deficiencies, enhancing insulin sensitivity, increasing mitochondrial biogenesis through dietary restriction, exercise, resveratrol (activates energy stress sensors), and peroxisome proliferator-activated receptor agonists (fibrates and thiazolidinedione agents). Mitochondrial biogenesis can be promoted with calorie restriction, intermittent fasting, or exercise. Both methods increase VO2 max or VO2 submax, increasing the ratio of ATP production: work. In this case, more of the oxygen is expelled in water molecules as sweat or increased urine (diuresis) from the body, and less of the oxygen is wasted by forming toxic reactive oxygen species.

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Mitochondrial Dysfunction and Insulin Resistance A discussion of supplementation for mitochondrial health will be given below.

SIDEBAR 8.2: ENDURANCE EXERCISE AS A ROUGH ESTIMATE OF METABOLISM AND ENTROPY Simple observations of a patient performing endurance exercise can give hints at their metabolic problems. Here are some common observations: Abnormally fatigued: nutrient hydrocarbon or mitochondrial content/function availability is insufficient to meet the metabolic demands. Excessive air hunger: the hydrocarbon nutrient and/or mitochondrial content and function availability is insufficient to utilize oxygen to meet metabolic demands. Lack of sweat or post-workout diuresis: the electron transport chain is not functioning properly. In healthy exercisers, oxygen is reduced to water along the mitochondrial electron transport chain, causing sweating and diuresis. The redox state induced by overexertion in these patients creates an unhealthy feedforward effect on mitochondrial dysfunction, producing inflammation and insulin resistance. Note: dehydration can cause fatigue and air hunger because there is less perfusion of tissue mitochondria, resulting in less capacity to meet bioenergetic demands.

8.1.2 Supplements for Mitochondrial Health (Clinical, Introductory Level) Mitochondrial function is a central determining factor of health. Mitochondrial redox stress impairs ATP production.

There are several critical vitamins, nutrients, and cofactors involved in supporting mitochondrial health and biogenesis. These “exercise in a pill” supplements help provide acetylCoA for the TCA cycle.

8.1.2.1 L-Carnitine Transfers Fuel into the Mitochondria Carnitine is an amino acid found in meat, fish, poultry, and the whey fraction of dairy products. It is also endogenously made from the amino acids lysine and methionine and can be obtained in supplement form. The L-isomer of carnitine, L-carnitine, is crucial for carrying long-chain fatty acids inside mitochondria to be oxidized. However, sometimes the demand for fatty acid oxidation exceeds biosynthetic capacity. Carnitine combines with long-chain fatty acids and acyl groups including palmitate. The carnitine-acyl linked product, acylcarnitine, is carried from the outer mitochondrial membrane to the intermembrane space with the help of the enzyme carnitine palmitoyltransferase 1 (CPT1; for a detailed depiction of this pathway see Figure 8.1). The long-chain acylcarnitine is promoted from the inner mitochondrial membrane to the mitochondrial matrix with the help of the transporter enzyme carnitine-acylcarnitine translocase (CACT). Within the mitochondrial matrix, acylcarnitine connects with CoA, with the help of the enzyme carnitine palmitoyltransferase-2, to reform long-chain acyl CoA, freeing up carnitine. The acyl-CoA can then undergo β-oxidation. Malonyl CoA inhibits CPT-1, preventing fatty acids from being transferred from the cytoplasm to the mitochondria for β-oxidation. An enzyme Malonyl CoA decarboxylase (MCD) lowers malonyl CoA levels by converting it to acetyl CoA, allowing unimpeded transport of fatty acids by CPT-1 into the mitochondria. Conversely, inhibition of MCD leads to excess malonyl CoA, reducing fatty acid transfer, diminishing fatty acid oxidation (3).

FIGURE 8.1  Extrinsic control parameters of mitochondrial function. Pathway depicting the role of L-carnitine in transporting long-chain fatty acids to the mitochondria to produce ATP. *CPT-1 = carnitine palmitoyltransferase 1; LC = long-chain.

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8.1.2.2 B Vitamins Are Essential for Energy Production Vitamin B1 (thiamine pyrophosphate) acts as an enzyme cofactor in the pyruvate dehydrogenase complex, converting pyruvate into acetyl-CoA. This step connects cytosolic glycolysis and mitochondrial pathways of bioenergetic metabolism, providing another source of 2-carbon units to the TCA cycle (Figure 8.2). Other roles of vitamin B1 include serving as part of enzyme complexes that convert glycolysis-produced pyruvate into the branched-chain amino acids leucine, isoleucine, and valine. Vitamin B1 also forms part of the α-ketoglutarate dehydrogenase complex that converts the TCA cycle intermediate α-ketoglutarate to succinyl CoA, which is subsequently turned into succinate. Vitamin B2 (riboflavin) forms the flavin adenine dinucleotide (FAD). FAD is a cofactor of succinate dehydrogenase. FAD accepts two electrons (and protons) from the TCA cycle intermediate succinate, forming FADH2 and malate as products. FADH2 transfers two electrons to the acceptor ubiquinone, a mobile component of Complex II of the electron transport chain. When ubiquinone accepts the electrons (and protons) in the respiratory chain, it is converted to ubiquinol and shuttles electrons to Complex III, then it is reconverted back to ubiquinone. Vitamin B3 (niacin) is a powerful modifier of bioenergetic metabolism. Vitamin B3 is used to synthesize nicotinamide adenine dinucleotide (NAD+). NAD+ can be converted to NADH with the addition of a hydrogen (H+) molecule and two electrons. NADH is produced at multiple steps in the

Metabolism and Medicine glycolysis and TCA pathways. While ATP is the biological currency of energy, NADH is the primary electron carrier produced by the bioenergetic pathways. It transforms the energy from food into ATP. NADH initiates this energy transfer by donating two electrons to Complex I of the electron transport chain. Within Complex I, the electrons are first transferred to NADH dehydrogenase, then subsequently to the flavin protein derived from vitamin B2 (flavin mononucleotide), and finally to iron-sulfur clusters, before being accepted by ubiquinone. Vitamin B3 improves adult-onset mitochondrial muscle diseases, the most common inherited metabolic disturbance. Vitamin B3 supplementation might also inhibit mitochondrially-mediated acceleration of aging. Other uses of vitamin B3 include inducing an endoplasmic reticulum stress response to overcome mitochondrial dysfunction. Vitamin B5 (pantothenic acid) is the precursor for coenzyme A, which is involved in the oxidation of pyruvate in the TCA cycle.

8.1.2.3 Alpha-Lipoic Acid and Dihydrolipoate Recharge Other Antioxidants Lipoic acid recharges vitamin C, glutathione, thioredoxin, Coenzyme Q10, and vitamin E, among others Lipoic acid serves as an important cofactor for several mitochondrial enzymes, promotes glutathione synthesis by upregulating the rate-limiting enzyme γ-glutamyl cysteine ligase, and enhances insulin sensitivity by directly binding and activating insulin receptors (4).

FIGURE 8.2  Summary of the role of B vitamins in metabolism. *ɑKG = ɑ-ketoglutarate; CO2 = carbon dioxide; CoA = coenzyme A; CoA-SH = coenzyme A not attached to an acyl group; CoQ10 = coenzyme Q10 (also known as ubiquinone-10); e = electron; FAD = the oxidized form of flavin adenine dinucleotide; FADH2 = the reduced form of flavin adenine dinucleotide; FMN = flavin mononucleotide; LCFAs = long-chain fatty acids; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; PDC = pyruvate dehydrogenase complex; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle); Vit = vitamin.

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Mitochondrial Dysfunction and Insulin Resistance Both alpha lipoic acid and dihydrolipoate are anti-oxidant free radical scavengers. They are regenerated by thioredoxin reductase as an electron donor and NADPH as a proton donor.

8.1.2.4 Coenzyme Q10 May Counter Myalgias Coenzyme Q supplementation might also improve mitochondrial function. The antioxidant properties of coenzyme Q make it a good candidate for the prevention and management of inflammation, oxidative free radical stress, and age-related disorders (neurodegenerative diseases, cancers, cardiovascular disease, inflammatory liver disease, and diabetes). Coenzyme Q is currently used in the prevention and treatment of statin cholesterol therapy-induced myopathy. Pharmacological research on the mitochondrial redox system would lead to valuable medications for the treatment of metabolic disease. Coenzyme Q10 is a mobile electron carrier in the respiratory chain. The reduced form of CoQ10, ubiquinol, is the predominant form in cell membranes. Ubiquinol serves as an electron transporter and an antioxidant. Its antioxidant functions protect the vulnerable inner mitochondrial membrane against superoxides (Figure 8.3). CoQ10 antioxidant deficiency may be a cause of skeletal myalgias (muscle pain); impaired protection against free radical stress leads to inner mitochondrial membrane peroxidation and mitochondrial dysfunction, with reduced production of ATP. CoQ10 is naturally produced in the body and found in many foods. CoQ10 supplementation is used off-label for statin-induced myalgias and congestive heart failure. Cholesterol-lowering statin therapies (for example, HMG [3-hydroxy-3-methyl-glutaryl] CoA reductase inhibitors) may deplete CoQ10 by reducing the production of mevalonic acid, a precursor of CoQ10. These HMG-CoA reductase inhibitors also reduce the biosynthesis of cholesterol in the cell membranes. While high cholesterol levels are dangerous, cholesterol rafts in the cell membrane have antioxidant properties; they protect against membrane lipid peroxidation. Possible side effects of HMG-CoA reductase inhibitors include impaired membrane fluidity and skeletal muscle cell surface insulin receptor signaling, resulting in decreased energy production. Other possible effects of HMG-CoA reductase inhibitors include impairing vasodilation in vascular smooth muscle cells, which may be due to compromised β-adrenergic receptors. These side effects of statin therapy contribute to myalgia. To combat statin therapy-induced myalgia, clinicians advise patients to begin CoQ10 supplementation, despite the lack of evidence of efficacy of CoQ10 for treating this problem.

activation promotes fatty acid oxidation in skeletal muscle and adipose tissue, reducing excess lipid-associated inflammation. This has the potential to improve insulin resistance and mitochondrial dysfunction. Other benefits of the vitamin D-bound vitamin D receptor include inducing the expression of the transcription factor nuclear respiratory factor 2 (NRF2). NRF2 promotes mitochondrial biogenesis. NRF2 also stimulates antioxidant response elements of genes, such as glutathione. Vitamin D deficiency can cause inflammation, oxidative stress, and mitochondrial dysfunction. Vitamin D deficiency might also cause insulin resistance, though the evidence is not conclusive (5–13).

8.1.2.6 Benefits and Dangers of Peroxisome Proliferator-Activated Receptor ɣ Supplementation Thiazolidinedione drugs are a class of oral hypoglycemics that bind to PPARɣ in adipocytes. These PPARɣ agonists are increasingly being recognized as pharmaceutical agents capable of promoting mitochondrial biogenesis and improving mitochondrial dysfunction. This is partly explained by their effect on sensitivity to insulin. The PPARɣ agonist pioglitazone enhances mitochondrial biogenesis in part by upregulating PGC1α, nuclear respiratory factors (NRFs), and transcription factor A (TFA or TFam) (14). Together, PGC1α and its co-activation of NRFs and TFA stimulate the replication of mitochondrial DNA. These factors also induce the transcription of mitochondrial and nuclear-encoded mitochondrial proteins needed for mitochondrial biogenesis, including electron transport chain proteins. Additionally, pioglitazone induces the transcription of fatty acid oxidation-related genes, such as carnitine palmitoyl transferase 1(CPT1), malonyl CoA decarboxylase (MCD), and medium-chain acyl CoA dehydrogenase (MCAD). Stimulating fatty acid oxidation in the liver has favorable effects on dyslipidemia, and enhanced mitochondrial function improves insulin sensitivity in all metabolic tissues. Another mechanism mediating pioglitazone-induced insulin sensitivity includes increased secretion of insulin-sensitizing adipokines, particularly adiponectin. Various effects of pioglitazone are independent of PPARɣ. There is speculation over pioglitazone’s mechanism of action on mitochondrial function and biogenesis. AMP-activated protein kinase (AMPK) signaling or binding mitochondrial membrane proteins may be possible pathways activated by pioglitazone (Figure 8.4).

8.1.2.5 Vitamin D Promotes Mitochondrial Function Mediated by Both Anti-inflammatory and Insulin Sensitizing Effects

SIDEBAR 8.3: HISTORY OF THIAZOLIDINEDIONE DEVELOPMENT AND TOXICITY

Vitamin D affects the immune system; it downregulates the NFkB pathway. When vitamin D is bound to the vitamin D nuclear hormone receptor (NHR), it upregulates the expression of the insulin receptor gene. The vitamin D-bound vitamin D receptor also cross-reacts with the peroxisome proliferator-activated receptor α (PPAR)α, another NHR. PPARα

Thiazolidinediones have a rocky and storied history. In 1997, troglitazone became the first in the class of PPARɣ agonists to become available for type 2 diabetes. It caused lethal hepatotoxicity in 63 patients and was withdrawn from the market in 2000. In 1999, two new drugs in this class, rosiglitazone and pioglitazone were FDA-approved.

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FIGURE 8.3  Antioxidant properties of coenzyme CoQ10. Ubiquinol serves as an antioxidant by donating a hydrogen atom from one of its hydroxyl groups to an electrophilic lipid peroxyl radical along the inner mitochondrial membrane. Donating this hydrogen atom results in the formation of the highly unstable ubisemiquinone, which is transferred to the aqueous phase. Ubisemiquinone donates an electron to oxygen, creating superoxide. Superoxides are more easily detoxified in the aqueous phase by antioxidants (superoxide dismutase, catalase, and peroxidases). Donating the electron to oxygen converts ubisemiquinone back into ubiquinone, which then accepts two electrons and protons from the electron transport chain, to regenerate ubiquinol. This ubiquinol-mediated method of neutralizing free radical electrophiles (particularly lipid peroxyl groups) inhibits the rapid chain reaction of lipid peroxidation stealing electrons from neighboring atoms across the lipid membrane. Ironically, oxygen is serving as an antioxidant in this system.

However, rosiglitazone increased the risk of heart attacks by 43% (15). As compared to pioglitazone, rosiglitazone increased the risk of heart attacks, strokes, and congestive heart failure (CHF) (16). This led to severe restrictions on rosiglitazone in the US and its withdrawal from the market in Europe. Unethical marketing practices by GlaxoSmithKline resulted in a fine of 3 billion dollars by the US Department of Justice. Subsequent investigations into rosiglitazone did not confirm increased cardiovascular outcome risk, prompting the FDA to issue a formal statement that their “concern was substantially reduced”. Prescribing restrictions in the US were removed. However, there remains a black box warning contraindicating the drugs for patients with class 3 or 4 congestive heart failure. The troubled past of thiazolidinediones teaches us four important concepts in medicine:

• The practice of medicine is sometimes a dangerous game because of the extraordinary complexity of biological systems. A careful risk–benefit analysis is needed. • Honest, thorough reporting of premarketing data is critical for proper prescribing guidelines. These data will help inform the risk–benefit profile. • Risk does not necessarily make a drug bad. Both pioglitazone and rosiglitazone have a black box warning contraindicating use for patients with significant heart failure. However, even drinking too much water can exacerbate CHF. Therefore, any compound can be dangerous in certain conditions. • Science has issues with replicability. Only about one-third of standards of care practices are supported by repeated testing.

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FIGURE 8.4  Possible mechanisms of mitochondrial biogenesis by thiazolidinedione drugs. One way that pioglitazone likely stimulates PGC1α and hence de novo mitochondrial synthesis, is mediated by AMPK. Pioglitazone at high doses binds to Complex I of the electron transport chain, promoting its disassembly. This reduces ATP production, and consequently the ATP: AMP ratio. This change in ATP to AMP ratio activates AMPK. Another way that thiazolidinedione drugs reduce ATP and the ATP/AMP ratio is by directly binding outer mitochondrial membrane proteins, such as mitochondrial pyruvate carrier proteins, inhibiting pyruvate entry into mitochondria and its subsequent oxidative metabolism.

Despite the troubled history of thiazolidinediones, pioglitazone is the only true insulin sensitizer, as defined by the euglycemic insulin clamp standard. Further, it promotes mitochondrial biogenesis, which is a potent and fundamental control parameter of healthy human physiology. This makes pioglitazone an appealing approach to metabolic diseases and chronic diseases of aging. Further, rosiglitazone

may have off-label uses, such as treating anxiety and oropharyngeal neuropathic pain by increasing mitochondrial function following trigeminal nerve injury (17). Ultimately, a high-dimensional precision model of healthcare, such as the Physiological Fitness Landscape, could help patients determine their personal benefit-to-risk ratios for thiazolidinediones (18–20).

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8.1.2.7 Dimethyl Fumarate Stimulates Antioxidant Genes Dimethyl fumarate is an immune-modulating anti-inflammatory agent, though it does not have significant immunesuppressive effects on its own. Rather, it is converted into the active metabolite monomethyl fumarate, which binds the transcription factor master redox switch, NRF2. This causes NRF2 to go to the nucleus and bind to the promoter region of the response elements of antioxidant target genes, including NAD(P)H quinone oxidoreductase 1 (NQO1), superoxide dismutase 1 (SOD1), heme oxygenase1 (HO1), and enzyme subunits that lead to the synthesis of glutathione. Stimulating these antioxidant genes makes monomethyl fumarate-activated NRF2 a promising candidate for roughly 200 human disease states characterized by oxidative stress, including cancers, cardiovascular diseases, and neurodegenerative disorders. Other actions of dimethyl fumarate include stimulating mitochondrial biogenesis, inhibition of the central inflammatory cytokine NFkB, and treating chronic relapsing multiple sclerosis (Tecfidera®).

8.1.2.8 Vitamin K Maintains Calcium Homeostasis and Improves Insulin Sensitivity Vitamin K2 (menaquinone) has cooperative relationships with vitamin D, which either directly or indirectly promotes

Metabolism and Medicine mitochondrial and metabolic health. Vitamin K2 maintains calcium homeostasis together with vitamin D. For example, vitamin D promotes the transcription of osteocalcin, which vitamin K2 activates. Activated osteocalcin acts as an enzyme cofactor for carboxylation of glutamic acid residues (Figure 8.5). Carboxylated osteocalcin promotes calcium uptake into bone and teeth, preventing its migration into soft tissues, such as vascular plaque calcification. Vitamin K2 also works with vitamin D2 to increase insulin sensitivity: while vitamin D stimulates transcription of the insulin receptor gene, vitamin K2-mediated upregulation of γ-carboxylation of osteocalcin glutamate residues potentiates insulin sensitivity. This process also promotes pancreatic beta cell proliferation and insulin secretion. These osteocalcin-mediated actions may be rooted in the anti-inflammatory effects of vitamin K2. For example, Reddi and colleagues showed that vitamin K2 improved lipopolysaccharide (LPS)-induced inflammation. Microbiota-derived LPS, or endotoxin, is a hallmark of insulin resistance and type 2 diabetes (21). Vitamin K2-dependent activated osteocalcin is also responsible for parathyroid hormone suppression. This may explain why parathyroid hormone suppression induces osteoporosis, cardiovascular disease, and depression (21–27). Vitamin K2 also promotes bladder cancer cell apoptosis. The mechanism of action involves triggering oxidative stress and activating serine/threonine kinases such as JNK and p38

FIGURE 8.5  Cooperativity of vitamin D and vitamin K2. Vitamin K2 enhances the actions of vitamin D, including calcium homeostasis and insulin sensitivity. Vitamin K2 deficits are connected to osteoporosis.

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Mitochondrial Dysfunction and Insulin Resistance mitogen-activated protein kinase (MAPK) pathways, causing the mitochondrial membrane potential to be lost and cytochrome C to be released, which promotes apoptosis (28).

8.1.2.9 Minerals and Trace Elements Minerals are critical for mitochondrial function, redox balance, and insulin sensitivity. Of all the trace elements, iron is the most abundant trace element in the human body and is crucial for bioenergetic metabolism. It is present in the iron-sulfur clusters and in the heme of cytochromes. While iron is essential, it is also the most toxic trace mineral. When free/unbound iron interacts with other atoms or molecules, it can generate free radicals. This sets off a chain reaction where electrons are stolen from the outer shell of other atoms that form parts of proteins, lipid cell membranes, and DNA. This can result in pancreatic damage that can lead to diabetes or exocrine insufficiency, and even cancer. Asbestos causes mesothelioma due to the 40% elemental iron of asbestos. Zinc is a trace mineral that is a cofactor helping to drive over 300 enzymes and their associated metabolic reactions. It also interacts with insulin and transcription factors of the steroid and thyroid superfamily of nuclear hormone receptors. The body requires large amounts of the mineral magnesium, which also serves as a cofactor for the activation of over 300 enzymes. Magnesium prevents the uncoupling of oxidative phosphorylation. Pathologically, excess uncoupling occurs in the setting of magnesium deficiency or hyperthyroidism. Manganese is a trace element that is required for the activation of mitochondrial antioxidant enzyme superoxide dismutase. Copper is the trace mineral that promotes cytoplasmic superoxide dismutase (29, 30).

8.2 Linchpin Concepts Connecting Mitochondrial Dysfunction to Chronic Diseases of Aging Primordial Earth’s atmosphere was believed to be highly oxidative. Since oxygen is one of the most electronegative elements, it has a very high tendency to oxidize the substrate via participating in an electron transfer reaction. The presence of excess oxygen in the environment could harm primitive organisms. Thus, organisms that could use oxygen for cellular respiration were at an advantage. The first mitochondria might have developed as a way to exploit aerobic respiration: large, heterotrophic anaerobic bacteria engulfed aerobic prokaryotic microorganisms (mitochondria ancestors). The two organisms formed a symbiotic relationship where the aerobic microorganism provided energy to the host anaerobic organism. Over time, this endosymbiotic relationship evolved into a eukaryotic cell, synchronized by mitochondrial function. Mitochondria have key roles in ATP production, calcium homeostasis, and many more according to new research. Besides ATP, mitochondria make metabolic building blocks for lipids, proteins, DNA, and RNA, as well as byproducts

that include reactive oxygen species (ROS) and ammonia. Mitochondria act as rheostats (biosensors) for oxidative stress and are able to either remove or use waste products. One of its main functions is to mediate cellular adaptations to lack of nutrients, oxidative stress, DNA damage, endoplasmic reticulum (ER) stress, etc. Mitochondria are also a hub for cell signaling processes, such as necrosis, apoptosis, autophagy, mitoptosis (mitochondrial-specific apoptosis), and mitophagy (a cellular process of eating its own mitochondria under certain conditions). Lack of energy production due to mitochondrial and epigenomic dysfunction leads to energy deficiency for biological processes (31). Mitochondria-linked diseases of energy metabolism are linked to many human conditions: glaucoma, inflammation, neurodegenerative diseases, type 2 diabetes, cancers, cardiomyopathies, and dysrhythmias. Organs that consume high amounts of energy are hit especially hard by diseases of energy metabolism. For example, the brain is only 2% of total body weight, but uses 20% of the body’s total oxygen. Thus, it is vulnerable to oxidative damage if mitochondrial function is impaired. In this section, we discuss mitochondria as compartmentalized organelles that serve as bioenergetic powerhouses, biosynthetic centers, balancers of reducing equivalents, and waste management hubs. We highlight how metabolism is compartmentalized in normal physiology and disease. A better understanding of the contributions of mitochondria to metabolism will shed light on their roles in disease and may give away other pathways to targeted therapies. Later in this section, we will discuss the basic mechanism of mitochondrial dysfunction, and how mitochondrial dysfunction is linked with oxidative stress and various components of metabolic syndrome. We will focus on heart disease, stroke, diabetes, and obesity, which are intimately related to oxidative damage and mitochondrial dysfunction. Using this mechanism, knowledge and the results of recent preclinical trials, we will discuss potential future treatments for mitochondrial dysfunction.

8.2.1 Mitochondria: The Bioenergetic Powerhouse of the Cell Mitochondria are famously known as the “powerhouse of the cell”, a term coined by Philip Siekevitz in 1957. They get this nickname from their roles in producing the “energy currency” adenosine triphosphate (ATP). Mitochondria are responsible for energy metabolism, production of free radicals, calcium homeostasis, metabolizing nutrients, and cell survival and death. Mitochondria are also required for metabolic and catabolic activities, Ca2 + buffering, apoptosis regulation, and synthesis of key metabolites. Mitochondrial dysfunction can include reduced oxidative capacity and increased production of reactive oxygen species (ROS). This occurs with aging and many metabolic disorders. Mitochondria are major producers of endogenous ROS, including free radicals such as superoxide anions, hydroxyl, peroxyl radicals, and other non-radicals capable of generating free radicals. Cells have many defenses against ROS, but ROS overproduction by dysfunctional mitochondria is linked to oxidative damage of lipids, DNA, and proteins. Excess

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FIGURE 8.6  Mediated by environmental and endogenous factors, mitochondrial dysfunction can lead to metabolic syndromes such as insulin resistance and type 2 diabetes. Source: adapted from (32). *Ca2+ = calcium; mtDNA = mitochondrial deoxyribonucleic acid; ROS = Reactive Oxygen Species.

ROS damages the already dysfunctional mitochondria, leading to even greater impairment of bioenergetics in the cell. Mitochondrial oxidative stress is associated with aging, cancer, and age-related metabolic disorders and neurodegenerative diseases (see Sidebar 8.5 and Figure 8.6 for a detailed range of causes and effects of mitochondrial dysfunction).

SIDEBAR 8.4: ALTERED MITOCHONDRIAL FUNCTION CREATES AN OPPORTUNISTIC ENVIRONMENT FOR CANCER When mitochondria become truly dysfunctional, ROS generation moves far to the right of the bell shaped curve, disrupting the molecular architecture and function of the mitochondria. ROS, in the form of H2O2, may diffuse into cell nuclei before converting into free radicals and other ROS’s, capable of promoting DNA oncogenic mutations and cancer cell initiation (33). A metabolic adaptation of cancer cells is the Warburg effect. The Warburg effect is hypothesized to occur as a result of dysfunctional mitochondria that may cause higher rates of glycolysis which is demonstrated to be a predominant

component in tumor cell progression and cancer development. While one of the primary functions of mitochondria is to produce ATP, compromised ATP production and associated excess generation of ROS are consequences of impaired mitochondrial function (34). Consequently, the generated redox stress further degrades mitochondrial structure and function of host cells. The redox stress additionally impairs energy production in host cells by oxidatively modifying, and thus inhibiting, distal enzymes in the glycolysis pathway. Moreover, ROS promotes a bottlenecking effect. At the same time, buildup of the proximal intermediates in the glycolysis pathway encourages various parallel inflammatory pathways, as explained by Michael Brownlee’s unifying hypothesis of diabetes. In counter-distinction, the metabolic wiring of cancer cells allows them to behave as uniquely opportunistic organisms within the host. In the setting of the Warburg effect, both mitochondrial and glycolysis pathways are upregulated (35). The glycolysis pathway is amplified for both energy production and as a springboard for parallel pathways of intermediates to provide the building blocks for protein, lipids, and nucleic acid macromolecules necessary for cell replication. Crucially, while ROS inactivate

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Mitochondrial Dysfunction and Insulin Resistance distal enzymes of glycolysis in the host cell, they do not appear to impact this pathway in cancer cells, underscoring a feature of the resilience of the Warburg effect in cancer cells (34). Mitochondrial function is often robust in cancer cells, further allowing cancer cells to bioenergetically outcompete for host energy resources. The phenomenon of anaplerosis is an important contributor to this cancer cell growth, via the process of glutaminolysis (36). Glutaminolysis occurs when the amino acid glutamine is decarboxylated to glutamate, which in turn is decarboxylated to the TCA cycle intermediate ɑ-ketoglutarate. This second step is coupled to the carboxylation of pyruvate to alanine, an amino acid that supplements parallel pathways of glycolysis as a macro molecular building block of cell replication. Therefore, glutamine should generally be avoided in the setting of cancer.

8.2.2 Mitochondria: Structure, Function, and Pathophysiology Mitochondria contain self-replicating genomes that encode many of the mitochondrial proteins involved in the electron transport system. Mitochondrial DNA (mtDNA) is passed from mother to offspring inherited and it’s packaged in nucleoprotein structures. Depending on the metabolic need and functions, mitochondrial number varies in the different organism, tissue, and cell types. For example, cardiomyocytes, and hepatocytes contain large numbers of mitochondria whereas red blood cells (RBCs) have no mitochondria as they are glycolytic. Structurally, mitochondria are composed of different compartments that include the outer membrane, the inner membrane separated by the intermembrane space, the cristae, and matrix. These compartments or regions are specialized for different metabolic and non-metabolic functions. While most cellular organelles consist of a single membrane, mitochondria have two: the outer mitochondrial membrane (OMM) and the inner mitochondrial membrane (IMM). These two membranes are separated by a small intermembrane space. The OMM and inner membrane space are more permeable than the IMM. The IMM contains protein complexes of electron transport chains, making it crucial for ATP production through the process of oxidative phosphorylation (OXPHOS). Mitochondria alone produce a central cellular pool of ATP (> 90%) via the TCA cycle and the ETS. The IMM of mitochondrial contains five multi-subunit complexes (Complex I-V). IMM also contains small, soluble, mobile electrons carriers, such as coenzyme Q and cytochrome C, which mediate the electron transfer between the complexes. NADH and FADH2 generated in the TCA cycle donate their electrons to complex I or complex II. Then electrons are transferred to complex III via coenzyme Q, then to complex IV,

and eventually to molecular oxygen through complex V. This transfer of electrons along the ETS is coupled with protons being effluxed across the IMM, creating an electrochemical gradient. This electrochemical gradient drives OXPHOS. Free radicals such as reactive oxygen species (ROS) are made continuously in our bodies. ROS are fundamental to many biochemical processes and regulate many cellular functions. Cells use multiple mechanisms to counter the effects of ROS-induced oxidative damage. These mechanisms involve diminishing ROS generation directly with the enzymatic defense system (superoxide dismutase [SOD1 and SOD2], catalase [CAT], glutathione reductase [GR], and peroxidase [GPx]), or by non-enzymatic systems (scavenging free radicals with antioxidants such as glutathione [GSH], vitamin E, and C, various flavonoids, and carotenoids). Mitochondria are major contributors to macronutrient metabolism-associated ROS generation. Under physiological conditions, ROS production is controlled in mitochondria to protect the cellular components from oxidative damage. In pathological conditions or excess macronutrient metabolism, the antioxidant defense system is overwhelmed; excess ROS generation exhausts the body’s antioxidant defense system. This can damage mtDNA, proteins, lipids, and the ETS. The resulting mitochondrial dysfunction leads to disrupted ATP production and other crucial mitochondrial functions. This results in an accelerated aging process and is associated with an extensive range of pathological conditions, such as diabetes, cancer, cardiovascular disease, and neurodegenerative disorders.

Electron Transport System Peter Mitchell was awarded the Nobel Prize in Chemistry in 1978 for his 1961 “chemiosmotic” hypothesis. His hypothesis states that electrons flowing from reducing equivalents, such as NADH and FADH2, through the mitochondrial electron transport chain (a set of five sequential multiprotein complexes and 2 electron shuttles located in the inner mitochondrial membrane), generate electrochemical and pH gradients. Generation of these gradients results in changes in free energy, which drives the proton motive force—the ability to efflux protons (H+) across the inner mitochondrial membrane. The proton motive force is used to generate ATP at the final complex of the electron transport chain. Dysfunction of any part of the electron transport system results in reduced efficiency of electron transfer to oxygen, and thus less energy to power the cell. The first component of ETS is NADH ubiquinone oxidoreductase, also known as Complex I. Complex I is the largest of the complexes. Its subunits are organized in an L-shaped structure. One arm of Complex I is embedded in the inner mitochondrial membrane, whereas the other arm overhangs into the matrix. The embedded arm contains multiple iron-sulphur clusters (Fe-S), which form the ubiquinone hydrogenase part of Complex I. The overhanging arm contains flavin mononucleotide (FMN) in the center and at least four Fe-S clusters, which form the NADH dehydrogenase part of Complex I. Complex I catalyzes the transfer of electrons from NADH to ubiquinone (coenzyme Q). The reaction catalyzed by Complex I is:

NADH + Q + 5H n + ® NAD+ + QH2 + 4H p + (8.1)

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FIGURE 8.7  Succinate dehydrogenase and electron transferring flavo-proteins (Acyl-CoA Dehydrogenase) contain FAD as a prosthetic group. FAD as a prosthetic group serves as an alternate way to tunnel electrons from the TCA cycle or from fatty acid oxidation. *ACAD = Acyl CoA dehydrogenase; CoA = coenzyme A; ETF = electron transferring flavo-protein, ETF-QOR = electron transferring flavo-protein coenzyme Q oxidoreductase, FA-CoA = fatty-acyl coenzyme A; FAD = the oxidized form of flavin adenine dinucleotide; FADH2 = the reduced form of flavin adenine dinucleotide; FeS = Rieske iron-sulfur protein; Q = coenzyme Q; QH2 = ubiquinol (coenzyme Q in the reduced state); SDH A, B, C, and D = succinate dehydrogenase parts A, B, C, D.

where Q = coenzyme Q (ubiquinone), Hn+ = the protons from the negative inner side of the membrane, Hp+ = the protons from the positive outer side of the membrane. Complex II (succinate ubiquinone oxidoreductase) tunnels electrons into the electron transport chain from the TCA cycle and β-oxidation of fatty acids. Complex II contains a soluble enzyme called succinate dehydrogenase (SDH) and a prosthetic group called flavin adenine dinucleotide (FAD), which is covalently attached to the flavoprotein. It is widely reported that electrons are transferred from FADH2 to Complex II. However, it is succinate (or fatty acyl-CoA in the case of β oxidation) that donates its electrons to FAD. Succinate binds to the flavoprotein subunit on SDH, donates its electrons to FAD, and becomes oxidized to fumarate. The electrons moved from succinate to FAD in this reaction are transferred to the ubiquinone pool in the mitochondrial matrix, transforming FAD to FADH2 (Figure 8.7). Complex II contributes very little to the proton motive force and is unable to pump the proton across the inner mitochondrial membrane, and thus produces less ATP than the other complexes. It is unclear from the literature as to why Complex II contributes very little to the proton motive force (see Sidebar 8.5). While free FADH2 has a negative redox potential, it does not contribute to the proton motive force at Complex II. FAD and FADH2 are prosthetic groups (cofactors that can covalently bind with enzymes such as SDH, Acyl CoA dehydrogenase, or ETF). In contrast, NAD+ and NADH are coenzymes (cofactors necessary for the activity of certain oxido-reductases and dehydrogenases, such as Complex I and PDH). These differences in their occurring forms result in FAD/FADH2 having more redox potential (positive) than NADH or succinate (see Sidebar 8.5). Therefore, NADH is a more efficient electron donor than FADH2 or succinate.

SIDEBAR 8.5: REDOX POTENTIAL BASICS Redox potential is a quantitative measure of the change in voltage when an atom or molecule gains an electron. Electrons are donated to molecules with higher redox potential. For example, in order for NADH to donate electrons to Complex I, NADH’s redox potential must be lower than that of Complex I. Similarly, in order for Complex 1 to donate its electrons to the electron-carrying molecule coenzyme Q, Complex I must have a lower redox potential than coenzyme Q. Accordingly, the electron transport system is organized with a sequential increase in the redox potential from NADH to O2 (NADH < Complex I < coenzyme Q < Complex III < Complex IV < O2). Alteration in redox potential can alter the flow of electrons in the ETC, leading to slippage and ROS generation. The pair of oxidizing and reducing agents that are involved in a particular reaction is called a redox pair. The oxidizing member of the redox pair has the higher redox potential. The oxidizing member receives electrons from the reducing member of the redox pair, which has the lower redox potential. Here is a list of standard redox potentials E’0 of redox pairs. NAD+/NADH FAD/FADH2 Fumarate/succinate FAD/FADH2 (protein bound) Ubiquinone/ubiquinol Cytochrome a3(oxidized)/cytochrome a3 (reduced) ½ O2/H2O

−0.320 V −0.220 V +0.031 V +0.060 V +0.095 V +0.385 V +0.810 V

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Mitochondrial Dysfunction and Insulin Resistance The balance of redox pairs maintains homeostasis. Redox pairs are correlated with Gibbs free energy, Nernst redox, and Henderson Hasselbalch acid-base states. The ratio of the redox pair NAD+/NADH defines the intracellular redox state, while NADP+/NADPH and GSH/GSSG are the major redox pairs involved in intracellular antioxidant systems. Coenzyme Q (ubiquinone) is a membrane-bound coenzyme that transfers electrons from Complex I to cytochrome c protein, a mobile carrier that mediates the transfer of electrons from Complex III to Complex IV. For each pair of electrons transferred from ubiquinol to cytochrome c, 4 protons are pumped from the matrix across the inner mitochondrial membrane (see Sidebar 8.6).

SIDEBAR 8.6: A CLOSER LOOK AT ELECTRON TRANSFER AT COENZYME Q Higher amounts of NADH produced during metabolism of the ketone β-hydroxybutyrate lead to greater donation of electrons to coenzyme Q and increased biosynthesis of coenzyme Q. This increases the velocity of electrons carried by CoQH2 from Complex I to Complex III. At Complex III (also known as cytochrome C reductase), one electron is transferred at a time from CoQH2 to cytochrome C. CoQH2 (ubiquinol, carry 2 extra electrons) → CoQ• (semiquinone, carrying 1 extra electron) → CoQ (ubiquinone, fully oxidized). Complex III (ubiquinol cytochrome c oxidoreductase) is a multimeric protein complex consisting of 11 subunits. It contains four redox centers: cytochrome c1, the Rieske iron-sulfur protein, cytochrome bH heme group b562, and cytochrome bL heme group b566. Cytochrome c is a small heme protein located in the intermembrane space that acts as a mobile electron carrier from Complex III to Complex IV (Figure 8.8). The mechanism by which electron transfer occurs at Complex III is best explained in terms of the “Q cycle” as proposed by Nobel laureate Peter Mitchell. Complex IV (cytochrome c oxidase) is the terminal enzyme of the electron transport chain. Mammalian Complex IV consists of 13 protein subunits. Complex IV catalyzes the sequential transfer of four electrons from electron-carrying cytochrome c to oxygen: 4 ( cytochrome c ) + 4H + + O2 ® 4 ( cytochrome c ) + 2H 2 O (8.2) 2+

3+

This reaction at Complex IV pumps two protons from the mitochondrial matrix to the intermembrane space. Electron transfer into Complex IV is initiated when cytochrome c binds to subunit II of Complex IV, located on the external side of the membrane. The electrons pass from cytochrome c to the Cu A center of subunit II, then the electrons are transferred to ligated residues within subunit I in the following order: heme a, heme a3, and Cu B binuclear center.

FIGURE 8.8  Schematic representation of the Q cycle. Two electron-rich ubiquinol molecules transfer four electrons to the Q0 site of Complex III. Two of these electrons are then transferred to the Rieske iron-sulfate protein, which then transfers them to oxidized cytochrome c1, reducing it. Reduced cytochrome c1 acts as an electron carrier to Complex IV. Unlike ubiquinone, cytochrome c can transfer only one electron at a time. Thus, electrons that are not transferred to the Rieske iron-sulfate protein are taken up by the bL heme group b566, transferred to the bH heme group b562, pass through the Qi site of Complex III, and are combined with free ubiquinone, to regenerate ubiquinol. Source: https​:/​/en​​.wiki​​pedia​​.org/​​ wiki/​​Q​_cyc​​le#​/m​​edia/​​File:​​Compl​​​ex​_ II​​I​.png​. *bH = bH heme group b562; bL = bL heme group b566; c1 = cytochrome c1; Cyt Cox = cytochrome c in the oxidized state; Cyt Cred = cytochrome c in the reduced state; FeS = Rieske iron-sulfur protein; H+ = hydrogen proton; IM = intermembrane; M = matrix; Q = ubiquinone (coenzyme Q in the oxidized state); Q0 = Q0 site of Complex III, QH2 = ubiquinol (coenzyme Q in the reduced state); Qi = Qi site of Complex III.

Complex V (F0-F1-ATP synthase) is an assembly of 16 different polypeptides that uses the proton motive force generated by Complexes I, III, and IV to catalyze ATP generation. ATP synthase has two reasons with different functions-the F0 region of the ATP synthase consists of three subunits; this region is responsible for proton conduction. The F1 region is a soluble protein consisting of five subunits; this region is required for the catalytic functions of the enzyme. To briefly summarize the reactions that take place in the ETC (Figure 8.9):

1) Electrons enter at Complex I (or Complex II). 2) The mobile intermediate coenzyme Q (CoQ, or ubiquinone) carries electrons to Complex III (ubiquinol–cytochrome c reductase). After CoQ unloads its electrons on Complex III, it becomes oxidized into ubiquinol. 3) Electrons from Complex III are transferred to another mobile intermediate, cytochrome c, which ultimately guides the flow of electrons to Complex IV (cytochrome c oxidase).

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FIGURE 8.9  Electron transport chain. Complexes I to IV are shown as a series of electron transporters within the inner mitochondrial membrane. Protons are pumped from the mitochondrial matrix out into the intermembrane space creating an electrochemical gradient. NADH donates electrons to Complex I (NADH oxidoreductase) and FADH2 donates electrons to Complex II (succinate dehydrogenase). These electrons ultimately flow through Complex III (cytochrome C oxidoreductase) and complex IV (cytochrome c oxidase). The electrons are finally accepted by free oxygen. Electron transport requires chains of redox reactions, with a small amount of free energy used at three sites to transport protons (H+) across the inner mitochondrial membrane. There is debate in the literature on the exact balance of protons in the electron transport chain. The currently accepted model is presented in this figure. Source: adapted from (37). *ATP = adenosine triphosphate; CoQ = coenzyme Q; e = electron; FAD = the oxidized form of flavin adenine dinucleotide; FADH2 = the reduced form of flavin adenine dinucleotide; H+ = hydrogen proton; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; O2 = oxygen; Pi = inorganic phosphate.



4) The process of transfer of electrons through these complexes creates a proton motive force that leads to the efflux of electrons from the mitochondrial matrix to the inner mitochondrial membrane space. This causes an electrochemical gradient across the inner mitochondrial membrane. The energy used to pump the protons is used to synthesize ATP via another complex called ATP synthase (F0·F1-ATPase) or Complex V. Complex V consists of a membranebound F0-ATPase and rotatory F1-ATPase. ATP synthase functions to couple proton flow to the conversion of ADP to ATP via a mechanism that is not completely understood.

8.2.2.1 Mitochondrial Function Mitochondria play numerous metabolic and non-metabolic roles in cells that are required for homeostasis. The central role of mitochondria is to produce ATP via a series of biochemical reactions involving the citric acid cycle and oxidative phosphorylation. In addition to energy metabolism, it is also involved in cellular signaling through ROS and Ca++, programmed cell death (apoptosis), heme synthesis reactions, steroid biosynthesis, cell proliferation, cell survival, and heat production, etc.

Role of Mitochondria in Glucose Metabolism Glucose is a major energy source for most living organisms. Metabolism of glucose is a multistep process involving three major pathways: glycolysis, the TCA cycle, and oxidative phosphorylation. Glycolysis occurs in the cytoplasm, while

Metabolism and Medicine the TCA cycle and oxidative phosphorylation take place in the mitochondria. Glucose oxidation is highly exergonic and yields a large amount of free energy (ΔG°′ = –686 kcal/mol), which is used to synthesize ATP. Glycolysis is the first step to breakdown glucose. Glycolysis does not require oxygen, which makes it a major metabolic pathway in anaerobic organisms. Through a series of enzymatic reactions, glucose is converted into pyruvate. In the process, there is a net gain of two molecules of ATP, via substrate-level phosphorylation. The details of glycolysis are presented in Sidebar 8.6. In addition to ATP, glycolysis generates the high-energy molecule NADH. The oxidizing agent NAD+ accepts electrons from glyceraldehyde-3-phosphate, forming NADH. NADH acts as a potent electron donor in many oxidation-reduction reactions. In the presence of oxygen, the NADH transfers its electrons to the mitochondrial electron transport chain, generating ATP via the process of oxidative phosphorylation. After donating these electrons, NADH reverts to NAD+ and reenters the glycolytic pathway. Recycling NADH/NAD+ allows glycolysis to continue. The end product of glycolysis is pyruvate. In the absence of oxygen, pyruvate is converted by the enzyme lactate dehydrogenase into lactate. In the presence of oxygen, pyruvate is transported into mitochondria, where it is converted into acetyl CoA. The enzyme pyruvate dehydrogenase complex (PDH) catalyzes the oxidative decarboxylation of pyruvate into acetyl CoA. This reaction yields one molecule of NADH, which enters the tricarboxylic acid cycle (TCA cycle), also known as the Krebs cycle. The TCA cycle involves a total of eight sequential reactions, which ultimately synthesize one highenergy phosphate bond, in the form of GTP. Each molecule of GTP can be used to synthesize one molecule of ATP. Each completion of the TCA produces three molecules of NADH and one molecule of FADH2. Like NADH, FADH2 contains high-energy electrons, which are also used to generate ATP in mitochondria during oxidative phosphorylation. In the oxidative phosphorylation process, the electrons from NADH and FADH2 are transferred to protein complexes embedded in the inner mitochondrial membranes and eventually combined with O2. The transfer of electrons from NADH to O2 releases a considerable amount of free energy (ΔG°′ = –52.5 kcal/mol), which is used to synthesize ATP. Most of the ATP derived from glucose metabolism is a product of the TCA cycle and oxidative phosphorylation, rather than glycolysis. Glucose metabolism through glycolysis and the TCA cycle generates a total of four molecules of ATP directly via substrate-level phosphorylation (two from glycolysis and two from the TCA cycle). Additionally, a total of 12 molecules of high-energy reducing equivalents are generated (NADH— two from glycolysis, two from the reaction catalyzed by PDH, and six from the TCA cycle; FADH2—two molecules from the TCA cycle). These reducing equivalents eventually contribute to the generation of ATP. See Sidebar 8.6 for a description of ATP yields from oxidation of glucose. Different substrates for the TCA cycle enter into the mitochondrial matrix via PDH, carrier proteins, or different shuttle mechanisms. On the other hand, fatty acid enters the mitochondria through the carnitine palmitoyltransferase system

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Mitochondrial Dysfunction and Insulin Resistance (CPT-I and CPT-II). Oxidation of different substrates leads to electron transfer to a specific site. For example, NADH derived from the oxidation of pyruvate, glutamate, and malate donates its electrons to Complex I, whereas complex II acts as an entry point for the electrons coming from succinate, fatty acyl CoA, Glycerol-3-phosphate, etc. Electrons generated from the oxidation of fatty acyl-CoAs can enter both via complex I or complex II by way of the metabolism of acetyl-CoA through the TCA cycle.

Insulin resistance is the inhibition of the enzyme complex pyruvate dehydrogenase (PDH), essentially decoupling glycolytic metabolism of glucose in the cytosol from completion of its full oxidative combustion in the mitochondria. Thus, this is a mechanistic hallmark for how insulin resistance contributes to bioenergetic and redox stress.

Role of Mitochondria in the Metabolism of Other Organic Molecules

The ETS does not perfectly transfer all electrons down the chain. In fact, Complex II can also contribute to ROS generation during fatty acid metabolism (see Section 1.7.6) and reverse electron transport (see Section 1.7.8). High levels of H2O2 and OH· in the mitochondria cause oxidative damage. Superoxide is not directly destructive, but indirectly generates hydroxyl radical when it reacts with copper or iron. Caloric excess can enhance ROS generation in mitochondria, exhausting the antioxidant defense system. ROS can damage mitochondrial components, especially the ETS and mitochondrial DNA. This damage causes mitochondrial dysfunction, leading to disrupted ATP production, among other crucial mitochondrial functions. As explained in Chapter 1, Section 1.7, there are several mechanisms of generation of ROS in the mitochondria which largely depend on the respiration state and electron donors. The major sites of ROS generation within mitochondria are controversial, however, experimental evidence suggests that complex I and III are the major sites of ROS generation. In some cases, complex II also contributes to the ROS generation (fatty acid metabolism and in the condition of reverse electron transport). Principally, there are two modes of generation of mitochondrial ROS: forward electron transfer (FET) and reverse electron transfer (RET). The first mode, FET, requires that the flavin mononucleotide (FMN) in Complex I is in an almost fully reduced state. This only occurs when the cellular NADH/ NAD+ ratio is high (such as under hyperglycemic conditions). FET generates ROS when function at Complex I is inhibited; damage to or mutation of Complex I, ischemia, loss of cytochrome c, or a low cellular demand for ATP all inhibit the function of Complex I. This inhibition of function raises the NADH/NAD+ ratio, which increases ROS production. One of the main problems with excess fatty acid oxidation is a massive influx of electrons to coenzyme Q. These excess electrons reduce coenzyme Q (ubiquinone) to CoQH2 (ubiquinol). This results in loss of redox potential and reversal of electron flow from ubiquinol to Complex I. This causes NAD+ to be reduced to NADH, raising the NADH/NAD+ ratio. RET collapses the PMF and associated proton electrochemical gradient, impairing downstream biosynthesis of ATP (Sidebar 8.8). Free electrons at Complexes I and II combine with O2 to produce reactive superoxide species with the ability to cause oxidative stress (38). ROS generation by RET can occur during the oxidation of succinate or fatty acids. RET-dependent mROS generation with succinate accumulation is observed during heart ischemia. mROS production during RET can be attenuated by inhibiting Complex II (succinate dehydrogenase), improving cardiac health. A slight depolarization of the mitochondrial membrane potential can also abolish RET.

While many cells prefer glucose as a fuel source, other cells prefer fatty acids. Heart, muscle, and liver cells prefer fatty acids as an alternative source of energy. The pathways involved in glucose oxidation can be used to metabolize fatty acids, nucleotides, and amino acids. For example, fatty acids can be broken down into acetyl coA, which enters the TCA cycle and undergoes oxidative phosphorylation. Nucleotides can be broken down into sugars, which enter the glycolytic pathway. Amino acids from protein are metabolized via the TCA cycle. Lipid metabolism is more efficient at generating ATP than carbohydrate or protein metabolism. Lipid metabolism is a complex process. The first step is to break down lipids to free fatty acids (FFA) and glycerol. Fatty acids are metabolized by the process of β-oxidation. In summary, fatty acids undergo an acylation process involving coenzyme A and ATP, to form fatty acyl-CoA. The fatty acyl-CoA is further degraded in a sequential oxidative process, leading to the removal of two carbons at a time. Each step of the oxidation process yields one molecule each of acetyl CoA, NADH, and FADH2. Acetyl CoA enters the TCA cycle, where it is metabolized in the same manner as glucose. The complete oxidation of a 16-carbon fatty acid (such as palmitate) yields a total of eight molecules of acetyl CoA and seven molecules each of NADH and FADH2. Therefore, oxidation of one molecule of palmitate generates a large amount of ATP (7 NADH × 2.5 P/O ratio = 17.5 ATP, 7 FADH2 × 1.5 P/O ratio = 10.5 ATP, and 8 acetyl CoA × 12 P/O ratio = 96 ATP). Altogether, oxidation of palmitate yields 106 – 110 ATP molecules. This is much higher than the net gain of 32 ATPs per molecule of glucose (see Sidebar 8.7). Because of their higher ATP yield, lipids serve as better energy storage molecules than polysaccharides or proteins. For more mechanistic details about lipid metabolism, see Chapter 1, Section 1.7.4.

SIDEBAR 8.7: METABOLIC EFFICIENCY OF GLUCOSE VERSUS FATTY ACID METABOLISM The ratio of P/O (the ratio of ATP produced per oxygen consumed) for glucose versus for fatty acids should be explicit, making the point that the complete oxidation of glucose is metabolically most efficient from redox and energy perspectives, with the highest amount of ATP produced requiring the least amount of oxygen (i.e. generating the least amount of ROS). Importantly, a hallmark of

Role of Mitochondria in Redox Homeostasis

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Overall, conditions that lower the NADH/NAD+ ratio tend to suppress ROS production.

SIDEBAR 8.8: HOW DOES REVERSE ELECTRON TRANSPORT HAPPEN? Reverse electron flow is the transfer of electrons through the ETC via reverse redox reactions. This usually requires the input of a substantial amount of energy, such as caloric excess. This backflow negates the proton electrochemical gradient, preventing ATP formation at Complex IV. Further, electron backflow leads to electron slippage and ROS generation. Excess fatty acid oxidation renders coenzyme Q (ubiquinone) into a reduced state (ubiquinol, QH2). Ubiquinol has a greater electronegative voltage than ubiquinone, causing electrons carried by ubiquinol to flow backward to Complex II. When the redox potential at Complex II is decreased (becomes more electronegative than Complex I), electrons flow back to Complex I (Figure 8.8). A high NADH/NAD+ ratio under hyperglycemic conditions exhausts the capacity of electron transfer at Complex I, which increases electron pressure at Complex I and III. Higher pressure means a faster electron leak at Complex I and III, producing more ROS. Superoxide can also be formed as a result of this high influx of electrons. Complex II contributes less to the redox potential difference (Sidebar 8.9), which makes Complex II less susceptible to ROS generation. However, vigorous oxidation of lipids can lead to excess-FADH2-mediated ROS generation at Complex II (Figure 8.10). Additionally, high FADH2 generated from fatty acid oxidation can negatively influence the function of Complex II (see Chapter 1 Figure 1.14). It has been proposed that the β-oxidation of fatty acids may result in ROS generation at a different site in the mitochondrial matrix, different from the ROS generation site at Complex III. Alternatively, it has been suggested that ROS production during fatty acid oxidation comes from electron transferring flavoprotein which accepts electrons from dehydrogenases (Acyl CoA dehydrogenase-ACAD) and transfers them to the coenzyme Q which is catalyzed by another enzyme called ETF-ubiquinone oxidoreductase (ETF-QO) present in the matrix side of the inner mitochondrial membrane (Figure 1.12 and Figure 1.14). As shown in Figure 1.12, ETF-QO covalently binds with flavin (FAD) and 4Fe-4S cluster (similar to complex II). ETF-QO functions as a convergence point for electrons coming from nine flavoprotein acyl-CoA dehydrogenases.

SIDEBAR 8.9: WHY IS ELECTRON FLOW WEAK AT COMPLEX II? Succinate donates electrons to bound FAD, producing FADH2. The difference in redox potential between bound succinate/FADH2 and coenzyme Q is very small and contributes minimally to the proton motive force. Only

FIGURE 8.10  Production of superoxides and ROS in the ETC. Excess energy substrate (hyperglycemia) induces the production of superoxides by the mitochondrial electron transport chain (ETC), leading to redox damage and ultimately mitochondrial dysfunction. In cells with high levels of glucose, a critical threshold in the voltage gradient across the mitochondrial membrane is reached, which blocks the transfer of electrons along the protein complexes of the ETC. These backed-up electrons interact with coenzyme Q to form superoxides. Source: adapted from (39). *cyt c = cytochrome c; e– = electron; H+ = hydrogen proton; H2O = water; Mn-SOD = manganese-dependent superoxide dismutase; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; O2 = oxygen; O2˙– = superoxide anion; Q˙ = semiquinone.

~1.5 molecules of ATP are generated per two electrons transferred from succinate/FADH2 to oxygen. Hypothetically, if electrons were transferred from free FADH2 to coenzyme Q, the difference in redox potential would be greater, producing enough energy to pump the proton. However, succinate has higher redox potential than free FAD, so succinate would not be able to donate its electron to FAD, meaning that FADH2 would not be synthesized. Other sources of mitochondrial damage include mutations in mitochondrial DNA or environmental toxins. These insults to mitochondrial health can cause homeostatic imbalances, such as: altered mitophagy (the process which eliminates dysfunctional mitochondria), decelerated ATP production, disturbed Ca2+ homeostasis, reduced mitochondrial membrane potential, and compromised mitochondrial respiration. There is a natural decline in mitochondria biogenesis with aging. This decline may be caused by mitochondrial fission and fusion, or possibly due to inhibition of mitophagy. Therefore, older patients have a higher susceptibility to mitochondria-related dysfunction; they have fewer “good mitochondria” remaining. While we know some of the risks of impaired mitochondrial function, the full extent of dysfunctional mitochondria on aging and metabolic health remains to be investigated. If reverse electron transport persists, it can exhaust the cell’s antioxidant capacity, leading to mitochondrial dysfunction and many age-related diseases (Sidebar 8.10).

Mitochondrial Dysfunction and Insulin Resistance

SIDEBAR 8.10: ANTIOXIDANT SYSTEM AND CELLULAR REDOX STATE Redox state is the balance of compounds (such as GSH/ GSSG, NAD+/NADH, and NADP+/NADPH) that can donate or accept electrons. Antioxidant systems maintain the balance of redox and fight oxidative stress by providing electrons. Harmful oxidizing agents such as hydrogen peroxide (H2O2) and superoxides (O2–) can be neutralized by adding electrons. However, when redox disturbance becomes severe enough, it overwhelms antioxidant capacity. This is essentially allostatic overload: the threshold when metabolic stress causes disease. Oxidative stress and redox homeostasis is maintained by coordinated systems of antioxidants. The embedded figure highlights the major cell antioxidant systems.

Antioxidant Defense System and Mitochondrial Dysfunction Under physiological conditions, ROS production is tightly controlled in mitochondria. This protects the cellular components from oxidative damage. The cell uses multiple mechanisms to counter the effects of ROS-induced oxidative damage. One way to reduce damage is to scavenge free radicals before they can form secondary ROS, using antioxidants: glutathione (GSH), vitamin E, vitamin C, and various flavonoids and carotenoids. There is also an enzymatic defense system, which uses superoxide dismutase (SOD1 and SOD2), catalase (CAT), glutathione reductase (GR), and peroxidase (GPx). In pathological conditions or when caloric excess overwhelms the ETC, the antioxidant defense system is unable to adequately neutralize ROS. The damage caused by uncontrolled ROS levels results in an accelerated rate of aging, which is associated with numerous pathological conditions, such as diabetes, cancer, cardiovascular disease, and neurodegenerative disorders.

8.2.2.2 Influence of Nutrient/Diet on Mitochondrial Function Our diets directly influence mitochondrial function. As discussed in Chapter 1, Section 1.7, macronutrients from the diet, such as carbohydrates and lipids, differentially affect the mitochondrial function. Carbohydrates, the major component of our diet, are broken down into monosaccharides (prominently glucose), which are further metabolized through glycolysis and TCA cycle pathway to generate high-energy reducing equivalents NADH and FADH2. NADH and FADH2 are shuttled to the ETS to generate ATP. In contrast, lipids are first converted into fatty acids, which are broken down by β-oxidation to yield NADH and FADH2, as well as acetyl-CoA.

339 Caloric excess negatively influences the ETS function, unbalancing metabolic homeostasis, resulting in metabolic disorders. For example, hyperglycemia elevates the ratio of NADH/NAD+, which puts too large of a burden on Complex I; Complex I is unable to transfer electrons fast enough from NADH through the ETS. This backlog of electrons at Complex I increases the electron leak, leading to loss of membrane potential and ROS generation. In parallel, enhanced fatty acid oxidation produces much more NADH and FADH2. Fatty acid-derived electrons from FADH2 are tunneled into the ETC at Complex II (also called electron-transferring flavoprotein [ETF]). These excess electrons traveling down the ETC overwhelm the Q cycle’s electron-carrying capacity, leaving coenzyme Q in a reduced state. Unable to pass these excess electrons forward to Complex III fast enough, reduced coenzyme Q passes these electrons backward, to Complex I. This event is known as reverse electron transport (RET). Excess electrons from RET cause ROS generation. These examples highlight the importance of moderating food intake for mitochondrial health. If food intake is moderated to the point of starvation (or a ketogenic diet), the liver generates ketone bodies (β-hydroxybutyrate, acetoacetate, and acetone). Ketone bodies are generated as a byproduct of β-oxidation. Acetyl CoA, instead of metabolizing through the TCA cycle, is used for ketone body formation. Ketone bodies, unlike glucose and fatty acids, are metabolically highly efficient; that is why they are considered super fuel. Another reason why ketone bodies are a superior fuel source is that they have antioxidant properties. When there are excess electrons in the respiratory chain, coenzyme Q can become half-reduced due to electron slippage, into the semiquinone form. Those slipped electrons react with molecular oxygen to form superoxides ROS. Ketone body metabolism may oxidize semiquinone back to coenzyme Q, fighting mitochondrial generation of oxidative free radicals. Ketone bodies may also upregulate activity of NADH dehydrogenase, which increases electron transfer from Complex I to Complex II. Increased synthesis of coenzyme Q and increased flow of electrons from coenzyme Q to Complex III are other hypothetical ketone body-mediated methods of enhancing efficiency of the respiratory chain without production of ROS. See Sidebar 8.6 for a discussion of electron transfer at coenzyme Q. The influence of metabolism of different nutrient substrates on mitochondrial function is further elaborated on in Section 9.3.4. There is extensive research on the impact of the ketogenic diet on metabolic homeostasis. The ketogenic diet is low in carbohydrates and rich in fat, perfect for diabetics. Diabetics have impaired mitochondrial function (diminished ETC function, resulting in impaired glucose oxidation). Therefore, diabetics are not able to use glucose as a primary energy source. Instead, the ketogenic diet can provide energy to diabetics by stimulating the biosynthesis of ketone bodies in the liver. Ketone bodies can serve as an alternative energy source under pathological conditions, such as when the carbohydrate metabolism becomes compromised in diabetes. The ketogenic diet also stimulates mitochondrial fatty acid oxidation, bypassing

340 glucose oxidation. Therefore, the ketogenic diet provides a glucose-independent energy source. There are few well-controlled clinical trials that investigate the effects of diet on mitochondrial function. Evidence from rodents, flies, and cell lines suggests that diet modifications may potentially improve mitochondrial metabolism, improving disease phenotypes. The exact biochemical mechanism by which diet influences mitochondrial function is unknown. One possibility is that poor diets promote mutations in mtDNA and defects in mitochondria function. Nearly all mutations and defects accompanying mitochondrial pathologies cause decreased OXPHOS enzymes’ activity. However, identifying the point mutation or exact molecule decreasing enzyme activity does not have widespread application to patient medicine; such discoveries would only be beneficial for treating that specific form of the disease. Instead, a broader approach to correcting mitochondria-related pathologies could entail modifications to diet.

8.2.3 Intertwined Relationship Between Mitochondrial Dysfunction and Insulin Resistance Insulin resistance and mitochondrial dysfunction have bidirectional cause and effect relationships. In the section to follow, we will describe examples by which mitochondrial dysfunction drives insulin resistance followed by an example by which insulin resistance drives mitochondrial dysfunction (Figure 8.11). The body has circadian rhythms when it comes to metabolism. The daytime is the feeding period, and the nighttime is the fasting period when lipid fatty acid oxidation happens. Mitochondrial dysfunction impairs lipid oxidation, leading to

Metabolism and Medicine ectopic lipid accumulation in skeletal muscle, and ultimately, a loss of metabolic flexibility (switching to the classical mode of energy production). Consequently, glucose metabolism (glycolysis) and mitochondrial energy metabolism (oxidative phosphorylation) are uncoupled. This throws off the metabolism’s circadian rhythm, resulting in lipid fatty acid oxidation occurring during the daytime feeding period. Daytime fatty acid oxidation is a hallmark of insulin resistance. Mitochondrial fatty acid oxidation (FAO) is one of the main metabolic pathways for bioenergenesis. FAO, however, is less efficient at energy generation than glycolysis because it requires more oxygen per unit of production of ATP. FAO produces more reactive and free radical oxidative species, which cause oxidative modifications to local mitochondrial structures, exacerbating mitochondrial dysfunction. This is yet another way that mitochondrial dysfunction can cause insulin resistance. These examples demonstrate how mitochondrial dysfunction can cause insulin resistance. On the other hand, insulin resistance can cause mitochondrial dysfunction by interfering with circadian rhythms. Insulin has cyclical patterns of secretion, which make it a powerful regulator of molecular clock function (see Section 8.2.3.3). Accordingly, disturbed timing of insulin signaling alters the integrated, synchronized activation of transcription regulators, such as PGC1α, which is crucial for promoting mitochondrial biogenesis (Figure 8.12). As previously discussed, dysfunctional mitochondria impair the ability of insulin to drive bioenergetics. These examples show that there is an interdependent and bidirectional relationship between insulin resistance and mitochondrial dysfunction.

8.2.3.1 The Evolution of Insulin Resistance in Insulin-Responsive Metabolic Tissues 8.2.3.1.1 Development of Insulin Resistance in Skeletal Muscle

FIGURE 8.11  Metabolic syndromes such as Type-2 Diabetes (and other metabolic syndromes) ultimately cause cell damage through oxidative stress caused by the promotion of mitochondrial ROS production. Source: adapted from (40). *DAG = diacylglycerol; DNA = deoxyribonucleic acid; JNK = c-Jun N-terminal kinase; NFκB = nuclear factor κ B; p38 MAPK = p38 mitogen-activated protein kinase; PKC = protein kinase C; ROS = reactive oxygen species.

While much remains to be understood about the relationship between mitochondrial dysfunction and insulin resistance, one known mechanism that links these two phenomena is impaired lipid oxidation. Simply stated, impaired mitochondrial function decreases the capacity of the cell to oxidize lipids (Figure 8.13) (42). This decrease in lipid oxidation allows the accumulation of bioactive lipid species in “ectopic tissues” (i.e. outside of adipose tissues and in tissues where lipid accumulation is not normally seen such as liver and skeletal muscle) where they can disturb insulin signaling. Mitochondrial dysfunction can also promote ROS formation, which can perpetuate oxidative damage in these tissues. In some individuals with a family history of insulin resistance, these changes can be detected very early on during the genesis of insulin resistance (IR) in skeletal muscles. Intramyocellular lipids accumulate even in the cells of lean adolescents (43–45), presumably due to subtle genetic defects in mitochondrial fatty acid oxidation. Though lean, the accumulation of ectopic lipid leads to skeletal muscle insulin resistance. In these individuals, this primary early defect can account for secondary changes often seen in patients with insulin resistance. For example, following a carbohydrate challenge, impaired muscle insulin action decreases muscle

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FIGURE 8.12  The role of PGC1α in cellular metabolism and the stress response. Cellular stress (including metabolic stress) induces PGC1α, which then interacts with transcription factors involved in regulating stress responses and metabolism. PGC1α acts as a co-activator to promote mitochondrial biogenesis, oxidative phosphorylation, and fatty acid metabolism. Importantly, it plays a key role in the detoxification of ROS and thereby facilitates metabolic adaptation. Source: adapted from (41). *α-KG: alpha ketoglutarate; ATP = adenosine triphosphate; CoA = coenzyme A; ETC = electron transport chain; H2O2 = peroxide; O2 = oxygen; O2- = superoxide anion; PGC1α = peroxisome proliferator-activated receptor ɣ coactivator 1 ɑ; ROS = Reactive Oxygen Species; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle); TFs = transcription factors.

FIGURE 8.13  Mitochondrial dysfunction leads to decreases in the ability of cells to oxidize lipids, which then accumulate in skeletal muscle resulting in chronic diseases of aging. Source: adapted from (42).

glucose uptake (i.e. impaired glucose tolerance) and redirects carbohydrate substrate to the liver, driving de novo lipogenesis and promoting hepatic lipid accumulation (hepatic steatosis) and dyslipidemia. In other individuals, adipose dysfunction can lead to dysregulated adipocyte lipolysis, releasing glycerol and fatty acids that are then cleared by the liver, re-esterified into triglyceride, and exported as VLDL. This IR-mediated dyslipidemia may become part of a positive loop exacerbating insulin resistance.

Increases in hepatic VLDL secretion could promote lipid accumulation in peripheral ectopic tissues. Triglyceride-rich VLDL particles release their lipid payload under the influence of lipoprotein lipase in the capillaries of skeletal muscle tissue. Re-esterification of these lipid substrates within myocytes can promote the accumulation of bioactive lipid species such as diacylglycerol (DAG) and ceramide species. Mitochondrial production of hydrogen peroxide and other reactive oxygen species (ROS), a tenant of mitochondrial dysfunction in this setting, promotes DAG and ceramide lipid peroxidation and lipotoxicity, which in turn activate inflammatory pathways that antagonize insulin signaling and cause insulin resistance. The greater the mitochondrial function becomes compromised, the greater the insulin resistance. This relationship may be reciprocal. Insulin signaling pathways do regulate transcription factors that are involved in mitochondrial biogenesis, homeostasis, and degradation, components of mitochondrial functionality tightly coupled with mitochondrial DNA replication. As such, decreased insulin signaling, from both insulin deficiency and resistance, can lead to parallel reductions in the protein components of mitochondrial bioenergetic pathways, the TCA cycle, fatty acid beta oxidation, and oxidative phosphorylation of the electron transport chain. There is therefore a direct correlation between insulin signaling and oxidative combustion of macronutrients by way of mitochondrial function. Conversely, there is an inverse relationship between these parameters and the mitochondrial generation of ROS. Increased ROS production at such quantities directly impairs mitochondrial function by degrading the molecular fidelities of mitochondrial DNA and inner and outer mitochondrial membrane proteins and

342 lipids. High levels of ROS also indirectly impair mitochondrial function through the induction of lipotoxicity (from DAG and ceramides), thus promoting inflammatory pathways that interrupt insulin signaling (46). This interwoven, feedforward, and self-amplifying loop of insulin resistance to mitochondrial dysfunction may promote chronic disease sequelae including dementia, cancers, and cardiovascular disease (47).

8.2.3.1.2 Development of Insulin Resistance in Liver and Visceral Adipose Tissue There is overlap between the processes that lead to the induction of IR in the liver and in visceral adipose tissue. Hepatic IR appears to largely originate from ectopic accumulation of bioactive lipid species. As described above, this can arise as a consequence of impaired muscle and adipose function, redirecting carbohydrate and lipid substrates to the liver. Other mechanisms have been proposed as well, including disturbed gut microbiota composition that results in subclinical endotoxemia in portal circulation (48–50). This subsequently induces inflammatory responses which may contribute to insulin resistance in the liver and perhaps also visceral adipose tissue (51, 52). Furthermore, an altered gut-derived endocrine system including a reduced release of hormone glucagon-like peptide-1 (GLP-1), and IR in the hypothalamus of the brain, causes impaired satiety and hence overeating. Consequently, there is an increase in systemic adiposity and associated weight gain. While a reduction in GLP-1 is a consequence of obesity, there is likely a self-amplifying loop of cause and consequence whereby low GLP-1 levels promote an obese state given that higher therapeutic levels of exogenously administered GLP-1 reduce body weight (53). IR manifests in adipose tissue by way of abnormally upregulated lipolytic activity that leads to the flux of free fatty acids and glycerol. When this occurs in visceral adipose tissue, this can expose the liver to increased concentrations of these substrates. Interestingly, the esterification of fatty acids in the liver appears to be primarily driven by substrate delivery and to a degree, independent of hepatic insulin signaling (54). Esterification of fats within the liver accounts for the majority of lipids formed within the liver and can contribute to the formation of nonalcoholic fatty liver disease. In contrast, many investigators have observed increases in de novo lipogenesis (DNL) in NAFLD. But, this increase in DNL in NAFLD is an intriguing “metabolic paradox” trying to reconcile how de novo lipogenesis (considered to be an insulin-responsive pathway) is maintained in an insulin-resistant state. Specifically, insulin signaling can clearly activate sterol responsive binding protein 1, a transcription factor considered a master regulator of de novo lipogenesis. But, how is this pathway maintained when insulin signaling itself is impaired? Some have postulated that the presence of bifurcations in insulin signaling in which signaling through one branch (regulating glucose metabolism) is impaired while signaling another branch (regulating DNL) persists. But, the existence and identity of this branch point have not been conclusively shown. The branch point hypothesis also disregards the finding that the defect in hepatic insulin action occurs at the most proximal point in the insulin

Metabolism and Medicine signaling pathway: lipid-mediated activation of PKCε impairs activation of the insulin receptor itself. This paradox can be explained by considering other mechanisms that regulate DNL and hepatic lipid synthesis. Increased hepatic glucose flux (i.e. from impaired peripheral glucose metabolism) can drive de novo lipogenesis via substrate push. Additionally, the carbohydrate responsive element binding protein (ChREBP) can increase the expression of lipogenic enzymes similar to SREBP1 but in response to a carbohydrate signal. Finally, increased fatty acid flux, from dysfunctional adipose tissue, can promote hepatic lipid esterification and also contribute to the development of a fatty liver in an insulin-resistant state. There is a notable distinction between visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT). The former is insulin resistant, deriving from the phenomenon of “subclinical endotoxicosis” described above. As well, visceral adipocytes of VAT are inherently insulin resistant in nature and are reported to derive from myeloid bone marrow progenitor cells (55, 56). In contrast, subcutaneous adipocytes of SAT are inherently insulin sensitive and are embryologically derived from mesenchymal cells purposed to accommodate neutral triglyceride fat stores. With the progressive accumulation of lipids within SAT, however, its adipocytes hypertrophy and outgrow their blood supply, leading to hypoxia and consequent inflammation that promotes the development of IR. However, some would consider visceral adipose tissue an ectopic depot as well (57).

8.2.3.2 Overconsumption, Mitochondrial Dysfunction, and Insulin Resistance Oxidative damage is an almost unavoidable consequence of oxidative metabolism and can accrue as a function of time and load. With regards to the latter, dietary excess can lead to increased substrate oxidation, oxidative damage and mitochondrial dysfunction. While low-energy states promote mitochondrial biogenesis, high-energy states degrade mitochondrial function. Dietary excess causes metabolism to cross the “take-over” threshold, the point at which quantum metabolism of ATP production collapses and is “taken over” by the less efficient classical mode of oxidative phosphorylation (see Volume 1, Chapter 4 for more information) (58). Brownlee’s Unifying Hypothesis Banting Award Lecture also described the take-over threshold as declining mitochondrial efficiency during hyperglycemia, promoting microvascular disease and insulin resistance-induced macrovascular disease (39). While Brownlee did not describe the external control parameter of dietary excess per se, conceptually, the idea of mitochondrial nutrient overload causing redox stress is essentially the same. Consequences of dietary excess include hyperglycemia in type 2 diabetes release of non-esterified fatty acids from insulinresistant adipose stores (59). Quantitative nutrient excess is a classic control parameter for causing mitochondrial dysfunction, which subsequently causes insulin resistance. Other control parameters include poor-quality diet, disturbed circadian behaviors, and the chronic stress response. Each of these parameters governs pathophysiology from varied perspectives. These control parameters generate redox and inflammatory stress cascades,

Mitochondrial Dysfunction and Insulin Resistance which may initially provoke either insulin resistance or mitochondrial dysfunction (60). Nutrient excess also increases adipose tissue mass, which can cause insulin resistance. Here’s how:

1) Individuals have a distinct capacity for adipose storage that is influenced by a number of factors, including genetics, age, biological gender, fitness, etc. When this threshold is exceeded, adipose dysfunction develops, with adipose death, recruitment of inflammatory cells and an overall pro-inflammatory milieu. 2) When adipocyte lipid storage is full, excess fat leaks into the bloodstream. Non-esterified fatty acids in the circulation are potentially taken up by peripheral tissues as ectopic lipid droplets (discussed in Chapter 7, Sections 7.3.6 and 7.4.1.4). Lipid storage of triglycerides in adipose tissue is neutral, but ectopic lipids are often reactive, promoting inflammatory cascades that disturb insulin signaling and consequently, mitochondrial function (61, 62). 3) The inflammation generated by redox stress may perturb mitochondrial function independent of, as well as interdependent with, inflammation-impaired insulin signaling. Altogether, the intertwined and bidirectional relationship between mitochondrial dysfunction and insulin resistance is an essential relationship in the development of chronic diseases of aging. It does not matter which condition precipitates the other; both conditions are major health problems.

8.2.3.3 Circadian Disturbances, Insulin Resistance, and Mitochondrial Dysfunction In addition to excessive food intake, other extrinsic stressors such as alterations in circadian patterns of eating and sleeping behavior, changes in lifestyle activity, infection, and mental stress can impair these systemic physiological factors and

343 lead to the development of metabolic diseases such as insulin resistance, hyperglycemia, dyslipidemia, obesity, type 2 diabetes, hypertension, and cardiovascular disease and accelerate the aging process (63). Circadian clocks regulate food intake, energy expenditure, whole-body glucose and lipid metabolism, and insulin sensitivity (64). Under normal physiological conditions, i.e., in a zone of healthy stability, the body maintains optimum circulating levels of glucose and lipids via systemic regulation of hormones (such as insulin, glucagon, glucocorticoid, epinephrine, etc.), nutritional status (fed and fasting states), circadian behavior (patterns of sleeping behavior and diet consumption), and gut microbiota composition. Allostasis is an adaptive process in which the body regains physiological stability (homeostasis) against acute stress. Allostatic load arises from repeated hits from these multiple stressors (chronic, devitalizing stress; see Chapter 2). By maintaining a healthy diet, a moderate level of calorie restriction, lifestyle activity (e.g., exercise), regular sleeping pattern, and low levels of psychological stress, one can stay in a stability zone within the Physiological Fitness Landscape (PFL), circumventing metabolic syndrome, and delaying the aging process. Figure 8.14 details how disruptions in circadian rhythmicity affect free energy and fitness across time, eventually leading to the development of chronic diseases of aging. An extensive discussion of parameters involved in the PFL and disease progression can be found at the end of the next chapter in Section 9.5. In humans, endurance and muscle mitochondrial function are at their max in the late afternoon, whereas low-energy sensitive signaling reaches its peak during morning hours. Dysregulation of mitochondrial dynamics (fission and fusion of mitochondria) might lead to the development of pathologies such as obesity and type 2 diabetes. Moreover, it has been observed that mitochondrial dynamics oscillate in a circadian pattern and it can be speculated that optimizing the timing of exercise sessions could be a therapeutic approach for the management of metabolic diseases. This suggests that circadian clocks may regulate whole-body energy metabolism through remodeling of the mitochondrial network.

FIGURE 8.14  Circadian insulin resistance occurs in a healthy physiological state (see first valley to the left). The loss of circadian cycling, however, represents the transition from health to disease. This is illustrated by the allostatic load that surpasses an initial energy barrier and symbolizes a zone of instability. As each successive peak and valley are navigated across time, free energy and physiologic fitness declines ultimately resulting in metabolic and chronic diseases of aging.

344 Carbohydrate (glucose) ingestion stimulates insulin secretion from the pancreas. Subsequently, insulin increases glucose uptake in peripheral tissues such as muscle, adipose, and other metabolic tissues. Concurrently, insulin also inhibits gluconeogenesis (endogenous glucose production). After eating a lipid-containing (fat-rich) diet, triglyceride gets packaged into triglyceride-rich lipoprotein such as chylomicron in the gut, which is then secreted into the bloodstream. Chylomicron particles distribute triglyceride into adipose tissues, muscle, and the heart. Chylomicrons from dietary fat fuel hepatic gluconeogenesis by providing glycerol as a substrate. Chylomicronderived adipose lipolysis by the liver promotes mitochondrial β-oxidation, generating acetyl coenzyme A (acetyl-CoA). During gluconeogenesis, acetyl-CoA is diverted away from tricarboxylic acid cycle (TCA) cycle metabolism and instead undergoes oxidative phosphorylation, which favors the production of ketone bodies (acetoacetate, β-hydroxybutyrate, and acetone). Adipose tissue stores triglycerides under fed conditions. During fasting conditions, where insulin levels are low, intracellular lipases are activated in adipose tissue. These include adipose triglyceride lipase (ATGL) and hormone-sensitive lipase (HSL). As a result, fatty acids are secreted from adipose tissue and sent to the liver, where they are resynthesized into triglycerides and subsequently packaged into lipoprotein and secreted from the liver as a very low-density lipoproteintriglyceride (VLDL-TG). Additionally, fatty acid released after lipolysis supplies energy demands of other tissue, such as muscle and heart. Perturbations of circadian rhythm have been shown to lead to dysfunction of adipose tissue. Excess overflow of free fatty acid from adipose tissue into the liver and muscle leads to ectopic lipid deposition, which causes insulin resistance, increasing blood glucose levels (hyperglycemia or type 2 diabetes). Additionally, studies have reported that ectopic lipid accumulation induces mitochondrial dysfunction, leading to insulin resistance. Moreover, during such pathophysiological conditions, elevated circulating fatty acids, glucose-driven lipotoxicity and glucotoxicity induce apoptosis of pancreatic beta cells. Consequently beta cells are unable to secrete insulin in late diabetic conditions (43, 65).

SIDEBAR 8.11: HOW POOR CIRCADIAN TIMING OF EATING PATTERNS RESULTS IN DYSGLYCEMIA AND DYSLIPIDEMIA, AND ITS RELATIONSHIP TO INSULIN RESISTANCE AND MITOCHONDRIAL DYSFUNCTION Timing of food consumption has a profound impact on metabolic diseases. For example, individuals with night-eating syndrome have a higher risk of obesity (66, 67). Eating nocturnally superimposes dietary lipids and carbohydrates onto the endogenously produced hepatic glucose, triglycerides, and adipose fatty acid outputs during the IR circadian phase. Consequent high circulating levels of glucose and lipids, also known as hyperglycemia

Metabolism and Medicine and hyperlipidemia, respectfully, promote pathological insulin resistance that prevents the return of daytime states of insulin sensitivity in the liver, adipose tissue, and skeletal muscles. Hyperglycemia in systemic tissues, including in insulin-responsive metabolic tissues, promote the intertwined circumstances of mitochondrial dysfunction and insulin resistance by overburdening mitochondria with excessive, non-insulin requiring uptake of glucose. This leads to the production of reactive oxygen species (ROS) at toxic levels. Hyperlipidemia, similarly manifests these same metabolic dysfunctions. For example, in skeletal muscle intramyocellular lipid (IMCL) accumulates when the capacity for mitochondrial fatty acid oxidation is surpassed. The resulting generation and peroxidation of DAG and ceramides propagate the vicious, interconnected amplification of insulin resistance and mitochondrial dysfunction. Time-restricted feeding habits improve obesity and obesity-associated disorders such as diabetes and hepatic steatosis. The transcription factor FOXO (Forkhead family of transcription factors) is the downstream target of insulin, which upregulates the genes involved in hepatic gluconeogenesis (the process of glucose production in the liver). Insulin deactivates FOXO through protein kinase B (Akt)-mediated FOXO phosphorylation. Therefore, during fasting conditions, when circulating insulin levels are low, FOXOs are activated and hepatic glucose production is increased. Under normal physiological conditions, the brain needs a continuous supply of glucose and hepatic glucose production is the only source of glucose during fasting. Under the pathophysiological condition, i.e. insulin-resistant state, hepatic glucose production increases abnormally, leading to hyperglycemia (increased blood sugar) (68, 69). The disruption of circadian cycling in humans (pattern of sleeping, eating behavior, physical activities) may cause insulin resistance or enhance hepatic glucose production. This suggests that the circadian clock may play a key role in maintaining whole-body glucose and lipid metabolism. Clinical studies have reported that serious cardiovascular events, including limb ischemia, sudden cardiac death, myocardial infarction, and aortic aneurysm rupture have shown circadian rhythmicity and reach a peak during the morning. Hypertension and cardiovascular disease are linked with sleep loss and there is approximately a 45% increase in the risk of a heart attack in individuals who sleep five or fewer hours per night. Restriction of sleep in healthy subjects during night periods impairs glucose homeostasis and insulin sensitivity (70). Data from mice and human studies indicate that an impaired circadian clock, perturbed sleep, and shifted light-dark patterns increases circulating leukocyte (inflammation), lipid (hyperlipidemia) levels, and atherosclerotic plaques (cardiovascular disease) (71). Additionally, sleep disturbances affect the human immune system. Sleep loss dysregulates the production of numerous proinflammatory cytokines such as interleukin-6 (IL6) and tumor necrosis factor (TNF), and circulating monocytes. Recent findings have revealed that gut microbe-derived mediators (short-chain fatty acids (SCFAs) and bile acids)

Mitochondrial Dysfunction and Insulin Resistance may act as potential signals between the gut microbiota and host circadian communication in metabolism (see Chapter 6). However, the molecular mechanisms underlying how gut microbiota maintain host circadian clocks are still unknown. SCFAs and modified secondary bile acids are two groups of metabolites that also oscillate and influence host circadian rhythms. Mice with genetic mutations in the genes Bmal1 and Per1/2 display significantly altered microbial populations and loss of rhythms in specific microbial populations (72). Gut microbes are also implicated in driving host molecular rhythms, as germ-free mice show completely different suprachiasmatic nuclei (SCN) and hepatic transcriptional patterns, predominantly in core circadian and metabolic pathways. Fecal samples from full-body knockout Bmal1 mice lack rhythmicity in SCFA levels. Additionally, jet-lagged mice treated with SCFA adapted faster to a new light-dark cycle, indicating that SCFAs can potentially reset the central clock (73). Bile Acids (BA) are another major group of metabolites that have a role in gut microbial and circadian regulation, which is described above in Section 8.2.4.2.4. The primary BA is synthesized in the liver and circulates to and from the intestinal tract to enable nutrient digestion and absorption. BAs are significant regulators of metabolic pathways via activation of nuclear hormone receptors, such as the farnesoid X receptor (FXR), and membrane receptor TGR5 (74, 75). Although most primary BAs, conjugated or unconjugated, are reabsorbed back into circulation, some escape absorption and are metabolized by colonic gut bacteria and transformed into secondary BA. Microbial modifications of host-derived BAs influence circadian gene expression (76). Core circadian clock genes regulate several vital enzymes in BA synthesis. In mice, both primary and secondary BAs vary significantly and peak toward the end of the dark phase, whereas unconjugated BA levels peak during the light phase (77). Analogous patterns were also observed in liver BA levels, suggesting that this particular microbial influence has a profound effect on metabolic organs and peripheral clocks. Potential perturbations to either BA synthesis or gut microbes could significantly influence host metabolic health. As discussed above, several systemic physiological functions are not transmitted out by a single organ but are instead the consequence of different inputs and outputs of many tissues. Imbalance of synchrony of inter and intra-organ may lead to the pathogenesis of metabolic diseases. In this perspective, approaches to improve orientation between the sequences of wake-sleep and feeding-fasting may improve physiological processes such as appetitive behavior, glucose homeostasis, lipid metabolism, and inflammation. Works to scrutinize the molecular intermediaries that coordinate circadian patterns and metabolic systems may improve therapeutics and protective interventions.

8.2.4 Metabolism of Macronutrient Substrates and Insulin Resistance Different macronutrients (glucose, fatty acids) are metabolized differently for energy production (Figure 8.15). Insulin resistance causes loss of metabolic plasticity, which often refers to the ability to switch between glucose and lipid oxidation.

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FIGURE 8.15  Influence of metabolism of different nutrients on mitochondrial stress. Source: adapted from (80).

However, under conditions of prolonged restriction of carbohydrate availability, ketones provide an alternative fuel for systemic tissues with a high metabolic demand. Under these circumstances, adipose tissue lipolysis delivers fatty acids to the liver where the acetyl CoA derived from these fatty acids is converted to ketone bodies. These ketone bodies, particularly beta-hydroxybutyrate and acetoacetate, circulate to the brain, skeletal and cardiac muscles where they are taken up into the cells and metabolized in mitochondria. The notion of ketone bodies as a “superfuel” is premised on their bioenergetic efficiency in terms of the amount of ATP produced per molecule acetyl CoA donated to the mitochondria in comparison to that derived from fatty acids or glucose (78), as well as a higher ATP produced per O2 consumed (P/O ratio) versus other nutrient substrates (79). While the decrease in calorie intake in the setting of ketosis appears to be the prime driver of metabolic benefits in humans, this effect is an integral function of the increased metabolic efficiency of ketone body bioenergetics. Fundamentally, these effects are rooted in the increased redox gradient generated along the electron transport system. While it is important not to conflate metabolic flexibility with ketogenic diets, the associated weight loss with these diets contributes to improved insulin sensitivity and thus metabolic plasticity. Further, it is also important not to conflate ketogenic with time-restricted diets, the latter inducing improved diurnal circadian metabolic physiology, including both insulin secretory patterns and peripheral insulin signaling. It follows that this strategy appears to be critical for physiological metabolic flexibility. Below, we provide short discussions of the distinctions and overlaps between intermittent fasting, ketogenic diets, timerestricted diets, and caloric restriction diets. These diet types have different risks and benefits.

8.2.4.1 Cellular Lipid Deposition, Mitochondrial Dysfunction, and Insulin Resistance All patients with type 2 diabetes mellitus have a degree of insulin resistance. Insulin is a small polypeptide hormone secreted by pancreatic β-cells when they sense an increase in plasma glucose. Broadly considered, one of the core actions of insulin is promoting energy storage. Insulin stimulates glucose uptake in peripheral tissues such as skeletal muscle, and adipose tissue while also promoting glycogen synthesis in these tissues and the liver. Insulin can also promote lipid synthesis, shifting energy stored as sugars into a more dense storage form of triglyceride. And, as insulin is released in response to a rise

346 in glucose concentration, part of the coordinated action of insulin is suppressing hepatic glucose production. When insulin action is impaired, as in insulin-resistant states, the dampened relationship between insulin concentration and glucose disposal taxes the β-cells to produce more insulin to overcome insulin resistance. In some individuals, the gradual reduction in insulin secretion gives way to hyperglycemia and the other features of diabetes. Genetic predisposition, obesity, sedentary lifestyles, and advancing age are some causes of insulin resistance (81, 82). In nearly all these scenarios, there is the accumulation of bioactive lipid species in insulin-resistant tissues. Under experimental conditions, the infusion of lipids can induce skeletal muscle insulin resistance by driving the accumulation of bioactive lipid species (e.g. sn 1,2 diacylglycerol, DAG) in monocytes. DAGs activate a family of kinases, the novel protein kinase C isoforms, which then impair insulin signaling. In patients, skeletal muscle lipids can also accumulate when substrate delivery exceeds oxidative capacity. For example, defects in mitochondrial fatty acid oxidation cause the accumulation of DAGs in the monocytes, which can cause insulin resistance (43).

8.2.4.2 Role of Intracellular Fatty Acid Metabolites in Insulin Resistance As discussed in Chapters 1 and 7, mitochondria are critical for maintaining cellular homeostasis. Glucose and lipid metabolism homeostasis is tightly regulated by intracellular pathways regulated by endocrine hormones (insulin, glucagon, glucocorticoids, etc.) and cellular “energy sensors” (AMPK, sirtuins [SIRT], O-linked N-acetyl glucosyl transferase [OGT], and mechanistic target of rapamycin [mTOR]). Hormonal, neural, and metabolite signals orchestrate interorgan communication between the liver, skeletal muscle, and adipose tissue to ensure whole-body glucose and lipid homeostasis. The development of insulin resistance is associated with disruption of these intracellular and interorgan pathways aggravating metabolic imbalances and fueling the development of more severe metabolic disease (i.e. diabetes mellitus, hyperlipidemia, etc.) with associated comorbidities (i.e. atherosclerosis). There is reasonable agreement that ectopic bioactive lipids can impair insulin signaling and lead to insulin. However, multiple mechanisms have been advanced to account for ectopic lipid accumulation. One is the dysfunction of mitochondrial metabolism owing to excess ROS generation. However, there is still debate going on whether mitochondrial dysfunction is a cause or a consequence of insulin resistance (81). Additional techniques to quantify mitochondrial function and assess mitochondrial quality in vivo are needed to better resolve this issue. However, it is very much clear that insulin resistance causes mitochondrial defects. With defective mitochondria, elevated lipid accumulation and FAO might further complicate the disease state. A growing body of evidence indicates that adipose tissue-derived cytokines can influence insulin signaling and liver and muscle cells’ function. Despite that, compelling evidence suggests that even free fatty acids or their intracellular fatty acid-derived intermediates such as diacylglycerol (DAG) or ceramides play a critical role in modulating insulin signaling.

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8.2.4.3 Fatty Acid Metabolism, Mitochondrial Function, and Insulin Resistance Over fifty years ago, Dr. Philip Randle and colleagues demonstrated an association between abnormal fatty acid metabolism and insulin resistance. Working with diaphragmatic muscle, they demonstrated that incubation with fatty acids enhanced fatty acid oxidation but inhibited two key enzymes of glycolysis (pyruvate dehydrogenase [PDH] and phosphofructokinase [PFK]). Specifically, the rise in acetyl CoA and NADH with fatty acid oxidation inhibited PDH. The increase in cellular citrate inhibits PFK. And the increase in G6P presumably inhibited hexokinase. Ultimately these changes would inhibit cellular glucose uptake. Though this may be operative to some degree in specific muscle types, in skeletal muscles, the primary defect in insulin-resistant states is one of impaired translocation of the GLUT4 transporter and less impairment in glucose oxidation. Though the Randle Hypothesis may not be a full mechanistic explanation for the development of insulin resistance in obese states, a core tenet remains true in that availability of fatty acids promote fat oxidation. Fatty acids are an important source of energy for most tissues. Fatty acid oxidation generates many more reducing equivalents (NADH and FADH2) than glucose or any other substrate. Fatty acid oxidation produces a large amount of ATP, making it well-suited for tissues with high energy demands, such as cardiomyocytes and skeletal muscle. Simplistically, the direct relationship between fatty acid availability and oxidation may actually prevent ectopic lipid accumulation, to a degree. However, fatty acid oxidation imposes a huge burden on the electron transferring capacity of the mitochondrial ETS. This may lead to altered redox potential across the mitochondrial membrane, resulting in ROS generation (Figure 8.16). ROS can have several beneficial effects on the cell at physiological levels (increases β-cell insulin secretion, decreases hepatic gluconeogenesis, and stimulates adipocyte lipid synthesis). On the other hand, pathologically elevated ROS levels can damage the mitochondrial oxidative phosphorylation system. These examples show that fatty acid oxidation can simultaneously be beneficial (preventing the accumulation of ectopic lipids) and detrimental (damaging mitochondria) in metabolic homeostasis and disease progression.

8.2.4.4 Influence of Timing and Fuel Selection on Metabolic Flexibility and Mitochondrial Function The cell can shift from one metabolic pathway to another based on the availability of various substrates. Choosing the right fuel (substrate) at the right time highlights the concept of “metabolic flexibility”. Any impairment or imbalance in this ability of cells may lead to the incomplete metabolism of a specific substrate, which can be harmful to the cell. It is increasingly clear that obesity and type 2 diabetes negatively influence nutrient-induced substrate switching (metabolic flexibility); a phenomenon is otherwise known as ‘‘metabolic inflexibility”.

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FIGURE 8.16  Interrelationship between fatty acid oxidation, mitochondrial dysfunction, and insulin resistance. The balance between uptake and utilization of lipids (fatty acids) is perturbed under the condition of insulin resistance. This causes oxidative stress and mitochondrial dysfunction in skeletal and cardiac myocytes, hepatocytes, and large vessel endothelial cells (coronary arteries). Lipid metabolism generates intermediates, such as diacylglycerol (DAG) and ceramide, which inhibit insulin signaling. β-oxidation of fatty acids reduces the NADH/FADH2 ratio from 5:1 to 2:1. This causes enhanced electron flow in the electron transport system, mediated by increased electron transferring FADH2 redox equivalents from acyl CoA dehydrogenase to electron transferring flavo-protein (ETF) and to coenzyme Q (CoQ). This causes the CoQ pool to be over-reduced, resulting in a change in membrane redox potential to lower than that of Complex I, hence favoring reverse electron transport (RET). During RET, electrons leak at either ETF or ETFQO, as well as Complex I and III, generating a significant amount of superoxide. (Solid lines represent increased flux over the dotted lines). *DAG = diacylglycerol, ETF = electron transferring flavoprotein, ETFQO = ETF coenzyme Q dehydrogenase.

Timing is one factor that greatly influences the metabolism of nutrients and mitochondrial function (83). For example, nocturnal eating leads to the enhanced conversion of glucose into triglycerides, which are eventually stored in adipose tissue. This is a growing area of research and the exact mechanism underlying metabolic inflexibility has yet to be elucidated. However, it is evident from existing studies that impairment in mitochondrial fuel selection may be insulin-independent and may cause impaired systemic glucose disposal (84–86). One strategy to restore mitochondrial metabolic flexibility is to manipulate the diet. Diets such as the ketogenic diet have been promoted as a way to improve metabolic health (see Chapter 1, Section 1.8 for a detailed discussion about the ketone body metabolism and mitochondrial function). Although there does appear to be controversy, there remains powerful literature and proponents of ketogenic states as metabolically favorable (78, 87). There is the argument that it takes approximately five days to mount significant ketosis (levels of ~6 mm/L). Veech and others propose that this is due to the long duration of carbohydrate restriction, and thus ketogenic diets, required to confer metabolic benefits, ketone body salts have more practical use. The idea is that ketone bodies “trick” the body into thinking it is in a state of starvation, thereby promoting increased total body

fatty acid oxidation, weight loss, associated improvements in insulin signaling, as well as enhanced cognitive functioning and physical endurance due to the metabolism of the ketone bodies themselves. That said, there is also data demonstrating that ketone bodies promote insulin resistance and related inflammation (88). Physiologically, it should be noted that insulin resistance is purposed to promote adipose tissue lipolysis, liberating fatty acid substrates to maintain ketogenesis, particularly for the brain, which cannot utilize fatty acids as a fuel source. Increased hepatic glucose output may also result in hyperglycemia. This metabolic milieu has been referred to as “pseudo-diabetes”. It should be noted that roughly a week of starvation, maximum ketosis is approached (levels ~10 mm/L), at which levels insulin secretion and signaling are upregulated, presumptively to plateau of adipose tissue lipolysis, thus preventing pathological elevations in ketone body levels (89). There is some data that despite weight loss, body fat is not lost with ketogenic dieting (88). There are also reports that energy expenditure is quite minimal, and calorie consumption is actually increased (90, 91). In summary, while potential metabolic benefits of physiological ketogenic states are compelling, it is becoming increasingly clear that they are nuanced, and the denouement of these niceties has more that remains to be understood.

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8.2.4.5 Is Mitochondrial Dysfunction a Cause or Consequence of Insulin Resistance? The ongoing debate over whether mitochondrial dysfunction is a cause or a consequence of insulin resistance is taking center stage and sparks a new paradox. Experimental evidence supports the hypothesis of ectopic fatty acid accumulation causing insulin resistance, though the exact mechanisms remain debated. Studies in obese humans show changes in mitochondrial function. The capacity of skeletal muscle to oxidize fat is comparatively lower in obese than to lean subjects, making it harder for obese patients to lose weight. Poor fat oxidation in skeletal muscle is correlated with mitochondrial dysfunction in obese and diabetic patients. Similarly, studies in aged patients with insulin resistance show suppressed mitochondrial substrate flux and ATP synthesis in skeletal muscle. These studies are correlational and do not prove that one condition causes the other. Pioneering studies from the Shulman and Roden groups have led to the proposal that insulin resistance is associated with defective mitochondria in skeletal muscle, especially in lean insulin-resistant offspring of patients with type 2 diabetes (44, 45, 92, 93). These defective mitochondria have abnormal oxidative metabolism, which prevents fatty acid oxidation, and instead diverts fatty acids to produce diacylglycerols (DAGs) and ceramides. Buildup of DAGs and ceramides interfere with insulin signaling. In particular, recent studies have implicated the accumulation of sn 1,2 diacylglycerol in the plasma membrane as the primary “pathogenic” DAG that activates PKCε (94). These are considered to be the lipogenic DAGs, intermediates of triacylglycerol synthesis. In contrast, lipolytic species (e.g. sn 1,3 DAGs) do not appear to be closely linked with insulin resistance. Moreover, DAGs that accumulate in other cellular organelles (e.g. lipid droplets) also do not appear to account for insulin resistance (95). DAG-mediated activation of PKCε impairs insulin receptor activation by phosphorylating a specific threonine residue and diminishing insulin receptor’s own kinase activity (96, 97). This ultimately limits the ability of insulin to regulate intracellular pathways that promote energy storage. It is possible that this mechanism of lipid-induced insulin resistance is an adaptive mechanism that diminishes insulin’s anabolic effects in times when the body becomes increasingly reliant on lipid metabolism (e.g. fasting and even starvation). In this setting, insulin resistance would presumably preserve glucose for brain metabolism. However, in modern societies, the surplus of nutrient availability in relation to the decreased caloric demands leads to obesity, dysfunctional adipocytes, and a maladaptive activation of these pathways that contributes to hyperglycemia.

SIDEBAR 8.12: ARE INSULIN RESISTANCE AND ALTERED MITOCHONDRIAL FUNCTION A DEFECT OR ADAPTATION? The early stages of insulin resistance should not be considered a deficiency. At these stages, insulin resistance may be an adaptive response to excess insulin secretion to prevent hypoglycemia or uptake of excess lipids beyond

Metabolism and Medicine the cellular storage capacity (59). The essential difference between insulin resistance in a healthy vs insulin-resistant individual is that, in the latter case, insulin resistance is chronic, having lost its circadian diurnal cyclicality. In these insulin-resistance individuals, circadian diurnal cyclicality is no longer synchronously coordinated with total body metabolic physiology (59). However, persistence of the underlying pathological stress drives altered mitochondrial function, same as it does with insulin resistance, towards dysfunction. Pathological nutrient or metabolic stress drives the alteration of mitochondrial function (99). In the same vein, altered mitochondrial function is not necessarily maladaptive, but rather often an adaptation. At high levels of prolonged pathological stress, however, what began as an adaptive response can transition into dysfunction. At this threshold, beyond the physiological range of reactive oxygen species (ROS) functioning as signaling molecules, widespread degradation of the molecular fidelity of mitochondria can occur (46). Altered mitochondrial function no longer becomes adaptive in this setting. Taken together, the state of dysfunctional mitochondria equates to a compromise in energy production and/or redox status of the cell. However, from the perspective of a renowned research scientist, Barbara Corkey, most studies that attribute changes in ATP production to dysfunctional mitochondria do not actually measure any defects in mitochondrial energy production adaptation (personal communication). ROS levels illustrate the idea of hormesis. ROS are important signaling molecules when at physiological levels (100). Too low or high ROS is pathological. Similarly, mitochondrial alterations lead to changes in ROS levels, which also demonstrate hormesis; ROS within physiological ranges are adaptive, whereas too far left or right on the bell-shaped curve is pathogenic. There is controversy regarding the idea that mitochondrial dysfunction is the root cause of insulin resistance (80). A limitation of the mitochondrial dysfunction hypothesis is the assumption that anything below maximal oxidative phosphorylation is a disease state. Oxidative phosphorylation is highly dependent on the energy demand (energy utilized to support the basal activity of the mitochondrial respiratory system and for ATP regeneration). Mitochondria in most cells probably do not run at maximal capacity, so this assumption that mitochondrial dysfunction causes insulin resistance is not compatible with the principles of bioenergetics. Simply, lower rates of substrate flux or ATP synthesis measured in resting conditions are not signs of mitochondrial dysfunction. Further conflicting with this hypothesis, those with diabetes and obesity have sufficient mitochondrial supply to produce enough energy via increased substrate flux and ATP synthesis. And, some have shown that increased mitochondrial function, not decreased, is linked with metabolic diseases such as NAFLD (101). Studies in animal models show that rodents fed a high-fat diet increase muscle capacity to catabolize lipids via upregulation of key mitochondrial enzymes (80, 102, 103). Despite these favorable

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Mitochondrial Dysfunction and Insulin Resistance adaptations that facilitate fatty acid oxidation, the high-fat diet still results in ectopic lipids accumulation and eventual reductions in mitochondrial oxidative capacity (104). These findings suggest that mitochondrial dysfunction might be a consequence of insulin resistance.

8.2.5 Future Perspectives As mitochondria play crucial roles in both cell survival as well as in cell death, they hold a great significance in physiology as well as in pathophysiology. Beyond “energizing” cells by metabolizing varied macronutrients to derive ATP, mitochondria are also responsible for numerous other non-metabolic functions such as ROS generation and signaling, phospholipid transfer, Ca2+ homeostasis, programmed cell death as mentioned, and cell proliferation and survival. Any spatial or temporal alterations that lead to abnormalities or mitochondrial structure and function, metabolic or otherwise, can lead to profound changes in cellular metabolism that eventually result in the causation or exacerbation of various metabolic disorders and syndromes. Impaired mitochondrial dynamics, defective mitochondrial biogenesis, and oxidative stress-induced mitochondrial dysfunction for instance are believed to cause the development or worsening of accelerated or premature aging, stroke, ischemia, hypertension, diabetes, dyslipidemia, obesity, heart disease, and neurodegenerative disorders. As discussed earlier, once mitochondrial respiration starts to decline due to the excess burden of electrons coming from glucose and lipids, a cell’s capacity to metabolize nutrients diminishes significantly causing the accumulation of harmful intermediate species. If cells fail to recover from this oxidative assault, symptoms of metabolic abnormalities start to appear at a systemic level. Therefore, targeting mitochondrial metabolism offers an excellent therapeutic strategy for the management of many metabolic diseases. Recently, different approaches have demonstrated useful management of metabolic syndromes. These range from lifestyle interventions (exercise and healthy and balanced diet) to pharmaceutical strategies focused on molecular targets of the mitochondria. It may be possible to promote increased mitochondrial function by inducing a degree of mitochondrial inefficiency with targeted mitochondrial uncoupling agents. These agents dissipate the chemical protein gradient created by oxidative metabolism in the mitochondria as heat, allowing for greater lipid oxidation. While systemic exposure to uncoupling agents can be extremely toxic (i.e. hyperpyrexia), modifying delivery using controlled-release formulations may preferentially target these agents to the liver and could emerge as a useful tool to treat nonalcoholic fatty liver disease (105). More work is needed to understand the therapeutic uses and limitations of this class of agents. Indeed, there is renewed attention towards the development of different therapeutic strategies and treatment options for metabolic diseases, inspiring future research into the understanding of mitochondria’s non-canonical roles. Perspectives along these lines will broaden our understanding of the connections between mitochondrial dysfunction and impairment in other cellular processes and lead to the development of new possibilities for metabolic disease management. There are still some unanswered questions that must

be addressed to understand the pathophysiology of metabolic diseases and accomplish these treatment goals. 1) Molecular links between metabolic diseases and structural/functional changes in mitochondria are not well understood. 2) Genetics and genetic susceptibility of patients with age-related metabolic syndromes are poorly understood. 3) The role of environmental factors and epigenetics in metabolic syndromes needs to be studied. How mitochondria respond to environmental factors is essential to understand their role in pathophysiology. 4) There is likely significant physiological heterogeneity in patients that develop similar metabolic diseases. Treatments may be tailored to address these different pathogenic pathways.

8.3 Chapter Take-Home Messages • Metabolism is a strong indicator of health or disease in individuals.Metabolic rates of individuals as functions of weight over time could becomea diagnostic tool for the onset and progression of diseases. Conversely, areturn to more efficient bioenergetic metabolism could be prognostic ofhealing processes taking hold. • Mitochondrial health determines bioenergetic metabolism efficiency.Mitochondria transform energy within the cell to ATP, the biologicalcurrency of energy. Clinical assessment of aerobic mitochondrial functionduring a stress test may have predictive value for premature chronic diseaseand mortality. • Aging and its associated diseases can be viewed as a result ofmitochondrial dysfunction over time. The production of free radicals,resistance to insulin, and metabolic inflexibility put our bodies at riskfor cumulative damage to all body systems, leading to an inevitable declinein function. • Vitamins, supplements, and medications can help optimize mitochondrialfunction; however, science has not yet discovered interventions as potent ashealthy eating and exercise for metabolic health and longevity. • Minerals are critical for mitochondrial function, redox balance, andinsulin sensitivity. Excess or deficiency in minerals can bepathological. • Besides ATP, mitochondria make metabolic building blocks for lipids,proteins, DNA, and RNA, as well as byproducts such as ROS and ammonia. Mitochondria also act as biosensors and are able to mediate cellularadaptations to lack of nutrients, oxidative stress, DNA damage, andendoplasmic reticulum stress through cell signaling processes, such asnecrosis, apoptosis, autophagy, mitoptosis, and mitophagy.

350 • Mitochondrial ATP production uses glucose and fatty acids as fuel sources.Oxidation of glucose is metabolically the most efficient (highest amount ofATP produced, generating the least amount of ROS). During insulinresistance, glycolytic metabolism of glucose in the cytosol is inhibitedfrom completing its full oxidative combustion in the mitochondria. This is amechanistic hallmark for how insulin resistance contributes to bioenergeticand redox stress. • Mitochondria biogenesis naturally declines with aging. The full extent ofdysfunctional mitochondria on aging and metabolic health remains to beinvestigated. • Mitochondrial dysfunction impairs lipid oxidation, leading to ectopiclipid accumulation in skeletal muscle, and ultimately, a loss of metabolicflexibility (switching to the classical mode of energy production).Consequently, glucose metabolism (glycolysis) and mitochondrial energymetabolism (oxidative phosphorylation) are uncoupled. • Mitochondrial dysfunction throws off metabolism’s circadian rhythm,resulting in lipid fatty acid oxidation occurring during the daytime feedingperiod instead of the nighttime fasting period. Daytime fatty acid oxidationis a hallmark of insulin resistance. • Overconsumption causes mitochondrial dysfunction, which subsequentlycauses insulin resistance and ultimately, disease. In addition to excessivefood intake, alterations in circadian patterns of eating and sleepingbehavior, changes in lifestyle activity, infection, and mental stress canalso impair lead to the development of metabolic diseases. • Insulin resistance causes loss of metabolic flexibility, which oftenrefers to the ability to switch between glucose and lipid oxidation.However, under conditions of prolonged restriction of carbohydrateavailability, ketones can provide an alternative fuel for systemic tissueswith a high metabolic demand. While potential metabolic benefits ofphysiological ketogenic states are compelling, it is becoming increasinglyclear that they are nuanced, and the denouement of these niceties has morethat remains to be understood. • Mitochondrial dysfunction and insulin resistance are essential in thedevelopment of chronic diseases of aging. Both conditions are major healthproblems. The idea that mitochondrial dysfunction is the root cause ofinsulin resistance is controversial. • Targeting mitochondrial metabolism offers an excellent therapeuticstrategy for the management of many metabolic diseases. These strategiesrange from lifestyle interventions (exercise and healthy and balanced diet)to pharmaceutical strategies focused on molecular targets of themitochondria.

Metabolism and Medicine

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9 Chronic Diseases of Aging as Metabolic Disorders

Abbreviations 2-DG 3BrP AMPA

2-deoxy-glucose 3 bromopyruvate α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid ACC acetyl CoA ALL acute lymphoblastic leukemia ADP adenosine diphosphate ATP adenosine triphosphate ATGL adipose triglyceride lipase AGE advanced glycation end product AD Alzheimer’s disease AMPK AMP-activated protein kinase Aβ amyloid beta ALS amyotrophic lateral sclerosis ApoB apolipoprotein B APOE-ε4 apolipoprotein E epsilon 4 APE1 apurinic/apyrimidinic endonuclease 1 ASS1 argininosuccinate synthetase 1 ACL ATP citrate lyase ANP atrial natriuretic peptide BCL-2 B-cell lymphoma 2 BVR biliverdin reductase BMI body mass index BNP brain natriuretic peptide BAT brown adipose tissue CVD cardiovascular disease CPT1 carnitine palmitoyltransferase 1 CNS central nervous system CESD cholesterol ester storage disease CoA coenzyme A CRC colorectal cancer DAMP damage-associated molecular pattern DNL de novo lipogenesis ETS electron transport system ER endoplasmic reticulum ELAM endothelial leukocyte adhesion molecule ET-1 endothelin-1 EGCG epigallocatechin-3-gallate ERK extracellular-signal-regulated kinase FA fatty acid FAS fatty acid synthase FDG fluorodeoxyglucose FFA free fatty acid GABA γ-aminobutyric acid GBM glioblastoma multiforme GLP-1 glucagon-like peptide-1 receptor DOI: 10.1201/9781003149897-9

GLUT1 GSK3 GRB-2 GDP GTP HAT HDAC HSL HPA axis HIF-1α IGFBP-1 Pi IDE IRS IDH LDH LDHA LDL-C LDLR LRP LMF LRP LXR LDL M-CSF MMP MAP Mt mPTP MAPK MCP-1 MI NMDA NLR NO NOS NSAID NHR Ox-LDL PRR PCI PGC1α PPARγ PPAR PTEN PI3K

glucose transporter 1 glycogen synthase kinase 3 growth factor receptor-bound protein 2 guanosine diphosphate guanosine-5'-triphosphate histone acetyltransferase histone deacetylase hormone-sensitive lipase hypothalamic pituitary adrenal axis hypoxia inducing factor 1 α IGF-1 binding protein 1 inorganic phosphate insulin-degrading enzyme insulin receptor substrate isocitrate dehydrogenase lactate dehydrogenase lactate dehydrogenase A LDL cholesterol LDL receptors LDL receptor-related protein lipid mobilizing factor lipoprotein receptor-related protein liver X receptor low-density lipoproteins macrophage colony-stimulating factor matrix metalloproteinase microtubule-associated protein mitochondria mitochondrial permeability transition pore mitogen activated protein kinase monocyte chemotactic protein-1 myocardial infarction N-methyl-D-aspartate NOD-like receptor nitric oxide nitric oxide synthase non-steroidal anti-inflammatory drug nuclear hormone receptor oxidized-LDL pattern recognition receptor percutaneous coronary intervention peroxisome proliferator activated coactivator 1α Peroxisome proliferator activated receptors gamma peroxisome proliferator activated receptor phosphatase and tensin homolog phosphatidylinositol 3-kinases

355

356 PIP3 PFK PET PCSK9 PKB PKC PP2A PDC PKM2 ROS RAGEs RCT SIRT1 SMC SOS SCD SAT SDH SCO2 TZD TLR TCA cycle TG TRL TIGAR T2D UPR VCAM-1 VEGF VSMC VLDL WAT SCRF/AICR

Metabolism and Medicine phosphatidylinositol (3,4,5)-trisphosphate phosphofructokinase positron emission tomography proprotein convertase subtilisin/kexin type 9 protein kinase B protein kinase C protein phosphatase 2A upregulation pyruvate dehydrogenase complex pyruvate kinase M2 reactive oxygen species receptors for advanced glycation end products reverse cholesterol transport sirtuin1 smooth muscle cell son of sevenless protein stearoyl-CoA desaturase subcutaneous adipose tissue succinate dehydrogenase synthesis of cytochrome c oxidase 2 thiazolidinedione toll-like receptor tricarboxylic acid cycle triglycerides triglyceride-rich lipoprotein TP53-induced glycolysis and apoptosis regulator type 2 diabetes unfolded protein response vascular cell adhesion molecule vascular endothelial growth factor vascular smooth muscle cells very low-density lipoprotein white adipose tissue World Cancer Research Fund and American Institute of Cancer Research

Chapter Overview This book’s primary aim has been to provide a fresh new perspective on biological systems and human physiology, especially related to metabolism and metabolic diseases, drawing largely on modern concepts in physics and information sciences. The final chapter is dedicated to the discussion of how the interwoven nature of mitochondrial dysfunction and insulin resistance (see Chapter 8) contribute to the progression of chronic diseases of aging such as cancer, Alzheimer’s disease, and cardiovascular disease. Taking into consideration other parameters such as the stress response, gut microbiota, circadian rhythms, immune responses, and bioenergetics, these diseases are discussed and presented as metabolic disorders. Finally, we propose a new model for personalized precision medicine utilizing the Physiological Fitness Landscape (PFL). Cancer is approached as a metabolic disease and discussed in the context of insulin resistance, bioenergetics, and metabolic flexibility. Therapeutic approaches such as dietary alterations including calorie restriction, fasting, and ketogenic diets

as well as the use of pharmaceuticals like metformin and NSAIDs are also detailed within this chapter. Alzheimer’s can likewise be seen as a metabolic disorder due to the high energy demands of the brain and its resultant sensitivity to mitochondrial dysfunction. We outline how disruption in mitochondrial efficiency promotes insulin resistance and affects nerve cells leading to such neurodegenerative disorders and associated cognitive impairments. Cardiovascular disease and cardiomyopathy are also associated with insulin resistance, obesity, and metabolic inflexibility and are examined as metabolic disorders here. This chapter concludes with the proposal of a new model of medicine: the Physiological Fitness Landscape. The significance of control and order parameters and the function of the PFL in creating a map to the restoration of health are discussed in detail. We emphasize the most important factors in maintaining a healthy life: vitalizing stress, diverse microbiota, proper chronophysiology, acid-base balance, redox homeostasis, and a healthy regimen of exercise and diet that keeps inflammation at bay. Altogether, we show how physical science can inform medicine.

9.1 The Role of Metabolism in the Chronic Diseases of Aging 9.1.1 The Relationship of Mitochondrial Dysfunction and Insulin Signaling in Metabolic and Chronic Diseases of Aging As discussed in Section 9.3, mitochondrial dysfunction is a significant feature of insulin resistance. On the other hand, evidence from animal studies also suggests that mitochondrial dysfunction might be a root cause of insulin resistance. Due to the bidirectional relationship between insulin resistance and mitochondrial dysfunction, it becomes relevant to target mitochondria to possibly treat metabolic disease states such as obesity, prediabetes, and type 2 diabetes mellitus. Both parameters have additional connections to chronic disease states of aging, including cancer, dementia, and cardiovascular disease, further deepening their association. Consistent with control parameters (potential stressors, e.g. physical or mental stress or disturbances in circadian cycling), those that govern human health and chronic disease can be antithetical in their systemic effects. Concerning insulin tolerance and mitochondrial functionality, for example, nutrient excess can cause metabolic inflexibility, which eventually can provoke the pathological web of insulin resistance and mitochondrial dysfunction. Conversely, calorie restriction can enhance mitochondrial metabolic flexibility and insulin sensitivity, when perhaps the reverse may seem more logical. Due to its role in redox reactions the function of mitochondria declines with the passage of time (age). In response, cells initiate mitophagy, a program that selectively degrades defective or nonfunctional mitochondria and can subsequently replace these mitochondria through mitochondrial biogenesis. This cellular program is crucial for maintaining metabolic homeostasis and any defect either in the clearance of defective mitochondria or in mitochondrial biogenesis could lead to

Chronic Diseases as Metabolic Disorders the development of metabolic disease. External control parameters of fasting, calorie restriction, and/or exercise, regulate cellular energy sensors such as AMP-activated protein kinase (AMPK) and sirtuin1 (SIRT1). These sensors elicit both spatial and temporal metabolic as well as molecular reprogramming to maintain homeostasis. Moreover, these sensors signal through peroxisome proliferator-activated coactivator 1α (PGC1α) in concert with various transcriptional activators to promote mitochondrial biogenesis (Figure 9.1). Mechanistic relationships between these control and signaling parameters in the context of pathways and networks were discussed in detail in the chapter on the biology of time. While in a low energy setting, the body is pressured to maximize the efficiency of energy production. This can be achieved in resting cells through the use of mitochondrial oxidative phosphorylation, a highly efficient process capable of producing up to 32 molecules of ATP per molecule of glucose. Glycolysis, in comparison, is a cytosolic process of lower efficiency that produces just two net molecules of ATP per molecule of glucose. If the body is in an alternative setting of excess energy from the diet, the use of mitochondrial oxidative phosphorylation can compromise overall mitochondrial function. This results in pathological accumulation of reactive oxygen species, causing redox modifications of mitochondrial and other cell structures. In addition to any decline of mitochondrial structure and function, the body’s capacity to generate free energy trapped in the unstable bonds of ATP is diminished. This energy is required for the continued functionality of each cell individually and the integrated physiological components of the whole body.

357 The above represents an example of self-amplifying deterioration, a zone of instability inherent to certain feedforward processes within an overall physiological fitness landscape. To reiterate, redox stress impairs mitochondrial function which, in a self-reverberating cycle, further exacerbates redox stress. With each cycle, the rate of entropy production accelerates while free energy availability declines. In the natural course of chronic pathophysiology, this relationship is not linear but rather resembles a connected series of hills and troughs to represent the body’s physiological fitness landscape. Per this metaphor, peaks may represent zones of instability, which in this case would be redox-impairment of mitochondrial function with dietary excess. Troughs on the other hand may represent intermittent states of stability. Connecting these two disparate states are inclines and descents that represent energies required to facilitate changes in state. Upward climbs, representing energy barriers to instability zones, can be overcome with the persistence of dietary excess and sedentary lifestyle promoting the reacceleration of redox stress, mitochondrial dysfunction, and entropy production rate. In contrast to low energy states that promote mitochondrial biogenesis, high energy states degrade mitochondrial function. Conditions such as chronic stress can push the system over the peak of these energy barriers, representing allostatic overload. This causes the system to be thrown out of its former state of equilibrium into a new zone of lower stability than before, which signifies the transition to a state of pathology. Fasting, calorie restriction, and endurance exercise are not the only external control parameters of mitochondria biogenesis, as will be described below. Some additional examples include peroxisome proliferator-activated receptor (PPAR)

FIGURE 9.1  AMPK and SIRT1 signaling promotes mitochondrial biogenesis. *AMPK = adenosine monophosphate kinase; DNA = deoxyribonucleic acid; FOXOs = Forkhead family of transcription factors; LKB1 = liver kinase B1; Mt = mitochondria; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NAMPT = nicotinamide phosphoribosyltransferase; PGC1α = peroxisome proliferator activated coactivator 1α; SIRT-1 = sirtuin 1.

358 pan agonist bezafibrate, PPAR agonists including thiazolidinediones (TZDs) and other fibrates, and the Sirtuin stimulant, resveratrol. While much remains to be understood about the relationships connecting mitochondrial dysfunction to insulin resistance, there is one known mechanism that includes partial and impaired lipid oxidation due to impaired mitochondrial function. In this case, mitochondrial dysfunction can lead to the creation of ectopic skeletal muscle reactive lipid species, yielding further reactive oxygen species that disturb insulin signaling. As previously expressed, high energy states degrade mitochondrial function. The induction of mitochondrial dysfunction by dietary excess, as described by Demetrius, occurs above the take-over threshold, the point at which quantum metabolism of ATP production collapses and is taken over by the less efficient classical mode of oxidative phosphorylation (discussed in Volume 1, Chapter 4) (1). Analogously, Brownlee’s Unifying Hypothesis (2005 Banting Award Lecture) described declining mitochondrial efficiency in a more classical sense. The hypothesis contextualized hyperglycemia to promote microvascular disease and insulin resistance to induce macrovascular disease (discussed in Chapter 1, Section 1.9). While Brownlee did not describe the external control parameter of dietary excess per se, the concept of nutrient overload causing redox stress and mitochondrial impairment remains present. Further, hyperglycemia in the case of type 2 diabetes, and non-esterified fatty acids liberated from insulin-resistant

Metabolism and Medicine adipose stores, are direct consequences of the cell’s inability to metabolize glucose and lipids, efficiently owing to perturbed metabolic machinery. In addition to the aforementioned classic control parameters that cause mitochondrial dysfunction and subsequent insulin resistance, this pathophysiology can also be governed by poor quality diet, disturbed circadian behaviors, and the chronic stress response. These alternative control parameters generate redox and inflammatory stress cascades, which may initially provoke either mitochondrial dysfunction or insulin resistance. Nutrient excess may also initially cause insulin resistance by increasing adipose tissue mass, alternatively termed adipocyte hypertrophy. The inflammatory nature of hypertrophied adipocytes within an enlarging adipose mass, systemically seeds inflammatory cytokines that signal to other metabolic tissues, like skeletal muscle where it can interrupt insulin signaling. Moreover, when adipocyte lipid storage capacity is exceeded, the overflow of non-esterified fatty acids into the circulation is potentially taken up by many peripheral tissues as ectopic lipid droplets (2, 3). Unlike lipids stored as neutral triglycerides within adipose tissue, ectopic lipids are often reactive, promoting inflammatory cascades that disturb insulin signaling and consequently mitochondrial function. Additionally, inflammation-generated redox stress may perturb mitochondrial function independent of, as well as interdependent with, inflammation-impaired insulin signaling (2, 3).

FIGURE 9.2  Pathways that promote cancer cell proliferation through hyperinsulinemia. Source: adapted from https​:/​/th​​efast​​ingme​​thod.​​com​/ h​​yperi​​ nsuli​​nemia​​-canc​​er​-​ca​​ncer-​​2/. *AKT = protein kinase B; BAD = B-cell lymphoma 2 agonist of cell death; Bcl-2 = B-cell lymphoma 2; eiF-4E = Eukaryotic translation initiation factor 4E; ELK-1 = E twenty six-like protein 1; ERKs = extracellular-signal-regulated kinases; GRB-2 = growth factor receptor-bound protein 2; IGF-1/2 = insulin-like growth factor 1/2; IGF-1R/2R = insulin-like growth factor receptor 1/2; IR = insulin receptor; IRS = insulin receptor substrate; JNK = c-Jun N-terminal kinases; MAPK = mitogen activated protein kinase; MEK = MAPK/ERK kinase; mTOR = mechanistic target of rapamycin; P = phosphate; P70 = ; PDK1 = phosphoinositide dependent kinase1; PI3K = phosphoinositide 3 kinase; SOS = son of sevenless protein.

Chronic Diseases as Metabolic Disorders

9.1.1.1 The Interdependent Relationship of Obesity, Inflammation, and Insulin Signaling in Cancer Obesity, inflammation, and insulin resistance can each catalyze one another and form an interdependent, self-amplifying cascade. Obesity can lead to the dissemination of pro-inflammatory cytokines making it often an inflammatory state. Dietary saturated fatty acids along with endotoxins from gut microbiota all fuel and further exacerbate inflammation by inducing ER stress-mediated activation and recruitment of proinflammatory immune cells that promote increased visceral adipose tissue. This self-amplifying cascade continues as obesity and inflammation powerfully drive hepatic insulin resistance. Insulin resistance then moves to drive compensatory hyperinsulinemia. Hyperinsulinemia may also be a pancreatic secretory response to food additives that promote a liver-originating redox disturbance. In this circumstance, insulin resistance is a compensatory response. In either case of hyperinsulinemia, the condition creates a favorable environment for the rapid proliferation of cancer cells (Figure 9.2). As described above, insulin resistance may advance subclinical cancers to clinical states, but not malignant transformation or cancer initiation per se. The typical driver of these processes

359 is redox stress resulting in DNA modifications that mediate the mutation of oncogenes or of tumor suppressor genes. In addition, redox stress and inflammation exacerbate each other in a bi-directional and feedforward manner. Under healthy conditions, insulin signaling pathways function to maintain tight control of glucose homeostasis. Failure of these pathways to operate in this optimal way leads to the development of insulin resistance and related pathology. The first major node of insulin signaling within cells is the insulin receptor, which is expressed (by alternative splicing) in two different isoforms: insulin receptor type A (IR-A) and insulin receptor type B (IR-B; Figure 9.3). Hyperinsulinemia promotes the downregulation predominantly of IR-B relative to IR-A. This is important because IR-A signaling tends to favor the pro-growth and survival pathways in the cell (MAPK and mTOR) over the metabolic effects. Further, insulin-like growth factor (IGF)-1 can activate IR-A, but not IR-B. In addition to binding both IR-A and IR-B, insulin can also activate the IGF-1 receptor, further favoring cell proliferation pathways mediated by MAPK and mTOR (Figure 7.20). This helps to explain existing data showing a significant correlation between endogenous hyperinsulinemia and cancer.

FIGURE 9.3  High circulating insulin-like growth factor 1/2 (IGF-1/2) binds to insulin-like growth factor (IGF) receptors and insulin-IGF heterodimers. IR-B signals through metabolic cascades (e.g. IRS-1,2/PI3K/Akt). During hyperinsulinemia, insulin promotes mitogenic and inflammatory signaling. IR-A and IGF-1R, as well as hybrid receptors IGF-1R/IR-A and IGF-1R/IR-B, signal through IRS-1,2/PI3K/Akt and Ras-Raf-MAP kinase pathways and JAK-STAT3 signaling. Activation of these pathways promotes tumor growth. Source: adapted from (4). *ERɑ = estrogen receptor ɑ; ERK1/2 = extracellular signal-regulated kinases 1/2; GFBP = growth factor binding protein; IGF-1 = insulin-like growth factor 1; IGF-2 = insulin-like growth factor 2; IGF-1R = insulin-related growth factor 1 receptor; IL = interleukin; IR-A = insulin receptor type A; IR-B = insulin receptor type B; IRS-1,2 = insulin receptor substrate 1, 2; JAK = Janus kinase; PI3K = phosphoinositide 3-kinases; STAT = signal transducer and activator of transcription proteins; TNFɑ = tumor necrosis factor ɑ.

360

SIDEBAR 9.1: TYPES OF INSULIN AND RECEPTOR AFFINITY Another major consideration is the type of insulin. In the 1990s, clinical development of the rapid-acting insulin analog AspB10 had to be terminated because of the risk for malignancies due to reduced dissociation rate from the insulin receptor and to a higher affinity for the IGF-1R relative to human insulin Neutral Protamine Hagedorn (NPH). Another type of insulin, Glargine, also sparked some concern. Relative to human NPH insulin, Glargine also had a higher affinity for the IGF-1R. However, this potential risk is reduced by the conversion of Glargine to active metabolites that have a lower affinity for the IGF-1R. Exogenous insulin, however, has an insulin-sensitizing effect by improving glucose control due to the reversal of glucotoxicity. As such, there is less downregulation of IR-B and thus less binding to IR-A and IGF-1R. Consequently, there is less induction of MAPK and mTOR signaling and associated protein synthesis, cell growth, and proliferation. Under circumstances of insulin resistance, fatty acids that are continuously liberated from adipose stores compete with glucose as the nutrient substrate required to meet the bioenergetic needs of individual cells and whole-body physiology. An oversupply of circulating fatty acids not only impairs insulin signaling and reduces glucose uptake into metabolic tissues, but it can also exhaust mitochondrial capacity for electron transfer through the process of oxidative phosphorylation, causing mitochondrial dysfunction, redox stress, and consequent insulin resistance. A growing body of evidence suggests that obesity not only promotes the growth of several types of cancers, but is also a common risk factor for developing cancer. Mechanistically, visceral adipose tissues in particular release adipose tissue cytokines, “adipokines”, which have been demonstrated to promote colorectal and breast cancers (5–7). However, obesity as a risk factor for the development of cancer is still unclear. Obese adiposity is engaged with the signaling of one such adipokine, leptin, in a cause and effect manner similar to that between obesity and insulin signaling such that obesity can yield leptin resistance or hyperleptinemia. Leptin itself, directly and indirectly, has independent mitogenic (i.e. cell division inducing) stimulating effects on cancer cells. Leptin imparts its indirect influence by promoting aromatase activity in estrogen-responsive cancer cells such as those of the breast and endometrium. Aromatase, highly present in adipose tissue, converts androgens to estrogens, especially testosterone to estradiol and androstenedione to estrone. As the breast is composed largely of adipose tissue, it becomes a breeding ground for tumor cell proliferation mediated by this pathway. Under these conditions, adipocytes and the infiltrating macrophages produce proinflammatory cytokines IL-1, IL6, and TNFα, which also promote aromatase activity. Additionally, insulin resistance-associated hyperinsulinemia directly suppresses hepatocyte production of sex hormone binding globulin (SHBG), which increases the ratio of free to total estrogen, further contributing to the exacerbation of hormone-dependent cancers. Fortunately, the large majority of clinical breast and

Metabolism and Medicine endometrial cancers, which grow in estrogenic environments, have low resilience and are less aggressive, rendering them treatable and often curable. Another important adipokine in the context of obesity and cancer is adiponectin. Under healthy conditions, adiponectin has anti-proliferative, pro-apoptotic, and anti-inflammatory effects as it inhibits TNFα, which typically activates NFκB to stimulate cell proliferation and promote cell survival. In an obese state, adiponectin secretion is inversely correlated to adipose mass, resulting in a reduction of its secretion. This leads to disinhibition of TNFα, activation of NFκB, and an increase in inflammation. In the absence of adiponectin, circulatory levels of IGF1 become elevated, which promotes cancer cell proliferation. In the case of reduced adiponectin-promoted cell survival, mutagenic effects of inflammation predominantly mediated by redox stress can yield cancer cell initiation via activation of TNFα and NFκB. The proinflammatory effect is a result of the loss of adiponectin inhibition of TNFα and downstream activation of NFκB, the amplifying hub of the inflammatory cascade. The interdependent relationship between obesity, inflammation, and insulin resistance is also linked to the calorie restriction mimetic, NAD+-dependent deacetylase sirtuin-1 (SIRT1). SIRT1 activity is upregulated by low-energy states, such as those resulting from endurance exercise and calorie restriction, and inhibited by oxidative stress, a state promoted by inflammation. This deacetylase appears to exert powerful effects on the health and life spans of all living systems including humans, mediated by its attenuating effects on cell and DNA repair and inflammation, as well as upregulating effects of mitochondrial biogenesis and insulin sensitivity. SIRT1 imparts an anti-inflammatory effect via deacetylation of NFκB and increases insulin sensitivity. Additionally, via the deacetylation of FOXO1, SIRT1 upregulates the transcription of insulin-sensitizing adiponectin. The overall insulinsensitizing effect in concert with the FOXO1 activation of PGC1α synergistically stimulates mitochondrial biogenesis. Furthermore, the positive regulation of mitochondrial structure and function reciprocally enhances insulin sensitivity, generating a feedforward loop. Consistent with the connection of mitochondrial dysfunction and insulin resistance to cancer, SIRT1 provides a mechanistic link for plausibly effective therapeutic strategies such as calorie restriction, intermittent fasting, endurance exercise, and high-dose resveratrol. These SIRT1-activating strategies should prove useful in the prevention of primary and recurrent cancers. Further, it is likely they could be beneficial as adjuncts to conventional cancer therapy. In one paradoxical circumstance, SIRT1 inhibits p53, a tumor-suppressing transcription factor that regulates stress response genes, promotes the induction of apoptosis of cells irreversibly damaged by redox stress, and mediates inhibitory anti-proliferative effects on the cell cycle. Intuitively, SIRT1 inhibition of these p53 functions should suggest a pro-carcinogenic effect, but since SIRT1 serves to prolong the cell cycle by inhibiting p53-induced apoptosis while also inhibiting cell replication, its activation makes successful DNA repair possible. This is consistent with the finding of an anti-oncogenic effect in vivo (8–10). Anti-inflammatory and anti-oxidant modalities are

Chronic Diseases as Metabolic Disorders also intuitively helpful by mitigating oxidative stress, which inactivates SIRT1. Indeed, there is data suggesting anti-cancer effects exerted by aspirin and non-steroidal anti-inflammatory agents (11). Nonetheless, the relationship, as with all potential therapeutic modalities in human disease, is likely to have many nuisances, including patient and cancer type specificity as well as dependence on dose, dosing schedule, and timing.

361 retrograde response also leads to suppression of the apurinic/ apyrimidinic endonuclease 1 (APE1), which causes genomic instability (17). Thus, there are direct lines by which altered mitochondrial metabolism could be a primary cause of cancer development.

9.1.1.2 Quest for the Truth While the issue of the relationships between exogenous insulin and cancer is controversial, it is necessary for all clinicians to keep an open mind to potential risk-benefit ratios. The endogenous and exogenous relationship of insulin to chronic disease is a complex and rapidly evolving area of research. In fact, this is another paragon example of the potential harm in the field of medicine underscoring the dangerous game we may be sometimes playing. By the same token, however, there are also often unforeseen potential benefits of interventions we as physicians can offer; with insulin as a case in point. The model and methodology of the Physiological Fitness Landscape proposed in this book provide a sharper focus on discerning the complexities of these issues, which are recapitulated by numerous biological systems.

9.2 Cancer as a Metabolic Disease? The last century has witnessed some fundamental discoveries in the field of metabolism such as the role of mitochondria in tumorigenesis, which is often a topic of debate. It has long been known that cancers exhibit high glucose uptake; radiologists routinely take advantage of this phenomenon by using glucose analogs, such as 18-Fluoro-2-deoxyglucose, to identify tumors in PET imaging. It was thought that this increased glucose uptake was a simple reflection of the high metabolic needs of cancer cells, which rapidly grow and divide. However, an illustrious discovery by Nobel laureate Otto Warburg threw a metaphoric wrench into the works, when he proposed that cancer cells had an “irreversible” defect in their mitochondrial respiratory chain. Therefore, cancer cells can metabolize glucose into lactate through glycolysis, even in the presence of sufficient oxygen. He further showed that cancer cells had a remarkably similar energy requirement to other cells, despite their rapid growth and proliferation rates (12). Even though he could not prove that cancer cells lack functional mitochondria or that the defect in mitochondrial respiration is a root cause of tumorigenesis, his landmark discovery of aerobic glycolysis is now considered a hallmark of nearly all cancers. Since the discovery of oncogenes and tumor suppressor genes, the idea of tumors as a metabolic disease has taken a back seat. Not until the start of the 21st century did scientists uncover evidence that metabolic alterations can precede and even cause the genomic instability of a cancer cell. The retrograde response describes the effects that altered mitochondrial function has on nuclear gene expression (13–15). In mammals, mitochondrial dysfunction can induce Hif1α and the oncogene Myc, which increase expression of glycolytic enzymes (16), but at the same time may promote tumorigenesis. The

Craig B. Thompson. Source: Rick DeWitt—private correspondence, CC BY-SA 4.0, https​:/​/co​​mmons​​.wiki​​media​​.org/​​w​/ind​​ex​.ph​​p​?cur​​i​d​= 62​​45827​​9.

Research from others, such as that of Dr. Craig B. Thompson’s group, has also modernized the concept of the Warburg effect and contributed greatly to our understanding of how altered metabolism can contribute to cancer formation and pathogenesis. His group has helped to elucidate the roles of growth factor signaling in cancer cell nutrient uptake and metabolism, uncovering the direct mechanistic links between cellular metabolism and cell growth and survival (18, 19). His seminal work has also led to new insights into how intracellular metabolite levels (such as 2-hydroxyglutarate and acetyl CoA) contribute to the regulation of gene expression, cellular differentiation, and oncogenic transformation (20–22), and how TCA cycle enzymes, such as isocitrate dehydrogenase (IDH1 and IDH2), succinate dehydrogenase (SDH), and fumarase play critical tumor-suppressive roles in suppressing HIF1α-mediated glycolysis. Mutations in IDH1/IDH2 genes are associated with various cancer types (21, 23–26). Research from his group has significantly contributed to the growing interest in the field of cancer cell metabolism, which is now being exploited as a target for translational therapies. While metabolic changes may underlie the oncogenic changes in cancer, oncogenic genes can also contribute to an altered metabolic phenotype. In 2006, Karen Vousden and colleagues uncovered the role of the protein TIGAR (TP53induced glycolysis and apoptosis regulator) in glucose regulation (27). TIGAR, as its name suggests, is induced by tumor suppressor protein p53, which itself is activated by a variety of cellular stressors, such as radiation, hypoxia, and DNA damage. Once activated, TIGAR suppresses glycolysis in cancer cells by decreasing the level of fructose-2,6-bisphosphate, which is required for the activation of the rate-limiting enzyme phosphofructokinase (PFK), thus blocking glycolysis at this step. TIGAR-mediated inhibition of PFK directs the pathway into the pentose phosphate shunt. At the same time, another group of researchers identified the role of p53 in regulating mitochondrial metabolism (28). They have identified a

362 molecule called synthesis of cytochrome c oxidase 2 (SCO2) as a downstream mediator of tumor suppressor p53 in a human cancer cell line. SCO2 regulates cytochrome c oxidase (Complex IV), a terminal electron donor for molecular oxygen in the electron transport system (ETS). Their study suggests that SCO2 couples with p53 to directly regulate mitochondrial respiration by modulating Complex IV activity. A mounting number of additional studies further support the Warburg hypothesis. As mitochondria play a vital role in apoptosis and ROS formation, it has been theorized that cancer cells prefer glycolytic routes to escape programmed cell death pathways. However, it has been observed that cells from different cancer types have fully functional mitochondria that play a critical role in tumorigenesis. This is an ongoing area of research, and many unanswered questions remain in understanding the role of mitochondria in cancer. While much is known about the altered metabolism of cancer cells, alterations in systemic metabolism are also a characteristic feature of many cancers. Cancer influences the function of metabolic organs such as adipose tissue, the liver, and the brain, promoting insulin resistance and increased concentrations of metabolic fuels. This is quite understandable as cancer cells need much more glucose than normal cells to meet their high metabolic demand. Therefore, the Warburg effect is not limited to only cancer cell metabolism, but it’s also indirectly related to whole-body metabolism. In the following sections, we will discuss the correlation between cancer cell metabolism and systemic glucose and lipid metabolism, and how these systems are exploited by cancer.

9.2.1 Obesity and Cancer To find evidence that cancer is a metabolic disease, one need look no further than the epidemiology of obesity and cancer. In 2003, Eugenia Calle published a landmark prospective study of over 900,000 adults and found that those who were obese had a substantially higher risk of dying from cancer (29). Both men and women were at risk for a wide range of cancers, with an estimated 90,000 cancer deaths per year attributable to obesity. Much of this increased mortality can be attributed to an increased incidence of cancer; the World Cancer Research Fund and the American Institute of Cancer Research (SCRF/ AICR) report convincing evidence that body fat increases the risk of developing esophageal, pancreatic, liver, colorectal, postmenopausal breast, endometrial, and kidney cancer, and there is probable evidence that it increases oropharyngeal, stomach, gallbladder, ovarian, and advanced prostate cancers. Obesity also makes cancer more difficult to cure, with obese cancer patients at higher risk of poorer outcomes from breast (30), colon (31), prostate (32), pancreatic (33), ovarian (34), and hematologic cancers (35). While there are a host of confounding factors that undoubtedly contribute to these obesity-cancer links (e.g. socioeconomic status, minority status, genetics, environmental exposures, behaviors, etc), animal models demonstrate a clear biological link between obesity and tumorigenesis and poor cancer outcome. For example, Steven Mittelman’s laboratory developed animal models of obesity and acute lymphoblastic leukemia (ALL) based on epidemiological data showing that children who are obese at diagnosis

Metabolism and Medicine of ALL have a 50% higher relapse rate than nonobese patients. They elegantly showed that obesity directly accelerated ALL development in a transgenic model (36), and worsened outcome after treatment with standard chemotherapies (37, 38). There are undoubtedly multiple mechanisms responsible for these biological links between obesity and cancer. Inflammation is a hallmark of cancer (39). Obesity is often associated with systemic inflammation, as immune cells accumulate in expanding adipose tissue and take on a proinflammatory phenotype (40). This leads to the release of inflammatory cytokines, such as TNFα, IL-6, IL-1β, and PAI-1 (41), all with putative roles in cancer pathogenesis. Obesity is also associated with insulin resistance, where insulin gradually loses its ability to suppress hepatic glucose production and stimulate systemic glucose uptake. Pancreatic beta cells compensate for this insulin resistance by secreting more insulin, leading to hyperinsulinemia. In one of the body’s few positive feedback loops, hyperinsulinemia causes a worsening of insulin resistance. Insulin regulates various aspects of cell growth, proliferation, and survival, which might support its pro-cancerous role. It controls cell growth via PI3KAkt-dependent activation of mTOR1, the master regulator of cellular biosynthetic processes (42). mTOR controls cellular biomass generation such as biosynthesis of lipids, proteins, and nucleic acids. Insulin-stimulated activation of Akt, or protein kinase B (PKB), favors cell survival through inhibition of various proapoptotic proteins, thus helping cancer cells to survive in highly stressful tumor microenvironments. Insulin also acts as a potent mitogen, inducing cell cycle progression through the MAPK/ERK signaling cascade. Interestingly, insulin resistance generally reflects resistance to the glucose uptake and the PI3K-activating effects of insulin, with relative sparing of its stimulation of the mitogenic pathways (43, 44)— this may help explain why insulin resistance is associated with both hyperglycemia and increased cancer incidence. Another effect of insulin is to increase systemic levels of free IGF-1. IGF-1 is the main messenger of growth hormone, and, like insulin, can stimulate the PI3K/AKT and MAPK/ERK procancer pathways. Epidemiologic evidence strongly links IGF-1 levels to cancer incidence, and patients without functioning growth hormone receptors (Laron Syndrome) show substantial longevity and an extremely low incidence of cancer (45). Several other hormones are altered in the obese state, which may contribute to cancer, but likely the most impactful is estrogen. Estrogens are produced in adipose tissue by aromatase activity on androgens, and are known to promote the development of breast, uterine, and ovarian cancers. Estrogen has also been linked to non-gynecologic cancers, such as lung cancer (46). The secretion of adiponectin from adipocytes has been shown to decrease angiogenesis, limit tumor growth in vitro, and promote apoptosis in cancer cells (47). As adiposity increases, circulating adiponectin decreases and leptin increases, mitigating the antitumor effects of adiponectin and contributing to cell proliferation, migration, and tissue invasion (48, 49). Finally, obesity is associated with increased fuel availability. The primary role of adipose tissue is to store and release lipids. As obesity develops, adipose tissue becomes inflamed and dysfunctional, leading to excess release of free fatty acids. With increasing insulin resistance, beta cell compensation

Chronic Diseases as Metabolic Disorders may become impaired, and a mild to frank hyperglycemia can arise. The obese, insulin-resistant state is also associated with increased circulating levels of branched-chain amino acids, which are important fuels for cancer cell protein synthesis and metabolism (50). Adipose tissue itself can release some amino acids, such as asparagine and glutamine, which can further fuel cancer cells (37). Thus, the obese state provides a fertile environment for cancer development and proliferation. Adipose tissue itself often directly interacts with cancer cells, as many sites where tumors grow or metastasize, such as the peritoneum, breast, and bone marrow, are rich in adipocytes. The systemic hormonal, inflammatory, and metabolic milieu of the obese, insulin-resistant state provides multiple advantages for cancer cells.

9.2.2 Insulin Signaling and the Warburg Effect While the obese body may provide a fertile soil for the development and growth of cancer, tumors actively hijack their local and systemic environments to further promote their own growth and survival. Many of these effects result in a more obese-like phenotype. Invasion of cancer into host tissues nearly universally results in inflammatory and immune responses. Immune cells release a host of cytokines, causing a myriad of systemic effects. TNFα and IL-6 mediate some of the insulin resistance seen in cancer patients. At the same time, the Warburg effect involves the upregulation of insulin signaling in cancer cells, which promotes cell survival, growth, and replication. Hyperinsulinemia in the setting of insulin resistance

363 favors glucose as the dominant systemic fuel source, which satisfies the bioenergetic and biomass needs of cancer cell growth and proliferation (51). Together, inflammation and insulin resistance ensure that increased fuels, including glucose, lipids, and amino acids are available in the systemic circulation, but relatively reserved for the cancer cell’s use. Progression to hyperglycemia and diabetes can be exacerbated by treatment regimens, including chemotherapies and other medications that contribute to insulin resistance and beta-cell toxicity (e.g. steroids, vinca alkaloids, anthracyclines, asparagines, etc.). Hyperglycemia and diabetes have been demonstrated to negatively influence the prognoses of certain cancer types including colorectal carcinoma, acute lymphocytic and acute myelocytic leukemia, and glioblastoma multiforme (52–54). In the cancer cell, insulin-mediated activation of Akt can stimulate the activity of hexokinase, which phosphorylates and traps the glucose within the cell. Hexokinase is often overexpressed in cancer cells (55) giving them an additional competitive advantage for available glucose over surrounding cells. The trapped glucose-6-phosphate is then metabolized by phosphofructokinase 1 (PFK1), the rate-limiting enzyme of glycolysis, which is also stimulated by Akt. Akt also stimulates the membrane translocation of glucose transporters, GLUT4 and GLUT1, and stabilizes PFK1(56, 57), further fueling cancer cells’ appetite for glucose and glycolytic metabolism. Finally, Akt also activates mTOR, which drives protein synthesis in part by inhibiting complete amino acid catabolism, redirecting them to glycolytic pathway intermediates and also to the process of ATP production (Figure 9.4).

FIGURE 9.4  Flowchart illustration of the glycolytic pathway in normal and cancer cells. *ADP = adenosine diphosphate; ATP = adenosine triphosphate; CoA = coenzyme A; GLUT1= glucose transporter 1; H+ = hydrogen proton; H2O = water; HIF-1α = hypoxia inducing factor 1 α; IRS: insulin receptor substrate; mTOR = mechanistic target of rapamycin; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; Pi = inorganic phosphate; PDC: pyruvate dehydrogenase complex; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

364 Cell growth is promoted here as well by way of this produced ATP, used to drive the initiation of protein translation in concert with the surplus of glucose that metabolizes to pyruvate, which then moves into mitochondria to be formed into citrate, a precursor of lipid biosynthesis. Glycolytic intermediates such as lactate and pyruvate can stabilize hypoxia inducing factor 1 α (HIFα), a master regulator of cancer cell metabolism. HIFα activation of pyruvate dehydrogenase kinase (PDK) inhibits the pyruvate dehydrogenase enzyme complex (PDC) lying at the nexus between the cytosolic glycolysis and mitochondrial tricarboxylic acid (TCA) cycle pathways, thereby preventing pyruvate decarboxylation and conversion to acetyl CoA. This ultimately prevents mitochondrial oxidative bioenergetic metabolism and increased reliance on aerobic glycolysis, per the Warburg effect. While the TCA cycle-mediated combustion of glucose and mitochondrial oxidative phosphorylation are 15–20-fold more efficient in terms of ATP yield, the cytosol’s glycolytic pathway of ATP production is 10–100-fold faster. Because cancer cells are often growing in a hypoxic environment, such as the bone marrow or the center of a poorly vascularized tumor, these responses may in part be an adaptation to these environments. However, even in the presence of oxygen, as long as there is abundant glucose availability, the Warburg effect serves the bioenergetic requirements of rapidly proliferating tumor cells. The process by which the Warburg effect additionally provides the biosynthetic building block requirements for cell growth and replication, termed anaplerosis, will be described below.

9.2.3 Oncogenic Signaling and the Warburg Effect While hyperinsulinemia promotes the Warburg effect in cancer cells through the PI3K-Akt-mTOR pathway (Figure 9.5) and other Akt-mediated signaling, metabolic independence from insulin and other growth factors is often observed in

Metabolism and Medicine cancer cells. Indeed, two of the “hallmarks of cancer” reflect the independence of cancer cells from these extracellular signals (39). “Sustaining proliferative signaling” occurs in the absence of the normal extracellular signals that would stimulate these pathways; and “evading growth suppressors” reflects the ability of the cancer cells to ignore extracellular signals that would normally slow proliferation or induce apoptosis. Intrinsic signals that promote cancer cell proliferation and survival include DNA amplification (increased copies of DNA segments); activating mutations of proto-oncogenes, such as PI3K, Akt, and Myc; and inactivating mutations of tumor suppressor genes, such as phosphatase and tensin homolog (PTEN). A major oncogenic signaling cascade is dependent on phosphoinositol 3 kinase (PI3K). When PI3K is oncogenically active, it phosphorylates cell membrane phospholipid phosphoinositol 4,5 bisphosphate (PIP2), converting it to phosphoinositol 3,4,5 triphosphate (PIP3). PIP3 then activates phosphoinositide-dependent kinase1 (PDK1) and downstream Akt. The tumor suppressor PTEN puts the brakes on this cascade by mediating the dephosphorylation of PIP3 to PIP2. However, in the setting of a PTEN-inactivating mutation, Akt expression becomes constitutive, indicating a sort of yin-yang relationship between Akt and PTEN genes in the context of tumor cell expression. Examples of human tumors associated with somatic PTEN-inactivating mutations include sporadic benign and malignant thyroid follicular tumors, glioblastoma multiforme, and endometrial and prostate carcinomas (58). Activation of PI3K and/or Akt oncogenes by amplification is characteristic in a large number of human cancer types including breast, ovarian, esophageal, pancreatic, and thyroid cancers (59–63). Many cancers are promoted by activating mutations of the proto-oncogenes RAS and/or RAF, as their activation triggers RAS-RAF-MAPK/ERK mitogenic pathways. RAS is a commonly activated proto-oncogene that lies upstream to Akt. As

FIGURE 9.5  The PI3K-Akt-mTOR pathway involved in cell growth and proliferation. *Akt = protein kinase B; mTOR = mechanistic target of rapamycin; P = phosphate; PDK1 = phosphoinositide dependent kinase 1; PI3K = phosphatidylinositol 3-kinases; PIP2 = phosphatidylinositol 4,5-bisphosphate; PIP3 = phosphatidylinositol (3,4,5)-trisphosphate; PTEN = phosphatase and tensin homolog.

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Chronic Diseases as Metabolic Disorders previously described to occur by AKT-activation, RAS notably induces GLUT1, and stimulates hexokinase and the ratelimiting enzyme phosphofructokinase 1 thereby promoting glucose uptake into cells, trapping glucose, and committing it to the glycolytic pathway. This represents another molecular mechanism by which cancer cells enlist the glycolytic pathway to satisfy their biomass and anabolic demands for cell growth and proliferation. RAS and AKT can function autonomously, be stimulated by insulin and other growth-promoting factors, or be engaged by some combination of the two.

9.2.4 Anaplerosis: Connecting the Warburg Effect and Mitochondrial Function in Proliferating Cells While Warburg proposed an irreversible defect in mitochondrial respiration, it is now known that the aerobic glycolysis of cancer cells does not always require mitochondrial impairment (64, 65). Cancer cells derive benefits from aerobic glycolysis, even in the absence of impaired mitochondrial function. One benefit of preventing complete glucose metabolism in the ETC is that the carbons can be used as building blocks for other important molecules, such as lipids, amino acids, and nucleosides, a phenomenon termed anaplerosis. Anaplerosis occurs when there is sufficient glucose availability for glycolysis to provide the necessary bioenergetics without the requirement of more efficient mitochondrial machinery. HIFα activates the enzyme pyruvate kinase M2 (PKM2) in proliferating cancer cells (exemplified in Figure 9.6), which inhibits the conversion of phosphoenolpyruvate to pyruvate by pyruvate kinase at the end of the glycolytic pathway. This slows down glycolysis, allowing the more proximal pathway to provide the carbon sources for cell replication. The glycolytic substrate 3-phosphoglycerate, required for nucleotide biosynthesis, generates

ribose from glucose-6-phosphate and provides bountiful amounts of serine, the precursor to glycine. The two nutrients that cancer cells crave the most are glucose and glutamine. As Akt is a key effector of glucose uptake and commitment to glycolytic metabolism into cancer cells in the context of hyperinsulinemia and hyperglycemia, the proto-oncogene c-Myc is the primary effector of glutamine uptake. Myc appears to be both necessary and sufficient to provide cancer cells with the nitrogen-containing amine groups needed for cell proliferation. Myc promotes glutamine uptake into cancer cells and activates the enzyme glutaminase to deaminate the nutrient to glutamate through glutaminolysis (66). Glutamate dehydrogenase further deaminates glutamate to α-ketoglutarate, which enters and replenishes carbons in the TCA cycle, maintaining it as the “biosynthetic hub” that provides building blocks for cancer cell replication (67). With amine groups donated from glutamine and glutamate, nonessential amino acids are produced from pyruvate and other intermediates of the glycolysis pathway. Myc yields everything necessary for nucleotide biosynthesis by providing glutamine, ribose, serine, and glycine. A ready supply of these glycolytic intermediates for anaplerosis is maintained in part by Myc, which stimulates transcription of glycolysis enzymes, while slowing down pyruvate kinase, the last step of glycolysis, through PKM2 as described above. Since glycolytic production of ATP is sufficient to meet the energetic needs of cell growth and proliferation in an environment of abundant glucose, mitochondria can instead be engaged to provide the necessary biosynthetic precursors. A major mechanism to achieve this involves the transport of citrate, a TCA cycle intermediate, from the mitochondria to the cytoplasm where it gets cleaved by ATP citrate lyase (ACL) to oxaloacetate and acetyl CoA under the influence of activated Akt. Oxaloacetate is reduced to malate and transported into the mitochondria to replenish the pool of TCA cycle intermediates. Malate can be reconverted back to oxaloacetate and then to nonessential amino acids alanine and aspartate. Acetyl CoA is the central building block for lipid synthesis.

9.2.5 Targeting Carbohydrate Metabolism for Cancer Therapy

FIGURE 9.6  The central role played by MyC in cellular processes. Source: adapted from (16). *ɑKG = ɑ-ketoglutarate; CoA = coenzyme A; e– = electron; ETC = electron transport chain; GLUT1 = glucose transporter 1; GLS = ; HIF-1 = hypoxia inducing factor 1; HK2 = hexokinase 2; LDHA = lactate dehydrogenase A; PDH = pyruvate dehydrogenase; PDK1 = pyruvate dehydrogenase kinase 1; PKM2 = pyruvate kinase isozyme M2; SLC1A5 = solute carrier family 1 member 5; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

Per the Warburg effect, the glycolytic metabolism of glucose may be metaphorically likened to a bioenergetic and biosynthetic umbilical cord of cancer cells. Aberrant metabolism is a characteristic feature of almost all types of cancer and offers a promising target for developing therapeutic strategies against aggressive tumors. Certain known alkylating agents are being used to treat cancers, which act to deplete energy by targeting enzymes in the glycolysis pathway, and to some extent may also target enzymes in the mitochondrial pathways of ATP production (68, 69). A particularly promising agent for the treatment of pancreatic, breast, colon, and other solid tumors appears to be pyruvate analog 3 bromopyruvate (3BrP). 3BrP mainly inhibits the activity of the glycolytic enzyme glyceraldehyde 3 phosphate dehydrogenase. However, with lower affinity, it also inhibits the glycolysis enzymes type 2 hexokinase and 3 phosphoglycerate kinase, as well as the TCA cycle enzyme succinate dehydrogenase. Another promising target that appears

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FIGURE 9.7  LDHA increases lactate production, which lowers the pH and promotes tumor growth. Therefore, targeting and lowering levels of LDHA could be a potential form of cancer treatment. *LDHA = lactate dehydrogenase A.

to be overexpressed in cancer cells is lactate dehydrogenase A (LDHA), a characteristic feature of the Warburg effect. LDHA reduces pyruvate to lactate, accompanying the regeneration of NAD+ from NADH. NAD+ is a crucial component necessary for maintaining glycolysis which produces the ATP required for cancer cell proliferation (Figure 9.7). Lactate lowers the pH in the tumor microenvironment and promotes cancer invasion and metastasis by facilitating the creation of an environment suitable for the recruitment of macrophages and other inflammatory immune cells. Therefore, agents that block overexpressed LDHA have favorable anti-cancer effects. Interestingly, there is some evidence that lactate released by tumors is not from the cancer cells themselves, but from the surrounding cancer-associated fibroblasts. In the “reverse Warburg effect”, cancer cells induce anaerobic metabolism in nearby cells within their microenvironment, resulting in the release of lactate and pyruvate, which the cancer cells can then use (70). It is not clear how many and which cancers exhibit the reverse Warburg effect rather than the classic Warburg effect, and techniques such as PET imaging may not be able to differentiate between the two. Cancer treatments are founded on exploiting differences between cancer and host cells; the Warburg effect may be one of those differences. Strategies to target aerobic glycolysis date back to the 1950s, when 2-deoxy-glucose (2-DG) was explored as a cancer treatment (71, 72). 2-DG is phosphorylated in cells, but cannot be converted to fructose-6-phosphate. The buildup of phosphorylated 2-DG leads to inhibition of hexokinase, and eventually to depletion of ATP (73). Preclinical and clinical trials using 2-DG in combination with other chemotherapies remain promising. At the other end of the spectrum, aerobic glycolysis results in the production of lactate and protons which must be effluxed from the cancer cells through monocarboxylate transporters. Small molecule inhibitors of these transporters have been developed, and offer a promising additional strategy (74). Since all cells rely on glucose uptake, targeting of glucose transporters, such as GLUT1 and GLUT4 may be difficult. However, some cancers seem to rely primarily on sodium-dependent glucose transporters, such as SGLT2. Indeed, SGLT2 inhibition shows remarkable preclinical activity against lung adenocarcinoma (75). Thus, while aerobic glycolysis offers survival advantages to cancer cells, it may also represent an Achilles’ Heel that can be targeted. Linking endogenous and potentially exogenous insulin to cancer is highly relevant to the Warburg Effect. The insulin

Metabolism and Medicine receptor homo- and heterodimerizes with the IGF-1 receptor. Insulin itself, like growth hormone and dietary protein, promotes the secretion of IGF-1 from hepatocytes, and decreases levels of the IGF-1 binding protein 1 (IGFBP-1), further increasing free levels of IGF-1. Insulin and IGF-1 are synergistically mediated by these namesake receptors to activate intracellular insulin signal transduction through the cell survival, growth promoting, and mitogenic Ras-PI3KAkt-mTOR metabolic pathway as well as to couple this pathway to the predominantly anti-apoptotic (cell survival) and mitogenic Ras-Raf-MAPK/ERK pathway. To reiterate the concepts introduced earlier, components of each of these pathways, namely Ras and Akt, stimulate glucose uptake into cancer cells by the glucose transporter GLUT1, as well as promote the glycolysis pathway by trapping glucose via hexokinase phosphorylation and activating the pathway’s rate-limiting enzyme PFK. Strategies that increase ketogenesis such as intermittent fasting or metformin also have demonstrated anti-cancer effects. In the liver, the absence of glucose availability, along with concomitant low insulin levels, promotes the oxidation of fatty acids to acetyl CoA, with subsequent formation of the ketone bodies, acetoacetate, and β-hydroxybutyrate. Hepatocytes release these ketone bodies into circulation to fulfill bioenergetic demands and be taken up by cells systemically, with a priority for the brain. As mentioned previously, cancer cells often do not have the metabolic machinery to convert ketones back into acetyl CoA for use in mitochondrial lipid and cholesterol synthesis or to be used as a substrate in the TCA cycle for energy production by downstream oxidative phosphorylation. In those that are able to convert ketones to acetyl CoA in the mitochondria, the capacity for metabolic glucose utilization through glycolysis appears to be slowed. In either case, ketosis appears to impart anti-neoplastic effects (76–78). Preclinical evidence appears to show a particular benefit of combining ketogenic and glucose depriving strategies, such as intermittent fasting along with pharmacologic approaches targeting steps in the glycolysis pathway (79). As described above, growth factors play important roles in linking metabolism to cancer initiation, progression, and treatment resistance. Furthermore, in addition to a connection between hyperinsulinemia and the clinical onset of cancer, there is also a documented correlation of hyperinsulinemia with cancer aggressiveness and mortality (80–82). While epidemiological data suggests that strategies that reduce endogenous insulin prevent cancer onset and recurrence (83–85), it is also hopeful that insulin reduction will impose therapeutic efficacy on existing cancers. It should also be recognized that IGF-1 promotes immune suppression, hence impairing immune cell cancer surveillance in favor of anabolism. Addressing IGF-1 levels could theoretically improve the efficacy of immunotherapy approaches to cancer treatment.

SIDEBAR 9.2: TARGETING METABOLIC FLEXIBILITY OF CANCER Unlike normal cells, cancer cells have a unique ability to switch to different metabolic pathways and can use a broad range of substrates to derive energy and biomass.

Chronic Diseases as Metabolic Disorders Several efforts have been made to target abnormal metabolic pathways to halt cancer progression. However, cancer cells are smart and have the ability to switch to alternative metabolic pathways, thereby escaping the anticancer effects of antimetabolite drugs. Thus, there is a need to find a target/drug that can diminish the ability of cancer cells to switch between different alternative pathways. Under normal metabolic conditions, cancer cells use glucose and metabolize it mainly through aerobic glycolysis. However, under metabolic stress conditions, these cells can switch to metabolism of alternate substrates such as lactate, fatty acids, or amino acids via mitochondrial oxidative phosphorylation. Targeting both of these pathways could induce metabolic catastrophe (depletion of the cellular pool of ATP) and eventually induce metabolic synthetic lethality. An ideal solution would be to find suitable targets to induce metabolic synthetic lethality in cancer cells, without affecting the metabolism of normal cells.

9.2.6 Targeting Amino Acid Metabolism in Tumorigenesis Another set of building blocks of cell replication are amino acids, tagging blockade of protein synthesis as another target for the metabolic approach to cancer prevention and treatment. Growth factors, like insulin, IGF-1, and EGF stimulate their respective tyrosine kinase receptors and promote protein synthesis by signaling through the intracellular PI3K/Akt/ mTOR pathway. Inhibiting any constituents of this pathway should contribute to the reduction of protein synthesis, necessary for cell growth and proliferation. mTOR inhibition can also downregulate GLUT1, important for the uptake of glucose into tumor cells (86–89). mTOR, the abbreviation of mammalian target of rapamycin, recognizes rapamycin as the initial drug used in the discovery that targeted this protein complex and regulator of protein synthesis. Recent mTOR inhibitors derived from rapamycin include everolimus and temsirolimus, both approved for treating several cancer types. For instance, everolimus treats advanced renal cell carcinoma, various neuroendocrine tumors, and estrogen receptor-positive breast cancer. Another useful property of mTOR that makes its inhibition an effective cancer strategy is its ability to upregulate GLUT1, important for the uptake of glucose into tumor cells (86–89). A plethora of inhibitors targeting multiple steps in the conversion of glutamine to glutamate, and ultimately to the α-ketoglutarate intermediate of the TCA cycle, appear to be valuable interventions in the treatment of both solid and hematological glutamine-addicted cancers. Beneficially, it is possible to select patients with glutamine-dependent malignancies that are likely to respond to these inhibitors. For example, radiolabeled glutamine analogs are used to assess glutamine uptake into tumors in vivo, as can staining for characteristics such as MYC oncogene overexpression. Glutamine is also broken down to some extent by certain asparaginase compounds used primarily for the treatment of leukemias. Asparaginase derived from Erwinia (“Erwinase”) has a high glutaminase activity, reducing systemic glutamine levels more than E. coli asparaginase. This glutaminase activity likely

367 contributes to asparaginase cytotoxicity, though this is sometimes debated (90–92). Interestingly, adipocytes release both asparagine and glutamine, contributing to a local protective effect from these drugs (92). Glutamine depletion per se has been evaluated as a potential therapeutic strategy, but with a high prevalence of systemic and neurological toxicities, this is a difficult strategy (93). As discussed above, a prominent feature of the Warburg effect could inform directions for treatment strategies of such dynamic circumstances. The Warburg effect describes glucose and glutamine as the two nutrient substrates to which cancer cells are most addicted, so it may be effective to utilize dietary restriction or pharmacological interventions to restrain these nutrients and/or any relevant metabolites. In the case of glutamine, dietary manipulation appears impractical because the body produces this nonessential amino acid from endogenous sources, so pharmacologically targeting glutamine transporters and metabolizing enzymes may prove to be successful. Conversely, dietary restriction of an additional nutrient, the essential amino acid methionine, holds promise as a possible treatment for breast, colon, prostate, and glioblastoma multiforme (GBM) cancers. In GBM, for example, methionine appears to activate oncogenic signaling, therefore its restriction could prove beneficial (Figure 9.8) (94, 95). Dietary restriction of the nonessential amino acid arginine may also play an important role in the management of certain cancers. Arginine potentially promotes cancer cell survival, growth, and proliferation by activation of mTOR as well as by enhancing circulating growth factor secretion, including that of insulin, IGF-1, and growth hormone, particularly after heavy resistance training (88, 96). Additionally, de novo synthesis of arginine via argininosuccinate synthetase 1 (ASS1) enzyme

FIGURE 9.8  Role of essential and non-essential amino acids in the management of certain cancers. *mTOR = mechanistic target of rapamycin.

368 is epigenetically repressed in some melanomas, hepatocellular carcinomas, and mesotheliomas wherein there appears to be greater reliance on exogenous intake and uptake of arginine from nearby cells. There is potential here for treatment development via exploitation of this dependency by dietary and pharmacologic interventions (97, 98). Methionine is one of the few nonessential amino acids whose plasma levels can be effectively reduced by low protein diets—as much as 50% within one day of dietary restriction. Levels plateau and dietary restriction is difficult, and so the use of bacterially-derived methionine has been evaluated as a complementary or alternate strategy. Methionase has demonstrated short-lasting efficacy in the colon (99-108). Serine and glycine are also nonessential amino acids that, as described above, are derived from the glycolysis intermediate 3 phosphoglycerate, initiated by the enzyme phosphoglycerate dehydrogenase 1, which leads to serine and subsequent conversion to glycine. These amino acids are building blocks to nucleic acids, lipids, and proteins, while serine itself is an activator of mTOR. Synthesis of these amino acids, therefore, catalyzes cancer cell growth and proliferation, but at the expense of depleting other amino acids and glycolysis intermediates (109). In addition to de novo biosynthesis of these two amino acids, some cancers can take up exogenous serine, necessary for repleting the glycolysis pathway and the building blocks for cancer cell replication. Accordingly, these tumors are sensitive to significant decreases in blood serine levels due to dietary restriction (110). Finally, regarding serine and glycine amino acids, some very aggressive melanoma and triple-negative breast cancers overexpress phosphoglycerate dehydrogenase making this a potentially promising therapeutic target in these cancers. This upregulated enzymatic activity produces serine and glycine but depletes glycolysis pathway intermediates and consequently can limit the supply of ATP. Accordingly, these cancers are likely vulnerable to the strategy of dietary restriction, which deprives the ability to replenish glycolytic pathway intermediates or metformin. The latter is known to inhibit the oxidative phosphorylation mode of ATP production (see below) (79, 111–115).

9.2.7 Targeting Lipid Metabolism in Tumors Nutrients are substrates for bioenergetic demands and the building blocks for cell growth and replication. Their manipulation, therefore, holds great promise in the metabolic perspective for human cancer prevention and treatment. This can also be extended to lipids, cholesterol, and ketone bodies as alternate fuel sources. Acetyl CoA is a precursor to acyl groups, required for free fatty acid, triglyceride, and phospholipid synthesis. The ratelimiting step in fatty acyl synthesis is the conversion of acetyl CoA (ACC) to malonyl CoA, through the action of acetyl CoA carboxylase. Acetyl CoA is also used to form isoprenoids, including cholesterol, through the mevalonate pathway. Cholesterol is needed to generate cell membrane lipid rafts that structurally organize proteins within cell membranes to facilitate signal transduction. Strategies that inhibit fatty acid synthesis or the mevalonate pathway (e.g. statins) may

Metabolism and Medicine provide benefits in cancer prevention or treatment outcomes (Figure 9.9) (23). Acetyl CoA is also a noteworthy regulator of histone acetylation versus deacetylation. When present at high levels in the cell, acetyl CoA promotes histone acetylation, which opens up gene transcription programs for cell growth and proliferation. Conversely, when acetyl CoA levels are low, SIRT1-mediated histone deacetylation represses these gene transcription programs. This highlights a mechanistic relationship between protection from prematurely reduced health span and chronic diseases of aging— including cancers—to calorie restriction and exercise. Both healthy and cancer cells can take up circulating fatty acids sourced from dietary nutrients digested by the gastrointestinal tract, microbiota metabolites, circadian and fastinginduced lipolytic release from adipose stores, or lipoproteins packaged in the liver or intestine. Cancer cells can overexpress CD36 (116), the putative free fatty acid transporter, and lipoprotein lipase (117, 118), the enzyme which releases free fatty acids from circulating lipoproteins. Additionally, cancer cells have the ability to biosynthesize fatty acids de novo and can also uptake circulatory fatty acids to utilize as structural building blocks for cell growth and replication. The availability/synthesis of unsaturated free fatty acids is particularly important to cancer cells, perhaps due in part to their important role in plasma membrane fluidity. Thus, cancer cells often overexpress stearoyl-CoA desaturase (SCD), which desaturates fatty acids. Cancer cells are highly dependent on amino acids from circulation as described previously. However, in the case of cholesterol, cancer cells make about half of their required amount de novo and are able to internalize the other half from the circulation. De novo synthesis of both fatty acids and cholesterol originates from acetyl CoA, the two-carbon molecule basic building block derived from citrate formed in the TCA cycle. Acetyl CoA reacts with bicarbonate, a single carbon molecule, under the influence of the rate-limiting enzyme ACC to produce malonyl CoA. Fatty acids are subsequently produced from the elongating actions of fatty acid synthase (FAS), which is activated by the molecular signaling pathways of MAPK and of PI3K/Akt. Cancer cell growth and proliferation are coupled by way of this FAS-mediated fatty acid synthesis’ metabolic pathway that positively feeds back onto reciprocally selfamplifying MAPK and PI3K oncogenic pathways. Further, FAS expression correlates with tumor aggressiveness, and overexpression occurs in many cancer types including head and neck, breast, ovarian, endometrial, gastric, colon, and lung (79, 86, 119–123). Moving to cholesterol, its synthesis begins with the thiolase enzyme-mediated merging of two acetyl CoA molecules to form acetoacetyl CoA. In a complex reaction, acetoacetyl CoA is converted by the enzyme HMG CoA synthase to 3-hydroxy-3-methylglutaryl-CoA (HMG-CoA), which is in turn reduced to mevalonate by the rate-limiting enzyme of cholesterol synthesis, HMG CoA reductase. HMGCoA reductase, like FASN, is overexpressed in several human cancers (124). De novo synthesis of fatty acids and cholesterol is highly important for cancer cell growth and proliferation, underscoring an exploitable opportunity for the development

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FIGURE 9.9  Schematic illustration of pathways involved in the synthesis of fatty acids and cholesterol. *ACC = acetyl-coenzyme A carboxylase; FA = fatty acid; FAS = fatty acid synthase; HCO3– = bicarbonate; HMG-CoA = 3-hydroxy-3-methylglutaryl-coenzyme A; IRS = insulin related substrate; MAPK = mitogen-activated protein kinase; PI3K/Akt = phosphatidylinositol 3-kinase / protein kinase B signaling pathway; TCA cycle = the citric acid cycle (also known as the tricarboxylic acid cycle or Krebs cycle).

of preventative and therapeutic strategies. Existing available strategies will be discussed ahead. Examples to be discussed include the enzyme fatty acid synthase inhibitor, cerulenin, and statin HMG CoA Reductase inhibitors, both with applicability to human cancer therapies (see Figure 9.9).

Targeting Cholesterol Metabolism Cholesterol is an important component of lipid rafts, which moderate cell membrane fluidity, protein organization, and signal transduction. Cancer cells often hijack these signal transduction pathways in the cell membrane, to promote their own autonomous growth and proliferation. Ongoing research is examining the efficacy of statins, which inhibit cholesterol synthesis, in fighting cancer by impairing cell membrane lipid rafts and their signal transduction (growth factor-stimulated receptor tyrosine kinases, insulin and IGF-1 receptors, and the epidermal growth factor receptor [EGFR]). Lovastatin has synergistic interactions with standard chemotherapy on inhibiting EGFR in colon cancer, non-small cell lung cancer, and squamous cell head and neck cancers. This inhibition leads to decreased activity of the Ras-PI3K-Akt and Ras-Raf-MAPK/ERK metabolic and mitogenic pathways, particularly in breast cancer tumors that overexpress the HMGCoA reductase gene (79, 125–129). In addition to targeting cholesterol synthesis in cancer management, related fatty acid metabolism provides an entirely different range of strategic opportunities.

Targeting Fatty Acid Metabolism Recent work from the Mittelman lab has shown that in the presence of ALL, adipocytes secrete free fatty acids that are used by the cancer cells as a source of nutrients, switching from glucose to fatty acid oxidation. Cerulenin and the compound C75 block the de novo lipogenic enzyme fatty acid synthase, thereby blocking the synthesis of fatty acid building blocks needed for cell replication and its important step of cell membrane formation. This approach is a general idea in cancer therapy. C75 is a dual agent that additionally acts as an agonist of carnitine palmitoyltransferase 1 (CPT1), the enzyme that carries fatty acids into mitochondria. CPT1 promotes fatty acid entry into mitochondria and fatty acid oxidation for energy needs, thus preventing it from becoming utilized for purposes of cell membrane biosynthesis. C75 acts both centrally and peripherally, promoting anorexia and inducing fatty acid oxidation respectively. In the hypothalamus, it inhibits increases in NPY/AgRP and decreases in POMC that normally occur in the fasting period between meals (Figure 9.10). This prevents the hunger response. Both drugs, Cerulenin and C75, result in a profound loss of adipose mass and weight. This may sound like a treatment opportunity for the management of obesity and obesity-related chronic diseases, but in cancer patients, the impact of this weight loss is too severe and is likely to reduce functional conditioning. Perhaps, it does pose an opportunity to improve the tolerability of dietary fasting strategies used intermittently for durations of four to five days. Nevertheless,

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Metabolism and Medicine

FIGURE 9.10  Cancer management through the targeting of fatty acid metabolism. *AgRP = agouti-related protein; CPT1 = carnitine palmitoyltransferase 1; FAS = fatty acid synthesis; NPY = neuropeptide Y; POMC = proopiomelanocortin.

there are alternative and seemingly acceptable fatty acid synthase inhibitors that do not promote weight loss, such as the polyphenolic catechin found in green tea, epigallocatechin3-gallate (EGCG), and other natural flavonoids like quercetin found in apples, berries, onions, red wine, and green tea. These molecules are effective inhibitors of de novo fatty acid synthesis and appear to induce significant responses of apoptosis in tumor models of cancers like that of the breast. Other strategies that have been evaluated are inhibitors of lipoprotein lipase (130), acetyl-CoA carboxylase (131), and steroyl-CoA desaturase (130). Moreover, other drugs discussed below, including metformin and aspirin, inhibit de novo fatty acid synthesis as a function of direct (aspirin) or indirect (metformin) inhibition of AMPK mediated suppression of ACC activity. Statins, on the other hand, activate AMPK by blocking ubiquinone in the ETC and subsequent ATP synthesis, thereby increasing the AMP/ATP ratio. There is evidence that various combinations of these options yield synergistic responses in cancer models (130). Using strategies described above in connection with the Warburg effect, a promising approach to the overall goal of targeting fatty acid metabolism for cancer management may be the development of pharmacological agents that reduce citrate formation by inhibiting glucose entry into glycolysis or glutamine entry into the TCA cycle (79, 132–136).

9.2.8 Targeting Whole-Body Metabolism (Systemic) for Cancer Management In regard to cancer prevention and treatment, the Warburg hypothesis opens a curtain on a valuable metabolic perspective to typically utilized dietary and pharmacologic approaches—a logical effect given that metabolism is the most defining hallmark of any living organism’s health. An efficiently integrated metabolism encourages optimal physiology and health, while deviation from and loss of metabolic

integrity can be tantamount to death. The astonishing complexity of every human being makes the context of an individual’s cancer type and accompanying unique characteristics crucial determinants of therapy, highlighting the necessity for a model, such as the Physiological Fitness Landscape, along with precision personalized scales of medicine that allow for dynamic adjustments of treatment over time. For example, with a given modality and regimen of therapy, tumor resistance may develop over time, requiring dynamic adjustments of any implemented treatments. Applying these insights to the development of treatment strategies has already begun to show promise in metabolic strategies for the prevention and treatment of cancers. As discussed earlier, owing to a very high metabolic demand, cancer cells require much more nutrients than the surrounding tissue. Tumors behave like an endocrine organ and secrete numerous signals that directly or indirectly influence the function of key metabolic organs. Tumor cells also interact with immune cells, resulting in the release of inflammatory signals. Inflammatory cytokines in turn cause insulin resistance, exhibited by excess glucose output by the liver, decreased glucose uptake by insulin-sensitive tissues like skeletal muscle, and increased lipolysis in adipose tissue. Additional cancer cytokines directly induce adipose tissue lipolysis, including lipid mobilizing factor (LMF), TNFα, and various interleukins. Moreover, studies suggest that tumors affect neuroendocrine function to destabilize the circadian clock and thereby cause impaired sleep behavior and glucose homeostasis. It is clear that cancer cells can mobilize and outcompete host tissues for nutrients, particularly glucose, amino acids, and fatty acids, promoting continued tumor growth while host cells starve (a condition of a wasting syndrome called cachexia, which is common in cancer patients). Strategies that can break the communication between the tumor with other metabolic organs or aim to restrict the nutrient to cancer cells

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Chronic Diseases as Metabolic Disorders could restrict cancer growth and metastasis as well as improve the patient’s metabolic health and survival. However, this is difficult to achieve. Here, we propose the promising targets and strategies to target systemic metabolism for the management of cancer.

Fasting Given the strong links between obesity, cancer, and cancer management described above and established by further research (38, 137–139), it is reasonable to wonder whether diet and exercise interventions can reduce cancer incidence and/ or improve treatment outcomes. In fact, the incidence of most cancers appears to be reduced following bariatric surgery (140), providing a proof of concept for this. There has been much interest in the use of fasting to improve cancer outcomes. Fasting can induce a number of potentially beneficial effects, including reducing fuel availability, growth factors, and inflammation. Fasting reduces circulating insulin and glucose (in hyperglycemic patients), and IGF-1 levels fall as well as free IGF-1 due to increases in IGF-1 binding proteins. Fasting also leads to rises in ketones, which as discussed above, may not be usable by cancer cells. One theory of how fasting improves cancer outcomes involves the targeted induction of stress in cancer cells. Healthy cells appear to have increased resilience to cell stress compared to that of cancer cells and are more often able to efficiently compensate during periods of stress such as when it becomes necessary to endure a low-energy state. Healthy cells accomplish this by self-inhibiting cell growth and division while calibrating limited energy resources for processes required for organism survival, including DNA and cell repair in response to damage induced by chemotherapy drugs. Host cells during fuel deprivation are also able to enter a state of autophagy, breaking down organelles and recycling proteins and other components to prolong survival. These host responses allow cells to resist many of the effects of chemotherapy. Cancer cells on the other hand tend not to respond to systemic signals that slow metabolism in times of caloric deficit, as they exhibit constitutively active metabolic and/or mitogenic pathways detached from regulatory control of insulin, IGF-1, and other growth promoting factors. Continued unrestrained growth and proliferation in conditions of fuel deprivation increase metabolic stress in the cancer cells, making them more vulnerable to chemotherapy, a phenomenon termed the “differential stress hypothesis” (141). Discerning which specific cancers are, and which are not vulnerable to dietary fasting is therefore crucial. Furthermore, a combination of dietary fasting with insulin, IGF-1, and other tyrosine receptor kinase inhibitor pharmacologic therapy has demonstrated synergistic effects against colorectal, breast, and lung cancers. Preclinical data supports the use of fasting as a complement to cancer treatment. While fasting does not consistently improve cancer outcomes in preclinical models in the absence of other treatment, it has a more consistent effect to synergize with chemotherapy and radiation. In addition, fasting reduces the toxicity of several chemotherapies as well as abdominal radiation. There have only been a few clinical

studies of fasting during cancer treatment, and most of these did not evaluate treatment outcomes. Fasting seems to consistently reduce treatment toxicity, and there are hints that it may improve treatment outcomes as well (142). While fasting appears to have many benefits, there are potential limitations to its use. Fasting poses the potential risk of raising amino acids in healthy individuals, though it is not yet clear if this occurs in the context of cancer. Cancer patients also tend to have a limited tolerance to fasting for a duration of three to five days, as well as the untoward, albeit reversible effect of weight loss of up to 10% body weight. Given that cancer cachexia is a poor prognostic sign, patients and healthcare workers may be hesitant to promote fasting in the face of weight loss. Some less extreme forms of fasting are being studied, including intermittent fasting and time-restricted eating, though whether these provide the same benefits is not yet clear. Other dietary interventions that may provide similar benefits to fasting but be better tolerated are described below.

Ketogenic Diets The ketogenic diet could be an attractive alternative to fasting. This low-carbohydrate diet shifts the body away from tumor-feeding glycolysis and towards mitochondrial fatty acid oxidation. Even though the brain can use ketone bodies as an energy source, malignant brain tumor cells cannot, leading to cancer cell death. In preclinical models, ketogenic diets induce an overall tumor growth delay (143), and synergy with cancer treatments such as irradiation, metformin, and chemotherapy (142). There have been several nonrandomized, uncontrolled trials in glioma patients, showing that the ketogenic diet was well tolerated and may confer some benefit to survival (144). There are variations of ketogenic diets that differ based on the percentage of carbohydrate, protein, and fat; the plant vs. animal origin of the fat; and the total daily calorie content. A ketogenic diet with 40% calorie restriction and a macronutrient ratio of 60% fat to 30% carbohydrate to 10% protein promotes significant reductions in blood glucose and IGF-1 levels. Another variation of the ketogenic diet that mimics short-term fasting has a ratio of 40% fat to 50% carbohydrate to 10% plant-derived protein, and it alternates between 500 and 1,000 calories a day, for five days (Figure 9.11) (145). Interestingly, the improvements in metabolic parameters following the ketogenic diet were still present when measured five days after resuming the normal diet. This finding underscores the durability and robustness of the ketogenic diet on metabolic health. There is controversy on whether high-fat, low-protein ketogenic diets are beneficial in cancer patients. Dietary protein can potentiate the growth of some cancers and limiting protein intake can stunt the growth of certain melanomas. In contrast, limiting protein intake has no effect on breast cancer. Nonessential amino acids can always be made by de novo synthesis from precursor molecules or muscle catabolism, by both normal cells and cancer cells. Cachexia, which is the loss of both weight and muscle mass, is common in cancer and exacerbated by this excessive de novo synthesis of amino acids by cancer cells. Rather than restricting overall protein intake, strategically limiting the intake of the single amino acid methionine may have anti-cancer effects (146–149). Future

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The Microbiome and Cancer Treatment

FIGURE 9.11  Metabolic effects of short-term fasting and ketogenic diets. *CHO = carbohydrate; CR = calorie restriction; FA = fatty acid; IGF-1 = insulin-like growth factor 1.

studies will need to assess the long-term safety and efficacy of low-protein diets or diets that restrict select amino acids.

Caloric Restriction Finally, modest caloric restriction has been used as a less extreme intervention than fasting or ketogenic diet. Caloric restriction has shown consistent efficacy to delay cancer progression in various animal models, including spontaneous, carcinogenesis, and transplant models. Fewer studies have evaluated caloric restriction during chemotherapy treatment. Switching obese mice from a high-fat to a low-fat diet improved the treatment efficacy of vincristine against acute lymphoblastic leukemia, though there it had no effect during dexamethasone or L-asparaginase treatment (150). Excitingly, a modest caloric restriction and exercise intervention was translated by the same group into a clinical trial with children during initial treatment for ALL. Though a non-randomized trial, the modest diet/exercise intervention showed a ~70% reduction in risk of detectable residual disease in the bone marrow after the first month of chemotherapy. This finding is being further investigated in a randomized multicenter trial. It may be that specific diets and ratios of macronutrients have applications for different cancer types, especially when in combination with the patient’s genetics and traditional cancer treatment plans. Diets, and therefore diet interventions in rodents, are very different from humans, and so there is a limit to what information can be gained in this type of research. The preliminary data that diet intervention can reduce cancer incidence and improve treatment outcomes are encouraging and

The microbiome is a rapidly developing field of biomedical research. Microbiomes co-evolved with host organisms. The human gastrointestinal tract is home to over 100 trillion singlecelled microbes, with three million different microbe genes. In comparison, the human body has roughly 30 trillion cells, with 20,000 human genes. By these numbers, we are more microbiome than human. This makes it challenging to determine how specific parts of the microbiome affect our health. Further complicating the issue is that components of our microbiome interact with each other; thus, metabolites created by one population might be modified by another and could have effects to favor or impair the expansion of yet another. In humans, specific microbiome compositions may have cancer-protective or predisposing effects, and the microbiome can affect chemotherapy responsiveness. These effects are related to the metabolites that the microbiota produce or inhibit, in addition to immune system modulation of the microbiome (157, 158). Conversely, chemotherapy and other clinical factors can greatly impact the gut microbiome. Rodent studies show that something as simple as caloric restriction is able to change the microbiome, prolonging life span (159, 160). Preliminary studies suggest that modifying diet can change the ratios of certain gut microbiota, which may be another adjuvant tool to prevent and fight cancer (161, 162). Thus, it will be important to tease apart the interactions between cancer, diet, treatment, and the microbiome to truly understand how to optimize outcomes.

9.2.9 Repurposing Metabolism-Related Drugs to Fight Cancer Targeted metabolic therapies using existing drugs may be another treatment for cancer. Metabolism-related medications that are already FDA-approved for other indications could be a valuable starting point. These FDA-approved drugs that have already undergone rigorous safety testing would be prime candidates for clinical trials for other diseases. For example, metformin is approved to treat insulin-resistant diabetes and polycystic ovary syndrome, and it might help prevent cancer. Diabetics treated with metformin have lower rates of cancers common in people with diabetes, such as breast, pancreatic, colon, and hepatic cancers. Further, metformin-receiving cancer patients have better outcomes. These and other emerging observations suggest that metformin may also be antineoplastic (163). It is speculated that metformin and dietary restriction can synergistically enhance standard cancer treatments (79, 164, 165).

Metformin Metformin is a widely used anti-diabetes drug that improves insulin sensitivity and reduces glucose availability. Essentially, the metabolic effects of metformin are equivalent to those produced by fasting, and metformin may be

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Chronic Diseases as Metabolic Disorders considered a “fasting mimetic” (Figure 9.12) (166–168). These effects restrain the energy-requiring processes of cancer cell growth and proliferation, while also decreasing systemic insulin levels. Metformin is reported to significantly raise blood ketone levels, a simple consequence of shifting metabolism from glucose-dominance to fatty acid oxidation. Beneficially though, cancer cells are typically unable to use ketones as an energy substrate (169). Interestingly, there is reported anti-neoplastic (anti-tumor growth) synergy between dietary serine amino acid restriction and biguanide metformin therapy (170). Metformin appears to exert antineoplastic effects largely mediated by its anti-hyperglycemic, anti-hyperinsulinemic, and IGF-1 lowering actions (171) (Figure 9.13). This glucose-lowering activity reduces carbon availability in glycolysis, thereby lowering the serine precursor, 3-phosphoglycerate. So, metformin’s synergistic effects with serine restriction likely relate to all of these combined effects. Metformin’s activity in the intestines describes its important glucose-lowering effect. In the intestines, this compound inhibits Complex I of the mitochondrial electron transport chain, thereby reducing NADH oxidation, raising the AMP/ATP ratio, activating tumor suppressor LKB and consequently the downstream energy sensor, AMPK. ATP production is therefore reduced, inhibiting hepatic gluconeogenesis and intestinal glucose uptake.

Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) Prostaglandins and other prostanoids have roles in inflammation, chronic disease states, cancer migration, invasion, and metastasis. The prostaglandin PGE2 is important for making and breaking cell connections via cadherin, an adhesion molecule that sticks cells together. Increasing COX-2 activity

generates high amounts of prostaglandins, which break down cell adhesions in epithelial and endothelial tissues, structurally reorganize the underlying basement membrane, and promote angiogenesis. Breaking cadherin connections allows precancerous lesions to grow across tissue layers, and to grow new blood vessels to supply them with nutrients. These processes significantly contribute to the migratory, invasive, and metastatic potential of cancers. Therefore, the anti-prostaglandin effects of aspirin and other NSAIDs may play a role in cancer prevention or may serve as adjunctive therapy. A meta-analysis of 51 randomized-controlled clinical trials showed that aspirin reduced short-term incidence of cancer and the long-term likelihood of cancer mortality (172, 173). NSAIDs thin the blood, increasing bleeding risk; however, NSAID-receiving patients in these clinical trials did not have an increased risk of major bleeding. Similarly, Domingo, et  al. showed that aspirin and other NSAIDs reduced the risk of colorectal cancer (CRC), improved the efficacy of primary interventions to treat CRC, reduced the likelihood of relapse, and reduced the likelihood of metastasis (10, 11, 172, 174–177). NSAIDs may also prevent the recurrence of colorectal adenomas following resection of either adenoma or carcinoma. Another way that aspirin potentially fights cancer is by blocking nutrients from reaching cancer cells. For example, high-dose aspirin has been shown to lower blood glucose levels in diabetic patients (178). Reduced blood glucose levels mean reduced glycolysis, mitigating the Warburg effect. Aspirin can also act similarly to fasting or metformin by activating AMPK. AMPK inhibits protein synthesis (through mTOR pathways). By inhibiting these fuel-synthesizing processes, aspirin blocks cancer cell growth and replication (179–183). Glucocorticoid steroids, it should also be mentioned, are also COX inhibitors, which could explain some of their benefits when combined with standard chemotherapy regimens.

9.2.10 Conclusion and Future Perspectives

FIGURE 9.12  Action of metformin as a fasting mimetic in tumor suppression. *AMPK = adenosine monophosphate kinase; ATP = adenosine triphosphate; LKB1 = liver kinase B1; mTOR = mechanistic target of rapamycin; NAD+ = the oxidized state of nicotinamide adenine dinucleotide; NADH = the reduced state of nicotinamide adenine dinucleotide; NAMPT = nicotinamide phosphoribosyltransferase.

Several lines of evidence support the hypothesis that cancer is a disease of altered metabolism. However, there are existing controversies regarding mitochondrial function in tumorigenesis. This is an ongoing research area, and hopefully, in the future, the exact function of mitochondria in tumorigenesis will be unfolded. Altered metabolism is not only considered an important hallmark of nearly all cancers; it is directly or indirectly linked to other hallmarks such as metastasis, angiogenesis, rapid proliferation and survival, immune response, etc. In addition to abnormal glucose metabolism, tumor cells adapt to unusual amino acid and lipid metabolism which differentiates them from normal cells. Cancer cells have a unique ability to operate both de novo biosynthesis and uptake of fatty acids from circulation, which supports the rapid proliferation of cancer cells. Not only are cellular metabolic abnormalities characteristic of cancer cells, but systemic metabolic abnormalities are also a distinctive feature of tumorigenesis. Cancer alters whole-body glucose and lipid metabolism in patients. As cancer cells display a unique metabolism compared to normal cells, this offers an excellent therapeutic target for treatment.

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FIGURE 9.13  Perceived role of Metformin as a potential antineoplastic agent largely mediated by its anti-hyperglycemic and anti-hyperinsulinemicactions. *3PG = 3-phosphoglyceric acid; ACC = acetyl-coenzyme A carboxylase; AMPK = adenosine monophosphate kinase; ATP = adenosine triphosphate; ETC = electron transport chain; F6P = fructose 6-phosphate; FA = fatty acid; G6P = glucose 6-phosphate; HMG-CoA = 3-hydroxy3-methylglutaryl-coenzyme A; IGF-1 = insulin-like growth factor 1; LKB-1 = liver kinase B1; mTOR = mechanistic target of rapamycin.

The challenge to validating the therapeutic efficacy of metabolic interventions will lie with the involved sophisticated computer algorithms, metabolomics, and other bioinformatics. Such technologies are undoubtedly required for a highdimensional personalized stratification of both the individual and the tumor. This will invoke the application of models such as this book’s proposed Physiological Fitness Landscape.

When optimally stratified, many potentially promising molecular metabolic targets and pharmacologic therapy combinations arise (Figure 9.14). To name a few, such targets and accompanying strategies can broadly include: insulin, IGF-1 receptors, and other tyrosine kinase growth receptors such as EGFR and HER2; increasing IGF-1 binding proteins that reduce the available free IGF-1; various steps in the insulin

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FIGURE 9.14  Rationale for combining diet and medications aimed at specific metabolic pathways in cancers. Source: adapted from (79).

signaling transduction pathways; steps in the glycolysis or the TCA cycle pathways; and transporter proteins like glutamine transporter. The main conclusion from the hypothesis that cancer is a metabolic disease is that restricted energy intake can regress tumor growth. The field has come a long way owing to decades of research, including the pioneering efforts of Steven Mittelman and colleagues. This includes research scaling up from an early recognition of the role adipocytes play in metabolic syndromes (184) all the way to the preclinical effects of a low-fat diet on acute lymphoblastic leukemia (150), and the effects adipocytes have in the metabolism of chemotherapeutics (35, 38, 137). It is understood that if appropriately combined with drugs targeting abnormal metabolism of tumors, energy-restricted diets and an improved lifestyle can provide a reasonable strategy for managing different cancers.

9.3 Alzheimer’s Disease: Another Chronic Metabolic Disease Like cancer, Alzheimer’s disease (AD) provides another example of a chronic metabolic disease state characterized by insulin resistance, mitochondrial dysfunction, and an overreliance on glycolytic metabolism. Metabolic compromise with reduced glucose metabolism is often present for many years prior to the onset of clinical dementia. Here we describe AD, a representative neurodegenerative disorder, as a metabolic disease state. This discussion is cast in the context of its relationship to cancer and the associated Warburg effect. It invokes an understanding of the related phenomena of the Reverse and Inverse Warburg effects, as well as insulin resistance in the pathogenesis of the disease (Figure 9.15). Metabolic dysfunction is tantamount to the mitochondrial dysfunction that underlies the pathogenesis of chronic disease states. While cancer cells flourish during upregulated aerobic glycolysis that outcompetes host cells for nutrient resources to serve their metabolic demands, AD occurs when neuronal cells are unable to upregulate glycolysis. This is the fundamental distinction in the metabolic pathogenesis of these two disease states.

9.3.1 Amyloid Beta and Synaptic Dysfunction In 1906, Alois Alzheimer described the neuropathological findings in the brain at the autopsy of a patient who had developed memory loss, personality changes, and language

problems (185). The patient’s brain had deposits of neurotoxic, soluble, oligomers of the protein Aβ in the synaptic space. Aβ plaques were first purified and characterized in the 1980s by Glenner and Wong (186, 187). Aβ interferes with insulin receptor tyrosine kinase activity and acts as a competitive inhibitor of insulin, reducing the affinity of insulin for its own receptor. Soluble Aβ may even be responsible for the removal of insulin receptors. Insulin inhibits Aβ binding to the synapse and reduced insulin levels in the brain allow Aβ plaque formation and AD progression. Accumulation of Aβ plaques leads to synaptotoxic effects in the hippocampus and other brain regions responsible for memory and cognition. The extent of memory and cognitive compromise correlates with region specific synaptic dysfunction rather than the burden of Aβ (188–193). Insulin treatment may be a means of fighting AD. Intranasal insulin is an experimental treatment option that might protect synapse from Aβ plaque accumulation by decreasing Aβ binding sites. Intranasal insulin accesses the brain through the trigeminal nerve and olfactory bulb (194–198). The insulin sensitizer rosiglitazone has been shown to increase the degradation of insoluble Aβ, which attenuates learning and memory deficits in AD.

9.3.2 The Shared Pathogenesis of Insulin Resistance and Alzheimer’s Disease The pathological features of insulin resistance and Alzheimer’s are interwoven and share many similarities. For example, while insulin resistance may be defined by low high-density lipoproteins and high triglyceride levels, these same characteristics are also features of AD. Moreover, amyloid formation is both a hallmark of AD and a common condition present with insulin resistance. Another striking similarity between insulin resistance and AD is glucose hypometabolism, characterized by the brain’s inability to use glucose as its primary energy source. Hypometabolism, as quantified by fluorodeoxyglucose (FDG) and positron emission tomography (PET) scanning is found in the prefrontal neocortex, the hippocampus, and other subcortical areas—the primary brain regions impacted by AD. Dysfunction in these brain regions contributes to cognitive decline in AD including impairments in learning, memory consolidation and retrieval, processing speed, cognitive flexibility, and visual motor skills. All of these cognitive impairments are accelerated by systemic insulin resistance. Early insulin resistance in the brain may be associated with pathological changes prior to cognitive dysfunction, thus, early detection may open the opportunity for preventive diagnostic and treatment strategies. However, cognitive deficits already present are generally irreversible but may be slowed. Mitochondrial dysfunction (with impaired bioenergetics) is a hallmark of insulin resistance and may be one of the underlying mechanisms of cognitive decline. Importantly, mitochondrial function and insulin resistance are bidirectionally interrelated (see Chapter 8, Section 8.3.3). They are both affected by the same major factors including inflammatory and redox stress, which are also bidirectionally interrelated. A central feature of insulin resistance is the presence of the inflammatory M1 macrophage in adipose tissue. This phenotype

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FIGURE 9.15  The inverse and reverse Warburg effect in the pathogenesis of AD. Glycolysis is the main source of energy production in astrocytes, where glucose is metabolized to lactate, and lactate is released into the extracellular environment. Neurons, whose preferred mode of energy generation is oxidative phosphorylation, can then use lactate as an additional energy source. During aging, a subset of impaired neurons upregulates oxidative phosphorylation to compensate for inefficient energy production. However, neurons undergo hypometabolism (reduced oxidative phosphorylation) as this equilibrium collapses, which leads to AD progression. The hypermetabolic state of neuronal oxidative phosphorylation leads to increased oxidative stress, inflammation, insulin resistance, further mitochondrial dysregulation, and increased levels of amyloid beta (Aβ). Insulin resistance impairs the degradation and clearance of Aβ from the brain. Mitochondrial dysfunction promotes insulin resistance, with insulin resistance reciprocally exacerbating mitochondrial dysfunction. *Mt = mitochondria; ROS = reactive oxygen species.

putatively promotes and perpetuates subclinical inflammation along with systemic circulating cytokines and other proinflammatory mediators, and subsequent insulin resistance (Figure 9.16). Inflammatory stress, redox stress, mitochondrial dysfunction, and insulin resistance all contribute to cognitive decline. When brain mitochondrial dysfunction occurs in association with brain insulin resistance, AD may develop. Several studies consistently showed that mitochondrial dysfunction is responsible for cognitive impairment in animals that have genetically-induced obesity and insulin resistance. This suggests that mitochondrial dysfunction plays a key role in both insulin resistance and cognitive decline (199). AD and insulin resistance have a shared pathogenesis (200– 210). During insulin resistance, chronic elevation of circulating glucose causes glycation of proteins and lipids, forming advanced glycation end products (AGEs). AGEs are capable of activating proinflammatory receptors for advanced glycation end products (RAGEs). This creates a self-perpetuating cascade of inflammatory cytokines, which are further amplified by the central inflammatory transcription factor, NF-kB.

Proinflammatory mediators are similarly elevated in the blood and cerebrospinal fluid in AD. While AGE activation of RAGEs is a traditionally recognized feature of insulin resistance and type 2 diabetes, this process is also present in AD. AGE activation of RAGEs leads to the formation of Aβ plaques and promotes the hyperphosphorylation of tau protein in neurofibrillary tangles—two main features of AD.

9.3.2.1 Dyslipidemia One of insulin’s functions is to inhibit lipolysis in adipose tissues and de novo lipogenesis (DNL) in the liver. During fasting, circulating insulin levels are low and levels of both adipose triglyceride lipase (ATGL) and hormone-sensitive lipase (HSL) are increased in white adipose tissue. This causes enhanced lipolysis of stored triglycerides (TG) and the release of free fatty acids (FFAs) into the blood. FFAs that reach the liver are resynthesized into TG, secreted in the form of apolipoprotein B (ApoB)-containing lipoprotein particles (also known as very-low-density lipoprotein [VLDL]). During

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FIGURE 9.16  Proinflammatory M1 macrophages and cytokines cause inflammation and redox stress in adipose tissue, which contributes to insulin resistance and mitochondrial dysfunction in a bidirectional, self-amplifying feedback loop. Mitochondrial dysfunction and insulin resistance are associated with cognitive impairment and Alzheimer’s disease.

insulin resistance, this lipoprotein metabolism is impaired and may cause dyslipidemia, an insufficient or excess amount of lipids in the blood. Dysfunction of lipoprotein lipase is another mechanism leading to dyslipidemia (211). Dyslipidemia is a common feature in individuals with diabetes, obesity, poor diet, and lack of exercise. The exact mechanistic connections between dyslipidemia and Alzheimer’s disease have not been fully elucidated, but emerging research suggests a strong connection (Figure 9.17). Genes for lipid metabolism may predict Alzheimer’s risk. For example, the apolipoprotein E (ApoE) genes are involved in cholesterol metabolism and transport. The apoE4 isoform contributes to the pathogenesis of AD. Another connection between dyslipidemia and Alzheimer’s disease is cell membrane lipid rafts. Lipid rafts promote the generation and

FIGURE 9.17  A putative set of events connecting peripheral metabolic dysregulation to dementia. In the setting of type 2 diabetes, hyperglycemia, dyslipidemia, increased circulating free fatty acids and elevated AGEs levels may increase blood-brain barrier permeability, allowing for an influx of FFAs into the brain, resulting in the release of proinflammatory cytokines, which in turn can trigger detrimental events in neurons. Such detrimental effects in the brain include insulin resistance-induced cognitive impairment and Alzheimer’s disease (211). *AGEs = advanced glycation end products; ER = endoplasmic reticulum; FFAs = free fatty acids.

aggregation of Aβ (212–215). Further, it appears that both insulin resistance and apoE4 allele-mediated mechanisms independently contribute to abnormal Aβ plaque accumulation in the brain, and thus to the pathogenesis of Alzheimer’s disease (210). High apoB-containing low-density lipoproteins (LDL) in the central nervous system (CNS) are also linked to AD, independent of AD susceptibility alleles (216).

9.3.3 The Role of Amylin in Amyloid Beta Accumulation Amylin (also known as islet amyloid polypeptide) is cosecreted with insulin to regulate metabolism and contributes to pancreatic beta cell deterioration and progression to type 2 diabetes. It also accumulates in the brain, which might make it important in promoting Aβ accumulation in AD (217, 218). Amylin colocalizes with Aβ in the brains of patients with AD, independently of a type 2 diabetes diagnosis. Insulin resistance is associated with impaired trafficking of Aβ, including the efflux of intracellular Aβ (210). Another point of convergence between insulin resistance and AD is the metalloproteinase insulin-degrading enzyme (IDE), which is important for the degradation of both insulin and Aβ. Insulin resistance-associated hyperinsulinemia competes with Aβ for breakdown by the IDE. Accordingly, the high levels of circulating insulin interfere with the normal Aβ degradation, allowing it to accumulate. During aging, this progressive accumulation of Aβ reduces the transport of insulin across the blood–brain barrier, although it’s unclear how insulin levels in CSF affect AD risk (220). Moreover, soluble Aβ potentiates insulin resistance in the brain by directly binding to the insulin receptor, impairing insulin signaling. This soluble Aβ-induced insulin resistance appears to be the critical link to tau hyperphosphorylated neurofibrillary tangles (221). Further, peripheral hyperinsulinemia inhibits the efflux of Aβ out of the brain (222, 223). Thus, insulin resistance and AD potentiate each other. Alzheimer’s disease has an apparent reciprocal relationship with insulin resistance whereby both states potentiate each other.

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9.3.4 Alzheimer’s Disease and the Reverse Warburg Effect The healthy brain prefers glucose as a metabolic fuel over fatty acid oxidation. Overall, aerobic glycolysis accounts for about 10–15% of glucose metabolism in the normal brain (224). Brain glycolytic upregulation is limited and unable to accommodate unusually wide compensatory requirements. This is in contrast to robust upregulation of glycolytic metabolism in rapidly proliferating immune cells or cancer cells (the “Warburg effect”). In the case of crisis, brain neurons rely on upregulated oxidative metabolism. However, neuronal fatty acid oxidation requires more oxygen than glycolysis, increasing the risk of hypoxia in conditions of ischemia. Further, the process of fatty acid oxidation in the brain has both a slower rate of ATP production and an increased generation of reactive oxygen species. This becomes especially problematic because the neurons of the brain have a lower capacity to handle oxidative stress via antioxidant systems. This oxidative stress may potentiate Alzheimer’s disease. Therefore, oxidative metabolism is the inferior mechanism of energy production in the brain, as compared to aerobic glycolysis, during non-crisis scenarios. During crisis scenarios of upregulated oxidative metabolism in the brain, astrocytes vigorously upregulate glycolysis, supplying the neighboring neurons with lactate through the lactate shuttle. The neurons convert this lactate to pyruvate, which is oxidized in the mitochondria via the TCA cycle and oxidative phosphorylation. This process is called the “reverse Warburg effect”. The reverse Warburg effect has been described but never conclusively confirmed in cancer research.

SIDEBAR 9.3: BRAIN FUEL SOURCES CHANGE DURING ALZHEIMER’S DISEASE The brain exhibits metabolic flexibility in the sense that it utilizes different fuels to adapt over the various stages of Alzheimer’s disease. Decades prior to onset of signs of dementia: glucose is the major fuel for the brain. Hypermetabolic responses compensate for subclinical disease rooted in mitochondrial dysfunction. They are also fueled by lactate from the reverse Warburg effect. Early in the disease course: ketone bodies (α-hydroxybutyrate, acetoacetate, and acetone) are the preferred fuel source. Activities of pyruvate dehydrogenase (PDH) and α-ketoglutarate (α-KG) enzyme complexes, crucial for oxidative mitochondrial metabolism, are reduced (225–228). Progressive loss of mitochondrial function accompanies worsening oxidative stress, amyloidogenesis, and insulin resistance. Mitochondrial functional reserve can no longer compensate and deteriorates into a glucose hypometabolic state (229). Ketone bodies are a rich source of mitochondrial ATP production. Ketone bodies are efficient: they require less oxygen per molecule of ATP produced than fatty acid oxidation, reducing hypoxia risk. Ketone bodies upregulate monocarboxylate transporters, which increase the transport of glucose and pyruvate across the blood–brain barrier (230–232); for a review, see (233).

Metabolism and Medicine

9.3.5 Insulin Resistance, Mitochondrial Dysfunction, and Oxidative Stress in Alzheimer’s Disease Insulin resistance may be at the core of Alzheimer’s disease (Figure 9.18). Insulin resistance impairs the export of Aβ into the extracellular space as well as degradation and clearance of Aβ from the brain. Mitochondrial dysfunction promotes insulin resistance, and insulin resistance reciprocally exacerbates mitochondrial dysfunction in a feedforward fashion. Furthermore, these two disease states contribute to Aβ-mediated interference of insulin receptors. Moreover, reduced insulin signaling promotes hyperphosphorylation of intracellular tau, which creates a vicious cycle that further impairs insulin signaling. We propose that insulin resistance and mitochondrial dysfunction are responsible for the hypometabolic state of glucose utilization present in Alzheimer’s disease. Other AD mechanisms that interfere with energy metabolism most commonly involve α-mediated impairment of Complex IV activity in the mitochondrial respiratory chain (235–237). This inhibits ATP production and promotes reactive oxygen species (ROS) accumulation which, in a feedforward fashion, perpetuate mitochondrial dysfunction (238, 239). Aβ also interferes with intracellular calcium channels and calcium homeostasis, which appears to promote hippocampal neuronal apoptosis. Insulin and pioglitazone administration ameliorate the effects of Aβ on calcium, further supporting the interplay of insulin resistance and AD (240, 241). Future research might uncover relationships between genetic predisposition for impaired mitochondrial glucose metabolism and predisposition for AD. Mitochondrial DNA is maternally inherited. Current research suggests that maternal family history of AD is predisposing for impaired glucose metabolism in the brain, though it is not clear if genetic predisposition for impaired glucose metabolism causes AD (242–246). Predicting AD predisposition from blood glucose levels would be a valuable diagnostic clinical tool. Preventative therapeutic approaches could then be applied such as non-pharmacological treatment for insulin resistance, which has already shown promise in improving cognitive function (199).

9.3.6 The Brain’s High Energy Requirements Make It Susceptible to Mitochondrial Dysfunction The human brain consumes ~25% of the body’s energy, despite being only about 4% of the body’s total weight. Thus, the brain is highly dependent on functional mitochondria. It follows that the accumulation of dysfunctional mitochondria leads to increased susceptibility to all neurodegenerative disorders including Parkinson’s disease, multiple sclerosis, AD (see Section 9.3.6), and accelerated cognitive decline due to aging. Alzheimer’s dementia, similar to other neurodegenerative disorders and chronic diseases of aging, is rooted in disturbed redox and energy homeostasis. Since cell mitochondria are central to both of these processes, it is not surprising that they are also central to programmed cell death, or apoptosis, of neurons that are involved in neurodegeneration. While effective mitochondrial function provides the high energy requirements of neural physiology and cognition,

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FIGURE 9.18  Insulin resistance in the development of Alzheimer’s disease (AD). Mitochondrial dysfunction with impaired bioenergetics and increased oxidative stress are shared features of the pathogenesis of insulin resistance and AD. Brain insulin resistance in type 2 diabetes can lead to the accumulation of toxic amyloid β (Aβ) plaques in the synaptic space in the hippocampus, producing cognitive decline characteristic of AD. Aβ plaques can, in turn, exacerbate brain insulin resistance, further accelerating cognitive decline. Genetic and environmental factors independently and synergistically contribute to the development of type 2 diabetes, brain insulin resistance, and predisposition for AD. Source: adapted from (234). *Aβ = amyloid β; AD = Alzheimer’s disease; AGEs = advanced glycation end products.

mitochondrial dysfunction becomes an aggressive and feedforward generator of ROS that endanger the structure/function and ultimately, viability of neural cells. Mitophagy, the degradation of mitochondria through autophagy, is thus an adaptive process to preserve nervous system physiology. Impairment of this process is an early driver in the pathogenesis of Alzheimer’s and other neurodegenerative diseases including Parkinson’s disease, amyotrophic lateral sclerosis (ALS), and Huntington’s chorea (247, 248). In addition to the energy deficit described above, redox stress is also important in the etiology and early pathogenesis of AD and other major chronic disease states. Redox stress induces mitochondrial dysfunction and promotes cerebral insulin resistance and consequentially, the amyloid beta and tau pathological sequelae. Alternatively, brain insulin resistance may be the primary instigating event of AD pathology. Brain insulin resistance triggered by neural ectopic lipid droplets of ceramide, for example, results in a self-amplifying feedforward loop of insulin resistance and mitochondrial dysfunction. Lipid microdroplets in neurons of the brain, such as those in the hippocampus and the amygdala, may promote accelerated cognitive decline, including Alzheimer’s disease. Accumulation of certain types of lipids, such as ceramides and likely diacylglycerol, have been shown to cause mitochondrial dysfunction. It has been proposed that this occurs through disturbed redox and bidirectional self-potentiation of inflammation with accompanying impairments in bioenergetics and ATP production of free energy. The high efficiency of glucose utilization to generate ATP through mitochondrial glucose oxidation compared to glycolysis, underlines the importance

of mitochondrial bioenergetics in the brain, which is overwhelmingly reliant on glucose.

9.3.7 Insulin Resistance and Cognitive Decline In contrast to the classical insulin-targeted metabolic tissues such as skeletal muscle and adipose tissue, insulin signaling in the brain appears to play a less prominent role in glucose transport. Rather, insulin signaling serves as a neuromodulator, regulating synaptic release and reuptake of various neurotransmitters in areas such as the hypothalamus and hippocampus, which mediate satiety and learning and memory, respectively (249–252). The role of insulin resistance in cognitive decline due to aging is supported by the presence of insulin receptors in the hippocampus and temporal cortex. Rodent studies show an upregulation of insulin receptors with learning (253). Moreover, intranasal and intravenous insulin has been shown to improve memory in both healthy and insulin-resistant humans (254–256). Insulin-resistant individuals have reduced hippocampal volume and compromised memory (257). The reduction of insulin receptors in the brain that occurs with aging is considered in part to be a manifestation of insulin resistance. Accordingly, rapid cognitive decline correlates with the degree of insulin resistance. This is also applicable to Alzheimer’s disease (see Sections 9.3.5) and to the insulin resistance sequelae of cerebrovascular disease and diabetes. Cerebrovascular disease is attributed to a clustering of insulin resistance and its downstream components of atherogenic metabolic syndrome that cause ischemic vasculopathy and consequentially, neuronal

380 apoptosis and cognitive dysfunction. Diabetes-related toxic hyperglycemia promotes mitochondrial generated redox stress and activation of AGE receptors, which together promote redox stress, mitochondrial dysfunction, and an upregulation of the parallel pathways of glycolysis. In essence, the latter events describe a cerebral equivalent to the Brownlee unifying hypothesis for the patho-etiology of microvascular disease in the eyes and kidneys (251, 258).

9.3.8 Molecular and Genetic Contributors to Alzheimer’s Disease Pathology Neural cell endoplasmic reticulum (ER) stress is an increasingly recognized contributor to the development of AD (259). The function of the endoplasmic reticulum is crucial for the proper geometry of proteins. This entails an elaborate folding process that follows the transcription and biosynthesis of an amino acid sequence. This produces a three-dimensional structure that exemplifies the body’s organizational complexity, considering the space required to produce just the right configuration/structure required for the dynamic functions of these proteins. Proteins, for example, are the biomolecular machine motors that make our muscles contract and generate ion pumps and produce ATP at the terminal end of the electron transport system. However, metabolic conditions, such as oxygenation, glucose levels, and pH need to be within narrow physiologic ranges for this precision process to occur. When they are not, it causes ER stress, impairing the ER’s ability to properly fold proteins. An accumulation of unfolded proteins can result in cell damage via inflammatory responses and redox disturbance. An adaptive cell stress response called the unfolded protein response (UPR) ensues, which attempts to attenuate the precarious danger. This process is mediated by the activation of three sensor proteins located in the ER membrane: IRE 1, ATF 6, and PERK (inositol requiring enzyme-1, activating transcription factor 6, and protein kinase RNA-like endoplasmic reticulum kinase, respectively). The effects of this response include stopping the production of new proteins, inducing autophagy of existing unfolded proteins, and increasing the capacity of the ER to fold new proteins going forward. The UPR is an incredibly adaptive measure. However, like stress at any hierarchical scale, if it persists or it’s too severe, damage is unavoidable. If the sequence of stress resistance programs, such as the upregulation of antioxidant and DNA/cell repair systems and autophagy are insufficient, cell apoptosis ensues as the next level of defense which protects whole body homeostasis. A progressive process of neural cell death in the brain is the fundamental basis of neurodegenerative disease. Mitochondrial dysfunction and ER stress, each a driver of redox disturbance, represent another bidirectional self-amplifying loop that drives AD pathogenesis. While ROS are generated from dysfunctional mitochondria that in turn provoke ER stress, they are also a signal that metabolic homeostasis is threatened, and accordingly mitophagy is triggered. However, depending on the degree of redox and energy imbalance, concurrent cell ER stress may be present and lead to the release of Ca2+ from the ER, which is taken up and accumulated in mitochondria. This signals that the damage is pervasive enough to induce apoptosis to contain the threat

Metabolism and Medicine to metabolic homeostasis. Subsequently, the buildup of Ca2+ stimulates the opening of the mitochondrial permeability transition pores (mPTPs) and, B-cell lymphoma 2 (BCL-2) proteins are activated to induce apoptosis. BCL-2 belongs to a family of proteins that interact under context-dependent conditions in the cell, which determine whether they promote cell survival or apoptosis. When redox and energy compromise to the cell reaches a threshold, the interaction of the BCL-2 family of proteins promotes apoptosis. This is mediated by the release of cytochrome c from the mitochondrial intermembrane space into the cytosol. Since cytochrome c is an electron transport protein loosely bound to the inner mitochondrial membrane where it transfers electrons to Complex III of the electron transport system, loss of this vital protein further exacerbates energy and redox stress. In the cytosol, cytochrome c initiates a cascade of enzymatic caspases. Like all chronic diseases of aging, circumstances that promote the expression of susceptibility genes, such as apolipoprotein E epsilon 4 (APOE-ε4) in the case of AD, can play a role in disease onset. In fact, hereditary predisposition of the APOE-ε4 genotype is potentiated by insulin resistance/ hyperinsulinemia. AD is sometimes referred to as type 3 diabetes or brain insulin resistance since insulin signaling regulation of tau and Aβ metabolism is a root cause of the disease (190). Neural cell resistance to insulin signaling compromises the secretion of Aβ from the cell. Impaired insulin signaling additionally compromises the ability to inhibit tau hyperphosphorylation. Tau can be understood in the important interdisciplinary context of understanding cognition through the perspectives of both biology and modern biophysics. In neurons, tau is a microtubule-associated protein (MAP). Microtubules are crucial for cognition and the fundamental notion of consciousness, “awareness of awareness”, an understanding rooted in the field of quantum biology. This is discussed in detail in the chapter on quantum biology in Volume 1. From the classical biological perspective of insulin resistance, we know that tau hyperphosphorylation in neurons from Alzheimer’s patients is three- to four-fold greater than it is in healthy neurons, and that it suppresses tau’s biological function. Tau hyperphosphorylation impairs clearance of intracellular Aβ. The associated hyperinsulinemia also prevents the clearance of extracellular toxic Aβ due to the competition of insulin with Aβ for degradation by insulin-degrading enzyme (IDE). Consequently, there is a toxic buildup of intracellular insoluble Aβ, which induces ROS that causes cell redox stress, and neurofibrillary tangles of hyperphosphorylated tau. Extracellularly, there is toxic accumulation of fibrillation Aβ plaques. Together, these processes disrupt neural and synaptic function, ultimately causing neurodegenerative dementia (255, 260).

9.3.8.1 The GSK3 Hypothesis of Alzheimer’s Disease Glycogen synthase kinase 3 (GSK3) is an important and underrecognized link between insulin resistance and diabetes to AD. GSK3 is a serine/threonine kinase, and as the name suggests, it’s important in the physiologic inhibition of glycogen synthase and glucose regulation. However, despite its name,

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Chronic Diseases as Metabolic Disorders GSK3 has pleiotropic actions in the cell. These diverse actions include inhibiting skeletal muscle GLUT4 translocation-mediated glucose uptake, a defining feature of insulin resistance, as well as several effects that connect insulin resistance and diabetes to Alzheimer’s (Figure 9.21). The latter effects include suppressing the expression of nuclear factor-E2-related factor 2 (NRF-2), a transcriptional regulator for antioxidant defense programs, and phosphorylation of tau. Insulin signaling through the PI3K/Akt pathway promotes inhibitory phosphorylation of GSK3. In the setting of chronic non-circadian insulin resistance, dysregulated overactivity of GSK3 promotes further oxidation and neuroinflammatory stress. This potentiates insulin resistance and mitochondrial dysfunction, thus instigating multiple feedforward unstable cascades. Moreover, insulin resistance promotes the hyperphosphorylation of tau, which impairs its capacity to clear neural Aβ buildup, further underscoring the link between insulin resistance, GSK3, and Alzheimer’s disease (261-265). More recently, the neuroprotective role of the enzyme biliverdin reductase (BVR), and its inhibitory relationship to GSK3, against oxidative stress that leads to Alzheimer’s disease has been recognized (Figure 9.19). In fact, BVR-A is a member of the insulin receptor substrate family, and its impaired functioning is frequently present in the setting of Alzheimer’s disease. BVR is well known for reducing biliverdin to bilirubin as the second step in heme catabolism. It is now understood to also be a coactivator protein of insulin-stimulated Akt-mediated inhibition of GSK3, thus underpinning its role in insulin signaling-induced cell redox stress resistance and protection against Alzheimer’s disease pathogenesis. BVR has been identified as an early biomarker for Alzheimer’s disease, with a high ratio of matrix metallopeptidase 9 to BVR in the blood. Intriguingly, bilirubin itself has potent antioxidant properties. It follows that BVR and GSK3 represent promising therapeutic targets for the treatment and potentially prevention of Alzheimer’s disease (266–269).

9.3.9 Pharmacologic Therapies for Alzheimer’s Disease In his almost three decades of clinical experience, this author has yet to see a tangible benefit from existing pharmacologic therapies such as Aricept® (acetylcholinesterase inhibitor) and Namenda® (N-methyl-D-aspartate (NMDA) receptor antagonist) in the treatment of AD or accelerated cognitive decline of aging. A range of current drug therapies for diabetes are actively being investigated that may hold promise to be repurposed for these indications. The strong underpinning of insulin resistance and diabetes in the pathogenesis of AD provides a rationale for why such drugs could work for this indication. AD seems to have components of both insulin deficiency and excess in the brain, although type 1 (insulin-deficient) diabetes has a much lower incidence of developing AD than type 2 (insulin-resistant) diabetes. It makes sense to explain the discrepancy as exogenous insulin excess being extracellular, whereas deficiency of insulin in the brain is not typically a deficiency per se, but rather reduced intracellular insulin signaling. However, actual insulin deficiency may occur as a result of pancreatic beta cell exhaustion with endogenous insulinopenia, which may evolve into type 2 diabetes, in addition to causing interruptions in the blood–brain barrier transport of insulin which is also described in AD, accounting for low insulin levels in some patients. Nonetheless, regardless of these nuances, there is reason for optimism for several pharmacologic strategies of protecting neural insulin signaling against the damaging effect of Aβ. Glucagon-like peptide-1 receptor (GLP-1) agonists are increasingly employed in the clinical practice of type 2 diabetes management as first-line agents. These agents are technically insulin secretagogues because they enhance beta cell insulin secretion. However, they indirectly improve insulin sensitivity by several mechanisms that include antagonizing glucagon release, improving the physiologic pattern of insulin release,

FIGURE 9.19  The Role of GSK3 in Alzheimer’s disease. The diverse actions of GSK3, including the inhibition of GLUT4 and the activation of neuroinflammatory stress, affect insulin resistance and further contribute to Alzheimer’s disease. *Akt = protein kinase B; BVR = biliverdin reductase; GLUT4 = glucose transporter type 4; GSK3 = glycogen synthase kinase 3; Keap1 = Kelch-like ECH-associated protein 1; NRF-2 = nuclear factorE2-related factor 2; IR = insulin receptor; IRS = insulin receptor substrate; P = phosphate.

382 and promoting weight loss by enhancing satiety. Alternative drugs in this class are growing with the recent availability of dulaglutide and semaglutide. Older drugs in this class, exenatide, and liraglutide, have been shown to mitigate Aβ antagonizing effects on insulin signaling, particularly at the insulin receptor substrate (IRS) node, and to reduce the progression of Alzheimer’s pathology (258, 270). An intriguing aspect of GLP-1 is the discovery of both hormonal and neurotransmitter systems, with the latter involving various parts of the brain such as the motivation reward centers of the limbic system. Accordingly, there is data showing a relationship of GLP-1 to various addictive behaviors (271, 272). A relationship to insulin resistance and AD will certainly be explored. Peroxisome proliferator-activated receptors gamma (PPARγ) agonists are the only drug class that are true insulin sensitizers defined by insulin clamp studies. The insulinsensitizing effects of these drugs are largely a consequence of favorably changing the topography of lipid stores away from ectopic sites, such as the liver and skeletal muscle, and replacing it with increased subcutaneous adipose tissue (SAT) lipid storage. By expanding SAT storage capacity, ectopic lipid droplets in the brain, such as the proinflammatory ceramides, are reduced. Additionally, PPARγ agonists have been demonstrated to reduce Aβ-promoted inflammatory responses of microglia and monocytes. Consequently, this protects against Aβ neurotoxicity of AD (273, 274). Rosiglitazone, a PPARγ agonist and antidiabetic medication, has become a target of interest for Alzheimer’s drug development. Patients with early cognitive impairment and AD treated with rosiglitazone showed preserved cognition over a six-month period (275). However, two phase-three clinical studies showed that an acetylcholinesterase inhibitor (such as Aricept®) combined with a PPARγ agonist is no better than acetylcholinesterase inhibitors alone at improving cognitive function in patients with mild to moderate AD (258, 276). Some studies suggest that rosiglitazone may contribute to adverse cardiovascular outcomes. However, the assertions of rosiglitazone promoting heart failure and cardiovascular disease turned out to be overstated and untrue, respectively. Further, low dose Pioglitazone is now often used as first line management of type 2 diabetes. It is therefore not unlikely that further studies will be looking at PPARγ agonists for the dual management of AD and insulin resistance with or without diabetes. Biguanide metformin is perhaps one of the most promising oral agents currently used to treat type 2 diabetes, with the potential future to manage AD. While metformin is not an insulin sensitizer per se, it does have insulin-sensitizing effects on the liver and brain. In the liver, it enhances the insulin signaling suppression of hepatic gluconeogenesis via the IR-IRS-1 to PI3K to Akt pathway for inhibitory phosphorylation of FOXO1, the master transcriptional regulator of gluconeogenic enzymes (277). In the brain, metformin sensitizes insulin signaling via the Akt pathway which results in mTOR upregulation of protein phosphatase 2A (PP2A). PP2A is the major mechanism of tau dephosphorylation, thus reducing the hyperphosphorylation of tau and preventing its detachment from microtubules, which prevents microtubule instability and tau neurofibrillary tangles, a hallmark of AD (278).

Metabolism and Medicine While these findings are encouraging, there are also reports that conflict with the notion that metformin is categorically favorable in the treatment or prevention of AD. Metformin monotherapy has been shown to increase the biogenesis of Aβ peptides, an AMPK-dependent process leading to both intracellular and extracellular Aβ in the brain. However, insulin therapy has the opposite effect of reducing neural cell amyloid accumulation, and there is an insulin-sensitizing synergistic effect of metformin in combination with insulin therapy to potentiate Aβ reduction (279). Taken together with the impact of metformin on preventing tau hyperphosphorylation and preserving microtubule stability which prevents neurofibrillary tangles, combination metformin/insulin therapy may be the ideal mechanistic tool for addressing the pathogenesis of AD. Seemingly analogous is epidemiological data showing that combination of metformin therapy with insulin secretagogue sulfonylureas, promoting endogenous hyperinsulinemia, reduces diabetes-related incidence of AD by 35% over a period of eight years (280). The intranasal route is the ideal strategy for administering insulin. It evades the obstacle of impaired insulin transport through the blood–brain barrier often present in AD patients and avoids the risk of hypoglycemia. Several studies show a link between intranasal insulin and improved cognition in patients with AD. For example, intranasal insulin improved the retention of verbal information in patients suffering from AD or mild cognitive impairment (281), while patients with mild-to-moderate symptoms of AD show reduced Tau-toAβ42 ratios and improvements in standardized cognitive tests after treatment with intranasal insulin (282). Insulin may exert its positive effects on cognition through its known role in the regulation of neurotransmitter receptors, such as N-methyl-D-aspartate (NMDA), α-amino-3hydroxy-5-methyl-4-isoxazole propionic acid (AMPA), and γ-aminobutyric acid (GABA), and through mediation in other neuronal signaling pathways (283). However, insulin’s positive effects may differ depending on the patient’s genetic risks for AD. For example, verbal memory, defined as remembering a story or a list of words, is improved with intranasal insulin in patients with AD or mild cognitive impairment who lack the APOE4 gene, whereas those who are APOE4+ show memory decline with intranasal insulin (281, 284). An ongoing trial known as the Memory Advancement by Intranasal Insulin in Type 2 Diabetes (MemAid) is currently evaluating intranasal insulin for positive improvements in memory and cognition in older people with type 2 diabetes (285). Indeed, intranasal insulin is a hot research pursuit with high expectations for controlling the devastating toll of Alzheimer’s dementia among insulin-resistant patients with and without diabetes (258, 286). Aβ is both a hallmark of Alzheimer’s and a common condition present with insulin resistance. Aβ interferes with insulin receptor tyrosine kinase activity and competes with insulin for binding to the insulin receptor. Reduced insulin levels in the brain lead to the formation of Aβ plaques and to cognitive decline characteristic of Alzheimer’s. In turn, Aβ plaques exacerbate brain insulin resistance, further accelerating cognitive decline

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(See Chapter 9). The amyloid hypothesis posits that Aβ formation drives neurodegeneration and AD progression. However, antibody targeting of Aβ has failed to produce meaningful cognitive improvements in humans [Doody, et al. 2014; Salloway, et al. 2014; Relkin, et al. 2017; Egan, et al. 2018]. Preliminary data shows that the novel compound aducanumab may reduce Aβ plaques and improve cognition in Alzheimer’s patients. From what we know about insulin signaling and Aβ, reduction of plaque load may indirectly improve insulin sensitivity in the brain, which would further improve cognitive symptoms. WHAT IS ADUCANUMAB? Aducanumab is a high-affinity, fully human monoclonal antibody that binds aggregated soluble and insoluble forms of Aβ. It was generated from the blood lymphocytes of older individuals with no or unusually slow cognitive decline [Decourt, et al. 2021]. WHAT IS ADUCANUMAB’S MECHANISM OF ACTION? Aducanumab reduces Aβ plaques by binding aggregated Aβ and recruiting microglia to amyloid deposits [Sevigny, et al. 2016]. Aducanumab binds to soluble Aβ and keeps Aβ from interacting with metabotropic receptors, which may ultimately improve cognitive function. Aducanumab produces a dose and time-dependent reduction of Aβ plaque levels in the brain compared to placebo. Aducunumab also reduces the levels of phosphorylated Tau, another hallmark characteristic of Alzheimer’s, in cerebrospinal fluid. WHAT ARE THE CLINICAL BENEFITS OF ADUCANUMAB? Aducanumab led to significant improvements in memory, orientation, and language, as well improved capacity to achieve day-to-day tasks including cleaning, doing laundry, traveling out of the home independently, and taking care of personal finances. If confirmatory trials show positive results, aducanumab would be the first therapy to both remove amyloid plaques and produce positive effects on cognition.

9.4 Metabolic Cardiomyopathy 9.4.1 An Overview Cardiovascular disease is the major cause of disease and death worldwide across different age groups (287). Heart failure is a common route of most, if not all, cardiovascular disease, which currently affects more than six million Americans (288). With a five-year mortality of approximately 50%, heart failure has posed a tremendous burden on our healthcare and socioeconomic system. Despite paramount clinical relevance

and extensive scientific interests, our understanding of heart failure remains rudimentary. As a matter of fact, there is currently no cure for heart failure. Under various cardiovascular disease conditions, the heart responds by profound remodeling and manifests different levels of cardiomyopathy. The underlying reason is the acute, adaptive reaction to external stress, which is essential for the heart to maintain pumping function. On the other hand, this weakens the heart over time. This so-called compensatory response usually goes awry and succumbs to failure under persistent, unresolved stress, such as uncontrolled, long-term hypertension (289). From a normal, functional machine to a defective engine, the heart undergoes remodeling at multiple levels, including structure, electrophysiology, function, etc. (290). Importantly, numerous studies have firmly established that metabolic remodeling precedes the majority, or even all, of other changes in the heart (291, 292). This phenomenon highlights the essential role of metabolic remodeling during cardiomyopathy development and argues that metabolic cardiomyopathy is probably coupling all forms of cardiovascular insults to heart failure development. In this section, we first discuss the various types of cardiomyopathy with a focus on metabolic disturbance as a central theme. We conclude by highlighting several pharmacological approaches to target metabolism in tackling devastating cardiovascular disease.

9.4.2 Physiological Cardiac Hypertrophy Hypertrophic growth is the only avenue for the heart to develop from the infant stage to early adulthood due to the limited replicating capacity of cardiac myocytes (293). This postnatal hypertrophic growth is driven by the increased demand for circulation. The enlargement of individual cardiac myocytes leads to an increase of heart size that at the same time enhances cardiac pumping function. The phenomenon of physiological cardiac hypertrophy was first reported in 1899 among cross-country skiers. It was later again reported in 1955 by Winsor and colleagues who used electrocardiograms in marathon runners to examine differences in hypertrophy that occurred as a result of prolonged physical exertion compared with hypertrophy occurring due to various states of disease. This study found that among marathon runners there was a characteristic high voltage QRS complex (indicates ventricular depolarization) and T wave (indicates ventricular repolarization), which suggests cardiac hypertrophy (294). The latter findings were distinct from the changes seen in a comparison cohort of patients with hypertrophic heart disease secondary to hypertension or aortic valve disease. Nonetheless, the idea of physiological cardiac hypertrophy remained under the radar and essentially unrecognized until the late 1980s. This adulthood cardiac hypertrophic growth is accompanied by no changes or slightly improved systolic and diastolic functions of the heart (295). Two common scenarios of physiological cardiac hypertrophy are pregnancy and exercise training. Under both situations, the heart manifests ventricular hypertrophic growth and maintains chamber size to accommodate elevated physiological requirements of blood pumping.

384 Both aerobic and resistance (with high repetitions) training increase sympathetic autonomic activity. The enhanced heart rate and contractility thus promote nutrient and oxygen delivery to satisfy metabolic demands, peripherally to exercising muscle as well as to the brain for attention and cognition. The notion of maximal oxygen consumption (VO2 max), which occurs after two to three minutes of strenuous exercise and is defined as the volume of oxygen consumed per minute, is significant because it underscores cell mitochondrial capacity for respiration. In the authors’ opinion, this is an underutilized index of mitochondrial function and accordingly, of metabolic insulin sensitivity in clinical healthcare and medicine. Secondarily, the contracting myocardial cells of the heart also have increased metabolic demands for fuel and oxygen. The transition at the start of life outside the mother’s womb accompanies dietary fat intake and a higher oxygen (more oxidative) environment that fundamentally promotes a switch in fuel preference from glucose to fatty acids (296). The newborn’s gene expression profile has increased the encoding of enzymes and other proteins involved in fatty acid uptake and its oxidative metabolism. Nonetheless, in the healthy postnatal heart, glycolytic metabolism of glucose-mediated by insulinresponsive (glucose transporter type 4 - GLUT4) and insulinindependent (GLUT1) cell uptake is unperturbed. Glucose mediated by GLUT4 remains an additional fuel source that can be further oxidized in the mitochondria following the initial glycolysis phase if fatty acids are less available (297). In the adult heart, glucose uptake becomes the preferred substrate over fatty acids; this is because glucose oxidation has greater efficiency of oxygen consumption relative to the amount of ATP produced. Furthermore, non-energy producing pathways that branch off glycolytic intermediates help provide the building blocks of cardiac cell growth as well as signaling. For example, the kinase mTOR (mammalian/mechanistic target of rapamycin), a central player of protein synthesis and cell growth, may be activated by the serine biosynthesis pathway branching off of glycolysis (298). Thus, glycolysis is a crucial and adaptive mediator of physiological cardiac hypertrophy, so long that it is coupled to mitochondrial oxidative metabolism. More about glycolytic intermediates in promoting cardiac hypertrophic growth will be discussed in pathological hypertrophy. The prolonged, elevated demands of cardiac contraction and afterload pressure are adaptively coupled to myocardial growth to prevent mechanical failure in much the same way that skeletal muscle grows in response to weight lifting (295). The initial growth signals, in addition to mechanical forces and vascular endothelial growth factor (VEGF), are largely the classical hormones that include insulin, insulin-like growth factor (IGF-1), thyroid and growth hormones. These signals are transduced through pathways that promote macromolecule anabolism of cardiac myocytes and support angiogenesis accompanying the necessary production of ATP (299). For example, the active form of thyroid hormone, T3, signals through the thyroid nuclear hormone receptor to transcriptionally regulate contractile and associated calcium handling proteins, beta-adrenergic receptors, and ion channels. The integrated matrix of hormonal interactions is highlighted by

Metabolism and Medicine the convergence of thyroid, IGF-1, VEGF, and insulin that all transduce through the central PI3K/AKT signaling pathway (300). While the signaling complexity is enormous and highly nuanced, the overshoot is the promotion of protein synthesis and cell growth and, at the same time, a commensurate regulation of AMPK to accommodate the bioenergetic demands of ATP production. Metabolic coordination requires: 1) efficiency of oxygen consumption and 2) the optimal nutrient fuel substrate for sufficient production of ATP. It is temporally synchronized with the capacity for glucose oxidation to its maximum availability during the active and fed state while flexibly switching to fatty acid oxidation during the circadian inactive and fasting state. This metabolic flexibility is an equitable term for circadian nocturnal insulin resistance, while non-circadian insulin resistance is tantamount to metabolic inflexibility. Glucose uptake into the cardiac myocyte that occurs by insulin and non-insulin-dependent transporters enters the glycolysis pathway of energy production. If excessive fatty acid oxidation occurs during the fed state, there is inhibition of glycosylation and glucose mitochondrial oxidation, according to the Randle cycle (301). The increase in oxygen consumption for fatty acid relative to glucose oxidation results in greater reactive oxygen species generation. As a consequence, this may cause redox stress that damages the molecular fidelity of mitochondrial and other cell structural chemistry, leading to mitochondrial dysfunction and inextricably, insulin resistance. Redox stress is a self-amplifying process by promoting further mitochondrial damage, exacerbating the bioenergetic inefficiency with lower capacity for ATP production per molecule of oxygen consumed (302). Moreover, the generation of redox stress impairs insulin signaling at the stage of PDC (pyruvate dehydrogenase complex) conversion of pyruvate to acetyl-CoA and consequent mitochondrial oxidation through the TCA (tricarboxylic acid) cycle and ETC (electron transport chain). It also promotes a roadblock in the glycolysis pathway. Accordingly, this potentiates the induction of inflammatory and further redox stress via the non-energy producing pathways that branch off the proximal intermediates of the glycolytic pathway. This ancient pathway in the state of synchronized and optimum health is an essential component for maintaining energy, acid-base, and redox homeostasis. Conversely, the de-synchronization and decoupling of glycolytic and oxidative metabolism is the basis for pathogenic insulin resistance, mitochondrial dysfunction, and is the central linchpin for the pathogenesis and evolution of cardiovascular and other chronic diseases (see next section).

9.4.3 Pathological Cardiac Hypertrophy Pathological cardiac hypertrophy is a pathophysiological response to chronic pressure overload, most commonly imposed by systemic hypertension or valvular heart disease (303). One of the biggest differences between pathological and physiological hypertrophy is that the former tends to decompensate and succumbs to heart failure, while the latter largely maintains cardiac output and function. Over the past decades,

Chronic Diseases as Metabolic Disorders numerous studies have explained the molecular mechanisms of pathological cardiac hypertrophy and the transition to heart failure. The most prevalent ones are over-production of reactive oxygen species, the metabolic switch from fatty acid to glucose, and derangements in calcium handling. Despite controversies, most people agree that the heart manifests an acute, adaptive phase of growth in response to pressure overload. This cardiac hypertrophy is instrumental for the heart to ameliorate ventricular wall stress and ensure cardiac output in the early phase of compensation to high blood pressure. However, under persistent, prolonged stress (e.g. uncontrolled hypertension), this adaptation may decompensate, resulting in heart failure. Both the prevention of adaptive hypertrophy and chronic hemodynamic stress may lead to a quick decline of cardiac function and frank heart failure. About two-thirds of cardiomyopathy and heart failure are ischemic in nature, while the remaining one-third are nonischemic etiologies of systolic and diastolic disease (304). In addition to the mechanisms just described, cardiomyopathy may also be onset by hyperglycemia in diabetic patients. Hyperglycemia-induced diabetic cardiomyopathy is mediated by glycolysis-promoted non-energy producing pathways that generate a sugar derivative called GlcNAc. This leads to advanced glycation end products (AGEs) and the stimulation of protein kinase C (PKC). PKC and AGE-induced NFκB and reactive oxygen species promote pro-hypertrophic factors, atrial natriuretic peptide (ANP), and brain natriuretic peptide (BNP). In addition, metabolically challenged conditions are also typically accompanied by hypertriglyceridemia, which may enhance the production of acetyl-CoA from fatty acids and further exacerbate non-energy producing pathways in cardiomyocytes. These pathways are also further potentiated by insulin resistance associated with mitochondrial dysfunction and the production of reactive oxygen species. There is significant heterogeneity and an incompletely understood complexity of heart failure in general, the extent of which has been brought more into focus since the recognition of hypertrophic ventricular dysfunction three decades ago. In the early phase of cardiac hypertrophic growth, insulin signaling in the heart is actually significantly enhanced, which is one of the underlying mechanisms of elevated growth (305). Chronically, however, the prolonged insulin-resistant state manifests as hypertension, and accordingly cardiac hypertrophy results. In this case, cardiac hypertrophy may be a secondary response. Analogously, insulin resistance is associated with several cardiovascular risk factors such as dyslipidemia, hypercholesterolemia, coagulopathy, and most notably, hypertension. Hypertension promotes the formation of plaques in arteries, known as atherogenesis, and ultimately advances cardiovascular disease and cardiomyopathy.

9.4.3.1 Diabetic and Metabolic Cardiomyopathy Cardiomyopathy under metabolically challenged conditions, such as obesity, is called diabetic cardiomyopathy. However, this occurs without any apparent conventional secondary etiologies such as hypertension or occlusive macrovascular

385 disease; thus, the so-called diabetic cardiomyopathy may be better called metabolic cardiomyopathy. Diabetic cardiomyopathy can also occur in the setting of insulin resistance with or without diabetes. Conversely, the term diabetic cardiomyopathy should be reserved for the setting of type 1 diabetes without insulin resistance. The following discussion of cardiac hypertrophy and cardiomyopathy, as distinguished from physiological hypertrophy, concerns primarily pathogenic cardiac hypertrophy in the context of cardiac insulin resistance and disturbed metabolism that ultimately progresses to heart failure. In certain contexts of physiological and pathological metabolic stress, there is an adaptive shift in the preference of carbon fuel substrates in the adult myocardium (289). Changes in metabolic demands or impairments in substrate utilization promote a switch or adjustment in gene expression favoring a given selection and degree of bioenergetic pathways. Fatty acid oxidation in the heart, under baseline physiological conditions, provides up to 70% of energy requirements, with aerobic mitochondrial oxidative phosphorylation contributing an estimated 95% of the ATP produced. Furthermore, in the baseline healthy resting state, this bioenergetic production is only about 20% of maximum mitochondrial capacity. Accordingly, with a stressor such as acute exercise, oxidative phosphorylation may be rapidly and robustly upregulated. Similarly, the stress of fasting may be accommodated by downregulating the glycolytic utilization of carbohydrates, with even greater reliance on fatty acid oxidation. Alternatively, ischemia promotes a metabolic switch away from aerobic metabolism, instead of relying on glycolysis-mediated ATP production by substratelevel phosphorylation, a non-oxygen requiring mode of energy production. The threshold for detection of coronary disease by stress test-induced ischemia is about 70% vessel occlusion (or 50% left main disease). This correlates with the suppression of mitochondrial oxidative phosphorylation. Consequently, AMP levels rise, as does the ratio of AMP/ATP, promoting the activation of AMPK (306). AMPK activates the enzyme phosphofructokinase-2 (PFK-2), hence accelerating the rate of glycolytic flux and production of ATP (307). However, this leads to the accumulation of pyruvate and NADH in the cytosol which inhibits the glycolysis pathway. As a consequence, lactate dehydrogenase expression is elevated to convert pyruvate and NADH to lactate for excretion. This creates a notso-efficient, albeit critical cycle of ATP production. Studies have shown that ATP generated via glycolysis only is essential to maintain ion channels under stress conditions and ensure viability. Loss of this capability may result in stiffness of myocardium and diastolic dysfunction, and even cardiac myocyte death. One possible cause of insulin resistance-induced non-ischemic metabolic cardiomyopathy is lipid overload. Lipid overload is caused by excessive caloric intake which may saturate the storage capacity of adipose tissue, the primary site of nutrient storage. When this saturation occurs, it can cause spill over to other organs, including the heart (308). A lipid-laden heart is a common feature in diabetic cardiomyopathy patients. Under baseline physiological conditions, fatty acid oxidation in the

386 heart provides up to 70% of energy requirements and allows cardiac muscles to quickly adapt to energy demands. In conjunction with lipid overload, fatty acid oxidation in the heart is both continuous and excessive. This disturbs the synchronized design of metabolism aligned to circadian rhythm; that is, it impairs the more efficient and cleaner combustion of glucose that promotes better cardiac performance during periods of high energy demands such as carbohydrate consumption and physical activity challenges (309). This loss of metabolic flexibility is the key manifestation of insulin resistance in the heart under chronic overnutrition. Ectopic fat accumulation is a fundamental component in the pathogenesis of diabetic cardiomyopathy (310). Ectopic fat accumulation is defined as the storage of triglycerides in tissues other than adipose tissue, the primary site of nutrient storage. Ectopic fat accumulation can occur in the heart and skeletal muscles and the consequences of these deposits are organ-specific (311). Ectopic fat accumulation is associated with diabetes, insulin resistance, and obesity. Obesity, commonly defined in terms of body weight or body mass index (BMI), should rather be defined as a state of insufficient subcutaneous adiposity to safely house excess body fat in neutral non-reactive lipid stores. The absence of adequate coupling of lipogenesis to adipogenesis is at the core of lipid storage occurring in organs for which there is no adaptive evolutionary design. The heart is one such organ! Furthermore, the accumulation of fat, including the formation of reactive lipid species in the heart, causes pathological effects of inflammatory apoptosis and myocardial fibrosis. The over-utilization of fatty acids as a fuel source leads to both an energy surplus (a low ratio of AMP/ ATP and inactive state of AMPK) and a high ratio of oxygen consumption/ ATP produced (relative to the oxidation of glucose). This promotes hypertrophic remodeling in an environment of excess superoxide generation and redox stress. All of these events may trigger diastolic dysfunction in the heart. A molecular-level linchpin in the pathogenesis of metabolic cardiomyopathy is the excessive production of reactive oxygen species that paralyzes the glycolytic enzyme glyceraldehyde 3-phosphate dehydrogenase (GAPDH). This is caused by the uncoupling of glycolysis to glucose oxidation in mitochondria. This results in excessive activation of the various non-energy producing pathways causing further redox stress, inflammation, and apoptosis of cardiac myocytes. The redox stress potentiates mitochondrial dysfunction and the associated inflammation induces cardiac insulin resistance. Mitochondrial dysfunction is an impairment of the powerhouse and the major bioenergetic supplier of ATP derived from the oxidation of all macronutrients, glucose, fatty acids, and amino acids. When reactive oxygen species exponentially increase in parallel with deteriorating mitochondrial dysfunction, GAPDH inhibits glycolytic ATP production and imposes an energy crisis. This reduced energy supply is further exacerbated by the increased energetic demands of the hypertrophic response in the heart, together triggering myocyte apoptosis. As a consequence, the death of cardiac myocytes leads to systolic impairment and likely heart failure.

Metabolism and Medicine

SIDEBAR 9.4: INSULIN RESISTANCE AND THE RENIN-ANGIOTENSINALDOSTERONE SYSTEM Another hallmark of insulin resistance is the increase in neurohumoral tone characterized by adrenergic activation and upregulation of the renin-angiotensin system (RAS). Angiotensin II is the main effector of the RAS, although it is also a downstream cleavage product of angiotensinogen released from adipose tissue. Furthermore, aldosterone, the terminal effector of the renin-angiotensin-aldosterone system (RAAS), is also now recognized to play a significant role in the pathogenesis of hypertrophic cardiomyopathy. These effector hormones increase myocardial demand by promoting circulatory overload and peripheral vasoconstriction, as well as direct beta-adrenergic receptor stimulation of the myocardium. Angiotensin II and aldosterone both promote fibrosis of cardiac muscle, in part by inducing cardiomyocyte hypertrophy coupled to the suppression of angiogenesis. Additionally, transforming growth factor-beta (TGF-β) induced by proinflammatory cytokines is robustly pro-fibrotic (and is measurable in blood samples as a biomarker of diastolic dysfunction). This combination of factors leads to interstitial fibrosis, which is largely responsible for a high incidence of fatal cardiac arrhythmias due to involvement of the conduction system. Accordingly, conventional medical treatment of cardiac failure targets the RAAS, adrenergic signaling, and fluid retention (by diuresis). Importantly, beyond optimizing fluid balance to the starling curve and relatively modest dose inhibition of the angiotensin-aldosterone and adrenergic systems, ventricular remodeling and cardiac performance benefits are limited. The promising management of cardiovascular diseases are linked to the growing insights of these disorders as metabolic disturbances.

9.4.4 Non-ischemic Dilated Cardiomyopathy The process of ectopic fat deposition (discussed in Chapter 7, Section 7.4.1.4) in tissues such as the heart and pancreas contributes to cardiomyopathy and diabetes, respectively. The combination of insulin resistance and hyperinsulinemia may pathologically affect the same tissue in different ways. For example, the pathways of insulin signaling in the setting of insulin resistance and hyperinsulinemia have counterbalancing effects on the endothelium (312). Resistance to the insulin signaling PI3K/AKT cascade results in under-stimulated vasodilating nitric oxide (NO) production relative to the hyperinsulinemia-mediated MAPK signaling-induced vasoconstricting endothelin-1 (ET-1; Figure 9.20). This is the molecular explanation of endothelial dysfunction, a prototypical manifestation of insulin resistance and the related metabolic syndrome. It also contributes to the pathogenesis of atherosclerotic plaque and ischemic cardiomyopathy reviewed a few paragraphs below. The distinction between the differential pathogenic effects of insulin resistance versus hyperinsulinemia is rooted in differential insulin sensitivities

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FIGURE 9.20  Impaired insulin signaling pathway in endothelial dysfunction. Hyperinsulinemia/insulin resistance can influence endothelial cell (EC) dysfunction mainly by acting on two specific pathways. It inhibits PI3-kinase and thereby elevates nitric oxidize (NO) production. NO acts as a signaling molecule that causes increased vasodilation in vascular endothelium and reduces the cell adhesion capability of ECs. On the other hand, hyperinsulinemia/insulin resistance activates MAPkinase signaling which regulates the secretion of endothelin-1 (ET-1). ET1 promotes vasoconstriction and induces cell proliferation and expression of adhesion molecule expression in vascular ECs. Source: adapted from (312). *ET-1 = endothelin-1; MAPK = ; NO = nitric oxide; PI3K/ Akt = phosphatidylinositol 3-kinase / protein kinase B signaling pathway.

among the many molecular targets of insulin within a given cell type and across cell types. In the example just given, MAPK/ET-1/vasoconstriction signaling responds to supraphysiological insulin stimulation relative to that of PI3K/Akt/ endothelial NO/vasodilation, which is comparatively insulin resistant. Another even more basic but perhaps less appreciated example is the differential sensitivities to insulin targeted signaling in cardiomyocytes concerning various pathways of glucose versus lipid metabolism. This informs powerful and fundamental support to the metabolic basis for the cardiomyopathy of insulin resistance and diabetes. This insight also helps to connect the dots bridging ectopic fat to the feedforward selfamplifying nature of insulin resistance and its pathogenic sequelae.

9.4.5 Ischemic Dilated Cardiomyopathy Ischemic heart disease is a leading cause of death worldwide. Coronary occlusion impairs oxygen and macronutrient substrate flux into the heart and consequently represses cardiac function by spasm, arrhythmias, and likely cardiac death. The most important approach to mitigate cardiac damage and improve clinical outcomes is fast, effective restoration of coronary blood flow either by percutaneous coronary intervention (PCI) or thrombolysis. However, this reperfusion after ischemia (I/R) per se leads to additional damage to the myocardium (reperfusion injury), which may account for up to 40% of the final infarct size (313, 314). Despite profound clinical interests, our understanding of I/R injury is rather limited. As a matter of fact, there is no therapy for reperfusion injury nowadays. During cardiac ischemia and I/R, numerous signaling transduction pathways are activated and key molecules are

altered. Over-production of reactive oxygen species, metabolic derangements, and calcium mishandling are among the most significant underlying reasons. All these adverse events collectively lead to the demise of cardiomyocytes, repression of contractility, and cardiac dysfunction. As a typical outcome, dilated cardiomyopathy ensues. Of central significance are the shared metabolic pathogenic features of both ischemic and non-ischemic cardiomyopathies: mitochondrial dysfunction and uncoupling of the glycolytic pathway to oxidative phosphorylation. In the early phase and short term, turning up glycolysis is beneficial in ischemic heart disease. This is accompanied by less reliance on oxygen, which is lacking, and emergency production of ATP, which is essential to maintain ion channels for cardiomyocyte survival. Under this ischemic condition, pyruvate as the second to last product of glycolysis cannot undergo oxidation in mitochondria. Instead, it is converted into lactate by lactate dehydrogenase (LDH). While glycolysis here is required for survival, prolonged ischemia causes accumulation of lactate and protons due to diminished perfusion. Upon reperfusion, the sudden flux of oxygen and nutrients activates calcium channels due to accumulated protons from ischemia. As a consequence, the mitochondrial permeability transition pore (mPTP) is opened for ion influx. Therefore, mitochondrial dysfunction takes place and cardiomyocytes are under metabolic insult.

9.4.6 Vascular Atherosclerosis 9.4.6.1 Lipoproteins, Cholesterol, and Vascular Atherosclerosis In the circulating blood, cholesterol is carried by numerous lipoprotein particles that perform the complex physiologic tasks of transporting dietary lipids (chylomicrons) and endogenously produced lipids (very low-density lipoprotein— VLDL). Chylomicrons are transported from the intestines to the rest of the body. In contrast, VLDL is derived from the liver and is composed of endogenous lipids. Triglyceride-rich lipoproteins (TRLs) such as chylomicrons and VLDL particles interact with the enzyme lipoprotein lipase, catalyzing the reaction of triglycerides into fatty acids (FAs) and glycerol. These lipids are then distributed to various tissues, such as adipose tissue, cardiac tissue, and skeletal muscle, where it is used as an energy source. Brown adipose tissue (BAT) also utilizes FAs as an energy substrate, whereas white adipose tissue (WAT) stores FAs in the form of triglycerides. After this process of distributing FAs to tissues for energy and storage, the major portion of remaining chylomicron and LDL (low-density lipoprotein—LDL) are absorbed by the liver: chylomicron remnants are taken up through the low-density lipoprotein receptor-related protein (LRP), and LDL is taken up through the LDL receptor (LDL-R; Figure 9.21) (315–317). In humans, LDL has a crucial physiological role as a vehicle for the transport of cholesterol to peripheral tissues. However, elevated circulating LDL cholesterol (LDL-C) levels are associated with increased risks of atherosclerosis. Atherosclerosis is characterized by plaque that is formed when lipids and fibrous elements deposit in the innermost layer of arteries (intima). As a result, this leads to a

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FIGURE 9.21  Schematic representation of lipoprotein metabolism. Lipoprotein lipase (LPL) induces hydrolysis of triglycerides from circulating triglyceride-rich lipoproteins (TRLs) such as chylomicrons and VLDL (very low-density lipoprotein) in capillaries of white adipose tissue (WAT), brown adipose tissue (BAT), heart, and skeletal muscle. As a result, fatty acids and glycerol are taken up by these tissues. Subsequently, chylomicron remnants and VLDL remnants (Low-density lipoprotein- LDL) are taken up by the liver via specific receptors such as LDL receptor-related protein (LRP) and LDL receptors (LDLR) respectively. Source: adapted from (316). *BAT = brown adipose tissue; LDL = low-density lipoprotein; LDLR = low-density lipoprotein receptor; LPL = lipoprotein lipase; LRP = low-density lipoprotein receptor-related protein; VLDL = very low-density lipoprotein.

restriction of blood flow and hypoxia in tissues that may ultimately result in stroke and myocardial infarction (MI). Thus, high LDL-C levels cause atherosclerosis, a leading cause of cardiovascular disease. During hypercholesterolemia (elevated circulating LDLC), LDL particles enter the intima. These LDL particles undergo oxidative modifications in the lipid and apolipoprotein B (apoB) components of LDL, forming Oxidized-LDL (Ox-LDL). Ox-LDL activates endothelial and smooth muscle cells (SMCs) to recruit white blood cells such as monocytes into the subendothelial layer. Here, monocytes differentiate into macrophages that scavenge Ox-LDL, accumulate neutral lipids, and transform into foam cells. Enlargement of foam cells in the arterial wall leads to the development of atherosclerotic plaques (Figure 9.22A, C). Furthermore, activated endothelial cells produce a number of pro-inflammatory molecules, including adhesion molecules, chemotactic proteins such as monocyte chemotactic protein-1 (MCP-1), and growth factors such as macrophage colony-stimulating factor (M-CSF; Figure 9.22A). M-CSF stimulates the proliferation and differentiation of macrophages. M-CSF also influences the expression of scavenger receptors, as well as other macrophage functions. Ox-LDL also inhibits the production of nitric oxide (NO), an important mediator of vasodilation, and the expression of endothelial leukocyte adhesion molecules (ELAMs). Furthermore, Ox-LDL triggers pattern recognition receptors (PRRs), specifically damage-associated molecular patterns (DAMPs) that are expressed by macrophages, including scavenger receptors, toll-like receptors (TLRs),

Metabolism and Medicine and NOD-like receptors (NLRs). These receptors activate the inflammatory response, which contributes to the formation of inflamed plaque (318). TLRs activate monocyte-derived cells that enter the plaque. These monocyte-derived cells become polarized into inflammatory M1 macrophages, which secrete pro-atherogenic cytokines (such as IL-6 and IL-12), nitrogen, and reactive oxygen species, which aggravate oxidative stress in the plaque. The shift from the relatively simple fatty streak to the complex lesion (damage or abnormal change) is characterized by the immigration of SMCs from the medial layer of the artery wall into the intimal. Here, SMCs can proliferate and take up oxLDL, contributing to foam cell formation. Moreover, SMCs synthesize extracellular matrix proteins for the development of the fibrous cap (Figure 9.22B, C). This segment of the lesion expansion is influenced by interactions between macrophages and T helper cells. Progressive atherosclerotic lesions cause advanced narrowing of the blood vessel lumen, leading to ischemic symptoms, acute cardiovascular events, and ultimately myocardial infarction. Stroke generally results from plaque rupture and thrombosis. Necrosis (swelling of cytoplasm, damage of plasma membrane, and spilling of cytoplasmic content) of foam cells leads to the development of a necrotic core and accumulation of extracellular cholesterol and cholesteryl esters. The fibrous plaque can rupture due to matrix metalloproteinases (MMPs) secreted by macrophages. Plaque rupture leaks lipids and tissue factors into the blood, triggering the coagulation cascade: platelet adherence and thrombosis. Atherosclerosis is the major cause of morbidity and mortality among obesity-associated diabetic patients. The main characteristic feature of type 2 diabetes (T2D) is insulin resistance and hyper-insulinemia, which accelerates atherosclerosis (i.e. macrovascular complications of diabetes). However, the mechanisms for the susceptibility and progression of atherosclerosis in patients with type 2 diabetes (T2D) are not fully understood. Emerging studies suggest that under normal physiological conditions, insulin induces phosphorylation of nitric oxide synthase (NOS) in endothelial cells (ECs) and vascular tissues, including the aorta. eNOS enzyme activation of aorta tissue causes vasodilation and suppression of vascular cell adhesion molecule (VCAM-1). If disinhibited, VCAM-1 recruits monocytes for induction of inflammation in atherogenesis. At the same time, insulin activates growth-factor-like pathways in vascular smooth muscle cells (VSMCs), mediated by mitogen-activated protein kinase (MAPK). MAPK signaling stimulates the proliferation and migration of VSMCs. The MAPK cascade becomes overactivated during insulin resistance/hyperinsulinemia, leading to impaired vascular function. Therefore, insulin resistance during type 2 diabetes may inhibit endothelial NO production and stimulate the MAPK pathway in VSMCs, possibly contributing to atherosclerosis development. Moreover, hyperglycemia during T2D also induces atherosclerosis. Elevated blood glucose induces a nonenzymatic reaction between glucose and glycating compounds, such as hyperglycemia-induced advanced glycation end products (AGEs). AGE-modified lipoproteins bind to the receptor of AGEs (RAGE) on endothelial cells to recruit inflammatory

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FIGURE 9.22  Initiation and progression of atherosclerotic lesions. A) Initiation. Low-density lipoprotein (LDL) is exposed to oxidative modifications in the subendothelial space, transforming into oxidized LDL (ox-LDL). ox-LDL changes the environment of endothelial cells, inducing the expression of cell adhesion molecules for the adherence of monocytes to endothelial cells. Adherent monocytes travel into the subendothelial space and differentiate into macrophages. Consequently, macrophages engulf ox-LDL and transform into foam cells. B) Progression. Smooth muscle cells (SMCs) migrate from the median portion of the arterial wall into the intima. Here, SMCs proliferate and secrete extracellular matrix proteins that form fibrous plaques. Communication between macrophage foam cells and lymphocytes (T-helper cells: Th1 and Th2) leads to the secretion of several cytokines, which establishes a chronic inflammatory process. C) Representative histological image of a cross-section of an aortic sinus. Notice the enlarged intima and atherosclerotic lesion. Sources: A) and B) adapted from (319); C) courtesy of Abhishek Kumar Singh, Carlos Fernandez Hernando’s Lab, Yale University. *ECs = endothelial cells; LDL = low-density lipoprotein; ox = oxidized; SMCs = smooth muscle cells; Th = T-helper cells.

cells and adhesion molecules, building atherosclerotic plaque. These studies suggest that insulin resistance and hyperglycemia may independently contribute to atherosclerosis. It is possible that a patient with both conditions could have additive or exponential damage to cardiovascular health (320–324).

SIDEBAR 9.5: IS INSULIN THERAPY CARDIOPROTECTIVE DURING SURGERY? Insulin controls glucose levels and may provide cardiovascular protection. Stress and illness can precipitate hyperglycemia-induced toxicity to the myocardium. In the 1960s, Dr. Sodi-Pallares devised a mixture of glucose,

insulin, and potassium (GIK) to be used during the perioperative phase of coronary artery bypass surgery to reduce myocardial infarctions. The rationale was that glucose is a more oxygen-efficient substrate than fatty acids and prevents arrhythmias. Dr. Sodi-Pallares and others (Digami and Van den Berghe) reported fewer cardiac events in surgical patients receiving GIK. However, these cardioprotective effects of insulin were not consistently replicable. More recent studies have found a paradoxical increase in mortality with insulin therapy, even unrelated to hypoglycemia. It is possible that these conflicting findings can be explained by “metabolic memory”, or a history of poor glycemic control.

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9.4.6.2 Current Therapies Decreasing circulating LDL-C levels and attenuating the inflammatory response represent the two key fundamental therapeutic strategies against atherosclerosis. Using statins to inhibit the endogenous cholesterol biosynthesis enzyme 3-hydroxy-3-methylglutaryl-CoA reductase (HMG-CoAR) is the most successful way to lower plasma LDL-C. Monoclonal antibodies against proprotein convertase subtilisin/kexin type 9 (PCSK9) reduce levels of LDL-C by blocking LDL degradation (evolocumab, trade name Repatha®). The antiinflammatory drug Canakinumab (IL-1β antibody) can reduce atherosclerotic progression by inhibiting inflammation. Apart from that, lifestyle interventions such as the emphasis on diet, physical activity, and elimination of tobacco use can prevent atherosclerotic disease.

9.4.6.2.1 Intuitive and Algorithmic Indications of Cholesterol Reduction Therapy The current American College of Cardiology and The American Heart Association recommends lowering cholesterol with statin drug (HMG-CoA Reductase) therapy for the primary prevention of cardiovascular disease. In the past, guidelines were almost solely based on the levels of low-density lipoprotein (LDL) levels in the blood. The new guidelines use a combination of LDL concentration levels and traditional risk factors (age, race, gender, total and HDL cholesterol, diabetes type 1 or 2, and systolic blood pressure) to calculate an individual’s ten-year risk of having a cardiovascular event. Corollaries of risk calculations include known coronary artery disease, an LDL above 190, or type 1 or 2 diabetes (between the ages of 40–79). If this risk is greater than 7.5%, moderate-to-high-dose statin therapy is recommended. The current algorithm ignores important variables when calculating the decision to initiate statin therapy. These missing variables include family history of atherosclerosis (firstdegree male relative younger than age 55/female relative younger than age 65), obesity (abdominal circumference), and smoking status. Several other disease states are associated with cardiovascular disease: rheumatoid arthritis, renal disease, primary biliary cirrhosis (related cholestasis often form lipoprotein X particles, large lipoproteins with unesterified cholesterol and phospholipids), high levels of lipoprotein A (LDL-like particle in which apolipoprotein A is covalently bound to apolipoprotein B; it is an independent risk factor for cardio-, peripheral-, and cerebro- vascular disease), cholesterol ester storage disease (CESD, an underrecognized autosomal recessive gene mutation of the enzyme lysosomal acid lipase resulting in the accumulation of cholesterol ester in the liver and accelerated risk of cardiovascular disease), and very low HDL (HDL below 20). Hematologic malignancies may precipitously cause HDL levels to fall below 20). Very low HDL also happens when HDL biogenesis is impaired, due to mutations in APOA1. This mutation presents with premature cardiovascular disease. In contrast, HDL levels below 20 due to Tangier’s disease (ABCA1 mutation) or fish-eye disease (LCAT mutation) are not associated with premature cardiovascular disease risk.

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SIDEBAR 9.6: CLINICAL CONSIDERATIONS OF STATIN THERAPY IN POSTMENOPAUSAL WOMEN Is it wise to prescribe statin therapy to a postmenopausal woman with elevated LDL but no other risk factors of coronary artery disease? Postmenopausal estrogen-deficient women given statin therapy have accelerated cognitive decline. Therefore, risk factors for Alzheimer’s disease and other dementias need to be carefully weighed. Tests for cognitive decline due to statin therapy would be needed regularly. Hormone replacement therapy may be a means of countering the cognitive effects of statin therapy, especially in female patients under 60 years old. However, hormone replacement at age 70 is correlated with greater myocardial infarction risk and increased cancer risk. On the other hand, hormone replacement therapy may be protective in type 2 diabetes: estrogen prevents apoptosis in pancreatic beta cells, and estradiol/estrogen receptor binding to the estrogen response elements of the promoter regions of the GLUT4 gene is important for glucose transport into skeletal muscle cells. Without hormone replacement therapy, estrogen-deficient postmenopausal women treated with statins have an increased incidence of type 2 diabetes. In order to answer the question of whether a specific postmenopausal patient should be prescribed statins, a balanced and creative team of subspecialists is needed to fully weigh the outcomes.

9.4.6.3 Prospective of New Therapies Lowering lipids with statins (plus ezetimibe) is not sufficient to eliminate the risk of atherosclerosis. Therefore, new approaches to lower triglyceride-rich lipoprotein particles and LDL-C levels, and increase HDL-C levels remain attractive avenues for the development of novel classes of anti-atherogenic drugs. Genome-wide association exome-sequencing and clinical studies have shown that loss-of-function mutations or suppression of angiopoietin-like proteins (ANGPTL3 and ANGPTL4) in humans lower circulating LDL-C, triglycerides, fasting blood glucose, and insulin sensitivity, and these loss-of-function mutations reduce the risk of type 2 diabetes and atherosclerosis (325). ANGPTL3 and ANGPTL4 are secreted proteins highly expressed in metabolic tissues. They regulate circulating triglyceride homeostasis by inhibiting enzyme lipoprotein lipase (LPL) activity. Depletion of liverspecific ANGPTL3/ANGPTL4 protein improves obesityassociated diabetes and atherosclerosis preclinically (326). In the future, hepatic ANGPTL3/ANGPTL4 inhibitors may be a means of treating type 2 diabetes and atherosclerosis. Other potential therapeutic targets for atherosclerosis are transcription factors that regulate cholesterol homeostasis and the inflammatory response. Liver X receptors (LXRs) are nuclear transcription factors that maintain cholesterol homeostasis through the process of reverse cholesterol transport (RCT). During RCT, LXRs transform excess cholesterol

Chronic Diseases as Metabolic Disorders from peripheral tissues (including macrophages of atherosclerotic lesions) into HDL, which is transported to the liver for bile acid synthesis and excretion (details about LXR are in the NHR chapter). Chronic administration of synthetic LXR agonists reduces atherosclerotic lesions in mice by inducing ABCA1 and ABCG1 (transporters of HDL-C) expression. This promotes cholesterol efflux from macrophages within atherosclerotic lesions and represses inflammatory gene expression. However, clinical trials in humans were less successful; LXR agonists caused hypertriglyceridemia and hepatic steatosis. Therefore, further research is needed to fine-tune LXRmediated treatments for metabolic disorders.

9.4.7 Metabolic Pharmacotherapy of Heart Disease 9.4.7.1 Metformin Metformin-induced pathways and effects are tissue-specific, and some are yet to be elucidated. In the liver, metformin’s anti-diabetogenic effects relate to its reduction of gluconeogenesis, an ATP-requiring process. Mechanistically, metformin blocks Complex I of the mitochondrial electron transport chain. This reduces ATP production, increasing the ratio of AMP/ATP, hence activating AMPK. It is worth restating that in addition to the master regulator AMPK, SIRT1 is another important energy-sensing molecule. In the case of SIRT1, the fuel gauge that it senses and activates is the ratio of NAD+/ NADH. AMPK and SIRT1 have a bilateral and feedforward relationship that inhibits energy-consuming pathways and promotes energy-producing signaling. Interestingly, there is no evidence of metformin-induced activation of AMPK in cardiac myocytes. While diabetes has doubled the mortality from myocardial infarction and congestive heart failure, metformin therapy demonstrates significant cardioprotection. For example, it reduces the risk of reinfarction in the setting of coronary artery disease, and of all-cause mortality in those with congestive heart failure. The reasons for this appear to be pleiotropic; metformin-activated AMPK in both cardiomyocytes and endothelial cells promotes activation of nitric oxide synthase by phosphorylation of a key serine residue. In both cell types, the result is the production of nitric oxide (NO) with both endocrine and paracrine effects. In cardiomyocytes, NO promotes early diastolic relaxation, hence prolonging the phase of ventricular filling as well as mitigating the contraction that exacerbates ischemic damage. In endothelial cells, NO produces vasodilation, improving oxygenation to the contracting myocardium. AMPK may also have a salutary effect of preserving the myocardium by inhibiting the opening of the mitochondrial permeability transition pore (mPTP), thus preventing mPTP-induced apoptosis (327). Interestingly, the under-recognized cardioprotective effect of both salicylates (aspirin) and statins is also due to this same mechanism.

9.4.7.2 Fibrates, TZDs, and Vitamin D In addition to metformin, small molecular agonists for PPARγ and α, TZDs and fibrates, respectively, improve hyperglycemia and dyslipidemia. They also both prevent atherogenesis

391 by increasing cholesterol effluent from macrophages in vessel walls, where they additionally reduce the expression of inflammatory and adhesion molecules. PPARγ and α agonists promote insulin-sensitizing effects and signaling pathways that are tissue-specific. For example, agonists of PPARγ increase glucose uptake into the cells of insulin-responsive tissues through GLUT4 transport molecules. These agents drive triglyceride synthesis as well as couple lipogenesis to adipogenesis of subcutaneous adipose tissue. This in turn preserves insulin sensitivity of tissues systemically by reducing hyperlipidemia and the associated deposition of ectopic fat. In the liver and visceral adipose tissue, PPARγ appears to play an indirect role in fatty acid oxidation, likely by promoting upregulation of PPARα. Hence, PPARγ promotes a salutary effect on changing the topography of fat deposition away from ectopic sites to more protective storage within subcutaneous adipose tissue. In this sense, pharmacologic activation of PPARγ may be an effective strategy for non-alcoholic liver and cardiovascular diseases, both strongly mediated by insulin resistance. PPARγ enhances insulin-dependent glucose uptake and utilization in a variety of tissues, including cardiac and skeletal muscle, and adipose tissue. However, the effects of PPARγ on metabolic gene expression, particularly increased glucose oxidation and decreased fatty acid oxidation in the myocardium, appear to be indirect, mediated by its effects on other tissues that beneficially influence circulatory levels of glucose and lipids. The stimulated effect on glucose oxidation is presumed to account, at least in part, for the beneficial effects on ischemia and reperfusion injury. The TZD drugs have a significant number of other demonstrated cardioprotective effects, including attenuated sympathetic autonomic activation, reduced cardiac expression of proinflammatory cytokines, angiotensin II production and activation, and reduced Endothelin I levels (328). Moreover, these drugs have been shown to promote regression of wall thickness and other markers of myocardial hypertrophy (329). These effects may largely be a function of PPARγinduced improvement of insulin sensitivity, i.e. reduced insulin resistance, in the heart. However, how much is contributed by the non-PPARγ effects of the drugs is yet to be clearly discerned. With that being said, TZDs and PPARγ agonists show significant side effects in the cardiovascular system, and their use in treating metabolic cardiomyopathy needs to be cautiously executed (330). PPARα plays a fundamental role in fatty acid oxidation in the liver and heart, where it is expressed at high levels. The competitive nature of acetyl-CoA metabolites from fatty acids and glucose substrates for oxidation in the mitochondria is responsible for PPARα-induced inhibition of pyruvate dehydrogenase enzyme complex (PDC). This is an insulin resistance effect that prevents the favorable metabolic efficiency of glucose oxidation. Accordingly, it is generally accepted that some of the cardioprotective benefits of PPARα activation are the result of extra-cardiac promotion of fatty acid oxidation. For example, the VA-HIT study showed improvements in major cardiovascular events among type 2 diabetes with hypertriglyceridemia and low HDL treated with the fibrate gemfibrozil (331). Intriguingly, the receptor for vitamin D, VDR, is another nuclear hormone receptor, which, like the PPARs, forms

392 heterodimers with the retinoid X receptor, RXR. In fact, VDR competes with PPARγ for RXR heterodimerization. Further, the active form of vitamin D, calcitriol, crosstalks with both the VDR and PPARγ (as heterodimers with RXR), and thus has the capacity to activate PPARγ-mediated effects. Calcitriol, coadministered with a histone deacetylase (HDAC) inhibitor, improves diabetic cardiomyopathy by its effects on regulating proinflammatory cytokines (332). HDAC enzymes compete with histone acetyltransferases (HATs) to remove or add acetyl groups to histone proteins that wrap around the DNA. This is a crucial process in the regulation of gene expression. Acetyl groups open the space between the histone and DNA, hence allowing nuclear hormone receptors and other transcriptional regulators to bind promoter regions on genes. This crosstalk of vitamin D-mediated effects may explain, at least in part, the wide-spanning potential benefits of vitamin D on human health, including the prevention of autoimmune disorders, cancers, cardiovascular disease, and type 2 diabetes. The fundamental effects of vitamin D are the regulation of both arms of the immune system, while PPARγ agonists affect insulin sensitivity. Since anti-inflammatory effects are intimately coupled to insulin sensitivity, it is often difficult to extricate which are PPARγ versus VDR-mediated effects. While vitamin D and PPARγ agonists have synergistic effects, they may also be antagonistic. For example, the anti-obesity effects of vitamin D are mediated by the suppression of PPARγ-mediated adipogenesis and lipogenesis.

9.4.7.3 Trimetazidine Another promising metabolic therapy is the cardiac antianginal drug trimetazidine, an inhibitor of beta-oxidation of fatty acids. While fatty acids are the major fuel macronutrient substrate, there is a physiological purpose for metabolic flexibility that switches from fatty acid to glucose utilization in the feeding state. The TRIMPOL-II study showed that this drug enhances cardiac exercise performance and reduces exerciseinduced ischemia (333). This makes perfect sense of circadian biology which teleologically links activity and feeding behavior together during the light phase of the daily cycle. Indeed, not only does the molecular clock regulate peripheral insulin sensitivity and insulin secretion in a circadian fashion, but also it was recently discovered that insulin directly feeds back on core clock components (334). It is well recognized that metabolism of glucose is an inefficient producer of ATP in comparison to the robustness of ATP production from fatty acid oxidation in the mitochondria. However, less appreciated is the greater efficiency of the oxidative phase of glucose metabolism compared to that of fatty acids in terms of the quantity of oxygen consumed per given amount of ATP produced. This reconciles, for example, the finding of less exercise-induced ischemia in the setting of trimetazidine-inhibition of fatty acid oxidation that promotes greater glucose oxidation. Thus, on the one hand, fatty acid metabolism is more efficient in terms of the amount of ATP produced per molecule of oxygen; on the other hand, glucose is more efficient in the sense that there is less waste of the energy contained in the bonds of the glucose molecule in the transformation process to ATP. This energetic waste parallels

Metabolism and Medicine the formation of reactive oxygen species and consequentially, redox and inflammatory stress. Several studies have demonstrated improvements in left ventricular ejection fraction in trimetazidine-treated patients with congestive heart failure (335–337). Thus, while the enormous energy demands of the heart dictate its primary reliance on fatty acids for ATP production, an over-reliance on this fuel substrate highlights a disruption in the organizational perfection of bioenergetics. Accordingly, the associated pathogenic levels of redox stress cause structural and functional mitochondrial and cell damage, cardiac insulin resistance, and progressive impairment in myocardial performance. It is important to recognize that treatment with trimetazidine would not be expected to improve cardiac function once mitochondrial function is globally disturbed, and aerobic metabolism by oxidative phosphorylation becomes uncoupled to glycolysis. Along the same line, PPARγ agonists like TZDs may actually improve cardiovascular disease by promoting glucose utilization, and at the same time, suppress fatty acid betaoxidation, according to the Randle cycle. TZDs may restore insulin sensitivity in the heart and stimulate glucose uptake and utilization. This effect, coupled with versatile actions in other organs, may enhance metabolic flexibility in the whole body, and consequently improve cardiac performance under metabolic cardiomyopathy. Glucose metabolism is not only mediated by the glycolysis pathway, but also, importantly, by the flux of pyruvate oxidation via the TCA cycle and the mitochondrial electron transfer chain that produces ATP. The latter is the oxidative phase of glucose metabolism. The mitochondrial oxidation of glucose competes with and inhibits fatty acid beta-oxidation (see Randle hypothesis discussed shortly). However, fatty acid beta-oxidation more potently inhibits glycolysis and the subsequent pyruvate oxidation through upregulation of pyruvate dehydrogenase kinase. During physiological states of fasting, circadian insulin resistance is characterized by upregulated subcutaneous adipose tissue lipolysis, promoting a high basal state of lipidemia to supply energy substrates to tissues systemically. This spares the limited glucose availability for the brain which is poorly adapted for fatty acid utilization. As discussed in detail above, a hallmark of pathological (noncircadian) insulin resistance is the ectopic deposits of lipids in non-adipose tissues, including the heart. In addition to the loss of metabolic flexibility and the inability to oxidize glucose as a clean-burning fuel, pathological insulin resistance is typically associated with obesity in the sense that total body fat exceeds the subcutaneous adipose tissue storage capacity. Consequently, the supply of fatty acids exceeds both the energetic demands and the mitochondrial capacity to convert them to ATP via oxidative phosphorylation. The accumulation of intracellular lipids that includes reactive lipid species promotes inflammatory cascades and redox stress that impair insulin signaling and damage cardiac myocytes. Associated mitochondrial dysfunction further induces oxidative stress with its own generation of reactive oxygen species, hence promulgating a feedforward destructive circuit. In the setting of ectopic fat deposits, glucose uptake and utilization are inhibited in a number of ways. Fatty acid conjugates of CoA (fatty acyl-CoA) as well as other reactive lipid

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Chronic Diseases as Metabolic Disorders metabolites, such as ceramides and diacylglycerol (DAG), activate inflammatory pathways that impair insulin signalingdependent GLUT4 translocation to the cell membrane. In the myocardium, both GLUT1 and GLUT4 are present; however, it is the insulin-dependent, GLUT4-mediated glucose transport that is predominant in the adult heart. In the healthy body, insulin-stimulated glucose uptake and oxidation are reciprocal events that supply the energy needs of the cell. Insulin-stimulated GLUT4 translocation from the endoplasmic reticulum to the cell membrane promotes glucose uptake, activating the glycolytic pathway or glycogen synthesis. The oxidation of glucose is mediated by the insulin-stimulated enzymatic activation of the pyruvate dehydrogenase complex (PDC). In the mitochondria, PDC decarboxylates pyruvate into acetyl CoA, which enters the TCA cycle, leading to ATP production by oxidative phosphorylation. Hepatocyte glucose uptake is dependent on insulin, though it does not require insulin signaling-induced GLUT4 translocation to the cell membrane. Conversely, PDC activity is insulin-independent in hepatocytes. Fasting-associated insulinopenia (inadequate insulin levels) encourages upregulation of adipose tissue lipolysis. The flow of fatty acids into the liver leads to the generation of excess acetyl CoA groups. The hepatocytes are unable to bioenergetically accommodate these excess acetyl CoA’s, which are instead channeled into pathways of ketone body formation, to be utilized as a fuel source for the brain, skeletal muscle, and cardiac muscle. ACC-2 is inactivated and MCD is activated in the skeletal and cardiac muscle when insulin is low, so fasting stimulates CPT-1-mediated transfer of palmitate into the mitochondria, where it is oxidatively metabolized to ATP. In cardiac insulin resistance, the diminished activation of GLUT4 is an important molecular contributor to pathogenicity. Following fatty acyl-CoA transport into the mitochondria, promoted by the PPARα-transcriptionally-regulated carnitine palmitoyl transferase (CPT-1), fatty acyl-CoA is catabolized via the process of beta-oxidation, which is also PPARαregulated, to acetyl-CoA and the byproduct of NADH. Fatty acid beta-oxidation competes with glucose substrate for the formation of acetyl-CoA. Accordingly, fatty acid-derived acetyl-CoA drives the exit of citrate, a TCA cycle intermediate, into the cytoplasm, where it inhibits the rate-limiting enzyme of glycolysis, PFK1. Moreover, within the mitochondria, both acetyl-CoA and NADH from fatty acid beta-oxidation stimulate the activity of pyruvate dehydrogenase kinase 4 (PDK4). PDK4, in turn, negatively regulates the pyruvate dehydrogenase enzyme complex (PDC) responsible for decarboxylating glycolysis-formed pyruvate after it is transported into the mitochondria, to produce acetyl-CoA. This action inhibits the subsequent mitochondrial oxidation of glucose. Insulin is a positive regulator of PDC activity, underscoring the yin-yang competition between insulin-mediated glucose vs. fatty acid catabolism and oxidation that occur during healthy states of feeding and fasting, respectively. Taken together, all forms of cardiomyopathy, ischemic, nonischemic, or diabetic, share the same molecular etiology of metabolic disturbance. Under the conditions of over-utilization of glucose, excessive production of reactive oxygen species from glucose catabolism adversely modifies key enzymes

of glycolysis. As a consequence, glycolysis may be inefficiently finished and metabolic intermediates are shunted to pathological pathways affecting cardiac performance. On the other hand, under conditions of over-utilization of fatty acids, excessive NADH and FADH2 saturate mitochondrial Complexes I and II. As a result, reactive oxygen species accumulate, which similarly lead to pathological consequences in cardiac myocytes. This unifying hypothesis can largely explain, arguably, all forms of cardiomyopathy, which not only shapes our understanding of the etiologies of cardiovascular disease, but also provides promising, druggable targets for effective therapeutic interventions.

9.5 The Physiological Fitness Landscape: A New Model of Personalized Precision Medicine The concept of Physiological Fitness Landscape is a potentially powerful predictive model and we hope that it will play a major role in the future of precision medicine. Within this methodology, each patient should be viewed as a complex, multi-dimensional dynamic system presenting with symptoms that have some overlap with other patients suffering from the same condition, but also with individual characteristics; hence there is a need for personalized precision medicine. In this context, every medical specialty or specialty physician interrogates a limited trajectory in a complex phase space* of dynamical behaviors exhibited by the patient. This could be seen as the analysis of a single dimension (parameter), such as glucose regulation, in the context of many other dimensions or parameters in the overall physiology or disease of an individual. Restoring one parameter to a range of normal values does not necessarily signal a return to health. For example, glycemia as a dimension in the Physiological Fitness (or Free Energy) Landscape represents the energy flow available to the system and its capacity to connect with other intersecting subsystems, for example, lipids, insulin secretion, and sensitivity. Insulin in the next order intersects signaling pathways that critically affect the total fitness manifold of the individual. This includes lipid regulation, satiety, endothelial cell vasodilation, and adhesiveness to immune cells (and hence inflammatory and redox stress, which disrupts cell function including nutrient oxidation), and organ tissue epithelial cell proliferative potential. Together, glucose and insulin are crucial intrinsic control parameters of the subsystems that in turn govern the entire physiological system’s regulation and those bioenergetically regulated by it.

* The multi-dimensional phase space referred here is a mathematical representation of physiological parameter values, each of which can be depicted as an axis. The patient’s disease can be mapped as a trajectory in this space traversing the values of these parameters (e.g. blood pressure, temperature, heart rate, electrolytes, hormone levels, etc.) in the course of the disease.

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SIDEBAR 9.7: PHYSIOLOGICAL FITNESS LANDSCAPE AND METABOLIC MEMORY When and why would successfully obtaining the therapeutic goal of normal blood glucose levels in a diabetic patient be detrimental? Normal blood sugar levels attained by continuous intravenous insulin infusion in hospitalized critically ill patients have been associated with unexplained increased mortality. For this reason, this common clinical biomarker as a parameter of the Physiological Fitness Landscape is chosen to exemplify an explanation of this model. Metabolic memory, or hyperglycemic memory, is an intriguing phenomenon with many unanswered questions. A number of landmark studies have demonstrated that tight glucose control immediately following the diagnosis of type 1 diabetes, but not if delayed by several months, is critical for long-term prevention of small vessel disease of the eyes and kidneys (338–347). Similarly, vigorous metabolic control of glucose, lipids, and hypertension immediately following diagnosis of type 2 diabetes, has been shown to prevent mortality and other endpoints of CVD (Steno 2 trial). Furthermore, there is ongoing active research in metabolic memory in diabetic cancer patients. A theoretical basis and experimental evidence for this phenomenon point to AGEs, other mediators of inflammation, and redox stress. Metabolic memory has also been called the “legacy effect” to highlight the enduring effect of metabolic disease, and it may be understood in the context of the proposed Physiological Fitness Landscape model. Furthermore, this model is fundamentally premised on the “fitness” of a biological system, which correlates positively with the free energy flow available to the system and inversely with the totality of inflammatory and redox stress in the system. On a multidimensional Physiological Fitness Landscape, an extraordinary quantity and complexity of parameters define this synchronized and intricately orchestrated biological design. However, when the robustness of free energy declines, metabolism and physiology become desynchronized as subsystems become isolated and compartmentalized, and total fitness degrades into a pathological state. Local interactions of these parameters include glucose production by the insulin resistance-triggered glycogenolytic and gluconeogenic enzymes; fatty acid release promoted by the lack of insulin inhibition of hormone-sensitive lipase in lipid storing adipocytes; lack of insulin stimulation of adipose tissue lipoprotein lipase that keeps VLDL lipoprotein lipid-containing substrates in the circulation available for uptake in peripheral tissues. Hyperinsulinemia, insulin resistance, and impaired glucose oxidation collectively promote the Warburg effect and hence epithelial cancer cell proliferation. The initial cell transformation is a result of one or more of the hallmarks of cancer, for example, hypoxia, the associated redox stress, and inflammation. Insulin resistance coupled to redox and inflammatory stress along with impaired glucose oxidation also characterizes

Metabolism and Medicine endothelial cell dysfunction contributing to hypertension and atherogenesis. Similarly, hypertrophic and diabetic cardiomyopathy is mediated by metabolic remodeling as a consequence of impaired redox and mitochondrial dysfunction that results in the uncoupling of glycolysis and oxidative phosphorylation energy production pathways. Alternatively, hyperinsulinemia and insulin resistance promote toxic redox and inflammatory neuronal cell stress. Dysfunctional neurons upregulate oxidative phosphorylation bioenergetics to compete with healthy neurons for limited nutrient substrate availability. This phenomenon, termed the inverse Warburg effect, characterizes Alzheimer’s disease and perhaps the accelerated cognitive decline of aging, a consequence of increased activation of apoptosis in dysfunctional neurons (348). Central elements for the synchrony of interdependent cycling of systems responsible for metabolic homeostasis and healthy physiology involve the locally intersecting core clock components with hormones, nuclear hormone receptors (NHRs), and other transcriptional regulators that integrally coordinate the bioenergetic and redox resistance programs of metabolic homeostasis. When conditions are good and systems are healthy, biological function is exquisite. However, when things go awry, the outcome is metabolic disease (e.g. hypertension, dyslipidemia, central obesity, glucose intolerance, diabetes, low grade or “meta” inflammation) resulting from waste at the bioenergetic transformation centers, i.e. mitochondria, and redox stress that degrades biological structure and function. This is followed by chronic disease manifestations of aging (often prematurely) including CVD, cancers, accelerated cognitive decline, and Alzheimer’s disease (Figure 9.23). What mediates things going awry? The short answer is stress. Stress responses, from the psychogenic perception of stress to the molecular scale mechanisms that carry it out, are teleologically adaptive. However, it is the chronicity of the stress response, not necessarily the external stress per

FIGURE 9.23  States of metabolic disease. Insulin resistance/hyperinsulinemia leads to chronic diseases of aging such as Alzheimer’s disease, cancer, cardiovascular disease, and type 2 diabetes. *CVD = cardiovascular diseases; T2D = type 2 diabetes.

Chronic Diseases as Metabolic Disorders se, that is the pathogenic underpinning of disease. Allostatic responses chiefly involve primary (catecholamines, HPA axis hormones, cytokines) and secondary mediators (insulin resistance markers of the metabolic and hemodynamic response [e.g. classically hyperglycemia, hyperinsulinemia, hyper/dyslipidemia, hypertension, and excess adiposity]). Moreover, secondary mediators of allostasis may include NHR’s and other transcriptional regulators. Together, these mediators respond to extrinsic and intrinsic stressors with the purpose of governing bioenergetic, redox, and acid-base demands of homeostatic stability.* This orchestration of the stress response is the central organizational design of metabolism that is responsible for human health and disease. Furthermore, this organizing framework is qualitatively captured by the Physiological Fitness Landscape, which we propose as a mathematical model that offers the significant potential to improve the power and predictive capacity of medicine. Allostatic overload defines states whereby allostatic responses to stressors are unable to effectively maintain parameters of homeostasis within their narrow optimally healthy physiological ranges. Accordingly, following the removal of the extrinsic stress, the homeostatic parameters are outside their optimal range and hence the allostatic mediators do not return to their normal baseline state. Consequently, the chronically activated primary allostatic parameters search for interactions with secondary metabolic and hemodynamic parameters of allostasis to find the next most stable zone of “fitness” (i.e. requiring the least amount of free energy to maintain parameters of homeostasis within or closest to normal, relative to their prior position preceding the recent stress). These mechanisms underlie the induction and pathogenesis of noncyclical insulin resistance, in turn responsible for the hyperglycemic and hyper/dyslipidemic environment, impaired satiety and obese state, endothelial cell dysfunction, and hypertension. Together, these promote atherogenesis as well as metabolic cardiomyopathy. The hyperinsulinemia response to (or trigger of) insulin resistance is also an important driver of many states of cognitive decline, including Alzheimer’s disease and dementia (349, 350). Brain regions such as the hippocampus contain high levels of insulin receptors that under normal circumstances, are critically involved in insulin’s ability to promote cognitive performance. However, periods of cortisol surplus that lead to a state of sympathetic dominance and pro-inflammatory insulin resistance, appear to alternatively promote hippocampal atrophy and accelerated cognitive decline. Studies have shown that patients with AD have impaired hippocampal insulin receptor signaling and increased levels of inflammation, similar to that seen in peripheral insulin resistance, although mediated through disparate mechanisms. In AD, production and aggregation of amyloid β (Aβ; and amyloid β oligomers) in the brain induce glial cell activation causing neuroinflammation. Part of the biological function of such inflammation is neuroprotective as it activates macrophage clearing of Aβ and thus reduces * The focus of homeostatic parameters in this book primarily concerns redox and free energy. However, it should be implicit that acid base is inextricably interwoven as the third fundamental parameter of homeostasis.

395 toxicity. However, it concurrently contributes to neurodegeneration by enhancing and sustaining levels of proinflammatory cytokines that alter synaptic function and contribute to dysfunction in hippocampal synaptic plasticity (251, 349, 351, 352). Additionally, hyperinsulinemia also contributes to the proliferation of many non-classical insulin-responsive metabolic tissue cancers (e.g. gastrointestinal, reproductive, and urogenital systems) (353). The pro-inflammatory redox disturbed state of allostatic overload causes mutagenesis and cell transformation, i.e. cancer cell initiation. Insulin resistance and redox (354–357) is a fundamental driver of mitochondrial dysfunction, which is essential to the progression of all the chronic diseases mentioned above. We can further visualize this physiological landscape as a factor of fitness across time (aging), during conditions of stress, and of the fitness of individual organ systems. The figures below schematically depict both the Physiological Fitness Landscape and the stress response behavior corresponding to traversing through this terrain. In these figures, we illustrate graphically how stress leads to the loss of fitness, which can be measured in terms of metabolic efficiency, for example. We then show the difference between healthy aging in terms of the fitness landscape with optimal health dropping gradually as a function of time and compare it to pathological aging with sudden drops in the fitness level as the patient progresses through the subsequent stages of the chronic disease he/she is suffering from (Figure 9.24). We also show the function of the response of the physiological systems to stress as the stress increases, resulting in the terminal stage of the disease (Figure 9.25). Finally, a susceptibility function is plotted in relation to stress as the patient progresses through the disease stages (Figures 9.24 and 9.25). It should be noted that stress represents any control parameter that affects human physiology, while the response to stress is the corresponding reaction of the body to this type of stress, which may affect the cardiovascular system, the immune response or the metabolic function response. As noted above, these systems are

FIGURE 9.24  Schematic illustration of the free energy loss in the course of aging in a healthy individual (top curve) compared to pathological aging (bottom curve) with progressing disease from its onset to demise after stage II. Note the reduction in lifespan in the case of pathological aging. *F = free energy; t = time.

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FIGURE 9.25  Schematic illustration of the fitness landscape changes affected by an increased amount of stress. Within a healthy state and stress S below a toxic level S* stress has a vitalizing effect. At S = S* allostatic overload leads to stage I stress-induced disease which then progresses to stage II when S > S12 and when S exceeds S2d terminal stage of the disease occurs. *F = free energy; S = stress.

interconnected responses to a given type of stress and will be seen across the physiological systems as they form networks. Regarding physiological fitness across time, the energy flow forms a composite trajectory across a metaphoric landscape, which is the representation of health and disease in terms of the totality of usable energy in the living system (the person). This total energy is the amplitude along the Y axis over time (X axis; Figure 9.24). Separate Physiological Fitness Landscapes may be constructed for the various organ systems critical for sustaining life, such as the cardiovascular or respiratory systems. If the altitude over time of the Physiological Fitness Landscape falls to zero, that equates to attaining the thermodynamic equilibrium of the system. If this occurs in a vital organ system, it amounts to the mortality of the individual. Therefore, following the onset of disease, and following each consecutive stage of disease progression, there is a reduction in free energy, ultimately resulting in a reduced lifespan. Accordingly, constructing such profiles of the Physiological Fitness Landscape for individual physiological systems, while limited in scope, is still valuable in gaining insights into the patient’s disease state. Moving the system out of equilibrium by both pharmacological and non-pharmacological means, for example by a cardiological stress test, provides an important quantitative assessment of this system in the form of its sensitivity (or conversely, stability) to external perturbations. The system’s ability to restore its balance (equilibrium) is a measure of its homeostasis. When a physiological system is moved out of homeostasis by an external perturbation (e.g. by the onset of disease), this equates to allostatic overload, whereby allostasis is unable to

maintain homeostasis (Figure 9.25). The robustness of the system is manifested by its ability to return to equilibrium following exposure to perturbation. When the system lacks sufficient resilience relative to the stress it is exposed to, its measures of flexibility are markedly impaired. This applies to the autonomic nervous system as well as hormonal and immune system responses capable of maintaining free energy and redox parameters within optimal narrow physiological ranges. When this occurs, in terms of the stress challenge, it provides sufficient energy to overcome the energy barrier represented by the slope and height of the adjacent physiological fitness landscape “mountain”. Consequently, the bioenergetic demands of the system responding to the stress require the insulin resistance response to make glucose, fatty acids, ketones, and other energy substrates available to peripheral tissues. Here, the classical insulin-responsive metabolic tissues are the unselfish providers for the sake of the survival of the larger system (the individual). The initial sensory input triggers stress resilience programs at the most basic and foundational scales of energy fuel gauges, particularly AMPK and SIRT-1. These gauges are governed by the autonomic, hormonal, and NHR, as well as the immune system allostatic responses purposed to maintain the stability of the parameters (free energy and redox) that are sine qua non for vital organ system function. In response to the energy requirements dictated by the allostatic mediators of the stress response, AMPK engages in energy-producing pathways while inhibiting energy-consuming pathways not essential to the survival response. In concert, SIRT-1 maintains redox levels mediated by molecular level stress resistance programs

Chronic Diseases as Metabolic Disorders and correlated inflammatory tone. Hence, SIRT-1 prevents the excessive loss of free energy as heat that irreversibly can no longer be used in the shared support network of physiology to distribute subsequent stress challenges. Ultimately, allostatic overload defines stability overload states that are not healthy homeostasis (free energy and redox states are stable following the cessation of the extrinsic stress but not in the physiologically optimal range). In this setting the allostatic parameters are chronically active, inducing pathogenic (noncyclical) insulin resistance, which is responsible for the hyperglycemic and hyper/dyslipidemic environment, impaired satiety and obese state, endothelial cell dysfunction, hypertension, and atherogenesis, in addition to other chronic disease manifestations of aging. Each of the individual system parameters (e.g. immune function suppression) is usually taken separately but in reality, these parameters are tightly connected, and changing one affects the others. A stable healthy system is not easily perturbed since its equilibrium state (a valley in the landscape) is surrounded by steep slopes of the surrounding metaphorical mountains, which can only be traversed when the amount of stress exceeds a critical value (allostatic overload). When this happens, the system is thrown out of its previous equilibrium and into a new stability zone with a lower amount of stability (less steep slopes and a lower energy level). This signifies a transition to a chronically pathological state of health. This situation can get progressively worse both with the passage of time (another parameter axis that represents aging) and the addition of more of the same type of stress (e.g. financial, or emotional), or other types of stress (e.g. physical exertion). The latter should be represented by another control parameter axis. When eventually the landscape becomes flat and featureless, this corresponds to an unresponsive system, i.e. death. The most fundamental parameters of health homeostasis and disease (loss of homeostasis) are the inextricably interwoven fabric of free energy, redox, and acid base. As energy is lost to heat (systemic inflammation [the classical tumor, rubor, calor, dolor localized]) and is thus unable to do the work of maintaining homeostasis, it is coupled to entropy (the redox stress of a biological system) which breaks down the organizational construction of the biological system. Therefore, as the amplitude of the Physiological Fitness Landscape falls in the setting of critical illness, for example, over a period of days to weeks, the interactions between physiological parameters (e.g. glycemia, lipids, insulin sensitivity, endothelial, epithelial, neuronal, neuroglial and immune cell functions, cardiovascular, renal, pulmonary, cognitive and neurological systems) across cascading hierarchical scales search for new stability zones to accommodate and compensate for energy being dissipated and irreversibly lost and, consequently, for entropy being created. That is, increasing inflammatory processes and redox disturbances promote the destructive incineration of organizational eloquence and complexity of biological structure and function necessary for health and ultimately life itself. Moreover, as argued throughout this book, entropy generation is tantamount to the gradual deterioration of the perfect cyclicity of the biochemical reactions for many scales of cycles. These include the metabolic cycles of ATP production, the many circadian hormonal cycles, the monthly reproductive cycle, and so on.

397 The rate at which redox stress disrupts the molecular fidelity of these cycles is tantamount to biological aging. There is an increasing and exponential divergence from returning to the original starting point taking place in the body. This ultimately is a measure of the accelerated rate of aging. A hallmark feature in the early pathogenesis of chronic disease is the time-coordinated desynchronization of integrated systems biology and redox stress with a cause-effect bidirectional relationship. Accordingly, the loss of the total free energy flow available to be shared by the entirety of the system becomes foundationally inherent in the self-amplifying nature of chronic diseases. As redox pathogenically degrades biological structural and functional chemistry, the inseparable inflammatory process mediates the loss of useful energy as heat that is unavailable for maintaining organizational fitness and stability. Free energy is the glue, the support structure for the biological system. The declining total shared free energy among the subsystems is metaphorically a reduction in the equitable stress distribution of a support network. This places greater stress on the connecting parameters between subsystems, for example between glucose and insulin sensitivity or secretion, so that glucose can be converted to ATP substrate that provides free energy. Temporal desynchronization thus represents a critical component of compartmentalization away from the integrated nature of systems biology. When connections between such vital parameters become entirely detached from regulatory control, the metabolic instability falling off a hilltop is incapable of finding a stability zone of interactions, thus falling to thermodynamic equilibrium tantamount to death. In the setting of critical illness, why does aggressive intervention to establish normal blood sugar in a person with a history of poor glucose control portend susceptibility for mortality despite the demonstrated absence of hypoglycemia? The Physiological Fitness Landscape model has to do with provocative stress that overcomes an energy barrier of resilience, resulting in greater metabolic inefficiency and leading to the loss of free energy punctuated by phases of physiological instability. This is followed by the system of interacting parameters finding a new, albeit metastable, equilibrium zone with the next most metabolically efficient arrangement possible. Consistent with the applicability of the second law of thermodynamics to biological systems, there is a progressive rise in entropy, equatable to redox stress and hence free energy loss, over the lifetime of an individual. The Physiological Fitness Landscape progresses along this topological terrain of hilltops and valleys until ultimately transforming the total randomness of thermodynamic equilibrium, completing the life-death cycle. Accordingly, heat lost from the inflammatory processes promoted by hyperglycemia and the accompanying impaired redox occurred after triggering stress; this was followed by a phase of physiological instability in search for a new metastable state positioned at a precipitously and significantly lower state of fitness consonant with the diagnosis of diabetes. The decline in metabolic efficiency defining the new state of fitness accompanying the onset of diabetes dictates the notion of metabolic memory or legacy effect. This “critical period” following the new development of diabetes, can intuitively be reasoned to have an enduring

398 impact on long-term metabolic behavior because it represents a precipitous fall into metabolic efficiency, or fitness, from the preexisting pre-disease state. The re-equilibration of the interactions between glucose and insulin and their respective connections to the many parameters of interwoven systems with which they intersect represented the best among the relatively limited options. While this was a comparatively fragile state of fitness relative to the preceding baseline healthy state, it nonetheless represented the most metabolically efficient arrangement of all the possible options. This new most stable state may have taken the system many months to settle into following a prolonged duration of instability. A subsequent “therapeutic” re-establishment of normal levels of specified parameters, such as glucose after this period of marked hyperglycemia, pushes the system back out of its delicate but stable balance. Ironically, the subsequent most efficient state of metabolic efficiency and stability between the gestalt or connecting parameters may occur at a lower altitude of physiological fitness on the terrain of the Physiological Fitness Landscape. Further, a stability zone far from a state of equilibrium may counterintuitively be unavailable when the parameter of glucose is brought into a normal range. Thus, thermodynamic equilibrium ensues which equates to the entropic state of mortality. The metabolic inefficiency is the extent of mitochondrial dysfunction and the coinciding severity of insulin resistance. Over the course of the years or even decades following a dramatic reduction in physiological fitness, metabolic memory may dictate a seemingly implausible and unfavorable patient response to aggressive therapy, due to a false presumption that a normal glucose level has a salubrious influence on health irrespective of circumstances. This has been exemplified by the use of intravenous insulin to establish tight glucose control in the setting of critical illness. While it became the standard of care after most patients showed improved survival it was later recognized that some patients experienced the opposite outcome. The latter group likely had a lower state of physiological fitness consistent with fewer options of metabolically stable interactions. Accordingly, the tissues of vital organ systems may be predicted to have had limited capacity to utilize the far more efficient mitochondrial bioenergetic oxidation of glucose and fatty acids, instead relying on insulin-independent glucose uptake and the inefficient glycolytic pathway of metabolism for ATP production. The use of intravenous insulin drives lipogenesis in adipose tissue and glucose into skeletal muscle. In the setting of high metabolic demands of critical illness, the lowering of circulating lipids and glucose deprives adequate levels of nutrients to tissues that require the energy substrates. Notably, activating the immune system for wound healing and combating infection has enormous energetic requirements. Metabolic cardiomyopathy exemplifies an uncoupling of glycolytic metabolism to glucose oxidation as a result of mitochondrial dysfunction. Consequently, the upregulation of glycolysis stimulated by intravenous insulin-induced glucose uptake into the cardiomyocytes promotes cardiotoxic inflammatory non-energy producing pathways. Crucially, this pathogenicity is potentiated by the impaired capacity to be taken up into functional mitochondria for further oxidation. It follows that in the setting of marked cardiac insulin resistance and mitochondrial dysfunction, a legacy effect provoked by

Metabolism and Medicine intravenous insulin in the critical care setting could result in a deleterious effect on morbidity as well as on mortality. In this case, it occurs because of insulin-driven glucose uptake into the cells of the myocardium. Moreover, this pathogenic process in the context of treatment-induced euglycemia, causes further expense in terms of total body pathogenicity; it deprives vital tissues, which rely on non-insulin mediated cell glucose uptake, of essential nutrients. This scenario is better recognized in the context of cancer. In this case, a hypoxiarelated shift from oxidative phosphorylation mode of energy production to the inefficient and pro-inflammatory glycolytic mode of metabolism is a measure of the severity of malignancy and is a hallmark of cancers. Recent publications indicate that this effect, also known as the Warburg effect, may be at play in the context of diabetes. It is known that the Warburg effect is irreversible even when normoxic conditions are restored in the environment of the tumor cells. Perhaps this irreversible loss of mitochondrial function is also true for diabetic patients, which would explain the above-mentioned paradoxical demise of patients with normal glucose levels. This observation might point to inherently limited options in regard to how these systems interact on a broader scale upon which vital organ systems and ultimate survival are dependent. There is an unpredictable critical point, beyond which energy lost from the system cannot be recovered; this prompts the notion of search. The many systems of interacting parameters search for a new stability zone lower in altitude on the fitness, or free energy, landscape. The key is to find a new trough within the terrain that avoids falling too far, that is without losing too much altitude of free energy flow or fitness, required for maintaining another “far-from-equilibrium” state of stability. However, the lower in altitude the system falls, the more vulnerable it becomes to stress overcoming its energy barrier. The energy barrier may simply be in an otherwise healthy person attempting to lift more weight than he or she is conditioned for. Analogously, it may be a caloric consumption that exceeds the mitochondrial capacity to burn clean or the resilience to handle the dose of psychogenic stress. Moreover, it can be a critical illness imposing energetic demands of immune system activation and other allostatic responses that exceed the nutrient availability or bioenergetic capacity of mitochondria. Accordingly, this increases the reliance on the much less efficient glycolysis mode of energy production. Again, this explains fundamentally why establishing a euglycemic “normal glucose” environment in the intensive care setting of critically ill diabetics with historically poor glycemic control, sometimes triggers unexpected mortality. A physiological fitness model not only helps to understand this and many other phenomena conceptually, but it provides a computerized and mathematical high-powered framework for selecting optimal strategies and targeted goals of therapy on a precision personalized scale of medicine. The model increases the armament of tools for ingesting data of control parameters by a vast potential. For example, drug strategies or blood glucose ranges, and intrinsic order parameters, such as VO2 max or VO2 submax (as proxy to mitochondrial capacity), redox markers, pH, measures of primary and secondary allostatic mediators, as well as of susceptibility and disease states. The integration of hundreds of thousands of such parameters

Chronic Diseases as Metabolic Disorders by this model enriches the predictability of the trajectory of a disease or susceptibility state, and the responses to alternative interventions or targeted goals of therapy. Therefore, the model employs the notion of landscape search to find the optimal solution, that is the trough highest in altitude in the terrain of the Fitness Landscape with the steepest slope (energy barrier of resilience) to an adjacent mountain (Figure 9.26). A crucial concept is the irreversibility of free energy lost from a living system. Energy, and hence fitness, can only be restored by extrinsically applying work to the system via cognitive or physical exercise. However, this seems only possible, with potential exceptions, in two types of tissues, cognitive regions of the brain and skeletal muscle, respectively. The increased level of fitness in these tissues is mediated by mitochondrial bioenergetic capacity for efficient ATP production necessary for skeletal muscle anabolism, and for neural and synaptic plasticity in the case of cognitive regions of the brain. “Free energy” should be defined as the potential for a system to make energy, bio-energetically in the currency of ATP, or for enhanced flow of energy for adaptive functioning. Mitochondrial oxidative metabolism is the most efficient means of doing this, and hence mitochondrial dysfunction and a decline of VO2 max or VO2 submax (an underutilized tool as a proxy) parallel the process of fitness decline, aging, disease, and the loss of altitude within the terrain of the fitness landscape. In the case of brain bioenergetics, neural plasticity includes increased mitochondrial biogenesis, and synaptic plasticity promotes a greater flow of energy between neurons in the form of neurotransmission. The energy barrier of the mountain to the left from which the system fell following a stress pushing it from a higher to a lower altitude trough, amounts to the work required, which is impossible by the physiological system to mobilize from its diminished energy machinery. Furthermore, any true reversibility of the decline in free energy or fitness would be equatable to the reversal of time. Typically, the best that can be done is to find a new stability zone, or trough, at

FIGURE 9.26  A characteristic plot of the stress-response effect where the physiological response represents an order parameter R and the stress level S represents a control parameter. Note the well-defined stages I and II of the stress-induced disease with stress exceeding levels S* and S12, respectively. The slopes of the R(S) curve become steeper and steeper with the progression of the disease until the terminal level S2d is reached.

399 an equal altitude with a reshuffling of interactions between parameters that may be expressed as a reversal of disease manifestations (such as normalizing blood glucose levels, blood pressure or lipids following weight loss). However, these are metastable states attainable through exercise, or calorie restriction approaches by dietary strategies (e.g. ketogenic diet, timerestricted eating, intermittent fasting), or pharmacologically or bariatric surgically induced. These practices lower energy balance and activate the sensors of low energy states, especially AMPK and SIRT-1. These energy fuel gauge sensors in turn stimulate nuclear hormone receptors and other transcriptional regulators that increase mitochondrial biogenesis, upregulate fatty acid oxidation, and promote redox cell stress resistance programs such as DNA and cell repair enzyme systems, and the biosynthesis of antioxidant programs. Nonetheless, the increase in free energy or fitness that parallels attenuation of pathological hyperactivity of primary and secondary allostatic mediators, including improvement of insulin resistance, is offset by the baseline redox damage and destruction of biological organization that is not reversible. Furthermore, the feedforward self-amplifying and destabilizing loops such as redox and inflammatory stress, mitochondrial dysfunction, and redox stress, as well as mitochondrial dysfunction and insulin resistance, together push the free energy trajectory down. This may also explain phenomena such as weight set points and metabolic compensation, which is responsible for “slowing down metabolism” following weight loss via diet and/or exercise requiring increasing amounts of exercise or dietary restriction to avoid weight regain. There is also increasing hunger which likely is a consequence of the lower bio-energetic potential because of pre-existing mitochondrial dysfunction. Accordingly, a significant proportion of dietary consumption gets deposited in tissues widespread as ectopic fat, which is not usable or not easily usable for energetic demands. Indeed, the likelihood of sustaining 10% weight loss is unusual over a twoto four-year period of time. Only in the setting of continued exercise and dietary restriction is weight regain not accompanied by the return of metabolic syndrome features such as hypertension and dyslipidemia. Thus, despite the weight regain from metabolic compensation, the favorable lifestyle practices influence insulin sensitivity effects including PPAR gamma nuclear hormone receptor-mediated subcutaneous adipogenesis recruited from mesenchymal stem cells. In this context, body weight does not have a punitive effect on the trajectory of fitness (or free energy) within the Physiological Fitness Landscape. Pharmacological weight loss often changes weight set points, thus explaining weight regain upon discontinuation of drug therapy. Bariatric surgery appears to favorably affect a triumvirate of gut microbiota composition, bile acid metabolism, and hormone metabolism in the wall of the GI tract. In these cases, there may also be GLP-1 mediated nesidioblastosis, i.e. pancreatic beta cell regeneration. Accordingly, successful bariatric surgery may offer the greatest potential for a more durable new stability zone within the fitness landscape, best conceptualized as a deeper trough and a steeper slope. What these successful strategies all have the potential to achieve is to slow the pace of biological deterioration and aging, and prevent the progression of its non-linear divergence from chronological aging (see biological special relativity).

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Metabolism and Medicine 4) Circadian behaviors—sleep/wake, fasting/feeding, others (extrinsic). 5) Microbiota composition (may be considered intrinsic or extrinsic). Proximal intrinsic control parameters elicited by the upstream extrinsic control parameters and the stress response are:

FIGURE 9.27  A typical plot of the susceptibility function for the stressdependent response of the physiological system. Susceptibility is defined as the second derivative of the free energy function with respect to the order parameter R (response of the system). It shows sharp peaks corresponding to the extreme sensitivity of the physiological system to stress level at transition points in the pre-disease (allostatic overload) and disease stages given by S = S*, S = S12, and S = S2d, respectively. The person’s extreme susceptibility points can be used as red flags in the disease development and progression.

Nevertheless, energy that has been lost as heat from a biological system, equating to an incinerating inflammatory process cannot be used to do the useful work of biological construction, including the reconstruction of the parallel process of redox stress-induced structural entropy. Moreover, these quasi-stability zones will inevitably decline in altitude to lower troughs as a function of natural aging. Over such time, the state of fitness becomes increasingly susceptible to being pushed over the free energy barrier of a mountaintop to fall to a lower altitude in the trough of an adjacent mountain, by control parameters of stress (including dietary, dyssynchronous circadian behaviors, psychogenic and microbiota). The result is an ineluctable movement towards absolute thermodynamic equilibrium (maximum entropy state), which is death (Figure 9.27). That critical point of elevated blood glucose levels in the example of a critically ill diabetic with a history of poor glucose control, in retrospect, was a final metabolic tendril, which was life support. Here, we summarize the main aspects of the adaptation of the Physiological Fitness Landscape to medical practice. A disease state may be any that involves a vital organ system e.g. CVD, all types of cancers, Alzheimer’s disease, and other neurodegenerative diseases. Mathematically, each time point for a patient’s disease state may be a composite of hundreds of thousands of parameters characterizing this patient’s physiology at this point in time. The most proximal control parameters (1, 3, 4, 5 are all bidirectional feedforward loop interrelated relationships; 1–5 are all stressors) are:

1) Diet-quality/quantity (extrinsic). 2) Stress-psychogenic/physical (extrinsic). 3) Stress response (intrinsic).

1) Primary allostatic parameters (note redox is also a homeostatic parameter to which only subtle perturbations elicit inflammatory cytokine responses). 2) Secondary allostatic parameters: a) Insulin resistance markers (e.g. hyperglycemia, hyperinsulinemia, hyper/dyslipidemia, hypertension, subcutaneous adiposity/obesity/ diabetes[?]). b) Other hormones, NHRs, and transcriptional regulators that govern bioenergetic and redox homeostasis. 3) Homeostatic (inextricably interwoven) parameters: a) Gibbs free energy. b) Redox. c) Acid-base status. 4) Allostatic overload states (visceral adiposity/obesity, diabetes, CVD, cancers, AD, accelerated cognitive decline, accelerated biological aging, and other chronic diseases of aging) emerge when allostatic responses are unable to maintain homeostatic parameters in physiological range. The single greatest challenge to the profession of medicine is predictability of sudden death, the onset and trajectory of disease, and its response to interventions. The Physiological Fitness Landscape model addresses this head on. While the concept is relatively simple, its implementation in the clinical setting will require introduction of algorithms whose parameters may need to be estimated “on the fly” and readjusted in the course of therapy. For chronic diseases this can be done in the course of routine examinations and tests. In the case of acute emergencies, computational models may need to be built using massive amounts of big data analytics. Irrespective of the various complications facing the early adopters of the model, this author is strongly convinced that it’s only a matter of time before the practice of medicine will undergo as massive a revolution as the one that swept through the area of telecommunications and information technology. Here, the stakes are even higher because there is no price high enough to preserve one’s health and extend our life spans.

9.6 Summary We have attempted to construct a rich tapestry of elements, interconnections and relationships involving the most important aspects of metabolic health at all scales. It is tempting to say that the emerging picture shows a bottom-up hierarchy starting at the molecular level and concluding at the

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Chronic Diseases as Metabolic Disorders whole-organism representation of the metabolism’s hierarchy of coherence and synchrony. However, such a sweeping generalization is too simplistic since the hierarchy involves a flow of signals in both directions, from molecules to cells to tissues and the entire body as well as a reverse flow of signaling that begins with our interactions with the outside world. As it turns out, the outside world cannot be cleanly separated from ourselves as we are social “animals” whose whole lives are tightly enmeshed with those of others close to us and with society in general. This is a source of both vitalizing stress and toxic stress, depending on the situation we are in, our individual sensitivities, and the severity as well as the duration of stresses. Another part of our “greater” selves is the microbiota, which comprises more genes and more cells than those that are an integral part of the human body. In a sense, we are indeed what we eat. Another important relationship between our body and the external world concerns the biology of time and how we synchronize our internal biological clocks with circadian cycles of the Earth revolving and orbiting around the Sun. It is becoming increasingly clear that not respecting the cycles of the day, year, and lifetime results in negative consequences for our health. How then do we integrate the many factors, both internal and external, into our bodies in an internally consistent, logical, and quantifiable framework that can guide us through life and also provide important information to the physicians in their diagnostic and therapeutic approaches aimed at maintaining optimal health and combating disease? In this book, we have provided an outline for a future methodology that does exactly this at an individual level. This framework is inspired by physics and it is based on the identification of order and control parameters that are respectively response functions to external perturbations to the homeostatic equilibrium that living organisms tend to preserve. The response of our body to external perturbations, best exemplified by the stress test used to assess our cardiac health, is a measure of the system’s flexibility or resistance to change. In terms of a mathematical formulation of the resultant picture of our state of health (or disease), we proposed to use the socalled physiological fitness landscape, which is an analogy of the free energy function commonly used in thermodynamics and the physics of phase transitions. This general formula is indeed a function of many parameters and forms a multi-dimensional manifold that allows navigation, akin to the use of GPS when we travel far and wide, but in this case, the journey involves lifestyle choices and pharmacological interventions aimed at health risk avoidance and maximum possible fitness. The input data for the construction of the personal physiological fitness landscape, of course, depends on our access to genomic, proteomic, metabolomics as well as physiological information about the construction and functioning of our body. Hence, in the future, the entire battery of big data analytics can be brought to bear on the resultant construction of precision medicine algorithms that the physiological fitness landscape platform will enable. An additional important element in the development of this methodology is the aspect of time, more specifically aging processes. The landscape will be periodically updated and its projections refined as new data become available. As always, the devil is in the details and we hope that this book has provided a

sufficient amount of them to spawn future studies in the area of metabolism as both a branch of science and medicine.

9.7 Take-Home Messages • Mitochondrial dysfunction and impaired insulin signaling have an intertwining relationship that leads to chronic diseases of aging. Here, we detail how these chronic diseases can be viewed as metabolic diseases. • Obesity provides fertile soil for the development and progression of cancer. Insulin resistance promotes the metabolic advantage of cancer cells at the expense of host cells, providing them with a metabolic advantage. • The high metabolic rate of cancer cells and their relative dependence on aerobic glycolysis offer potential therapeutic targets. However, the metabolic flexibility of cancer cells makes this a complex and everchanging battle. • Dietary approaches such as fasting, calorie restriction, and ketogenic diets are very promising avenues for improving cancer treatment outcomes. Repurposing of some pharmaceuticals such as metformin and NSAIDs might offer additional benefits. • The brain has high energy demands and therefore it is sensitive to dysfunctional mitochondria. Dysfunctional mitochondria generate ROS, which affect nerve cells and lead to increased susceptibility to all neurodegenerative disorders including Alzheimer’s. • Mitochondrial dysfunction promotes insulin resistance, resulting in the inability of the brain to use glucose as its primary energy source. This causes alterations in the areas of the brain associated with learning and memory, ultimately leading to irreversible cognitive impairment. • Insulin resistance is also associated with several cardiovascular risk factors, most notably hypertension. Hypertension contributes to cardiovascular disease and cardiomyopathy. • Obesity saturates the storage capacity of fat tissue. This causes fat to be spilled to other organs such as the heart. A lipid-laden heart impairs cardiac performance and causes redox stress, which impairs insulin signaling and damages cardiac myocytes. The resulting mitochondrial dysfunction furthers oxidative stress, hence promulgating a feedforward destructive circuit. • The massive amount of accumulated clinical data can only be the source of useful information when combined with the computational power and algorithms of Big Data analytics. • The external control parameters for human health and disease involve the quantity, quality, and timing of diet and stressors as well as of other cycled external

402 cues. The quality of diet is largely a function of both the presence of a diversity of healthy foods and the absence of nutrient-depleted foods. The free energy landscape is a powerful concept that describes the state of health and disease of an individual in terms of a multi-dimensional complex manifold which is a function of the many control parameters defining it and whose number is only limited by our ability to measure them. • While medicine is rapidly being transformed by modern technology and data science causing it to converge toward quantitative sciences, the critical aspect of the human interaction between the patient and the physician is as important as ever.

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Epilogue Personal Anecdotes Linking Three Generations Anecdote 1—Words of Wisdom My dad was a practical man, a “man’s man”, an accomplished but humble man, and in a real sense, he elevated the very fabric of life and the richness of existence. He earned a cadre of accomplishments, accolades, and titles. Although a “big fish”, he reminded us all he was in a small pond. This makes me think of a quote by Joseph Goldstein, a 1985 Nobel Prize winner along with Michael Brown for their work on the metabolism of cholesterol. The two continued to have a long and illustrious partnership replete with ongoing extraordinary accomplishments, which they attribute to their fondness and respect for each other; their friendship. When asked how he defined friendship, Goldstein’s answer was, “Two bodies that share one soul”. It struck me that therein lies the very subjective and personal nature of the pride and love that is typically seen within families, as exemplified by mutual feelings between parents and children. These are lifeline blood relationships that view one another through magnified and very protective lenses. Their souls are in the same place, they care about the same things, they want to solve the same problems and anyone’s success is a shared success. My dad was a lifelong Giants fan, when they lost, he got visibly aggravated, calling them all, “A bunch of morons”. But, when they won, it was a better story. In fact, when I was in college, I remembered to seize the opportunity with a well-timed call to say something to the effect of “Hey Dad, Big Blue was true, and by the way, my phone bill is due!” See, you had to catch him in a good mood. Leadership starts with humility, something of a trademark quality that describes my dad. “Let us not fool ourselves”, he would say, “Muhlenberg is not Columbia Presbyterian”. But what he implied is that we can grow and anything is possible if we work as a team with dedication and hard work to open the curtain to a league no longer too competitive for a small regional medical center like Muhlenberg. Well, it was a tragedy that Muhlenberg closed, the sacrificial lamb to political football. But the symbolic accomplishments of Muhlenberg epitomize a man who always fought for the little guy. Under my dad’s direction, it opened the first coronary care unit in the state of New Jersey in the 1960s (simultaneously with Hackensack). The earliest coronary care unit nurses were trained in this unlikely hospital. My dad was one of only 500 cardiologists in the country in the 1950s. Fast forward to the present day and there are more than 50,000 cardiologists. In the 1960s and 1970s, my dad had a fellowship for training cardiologists in this obscure hospital in Plainfield, New Jersey. You see, Muhlenberg was a small pond that played a very seminal role in the soon-to-be exploding field of cardiology. This small hospital, built in 1878, was a historical rainbow in the evolution of modern-day medicine. Being credited with these achievements is never what made my dad feel important.

Rather, feeling important was in the fabric of his personality and the reason why he enjoyed swimming so much in a small pond, because he could make a difference and make that pond larger. He enjoyed the worthwhile purpose of protecting the sanctity of life and the orchestration of a coordinated effort by every member of this small pond either directly or indirectly. The journey brought everyone closer. It was psychologically vitalizing for everyone at Muhlenberg who went to work feeling proud and with a sense of purpose for the accomplishments far bigger than the summation of individual contributing efforts. That explains the camaraderie, the family-like atmosphere, and the unselfish motivations that were so pervasive through that institution up until the day it closed. Leaders themselves are not the ones that get great things accomplished in the setting of a hospital or medical center. But they set the positive climate and catalyze a feeling of empowerment to take on the challenges with a collective symphony of individual efforts. We lost the battle in 2008 to keep Muhlenberg from closing. Not every battle can be won. So, I want to revisit two questions, what is a big fish in a small pond and why was my father proud of this analogy? I believe the answer to the first question is someone who helps to grow the size of the pond and all of the fish in it feel stronger and safer. It was his bedside manner, both inside the hospital and outside as well, that will remain one of his signature trademarks. And because of that, he developed a very large network of people around him. A patient of his called my oce last month to ask how my dad was doing. I relayed the message to my dad who said, “Oh yeah, he took me fly-sailing one afternoon”. My dad loved people from all walks. He did not like certain characteristics, but rarely did he dislike an individual. Growing up my dad was very athletic. He played baseball, football, and basketball. Realistic or not, he only thought of his future in terms of sports. School was never important to him through his high school years. At the age of 17, polio struck. He was confined to a wheelchair, delaying the start of college by two years. He went to the University of Virginia and completed combined college and medical school in six years. He often spoke about his parents being overprotective, which he thought was the worst thing you could do for a kid’s selfesteem, and only served to stifle potential. He was enamored by potential and how abounding it can be. He felt he needed to break loose to find those boundaries. He refused to accept that he had physical disabilities. He took the train to college on two crutches. When he arrived at the University of Virginia, he saw it was all hills. At that point, he threw away his crutches. He simply would not accept that he was disabled. He never saw himself as disabled and he never complained. I mean, no one ever heard the man complain about anything. It was polio that ironically saved him from a life that otherwise rebelled against school. He credits becoming a physician as an adjustment to the adversity of polio, because he could no

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414 longer play sports. This was quite a transition and adjustment to adversity in life if you think about it. A young man who derived his ego largely from his physicality now faced challenges that were far greater than physical. This would be the harbinger for what became emblematic of how he taught us all how to live with change and adversity. He played golf even though he could not use his legs or shift his weight. In fact, he had all he could handle just to maintain his balance without falling, but he managed to compensate. He developed his own swing that relied only on his arms. He could not drive the ball far, so he focused on his pitch and putt game and he shot in the mid-80s. It seems that there is not any category of people my dad was not adept at relating to. He simply loved people, and his soul shined and merged with other souls. There was a very unique bond between him and my son Matthew. The two shared special personality traits, both of them with disabilities of their own but keenly sensitive to hardships and the well-being of others. Both are deeply caring and have the innate ability to connect at an emotional level. His advice for Matthew was to focus on the positive, do the best that he could do, and not worry or focus on the things he cannot do. Life is too short to waste it on frustration. He said that Matthew is a wonderful and very likeable little boy and that his personality will get him by in life. He also had a knack for relieving pain and suffering, not only in his role as a physician but through his humor, empathy, and compassion. He had an ability to enter into another person’s model of the world, understand that world and communicate that to the individual. He had an innate ability that empowered and motivated a positive vitality and wellness in us all. Said another way, he embodied the idea of human beings sharing a soul of priceless value, engaging a connection that evolves vitalizing emotions that strengthen your core of self-esteem and optimism, and that makes it easy to invite the challenges we all face. He always thought it was important to get the most out of life. He would tell me in school not to spend time studying if you are not going to be productive. Rather you could spend that time going out and enjoying yourself, playing a game of basketball, or whatever it was you would rather do. He also said, “don’t waste time doing things you do not do well; do the things that you do well and let other people do the things that they do well”. He recognized that he made mistakes in life as everyone does. He was not judgmental and realized that none of us are perched on a loft of perfection, but the fabric of your character should be strengthened by the mistakes that are made. He often said, “Don’t be afraid to work hard”, “have a sense of humor”, and “don’t focus on the negative”. His life perfectly symbolizes the theme of this chapter, that is, being an energy generating and energy-transducing member of society who elevates us all by being part of a greater whole.

Anecdote 2—of an Inspiring Model I am sure Matthew wishes more than anything to be an ablebodied competitor on his high school football team alongside the guys by whom he is so inspired. Matthew has athletic genes

Epilogue on both sides of his family, and he has the inner being that makes you think what might have been. His passion and decisiveness to be involved with the team was a good match for a group of guys who understand humility, which is outstanding at such a young age. Descriptive of many of life’s lessons that come unintended, success is a journey, not an outcome. The self-taught lessons in a hard-fought but disappointing zero and 12 season records show a real model of perfection, but was not one that the Somerville Pioneers practiced for. There was an honest, mutual, and reciprocal community of fellowship and team spirit that crushes the barometer of the win/loss record. To be part of a team in sports is a microcosm of life. It extends to both sides of the ball because even your competitor in a game is a teammate in life. Success is happiness, attainable by enjoying the passage of time. This is made possible not only by the people who love us and care about us but also who respect us. We are all on the same playing field, sharing a collective soul, some emboldening it, others diminishing it. The disability of being in a wheelchair is only a perception, however, potentially one that offers positive insight. Recognizing that others must take very little for granted should teach empathy, not sympathy. It has the capacity to touch the cord of vulnerability that we see in others before we do so in ourselves. This experience may accompany or form the element of sensitivity and humility, traits that reflect the vulnerabilities that we in fact see in ourselves before we see them in others. Not only is Matthew inspired by the game of football and the players on his high school team, but the players also reciprocally express that Matthew himself was an inspiration to them, which speaks volumes about the character of those young men. The post-season awards dinner included quotes by two of its graduating seniors that Matthew was “their most inspirational figure”. Indeed, this was a proud moment that everyone on the team deserved to share. I believe the lesson that was learned by these gentlemen is the real-life experience that being touched by another person’s weakness invites a camaraderie of strength and selflessness. Many of our own special needs are unrecognized because we cannot see them, but they often would not exist if we played life as a team sport with no scoreboard. I am proud of Matthew for playing a team sport without being on the field and of his teammates for making him feel like an equally valuable player. The lesson taught here is that getting a raw deal in life is transcended by the meaning and purpose of personal connection. Another lesson is that any competitive team is more than the sum of its parts. Team members form a living organism that is an emergent property whose abilities can hardly be predicted based on the information concerning the individual players. Sometimes a team formed from all-star players performs at a mediocre level and sometimes a team of average players rises to the level of perfection. Living organisms are composed of “team members” in the form of individual cells. When they work together, the person achieves optimal health. I do hope that you, the reader, have enjoyed this journey as much as I have. If you happen to be a physician like me, I encourage you to put on your thinking hat and see each

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Epilogue  patient as both a human being and a new and unique complex system that should not be just a routine case to be seen, classified in a 15-minute examination and given a standard prescription. Coherence and synchronization of activities of parts ensure an optimum level of efficiency corresponding to a state of health in a cell, an organ,

an organism, and a society as a whole, which has been one of the key take-home messages in this book volume.

My late father, who was a doctor of significant renown, used to jokingly quip that “following the guidelines is exactly what you need … if you are a moron”. He intuitively embraced precision medicine before it was even defined.

Index 2,4 dinitrophenol (DNP), 13 2-deoxy-glucose (2-DG), 366 3 Bromopyruvate (3BrP), 365 4Rs, 258–259

A AAAs, see Aromatic amino acids Aberrant metabolism, 365 Abnormal stress response, 247 ACC, see Acetyl-CoA carboxylase ACE2, see Angiotensin-converting enzyme Acetyl CoA, 15–16, 42, 218, 368 Acetyl-CoA carboxylase (ACC), 254 ACTH, see Adrenocorticotropic hormone Acute lymphoblastic leukemia (ALL), 205, 362 Acute stress, 247 Adenosine triphosphate (ATP), 298 Adiponectin, 306–307 Adipose tissue, 282 Adrenocorticotropic hormone (ACTH), 240 Aducanumab, 383 Advanced glycation end products (AGEs), 292, 376, 388 Advancing allostatic overload, 65 AGEs, see Advanced glycated products Aging, 193 biological entropy production rate, 13–14 genesis of acceleration and chronic diseases, 36–41 and mitochondrial dysfunction, 323–348 AHR, see Aryl hydrocarbon receptor Air hunger, 324–325 Alcohol, 256–257 ALL, see Acute lymphoblastic leukemia Allostasis, 52–53 Allostatic overload, 195, 311 Alpha-lipoic acid, 326–327 Alzheimer’s disease, 296, 303–305 amylin role in amyloid beta accumulation, 377 amyloid beta and synaptic dysfunction, 375 brain’s high energy requirements, 378–379 and cancer treatment, 206–207 cognitive decline, 379–380 insulin resistance shared pathogenesis, 375–377 mitochondrial dysfunction, 378 molecular and genetic contributors, 380–381 oxidative stress, 378 pharmacologic therapies for, 381–383 and reverse Warburg effect, 378 Amino acid metabolism, 367–368 AMP-activated protein kinase (AMPK), 254, 391, 396 mitochondrial biogenesis, 196–197 mitochondrial function, and fitness, 197–198 Amylin, 377

Amyloid beta, 375, 377 Amyloid plaques, 304 Anabolic pathways, 5 Anaplerosis, 365 Angiopoietin-like proteins, 390 Angiotensin-converting enzyme 2 (ACE2), 39 Angiotensin II, 386 Antibiotics, 257–258 Antioxidant defense system, 118–119, 339 Anxiety, 50, 69–70, 239 Apoptosis through targeted activation of caspase (ATTAC), 285 Aromatic amino acids (AAAs), 255, 256 Aryl hydrocarbon receptor (AHR), 37–38 Atherosclerosis, 387 ATP, 337, see Adenosine triphosphate Autophagy, 194 and antioxidant systems, 201 and insulin signaling, 200–201 and nutrient scarcity, 199–200

B Bacteroides fragilis, 236 Bacteroides species, 228 BCAAs, see Branched-chain amino acids BCFAs, see Branched-chain fatty acids Beta-hydroxybutyrate and FOXO signaling, 215 β-hydroxybutyrate mechanism action, 28 Bifidobacteria, 261, 262 Bifidobacterium, 260 Bifido factor, 235 Bile acids, 114–117 metabolism, 116, 241, 242 and glucose metabolism, 117 nutrient signaling vs. circadian networking, 123–126 Biliverdin reductase (BVR), 381 Biochemical characteristics, 17–18 Biochemistry of, electron transport system, 17 Bioenergetic metabolism vs. quantum metabolism (QM), 7, 9, 10 Bioenergetics acetyl CoA, 15–16 β-oxidation of fatty acids, 15 cellular development, 297–298 electron transport system, 15 glycolysis, 15 powerhouse of the cell, 331–333 TCA cycle, 15 Biological clocks, metabolism, and ATP, 144–147 CLOCK-BMAL1, 147–148 cyclical processes, 146 entropy production rate (EPR), 144 highest frequency cycle time, 145 metabolic rate and efficiency, 145 mitochondrial biogenesis and oxidative aerobic metabolism, 146

time and metabolism, 144 VO2 max or VO2 submax, 145 wave function, 146–147 Biological cycles, 133 Biological motors, 5 Biotin, 233 Body, organizing framework, 245 Bottom-up control parameters, 262–265 Bottom-up force, 230 Brain glucose metabolism, 304–305 Branched-chain amino acids (BCAAs), 255, 256 Branched-chain fatty acids (BCFAs), 255, 256 Brownlee hypothesis, 287 Brownlee’s unifying hypothesis, 43 Butyrate, 253 BVR, see Biliverdin reductase

C Caloric restriction, 248, 372 Cancer as metabolic disease, 361–362 amino acid metabolism, 367–368 anaplerosis, 365 carbohydrate metabolism, cancer therapy, 365–366 future perspectives, 373–375 insulin signaling and Warburg effect, 363–364 lipid metabolism in tumors, 368–370 metabolism-related drugs, 372–373 obesity, 362–363 oncogenic signaling and Warburg effect, 364–365 whole-body metabolism, 370–372 Carbohydrate metabolism, cancer therapy, 365–366 Carbohydrates, 339 Cardiovascular disease (CVD), 287, 296 Cardiovascular (CV) system, 157 Carnitine, 251 Carnitine palmitoyltransferase 1 (CPT1), 369 Catabolic pathways, 5–6 Catecholamines, 310 Cell redox stress resistance programs, 208 Cellular and organ system clock organization clock synchronization, external cues, 151 food, feeding/fasting cycles, 152–154 light, 151–152 exercise, 154–155 hypoxia, 155–156 phase shifts, 156 stress, 155 suprachiasmatic nucleus (SCN), 148–151 Cellular bioenergetics, 297–298 Cellular lipid deposition, 345–346 Cellular networks, 5 Cellular redox state, 339 Cellular redox systems, 119 Cellular respiration, 2 and antioxidant processes, 16

417

418 Central insulin signaling pathways, 206 Central nodal pathway, 205 Central tolerance, 236 Ceramides, 285–287 Cholesterol, 387–389 metabolism, 369 reduction therapy, 390 Chronic anxiety and uncertainty, 69–70 Chronic diseases, 193 The Warburg effect, old hypothesis, 41–42 The Warburg effect, unifying hypothesis, 43–44 Chronic diseases of aging, metabolism in Alzheimer’s disease amylin role in amyloid beta accumulation, 377 amyloid beta and synaptic dysfunction, 375 brain’s high energy requirements, 378–379 cognitive decline, 379–380 insulin resistance shared pathogenesis, 375–377 mitochondrial dysfunction, 378 molecular and genetic contributors, 380–381 oxidative stress, 378 pharmacologic therapies for, 381–383 and reverse Warburg effect, 378 cancer as metabolic disease, 361–362 amino acid metabolism, 367–368 anaplerosis, 365 carbohydrate metabolism, cancer therapy, 365–366 future perspectives, 373–375 insulin signaling and Warburg effect, 363–364 lipid metabolism in tumors, 368–370 metabolism-related drugs, 372–373 obesity, 362–363 oncogenic signaling and Warburg effect, 364–365 whole-body metabolism, 370–372 metabolic cardiomyopathy, 385–386 ischemic dilated cardiomyopathy, 387 metabolic pharmacotherapy, 391–393 non-ischemic dilated cardiomyopathy, 386–387 pathological cardiac hypertrophy, 384–386 physiological cardiac hypertrophy, 383–384 vascular atherosclerosis, 387–391 mitochondrial dysfunction vs. insulin signaling, 356–358 obesity, inflammation, and insulin signaling, 359–361 Chronic inflammation, 262 Chronic insulin resistance and hyperinsulinemia causes, 30–31 Chronic overnutrition, 217 downstream effects, 219 ectopic lipid deposition, 218–221 metabolic signals resulting, 220 the role of metabolic flexibility, insulin sensitivity, 217–218 Chronic stress response, 247 Chronobiology, 135

Index Chronobiology and nuclear hormone receptors, 158 lipid sensors, 160 peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α), 162 peroxisome proliferator-activated receptors (PPARs), 162 retinoid-related orphan receptor (RORs), 160–162 rev-erbs, nuclear hormone receptors, 162 retinoid X receptor (RXR) heterodimeric receptors, 159 constitutive androstane receptor (CAR), xenobiotic metabolism, 160 farnesoid X receptor (FXR), 159–160 thyroid hormone receptor (TR), 159 steroid receptors, 158 glucocorticoid receptor (GR), 158–159 Chylomicron, 344 Circadian, 307 behaviors, 244 biology and medicine, 183 control energy metabolism, 83 cycles, 202–203 disruption, 167–168 disturbances, 343–345 interactions, nutrient balance, 170–172 misalignment, endogenous oscillating cycles, 177–178 rhythms, 141, 249–250 in humans, 157 and metabolic, 171 synchronized physiological conditions, 203 Circadian insulin signaling and hormesis, 209–210 importance of, 36 resistance and cell redox stress resistance programs, 210 transition to chronic non-cyclical insulin resistance, 211 energy sensor responses to non-cyclical insulin resistance, 211–212 nocturnal eating, overconsumption and metabolic disease, 212–213 Clostridial species, 228 Clostridium botulinum, 229 Clostridium difficile, 230 Clostridium genus, 229 Clostridium perfringens, 230 Clostridium tetani, 229 Coenzyme Q, 337 Coenzyme Q (ubiquinone), 335 Coenzyme Q10 (CoQ10), 327 Cognition, 214–215 Cognition emotion top-down control, 91 Cognitive decline, 379–380 Complex I, 333, 337 Complex II, 334, 337, 338 Complex III, 335 Complex IV, 335 Complex V, 335 Constitutive androstane receptor (CAR), 160 Constructive and destructive interference, 79 Copper, 331 Cori Cycle, 300

Coronavirus disease from 2019 (Covid-19), 12–13, 38–39 exercise-induced, 92–93 Corticotropin-releasing factor (CRF), 240, 247 Corticotropin releasing hormone (CRH), 310 CPT1, see Carnitine palmitoyltransferase 1 The Crabtree effect, 42 CRF, see Corticotropin-releasing factor CRH, see Corticotropin releasing hormone Cryptochrome molecules, 44–45 CVD, see Cardiovascular disease Cytochrome c, 335

D Danger-associated molecular patterns (DAMPs), 262 DCA, see Dichloroacetate Declining health, 56 DeFronzo, Ralph, 278–280 Delta slow wave sleep, 202–203 Dendritic cells, 237 Devitalizing stress, 193–194 DI, see Disposition index Diabetic cardiomyopathy, 287, 385–386 Diabetic ketoacidosis, 29 Diacylglycerols (DAGs), 241, 285, 291, 292, 348 Dichloroacetate (DCA), 14, 300 Diet, 244, 250–252 Dietary manipulation or supplementation, 30 Dihydrolipoate, 326–327 Dimethyl fumarate, 320 Disease state, 400 synchrony and desynchrony, clocks, 163–183 Disposition index (DI), 291 DNA glycation, 292 DNA repair, 194 Dopamine, 248 Drug pioglitazone, 38 Dysbiosis, 234 Dysfunctional mitochondria, 2 Dysfunctional mitochondrial metabolism, 13 Dysfunctional serotonergic system, 248 Dysfunction in electron transport system, mitochondrial function, and chronic disease basics of, 17 biochemical characteristics, 17–18 biochemistry of, 17 cellular respiration and antioxidant processes, 16 clinical application and insulin resistance and type 2 diabetes, 21–23 clinical perspective, 18 fatty acid metabolism, 24–25 glucose and lipid metabolism, 18–19 macronutrients contributions, proton motive force, and oxidative stress, 23–24 metabolic disease, treatments of, 25–26 improving mitochondrial metabolism, 25–26 outcome, 26–27 pharmacologic intervention, 26 mitochondria, 16 redox potential and biochemical reactions, 20–21

419

Index Dyslipidemia, 376–377 Dysregulation, 195 Dyssynchronous insulin signaling, 290

E Early-life stress, 247 Ectopic fat accumulation, 386 Ectopic lipids, 285 accumulation, 291–292 chronic overnutrition, 218–221 EDGF, see Epidermal derived growth factor The effects of stress on fitness function, 95 Electron transport chain (ETC), 5–6, 294, 335, 336 Electron transport system (ETS), 15, 298, 333–337 metabolic disease, treatments of, 25–26 mitochondrial redox system, therapeutic implications, pharmacologic intervention, 26 Electron transport system dysfunction clinical perspective of, 18 mitochondrial function and chronic disease basics of, 17 biochemical characteristics, 17–18 biochemistry of, 17 cellular respiration and antioxidant processes, 16 clinical perspective of, 18 fatty acid metabolism, 24–25 glucose and lipid metabolism, 18–19 insulin resistance and type 2 diabetes, 21–23 macronutrients contributions, 23–24 metabolic disease treatments, 25–26 redox potential importance, biochemical reactions, 20–21 outcome, 26–27 Emotional nervous system, 247 Emotional stress, 247 Emotion cognition top-down control, 91 Endocrine system, 204 Endotoxicosis and insulin resistance, 39–40 parameters of, 40 Endurance capacity, 11 Energetically challenged brain, 65 Energy expenditure, 70–71 Energy sensing functions of, AMPK and SIRT1, 196 activation of PGC-1a, 199 AMPK, mitochondrial function, and fitness, 197–198 AMPK role of, mitochondrial biogenesis, 196–197 circadian fluctuations importance, insulin signaling and FOXO activation, 202–204 deacetylation and direct phosphorylation, 200 FOXO regulation, cellular metabolism, 201–202 FOXO role of, and stress resilience programs, 198 FOXO transcription factors and autophagy, 198–199 autophagy and antioxidant systems, 201

autophagy and insulin signaling, 200–201 autophagy and nutrient scarcity, 199–200 goal of, 204 mechanistic links, 197 PGC-1α role of, downstream transcription factors, 198 Energy sensors and fuel gauges, 32 circadian biology and metabolic homeostasis, 32–33 parameters of diet and an ETC mechanistic model of human metabolic health and disease, 33–36 Enteric nervous system (ENS), 238 Entropy production rate (EPR) and aging ATP, 13 dichloroacetate promotes, 14 pharmacological implications dichloroacetate (DCA), 14 Imeglimin, 14 Irisin, 14 mitochondria, 14 pyruvate dehydrogenase complex (PDC), 14 redox and inflammatory stress, 13 Environmental signals integration, 121–122 EPI, see Exocrine pancreatic insufficiency Epidermal derived growth factor (EDGF), 232 EPR, see Entropy production rate Estrogen, 282 ETC, see Electron transport chain ETF-ubiquinone oxidoreductase (ETF-QO), 338 ETS, see Electron transport system Excess energy substrate, 212 Excessive air hunger, 325 Excess nutrient intake, 33 Exercise response, 120–121 Exocrine pancreatic insufficiency (EPI), 258 External parameters, 32 Extrinsic control parameters, 96, 312 circadian behaviors, 244 circadian rhythms, 249–250 diet, 244, 250–262 microbiota as, 244–247 physical factors, 244 psychogenic factors, 244 stress and microbiota, 247–249

F FAD, see Flavin adenine dinucleotide Faecalibacterium prausnitzii, 260 FAO, see Fatty acid oxidation Farnesoid X receptor (FXR), 107, 115–116, 123–126, 159–160 bariatric surgery improvement, 117 gut microbiota, 118 Fasting, 214–215, 371 cycles, 152–154 hyperinsulinemia, 212 muscle wasting, 29 survival endurance, 216–217 Fasting-induced adipocyte factor (FIAF), 253, 254 FAT-ATTAC, 285 Fatty acid metabolism, 369–370

mitochondrial function, and insulin resistance, 382 relevance aging and chronic diseases, 24–25 Fatty acid oxidation (FAO), 17–19, 24–25, 276 Fecalbacterium prausnitzii, 240 Fecal microbiota, 240 Fecal microbiota transplantation (FMT), 227, 228, 261–262 Fecal transplantation, 248 FET, see Forward electron transfer FGF-21, see Fibroblast growth factor 21 FIAF, see Fasting-induced adipocyte factor Fibrates, 391–392 Fibroblast growth factor 21 (FGF-21), 286 Firmicutes phylum, 261 Flavin adenine dinucleotide (FAD), 326, 334 Flavin-containing monooxygenases (FMOs), 252 FMT, see Fecal microbiota transplantation Forkhead box O (FOXO), 344 regulation, cellular metabolism, 201–202 and stress resilience programs, 198 transcription factors and autophagy, 198–199 autophagy and antioxidant systems, 201 autophagy and insulin signaling, 200–201 autophagy and nutrient scarcity, 199–200 Forkhead box protein 1 (FOXO1), 199–202, 299 Forward electron transfer (FET), 337 FOXO1, see Forkhead box protein 1 FOXO3A, 204 Free radicals, 292–293 FXR, see Farnesoid X receptor

G G-6-P, see Glucose-6-phosphate G6Pase, see Glucose 6-phosphatase GALT inhabitants, 237 Gastrointestinal microbiota, 245 Gamma aminobutyric acid (GABA), 239, 248 Gastrointestinal tract, 235 GBA, see Gut-brain axis GBM, see Glioblastoma multiforme The General Adaptation Principle, 51 Genesis of acceleration aging and chronic diseases endotoxicosis and insulin resistance, 39–40 insulin resistance, diet, peripheral clocks and metabolism, 36 insulin resistance and hyperinsulinemia, 36–37 lipolysis loss of VAT and autonomic dysfunction, 38 obesity and SARS-CoV-2, pulmonary fibrosis, 38–39 visceral adiposity, inflammatory diet and insulin resistance, 40–41 visceral adiposity, protective role, 37–38 Genetics and lifestyle, mitochondrial health, 36 Germ-free mice, 240 GH, see Growth hormone Glioblastoma multiforme (GBM), 367

420 GLP-1, see Glucagon-like peptide-1 GLP-2, see Glucagon-like peptide-2 Glucagon, 277 Glucagon-like peptide-1 (GLP-1), 123, 253, 342, 381, 382 Glucagon-like peptide-2 (GLP-2), 231 Glucocorticoid mechanism action, 110 Glucocorticoid receptor (GR), 158–159 Glucocorticoids, 150, 247 Gluconeogenesis, 116 Glucose 6-phosphatase (G6Pase), 290 Glucose-6-phosphate (G-6-P), 284 Glucose and lipid metabolism, 18–19 Glucose metabolism, 116–118 bile acids, 117 gluconeogenesis, 116 insulin, 116–117 microbial bile acid conversion, 118 Glucose transporter type (GLUT), 296 Glucose vs. fatty acid metabolism, 337–338 GLUT, see Glucose transporter type GLUT1 and GLUT4, 393 Glyceroneogenesis, 300 Glycine, 368 Glycogen synthase kinase 3 (GSK3), 380–381 Glycolysis, 15, 336 Gnotobiosis, 228 Goal-oriented behavior, 75 GR, see Glucocorticoid receptor Growth hormone (GH), 282, 310 GR signaling and cortisol resistance, 71 GSK3, see Glycogen synthase kinase 3 Guanosine-5’-triphosphate (GTP), 6 Guilds, 233 Gut bacteria, 238 Gut-brain axis (GBA), 247 Gut microbiota, 227, 234, 247, 251, 261 vs. human host, 227–228 GW501516, 259

H HCl, see Hydrochloric acid HDACs, see Histone deacetylases HDL, see High-density lipoprotein Hexokinase, 363 High-density lipoprotein (HDL), 390 High-fat diet, 248 Hippocrates, 226 Histone deacetylase (HDAC), 253, 392 Histone modification, 232 Homeostasis, 4 Hormesis, 58 and circadian insulin signaling, 209–210 stress responses, 193–194 Hormones display circadian rhythmicity, 156–158 Host health, 244–245 Host metabolism impacts, 240–241 HPA, see Hypothalamic-pituitary-adrenal Human health and disease, 97 Human longevity, 204 Hunter-gatherer lifestyle, 165 Hurstings, Stephen, 281 Hydrochloric acid (HCl), 258 Hydrogen sulfide, 256 Hyperinsulinemia, 194, 200, 293, 359, 394 Hyperlipidemia, 286

Index Hypermethylation, 233 Hypertension, 279 Hypothalamic-pituitary-adrenal (HPA), 235, 239, 240, 244

I IGF, see Insulin-like growth factor IGF-1 receptors, 281 IGFBP2, see Insulin-like growth factor binding 2 ILCs, see Innate lymphoid cells IMCL, see Intramyocellular lipid Imeglimin, 14 IMM, see Inner mitochondrial membrane Immune responses, 244 Impaired bioenergetics and redox stress, 211 Impaired insulin signaling, 304 Incretin hormone, 246 Inhaled intranasal insulin, 305 Innate lymphoid cells (ILCs), 249 Inner mitochondrial membrane (IMM), 333 In-phase oscillations, 80 Inspiring model, 414–415 Insulin, 116–117, 208–209 Insulin-like growth factor (IGF), 281 Insulin-like growth factor binding 2 (IGFBP2), 306 Insulin receptor (IR) activation of, 207 signaling pathway, 208 Insulin receptor substrate-1 (IRS-1), 282 Insulin resistance, 40, 173, 194–195 development in liver and visceral adipose tissue, 342 in skeletal muscle, 340–342 diet, peripheral clocks and metabolism, 36 and hyperinsulinemia, 36–37, 221 and mitochondrial dysfunction, 44 traditional view of, 37 and type 2 diabetes, clinical application and redox state, 21–23 Insulin resistance role, metabolic disease Alzheimer’s disease, 304–305 amyloid plaques, 304 bioenergetics and development cellular bioenergetics, 297–298 mitochondrial function, 298–299 mitochondria role, 298 pyruvate dehydrogenase enzyme complex (PDH), 300–301 brain glucose metabolism, 304–305 as chronic control parameter, 308–310 control parameters, insulin signaling Alzheimer’s disease, 296 cancer dysregulation, 297 cardiovascular disease, 296 free radicals role, 292–293 under healthy and pathologic conditions, 277–278 historical context, 278–279 body effects, 280–282 ceramides, ectopic lipids, and ROS, 285–286 chronic diseases of aging as manifestations, 286–292 C. Ronald Kahn and critical nodes, 282–283

Gerald Shulman, 283–284 Philipp Scherer’s work, 284–285 Syndrome X, 279–280 impaired insulin signaling, 304 implications, across different tissues of body, 293–294 insulin signaling, cancer bioinformatics, defining simple rules, 303 mitochondrial dysfunction, 302–303 integrated systems biology approach, 305 adiponectin, 306–307 leptin, 306–307 osteocalcin, 306 metabolic flexibility dyssynchronous insulin signaling, 290 ectopic lipid accumulation, 291–292 pathogenic hyperinsulinemia development, 290–291 respiratory quotient, 289–290 on microtubule dynamics, 304 vs. mitochondrial dysfunction, 294–296 neurofibrillary tangles, 304 order and control parameters, 308 overview, 276–277 oxidative stress, 292–293 physiological role, 277 prolonged stress response, 311 stress as allostatic response, 310–311 therapeutic strategies, treatment, 305 upstream control parameters, 311 Insulin sensitivity, 198 metabolic flexibility, 217–218 Vitamin K maintains calcium homeostasis, 330–331 Insulin signaling, cancer bioinformatics, defining simple rules, 303 mitochondrial dysfunction, 302–303 Insulin-stimulated glucose uptake (ISGU), 293 Insulin therapy, 389 Integrated systems biology approach, 305 adiponectin, 306–307 leptin, 306–307 osteocalcin, 306 Interconnected control parameters, 210 Intermittent fasting, 153 Intestinal barrier function, 239 Intracellular fatty acid metabolites, 346 Intracellular lipid accumulation, 284 Intramyocellular lipid (IMCL), 293 Intrinsic control parameters, 400 Intrinsic order parameters autonomic branches, central stress response, 244 hypothalamic-pituitary-adrenal (HPA) axis, 244 immune responses, 244 microbiota as, 244–247 through lens of innate immune system, 262 Irisin, 14 Iron, 331 IRS-1, see Insulin receptor substrate-1 ISGU, see Insulin-stimulated glucose uptake

J Janus kinase (JAK), 297

421

Index K Kahn, Ronald, 282–283 Kahn Lab, 282 Ketoacidosis, 215 case report, 29 Ketogenesis, 214–215 Ketogenic diet, 27, 248, 339, 371–372 Ketogenic pathway vs. cholesterol synthetic pathway, 27 Ketone body metabolism approaches to achieve ketosis, 216 beta-hydroxybutyrate esters, athletes metabolic performance, 216 beta-hydroxybutyrate esters, military metabolic performance, 216 backup fuel, 217 evolutionary insights, 214 fasting, ketogenesis, and cognition, 214–215 health and disease, 27 benefits, non-diabetic diseases, 30–31 benefits and dangers, diabetes, 29–30 conclusions, 32 role of, starvation, 28–29 super fuels and electron scavengers, 28 Yin-Yang perspectives, 31–32 human health and survival endure fasting, 216–217 ketosis—a danger or a health signal, 215 Ketones, 32 Ketosis, 29–32 Krebs cycle, 3

L Lactate dehydrogenase A (LDHA), 366 Lactobacilli, 260, 262 Lactobacillus rhamnosus B-1, 248 Lactobacillus sp., 230, 231, 260, 261 L-carnitine, 325 LDHA, see Lactate dehydrogenase A LDL, see Low-density lipoprotein Leaky gut syndrome, 231 Legacy effect, 394 Leptin, 306–307 LeRoith, Derek, 281 Lipid homeostasis, 111–116 bile acid metabolism, 116 bile acids, 114–115 farnesoid X receptor (FXR), 115–116 Liver X receptors (LXRs), 113–115 peroxisome proliferator-activated receptors (PPARs), 111–113 thiazolidinediones (TZD), 113 Lipid metabolism, 337 electron transport system, 18–19 tumors, 368–369 cholesterol metabolism, 369 fatty acid metabolism, 369–370 Lipid sensors, 160 peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α), 162 peroxisome proliferator-activated receptors (PPARs), 162 retinoid-related orphan receptor (RORs), 160–162

rev-erbs, nuclear hormone receptors, 162 Lipopolysaccharide (LPS), 231, 240 Lipoprotein, 387–389 Lipoprotein lipase (LPL), 253 Liver X receptors (LXRs), 107, 390, 391 regulate cholesterol metabolism, 115 regulate liver lipogenesis, 114 Longevity, 193 Long-term depression (LTD), 78 Long-term potentiation (LTP), 76–77 Loss of physiological fitness, 94 Low-density lipoprotein (LDL), 286–288, 293, 387, 390 LPL, see Lipoprotein lipase LPS, see Lipopolysaccharide LTD, see Long-term depression LTP, see Long-term potentiation LXRs, see Liver X receptors

M Macronutrients redox potential, proton motive force and oxidative stress, 23–24 substrates metabolism, 345–349 Macrophages, 237 Magnetic resonance spectroscopy (MRS), 284 Malonyl CoA decarboxylase (MCD), 325 Mammalian target of rapamycin (mTOR), 196–197 Manganese, 331 MAO, see Monoamine oxidase MAPK, 303; see Mitogen-activated protein kinase MAPs, see Microtubule-associated proteins Maternal stress, 247 MCD, see Malonyl CoA decarboxylase Measuring time, biology, 142–144 aging process, 143–144 biological clocks, 142 quantum metabolism, 143 time dilation, 143 Mechanistic insights insulin resistance, cellular level, 204–205 nodes of insulin signaling, 205–206 the role of GSK3 in cell resistance, 206–207 the role of mTOR in cell resistance, 207–209 Mechanistic target of rapamycin (mTOR), 367 Medicine, 52–53; see also individual entries Melatonin, 141, 202–203 and metabolism, 149 Metabolic adaptations, 196 Metabolic cardiomyopathy, 385–386 ischemic dilated cardiomyopathy, 387 metabolic pharmacotherapy, 391–393 non-ischemic dilated cardiomyopathy, 386–387 pathological cardiac hypertrophy, 384–386 physiological cardiac hypertrophy, 383–384 vascular atherosclerosis, 387–391 Metabolic demand, 64–65 Metabolic disease, 212–213 states, 59 synchrony and desynchrony, 172–175 treatments, 25–26

The Warburg Effect old hypothesis, 41–42 unifying hypothesis, 43–44 Metabolic dysfunction, 293 Metabolic efficiency, 8–10, 264 glucose vs. fatty acids, 15 Ketone bodies, 15 Metabolic flexibility, 276, 346 insulin resistance, 289–291 insulin sensitivity, 217–218 Metabolic inflexibility, 218, 221, 346–347 Metabolic pathways and cellular respiration adenosine triphosphate (ATP), 5–6 electron transport chain’s (ETCs), 5–6 energy production modes adenosine triphosphate (ATP), 8 bioenergetic metabolism vs. quantum metabolism (QM), 7 classical mode, 7 molecular collisions, 7 quantum mode, 7 synchronization of, classical and quantum mode, 7–8 guanosine-5’-triphosphate (GTP), 6 human health state, 7 metabolic cycles and metabolic rate aerobic glycolysis, 10 cellular metabolism, 9 efficiency, 8–10 human nervous system, 9 metabolic rate vs. allometric scaling law, 8 oxidation-reduction (redox) reaction, 9 quantum metabolism, 9 ROS, 9 takeover threshold, 10 metabolic rate, efficiency and cellular respiration, clinical medicine adenosine triphosphate (ATP), 11 COVID-19, 12–13 endurance capacity, 11 VO2 max and VO2 submax, 11 Metabolic pharmacotherapy, 391–393 Metabolic/physiological fitness landscape, 135 Metabolic rate, 324 efficiency and cellular respiration, 10–13 metabolic cycles, 8–10 take-over threshold, 195 Metabolic sensors and regulators, AMPK and SIRT1, 34 Metabolic switch, 201–202, 276 Metabolism; see also individual entries biological motors and engines fuels, 4–5 and clinical medicine, 89 description, 1–2 function and dysfunction result, 2 remarks, 4 scales of time and space, 164–167 Metformin, 372–374, 391 Methanobrevibacter smithii, 260 Methionine, 368 Methyltransferases, 233 Microbial bile acid conversion, 118 Microbial dysbiosis, 238 Microbial dysregulation, 238 Microbial methyltransferases, 233 Microbiome, 372 Microbiota, symbiotic entanglement

422 as extrinsic and intrinsic order parameter, 244–247 extrinsic control parameters circadian behaviors, 244 circadian rhythms, 249–250 diet, 244, 250–262 physical factors, 244 psychogenic factors, 244 stress and microbiota, 247–249 intrinsic order parameters autonomic branches, central stress response, 244 hypothalamic-pituitary-adrenal (HPA) axis, 244 immune responses, 244 microbiota and human liaison composition, 228–230 ecology and supraorganism, 233–234 epigenetic systems, 232–233 genetics, 232 gut microbiota, 227 human host vs. gut microbiota, 227–228 microbiota-mediated inflammation, 230–232 supraorganism co-development, 234–235 co-evolution, 241–243 gastrointestinal tract, 235 host metabolism impacts, 240–241 hypothalamic-pituitary-adrenal (HPA) axis, 240 microbiota and immune system, 235–238 nervous system, 238–240 Microbiota-gut-brain axis, 238–239 Microbiota-mediated inflammation, 230–232 Microtubule-associated proteins (MAPs), 304 Minerals and trace elements, 331 Mitochondria, 16, 289 antioxidant defense system, 339 bioenergetic powerhouse of the cell, 331–333 electron transport system, 333–336 function, 333 in glucose metabolism, 336–337 and GR signaling, 71 in metabolism of organic molecules, 337 pathophysiology, 333 in redox homeostasis, 337–339 structure, 333 Mitochondrial DNA (mtDNA), 333 Mitochondrial dysfunction, 254, 323–324, 401 air hunger, 324–325 in Alzheimer’s disease, 378 vs. insulin resistance, 294–296, 340–345 macronutrient substrates metabolism, 345–349 mitochondria antioxidant defense system, 339 bioenergetic powerhouse of the cell, 331–333 electron transport system, 333–336 function, 333 in glucose metabolism, 336–337 in metabolism of organic molecules, 337 pathophysiology, 333

Index in redox homeostasis, 337–339 structure, 333 nutrient influence, 339–340 supplements, mitochondrial health alpha-lipoic acid, 326–327 B vitamins, 326 CoQ10, 327 dihydrolipoate, 326–327 dimethyl fumarate, 320 L-carnitine, 325 minerals and trace elements, 331 peroxisome proliferator-activated receptor γ (PPARγ), 327–329 vitamin D, 327 vitamin K2, 330–331 Mitochondrial dysfunction vs. insulin signaling, 356–358 Mitochondrial function, 298–299, 336 Mitochondria role, 298 Mitogen-activated protein kinase (MAPK), 388 Modern-day humans, 166 Modern-day stress response model metabolic demand, 64–65 uncertainty reduction model, 65–66 Molecular clocks, 147–148 Monoamine oxidase (MAO), 305 MRS, see Magnetic resonance spectroscopy mtDNA, see Mitochondrial DNA mTOR, see Mechanistic target of rapamycin Mucosal immune system, 235 Multidimensional physiological fitness landscape, 394 myCircadianClock, 136

N N-acetyl glucosamine (GLcNAc), 385 NAFLD, see Non-alcoholic fatty liver disease National Institutes of Health (NIH), 228 NEFAs, see Non-esterified free fatty acids Nervous system, 238–240 Neural and humoral signals, 160 Neural circuitry reward, 73 Neural circuitry stress chronic anxiety and uncertainty, 69–70 energy expenditure, 70–71 interconnections, 66 neuroendocrine response and insulin resistance, 66–67 stress vs. norepinephrine, 67–68 uncertainty, 68–69 Neuroanatomy stress response, 70 Neuroendocrine and autonomic stress response, 63 Neuroendocrine response and insulin resistance, 66–67 Neuroendocrinology, 307–311 Neurofibrillary tangles, 304 Neuroglycopenia, 213–214 Neuron-derived orphan receptor 1 (NOR1), 119 NHR, see Nuclear hormone receptor NIH, see National Institutes of Health Nocturnal eating, 212–213 and insulin resistance, 178–181 Non-24 syndrome, 151 Non-alcoholic fatty liver disease (NAFLD), 256

Non-coding RNA, 233 Non-esterified free fatty acids (NEFAs), 298, 299 Non-ischemic dilated cardiomyopathy, 386–387 Non-steroidal anti-inflammatory drugs (NSAIDs), 373 NOR1, see Neuron-derived orphan receptor 1 Norepinephrine, 248 NRF2, see Nuclear respiratory factor 2 NRH, see Nuclear hormone receptor NRs, see Nuclear receptors NSAIDs, see Non-steroidal anti-inflammatory drugs Nuclear hormone receptor (NHR), 134, 276 classifications, 109–111 adopted receptors, 110 ligand-dependent control, 111 orphan receptors (ORs), 110 rev-erb receptors, 110–111 steroid hormone receptors, 110 SUMOylation, 111 clinical applications, 122 environmental signals integration, 121–122 exercise and energy, 121 function of, 112 ligand-dependent control, 111 metabolism and circadian clocks, 124 metabolism and exercise mimetics, 162–163 pharmacological targets, 122 redox homeostasis, 118–119 role of, 212 RORs, metabolic fitness, 119 sense and energy modulation, 111 exercise response, 120–121 glucose metabolism, 116–118 lipid homeostasis, 111–116 skeletal muscle, 120 structure, 109 structure and function, 109 Nuclear receptors (NRs) biochemical techniques, 107 FXRs and LXRs, 107 GR and PPARs, 107 orphan receptors (ORs), 107 seminal contributor, 108 steroid ligand, 106 timeline of, 108 Nuclear respiratory factor 2 (NRF2), 327 Nutrient signaling vs. circadian networking, 123–126

O Obesity, 362–363 cortisol and cushing’s, 182–183 and SARS-CoV-2, pulmonary fibrosis, 38 angiotensin-converting enzyme 2 (ACE2), 39 ectopic fat, 39 hypoxia and inflammation, 39 O-linked N-acetylglucosamine (O-GlcNAc), 304 Omentum, 37 OMM, see Outer mitochondrial membrane Orphan receptors (ORs), 110 Osteocalcin, 306

423

Index Outer mitochondrial membrane (OMM), 333 Overconsumption, 212–213 Oxaloacetate, 300 Oxidative stress, 292–293 in Alzheimer’s disease, 378 disrupt, 262 Oxidized-LDL (Ox-LDL), 388 Oxygen consumption vs. allostasis, 11 Oxytocin, 59–60

P PAMPs, see Pathogenassociated molecular patterns Parathyroid hormone (PTH), 306 The Pasteur effect, 42 Pathogenassociated molecular patterns (PAMPs), 235, 262 Pathological cardiac hypertrophy, 384–385 diabetic and metabolic cardiomyopathy, 385–386 Pattern recognition receptor (PRR), 231, 262 PDC, see Pyruvate dehydrogenase complex PDH, see Pyruvate dehydrogenase enzyme complex PEPCK, see Phosphoenolpyruvate carboxykinase Peptide YY (PYY), 253 Peripheral tolerance, 236 Peroxisome proliferator-activated receptor gamma (PPARγ), 301, 327–329, 382, 391 Peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α), 162 Peroxisome proliferator-activated receptors (PPARs), 111–113, 162 Personalized response to dietary composition (PREDICT 1), 251 PFL, see Physiological Fitness Landscape PGC-1α, see Proliferator activated receptor coactivator PGC-1α, downstream transcription factors, 198 Pharmacological implications clinical applications, 122 dichloroacetate (DCA), 14 Imeglimin, 14 Irisin, 14 mitochondria, 14 pyruvate dehydrogenase complex (PDC), 14 Philosophical and mechanistic perspectives, 192 longevity, aging and chronic diseases, 193 physical and biological systems, 192–193 Phosphatidylinositol- 3 kinase (PI-3K), 282 Phosphoenolpyruvate (PEP), 300 Phosphoenolpyruvate carboxykinase (PEPCK), 301 Phosphoinositol 3 kinase (PI3K), 364 Physical and biological systems, 192–193 Physical factors, 244 Physical time, biology aging process, 138 aging rate, 137 arrow of time, 137 chronological time, 139

circadian rhythms, 138 entropy, 137–138 first law of thermodynamics, 138–139 homeostatic, 138 inflammation, 138 metabolic efficiency, 138 second law of thermodynamics, 137 special relativity, 139 time dilation, 137 Physiological cardiac hypertrophy, 383–384 Physiological fitness and feedback loops, 91 Physiological Fitness Landscape (PFL), 50, 53–56, 62, 393–400 and feedback loops, 91 healthy and stressed, 96 human progression, 97 organizing principle of, 87 PI-3K, see Phosphatidylinositol- 3 kinase Polyunsaturated fatty acids (PUFAs), 125 PPARs, see Peroxisome proliferator-activated receptors PPARγ, see Peroxisome proliferator-activated receptor gamma Prebiotics, 256 PREDICT 1, see Personalized response to dietary composition Probiotics, 259–261 Proliferator activated receptor coactivator (PGC-1α), 253, 254 Prolonged fasting leads, muscle wasting, 29 Protein kinase Cε (PKCε), 284, 291 Proteobacteria, 230, 231 Proteolytic fermentation, 255–256 Proximal control parameters, 400 PRR, see Pattern recognition receptor Pseudo-diabetes, 347 Psychogenic factors, 244 Psychogenic stress, 194 PTH, see Parathyroid hormone PUFAs, see Polyunsaturated fatty acids Pulmonary fibrosis, 38–39 Pyruvate, 336 Pyruvate dehydrogenase complex (PDC), 14, 254, 393 role, energy production and insulin resistance, 299–300 Yin and Yang of glyceroneogenesis, 300–301 Pyruvate dehydrogenase enzyme complex (PDC), 393 Pyruvate dehydrogenase kinase (PDK), 299, 303–305 PYY, see Peptide YY

Q Q cycle, 335 Quantum consciousness, 81 Quantum metabolism, 54 Quantum vs. classic metabolism, 8 metabolic rate (MR), 10

R RAGE, see Receptor for AGEs RANKL, see Receptor activator of nuclear factor kappa-B ligand RAS, see Renin-angiotensin system

Ras-Raf-mitogen activated protein kinase (MAPK), 279, 282 Reactive oxygen species (ROS), 118–119, 283, 285–286, 332 Reaven, Gerald, 279, 295 Receptor activator of nuclear factor kappa-B ligand (RANKL), 306 Receptor for AGEs (RAGE), 292 Redox homeostasis, 118–119 cellular systems, 119 oxidative stress, 119 reactive oxygen species (ROS), 118–119 Redox pair, 334 Redox potential, 334–335 biochemical reactions importance, 20–21 Redox reaction, 9 Redox stress, 200–201, 384 Reinoculate, 258–259 Remove, 258 Renin-angiotensin system (RAS), 386 Repair, 259 Replace, 258 Resilience, 305 Respiratory quotient (RQ), 289–290, 312 RET, see Reverse electron transfer Retinoid-related orphan receptor (RORs), 160–162 Retinoid X receptor (RXR), 159 and heterodimeric receptors, 159 constitutive androstane receptor (CAR), xenobiotic metabolism, 160 farnesoid X receptor (FXR), 159–160 thyroid hormone receptor (TR), 159 Reverse electron flow, 24, 338 Reverse electron transfer (RET), 337, 339 Reverse Warburg effect, 366, 378 Richard Bergman’s group, 291 Robustness theory, 305 RORs, metabolic fitness, 119 ROS, see Reactive oxygen species Rotterdam Study, 304 RQ, see Respiratory quotient RXR, see Retinoid X receptor (RXR) RXR Big Bang, 107

S SARS-CoV-2, pulmonary fibrosis, 38 angiotensin-converting enzyme 2 (ACE2), 39 ectopic fat, 39 hypoxia and inflammation, 39 SAT, see Subcutaneous adipose tissue SCFAs, see Short-chain fatty acids Scherer, Philipp, 284–285 SCO2, see Synthesis of cytochrome c oxidase 2 SDH, see Succinate dehydrogenase Segmented filamentous bacteria (SFB), 236 Sense and energy modulation, 111 exercise response, 120–121 glucose metabolism, 116–118 lipid homeostasis, 111–116 Serine, 368 Serotonin reuptake inhibitors (SSRIs), 248 SFB, see Segmented filamentous bacteria Shift work and metabolism, 169 Short-chain fatty acids (SCFAs), 236–240, 252, 260, 261, 345

424 Short-term and prolonged stress, 72 Shulman, Gerald, 283–284, 294 Shulman lab, 284 Sirtuin-1 (SIRT1), 360, 391, 396 Skeletal muscle, 120–121 SKI, see Sloan Kettering Institute Sloan Kettering Institute (SKI), 4 Small intestinal bacterial overgrowth (SIBO), 258, 259 SMCs, see Smooth muscle cells Smooth muscle cells (SMCs), 388 Social networks impact, 60 heterogeneity, 59 hormesis, 59 vitalizing vs. devitalizing, 59 Social stress, 247 Sphingosine-1-phosphate (S-1-P), 285 SREBP1c, see Sterol regulatory binding protein 1c SSRIs, see Serotonin reuptake inhibitors Statin therapy, 301–302 Steroid receptors, 158 glucocorticoid receptor (GR), 158–159 Sterol regulatory binding protein 1c (SREBP1c), 290 Stress, 51, 247–249 allostasis, 52–53, 55 allostatic load and overload, 52 as allostatic response, 310–311 anxiety, 50 autonomic and hormonal response, 68 brain senses, 50 complex network, 50 control parameter, 53 description, 49–50 dose and duration, 65 eating, 246 hippocampal neurons, 67 homeostasis, 50, 52 homeostatic parameters, 52 hormones, 52 interdisciplinary nature, 54 medicine, 52–53 motivation and reward, 71–72 addictions, possible interventions, 76 circuitry, stress, and uncertainty model., 74–75 gender differences response, 75–76 neural circuitry reward, 72–74 neural circuitry chronic anxiety and uncertainty, 69–70 energy expenditure, 70–71 interconnections, 66 neuroendocrine response and insulin resistance, 66–67 stress vs. norepinephrine, 67–68 uncertainty, 68–69 perception, 50–51 physical concepts and medical practice, integration of, 80–81 biology integration, 88–90 mediators shift, health to disease, 90–94 Physiological Fitness Landscape, 88, 94–97 stress and control parameters, 81–88 Physiological Fitness Landscape model, 50

Index prolonged allostasis, 56 psychogenic, 50 quantum consciousness, prefrontal cortex, 78–80 quantum metabolism, 54 synaptic plasticity, 76 long-term depression (LTD), 78 long-term potentiation (LTP), 76–77 will power and consciousness, 78 Stress and acceleration disease, 92 Stress and chronic diseases, 92 Stress and circadian physiology, 88 Stress and cognitive decline, 74 Stress and hypoglycemia, 88 Stress and metabolic rhythms, 85 Stress and microbiota, 88 Stress paradox, 66 chronic metabolic diseases, 58–59 clinical example chronic stress response, 61 contributing factor, 61 hormesis, 62 human connection, 60–61 oxytocin, 59–60 social networking, 60 type 1 diabetes, 60 consciousness, 59 external stressors, 58 hormesis, 58, 59 psychological and physiological pathology, 58 social networks impact heterogeneity, 59 hormesis, 59 vitalizing vs. devitalizing, 59 Stress responses, 54 allostatic load and overload, 54–57 calorie restriction cell stress leading to allostatic overload, 194–195 hormesis, vitalizing stress, and devitalizing stress, 193–194 metabolic rate and take-over threshold, 195 natural physiological response, 194 declining health, 56 homeostasis, 54–57 neuroendocrine and autonomic, 56 Physiological Fitness Landscape, 62 the stress paradox, 66 synchronized physiology and metabolism, effects of, 62–64 vital organ system, 55 Stress vs. anxiety vs. depression, 74 Stress vs. norepinephrine, 67–68 Subclinical endotoxicosis, 246 Subcutaneous adipose tissue (SAT), 37, 342 Succinate dehydrogenase (SDH), 334 Suprachiasmatic nucleus (SCN), 133, 135 hypothalamic nuclei, 69 Supraorganism, 227, 233–234 co-development, 234–235 co-evolution, 241–243 gastrointestinal tract, 235 host metabolism impacts, 240–241 hypothalamic-pituitary-adrenal (HPA) axis, 240

microbiota and immune system, 235–238 nervous system, 238–240 Symbiotic bacteria, 236 Symmetry, 307–311 Synaptic dysfunction, 375 Synaptic plasticity, 76 long-term depression (LTD), 78 long-term potentiation (LTP), 76–77 will power and consciousness, 78 Synchronized physiology and metabolism, 62–64 Synchrony and desynchrony environment, 163–164 adrenal insufficiency, 182 circadian disruption, causes of, 167–168 circadian interactions, nutrient balance, 170–172 circadian misalignment, endogenous oscillating cycles, 177–178 cortisol, Cushing’s and obesity, 182–183 cyclical insulin resistance, forkhead box O (FOXO), 175–177 glucose, insulin, and metabolic disease, 172–175 metabolism explained by scales of time and space, 164–167 nocturnal eating and insulin resistance, 178–181 redox status and circadian rhythms, 181 sleep, 168–169 Syndrome X, 279–280 Synthesis of cytochrome c oxidase 2 (SCO2), 362

T T2D, see Type 2 diabetes T2DM, see Type 2 diabetes mellitus Take-over threshold, 195, 209 Therapeutic interventions, fitness landscape model, 183 Thiazolidinediones (TZD), 113, 291–292, 301, 327–328 Thyroid hormone receptor (TR), 159 TIGAR, see TP53-induced glycolysis and apoptosis regulator Time biology biological time, 139–142 angular momentum, 141 arrow of time, 140–141 entropy increase, 141 first law of thermodynamics, 140 fitness landscape, 142 inflammation, 141–142 metabolism, 140 perfect periodicity, 140 second law of thermodynamics, 140–141 suprachiasmatic nucleus (SCN), 142 temporal structures characterize, 139 historical context, 135–136 measuring time, 142–144 aging process, 143–144 biological clocks, 142 quantum metabolism, 143 time dilation, 143 molecular clocks, 147–148

425

Index overview, 133–134 physical time, 137–139 aging process, 138 aging rate, 137 arrow of time, 137 chronological time, 139 circadian rhythms, 138 entropy, 137–138 first law of thermodynamics, 138–139 homeostatic, 138 inflammation, 138 metabolic efficiency, 138 second law of thermodynamics, 137 special relativity, 139 time dilation, 137 Time dilation, 137, 143 Time-restricted eating (TRE), 153 TLR2, see Toll-like receptor 2 TLR4, see Toll-like receptor 4 TLR5, see Toll-like receptor 5 TLRs, see Toll-like receptors TMAO, see Trimethylamine N-oxide TNF-alpha, 288 Toll-like receptor 2 (TLR2), 231 Toll-like receptor 4 (TLR4), 231, 262 Toll-like receptor 5 (TLR5), 262 Toll-like receptors (TLRs), 37–38, 262 Top-down control parameters, 262–265 TP53-induced glycolysis and apoptosis regulator (TIGAR), 361 Transcriptional gene repression, 233 Transgenic mouse models, 249 Tricarboxylic acid cycle (TCA cycle), 336, 337 Triglycerides, 220–221, 301 Trimetazidine, 392–393 Trimethylamine (TMA), 251, 252 Trimethylamine N-oxide (TMAO), 252

True insulin sensitizers, 286 Type 1 diabetic, 213–214 Type 2 diabetes (T2D), 246, 388 Type 2 diabetes mellitus (T2DM), 284 TZD, see Thiazolidinediones

Vitamin K2, 330–331 VLDL, see Very low density lipoprotein VSMCs, see Vascular smooth muscle cells

U

The Warburg effect, 2, 41, 287, 398 and insulin signaling, 363–364 old hypothesis, 41–42 and oncogenic signaling, 364–365 unifying hypothesis, 43–44 WAT, see White adipose tissue Weizmann Institute of Science, 3 White adipose tissue (WAT), 277 Whole-body metabolism, 370–371 caloric restriction, 372 fasting, 371 ketogenic diet, 371–372 microbiome and cancer treatment, 372 Women’s Health Initiative Observational Study, 280 Words of wisdom, 413–414

Uncertainty reduction model, 65–66 Unfolded protein response (UPR), 380 Unifying hypothesis vs. take-over threshold, 195 UPR, see Unfolded protein response Upstream control parameters, 311 Uridine, 285

V Vascular atherosclerosis, 387–391 Vascular cell adhesion molecule (VCAM-1), 388 Vascular smooth muscle cells (VSMCs), 388 VAT, see Visceral adipose tissue VCAM-1, see Vascular cell adhesion molecule Very low density lipoprotein (VLDL), 279, 291, 293, 387 Visceral adipose tissue (VAT), 37, 342 Visceral adiposity inflammatory diet and insulin resistance, 40–41 protective role, 37–38 Visible light wavelengths, 80 Vitalizing stress, 58, 193–194 Vitalizing vs. devitalizing, 59 Vitamin B1, 326 Vitamin B2, 326 Vitamin B3, 326 Vitamin D, 306, 391–392 mitochondrial function, 327 and vitamin K2 interactions, 330

W

X Xenobiotics, 37–38, 257–258 constitutive androstane receptor (CAR), 160 metabolism, 160

Y Yin and Yang of glyceroneogenesis, 300–301

Z Zinc, 331 Zonulin, 232