Epigenetics in Allergy and Autoimmunity [1st ed.] 9789811534485, 9789811534492

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Advances in Experimental Medicine and Biology 1253

Christopher Chang Qianjin Lu   Editors

Epigenetics in Allergy and Autoimmunity

Advances in Experimental Medicine and Biology Volume 1253

Series Editors Wim E. Crusio, Institut de Neurosciences Cognitives et Intégratives d’Aquitaine, CNRS and University of Bordeaux UMR 5287, Pessac Cedex, France John D. Lambris, University of Pennsylvania, Philadelphia, PA, USA Heinfried H. Radeke, Institute of Pharmacology & Toxicology, Clinic of the Goethe University Frankfurt Main, Frankfurt am Main, Hessen, Germany Nima Rezaei, Research Center for Immunodeficiencies, Children’s Medical Center, Tehran University of Medical Sciences, Tehran, Iran

Advances in Experimental Medicine and Biology provides a platform for scientific contributions in the main disciplines of the biomedicine and the life sciences. This series publishes thematic volumes on contemporary research in the areas of microbiology, immunology, neurosciences, biochemistry, biomedical engineering, genetics, physiology, and cancer research. Covering emerging topics and techniques in basic and clinical science, it brings together clinicians and researchers from various fields. Advances in Experimental Medicine and Biology has been publishing exceptional works in the field for over 40 years, and is indexed in SCOPUS, Medline (PubMed), Journal Citation Reports/Science Edition, Science Citation Index Expanded (SciSearch, Web of Science), EMBASE, BIOSIS, Reaxys, EMBiology, the Chemical Abstracts Service (CAS), and Pathway Studio. 2018 Impact Factor: 2.126.

More information about this series at http://www.springer.com/series/5584

Christopher Chang Qianjin Lu •

Editors

Epigenetics in Allergy and Autoimmunity

123

Editors Christopher Chang Division of Pediatric Immunology and Allergy Joe DiMaggio Children’s Hospital Hollywood, FL, USA Division of Rheumatology, Allergy and Clinical Immunology University of California Davis Davis, CA, USA

Qianjin Lu Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics Second Xiangya Hospital, Central South University Changsha, Hunan, China

ISSN 0065-2598 ISSN 2214-8019 (electronic) Advances in Experimental Medicine and Biology ISBN 978-981-15-3448-5 ISBN 978-981-15-3449-2 (eBook) https://doi.org/10.1007/978-981-15-3449-2 © Springer Nature Singapore Pte Ltd. 2020 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore

This book is dedicated to all patients with allergic and autoimmune diseases, in the hope that one day there will not just be treatments but cures.

Preface

As personalized medicine becomes more and more of a mainstream term, there is no consensus on how to achieve this lofty goal. The dream of being able to precisely identify patients who will respond optimally to a given treatment has not yet been realized, but epigenetics, the study of how genes are turned on and off by changes not in DNA sequence but in alterations of various elements of chromatin, including nucleotides within the DNA and proteins which regulate expression that are in close physical contact with DNA, offers great promise in ultimately achieving this goal. The study of the impact of epigenetics in health and disease originated only about 40 or so years ago and began in the oncology arena, but then quickly progressed to include autoimmune diseases. Our understanding of the role of epigenetics has been facilitated by large populations studies and by the existence of discordant twins, in other words, monozygotic twins who generally have identical DNA but still manage to manifest changes in disease presentation. This work is intended to cover the topics relating to epigenetics in allergic diseases and autoimmune diseases. The aim is to provide a comprehensive source of information for scientists, clinicians, fellows, residents and students who are interested in cutting-edge developments in epigenetic research designed to elucidate mechanisms of disease and the fulfilment of that promise of personalized medicine. My colleague and co-editor, Professor Qianjin Lu, is the Head of the Hunan Key Laboratory for Epigenetics Research and has published numerous papers on the role of epigenetics in dermatology and rheumatology. I have been privileged to have shared in the publication of some of these articles. Professor Lu and I have selected the world’s foremost experts in epigenetics in their research field to cover diseases ranging from allergic rhinitis and asthma to primary biliary cirrhosis and multiple sclerosis. We hope that this book will help the reader understand the importance of this research to the future of mankind, not only in preventing and treating diseases, but also in the appreciation of how good health can be maintained. This project was first conceived three years ago, at the 2017 International Symposium of Autoimmunity in Beijing, China. Professor Lu and I would like to thank Peng Zhang, our tireless publications liaison at Springer who first approached us with the proposal, and Professor Haijing Wu, who co-authored the chapters on vii

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food allergies and systemic lupus erythematosus and also helped with proofing and many of the administrative tasks one faces when editing a scientific work. We would like to extend our thanks to the authors of each of the individual chapters, for their willingness to devote large amounts of time to share their expertise with us. We would also like to thank our families, who endured many solitary hours without us as we retreated to our workspaces to continue our own work in bringing this book into production. It has been a challenging but rewarding task. Finally, we hope that an appreciation of the importance of epigenetics in health and disease will spawn further research in this area and the book will provide a launching pad for young investigators interested in developing a career in epigenetics. Hollywood, FL, USA May 2020

Christopher Chang

Contents

Part I

Introduction

1

Epigenetics in Health and Disease . . . . . . . . . . . . . . . . . . . . . . . . . . Lian Zhang, Qianjin Lu, and Christopher Chang

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The Development of Epigenetics in the Study of Disease Pathogenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Matlock A. Jeffries

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Epigenetic Methods and Twin Studies . . . . . . . . . . . . . . . . . . . . . . Angela Ceribelli and Carlo Selmi

Part II

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Allergic Diseases

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The Role of Genetics, the Environment, and Epigenetics in Atopic Dermatitis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107 Zhanglei Mu and Jianzhong Zhang

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The Epigenetics of Food Allergy . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 Christopher Chang, Haijing Wu, and Qianjin Lu

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Epigenetics and the Environment in Airway Disease: Asthma and Allergic Rhinitis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Andrew Long, Bryan Bunning, Vanitha Sampath, Rosemarie H. DeKruyff, and Kari C. Nadeau

Part III

Autoimmune Diseases

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The Epigenetics of Lupus Erythematosus . . . . . . . . . . . . . . . . . . . . 185 Haijing Wu, Christopher Chang, and Qianjin Lu

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Epigenetics of Psoriasis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209 Shuai Shao and Johann E. Gudjonsson

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The Role of Epigenetics in Type 1 Diabetes . . . . . . . . . . . . . . . . . . 223 Zhiguo Xie, Christopher Chang, Gan Huang, and Zhiguang Zhou

10 Epigenetics of Primary Biliary Cholangitis . . . . . . . . . . . . . . . . . . . 259 Yikang Li, Ruqi Tang, and Xiong Ma 11 Epigenetics in Primary Sjögren’s Syndrome . . . . . . . . . . . . . . . . . . 285 Anne Bordron, Valérie Devauchelle-Pensec, Christelle Le Dantec, Arthur Capdeville, Wesley H. Brooks, and Yves Renaudineau 12 Epigenetics in Multiple Sclerosis . . . . . . . . . . . . . . . . . . . . . . . . . . . 309 Vera Sau-Fong Chan 13 The Epigenetic Regulation of Scleroderma and Its Clinical Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375 Yangyang Luo and Rong Xiao

Editors and Contributors

About the Editors Dr. Christopher Chang is a Clinical Professor of Medicine in the Division of Rheumatology, Allergy and Clinical Immunology at the University of California, Davis. He is Professor of Pediatrics at Florida International University and Florida Atlantic University and is Medical Director of Pediatric Immunology, Allergy and Rheumatology at Joe DiMaggio Children’s Hospital, Memorial Health Systems. He is also a visiting Professor at Xiangya School of Medicine, Central South University in Changsha, Hunan, China. Dr. Chang is a fellow of the American Academy of Allergy, Asthma and Immunology and the American College of Allergy, Asthma and Immunology, and a member of the Clinical Immunology Society and the American Association of Immunologists. His interests are mainly focused on epigenetic regulation in allergy and autoimmune diseases. He has published more than 20 articles in this field. He is also Editor-in-Chief of the Journal of Evidence-Based Integrative Medicine, Co-Editor of the Journal of Translational Autoimmunity and Associate Editor of Clinical Reviews in Allergy and Immunology. Dr. Qianjin Lu is currently Professor and Director of the Institute of Dermatology at the Central South University. He is also Director of the Hunan Key Laboratory of Medical Epigenomics, and current President of the Chinese Society of Dermatology. Professor Lu has accumulated rich clinical experience in dermatology, especially in the areas of lupus and psoriasis. He has conducted research in epigenetic and autoimmunity for more than twenty years and he is especially interested in epigenetic regulation in the pathogenesis of systemic lupus erythematosus and psoriasis. Professor Lu has published 200 papers in high impact journals including Lancet, JAMA, Blood, J Clin Invest, Ann Rheum Dis and J Immunol, etc. In recent years, Professor Lu was honored with several awards such as Second Prize of the National Scientific and Technological Progress Award, First

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Prize of the Natural Scientific Research Award of Hunan Province, First Prize of the Scientific and Technological Progress Award of Hunan Province and Outstanding Medical Scientist of China.

Contributors Anne Bordron INSERM U1227, «Lymphocyte B et autoimmunité», Labex Igo “Immunotherapy Graft, Oncology”, Réseau épigénétique du cancéropole Grand Ouest, Université de Brest, Brest, France Wesley H. Brooks Department of Chemistry, University of South Florida, Tampa, FL, USA Bryan Bunning Division of Pulmonary and Critical Care Medicine, Department of Medicine, Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford, CA, USA Arthur Capdeville INSERM U1227, «Lymphocyte B et autoimmunité», Labex Igo “Immunotherapy Graft, Oncology”, Réseau épigénétique du cancéropole Grand Ouest, Université de Brest, Brest, France Angela Ceribelli Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy Vera Sau-Fong Chan Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China; Queen Mary Hospital, Hong Kong SAR, China Christopher Chang Division of Pediatric Immunology and Allergy, Joe DiMaggio Children’s Hospital, Hollywood, FL, USA; Division of Rheumatology, Allergy and Clinical Immunology, University of California Davis, Davis, CA, USA Rosemarie H. DeKruyff Division of Pulmonary and Critical Care Medicine, Department of Medicine, Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford, CA, USA Valérie Devauchelle-Pensec INSERM U1227, «Lymphocyte B et autoimmunité», Labex Igo “Immunotherapy Graft, Oncology”, Réseau épigénétique du cancéropole Grand Ouest, Université de Brest, Brest, France; Department of Rheumatology, CHU Cavale Blanche, Brest University Medical School, Brest, France Johann E. Gudjonsson Department of Dermatology, University of Michigan, Ann Arbor, MI, USA

Editors and Contributors

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Gan Huang Department of Metabolism and Endocrinology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, National Clinical Research Center for Metabolic Diseases, Changsha, Hunan, China Matlock A. Jeffries University of Oklahoma Health Sciences Center, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA Christelle Le Dantec INSERM U1227, «Lymphocyte B et autoimmunité», Labex Igo “Immunotherapy Graft, Oncology”, Réseau épigénétique du cancéropole Grand Ouest, Université de Brest, Brest, France Yikang Li Department of Gastroenterology and Hepatology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China Andrew Long Division of Pulmonary and Critical Care Medicine, Department of Medicine, Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford, CA, USA; Department of Pharmacy, Lucile Packard Children’s Hospital, Stanford, CA, USA Qianjin Lu Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, Second Xiangya Hospital, Central South University, Changsha, Hunan, China Yangyang Luo Department of Dermatology, Hunan Children’s Hospital, Changsha, China Xiong Ma Division of Gastroenterology and Hepatology, Key Laboratory of Gastroenterology and Hepatology, Ministry of Health, State Key Laboratory for Oncogenes and Related Genes, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China Zhanglei Mu Department of Dermatology, Peking University People’s Hospital, Beijing, China Kari C. Nadeau Division of Pulmonary and Critical Care Medicine, Department of Medicine, Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford, CA, USA Yves Renaudineau INSERM U1227, «Lymphocyte B et autoimmunité», Labex Igo “Immunotherapy Graft, Oncology”, Réseau épigénétique du cancéropole Grand Ouest, Université de Brest, Brest, France; Laboratory of Immunology and Immunotherapy, Brest University Medical School, CHU Morvan, Brest, France Vanitha Sampath Division of Pulmonary and Critical Care Medicine, Department of Medicine, Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford, CA, USA

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Carlo Selmi Humanitas Clinical and Research Center—IRCCS, Rozzano, Milan, Italy; BIOMETRA department, University of Milan, Milan, Italy Shuai Shao Department of Dermatology, Xijing Hospital, Fourth Military Medical University, Xi’an, Shannxi, China; Department of Dermatology, University of Michigan, Ann Arbor, MI, USA Ruqi Tang Department of Gastroenterology and Hepatology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai Institute of Digestive Disease, Shanghai, China Haijing Wu Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, Second Xiangya Hospital, Central South University, Changsha, Hunan, China Rong Xiao Department of Dermatology, The Second Xiangya Hospital, Central South University, Changsha, China Zhiguo Xie Department of Metabolism and Endocrinology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, National Clinical Research Center for Metabolic Diseases, Changsha, Hunan, China Jianzhong Zhang Department of Dermatology, Peking University People’s Hospital, Beijing, China Lian Zhang Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, Second Xiangya Hospital, Central South University, Changsha, Hunan, China Zhiguang Zhou Department of Metabolism and Endocrinology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China; Key Laboratory of Diabetes Immunology (Central South University), Ministry of Education, National Clinical Research Center for Metabolic Diseases, Changsha, Hunan, China

Part I

Introduction

Chapter 1

Epigenetics in Health and Disease Lian Zhang, Qianjin Lu, and Christopher Chang

Abstract Epigenetic mechanisms, which include DNA methylation, histone modification, and microRNA (miRNA), can produce heritable phenotypic changes without a change in DNA sequence. Disruption of gene expression patterns which are governed by epigenetics can result in autoimmune diseases, cancers, and various other maladies. Mechanisms of epigenetics include DNA methylation (and demethylation), histone modifications, and non-coding RNAs such as microRNAs. Compared to numerous studies that have focused on the field of genetics, research on epigenetics is fairly recent. In contrast to genetic changes, which are difficult to reverse, epigenetic aberrations can be pharmaceutically reversible. The emerging tools of epigenetics can be used as preventive, diagnostic, and therapeutic markers. With the development of drugs that target the specific epigenetic mechanisms involved in the regulation of gene expression, development and utilization of epigenetic tools are an appropriate and effective approach that can be clinically applied to the treatment of various diseases. Keywords DNA methylation · Histone modification · miRNA · Immune dysfunction · Checkpoints · Signaling pathways · Cytokines

L. Zhang · Q. Lu Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, Second Xiangya Hospital, Central South University, Changsha, Hunan, China C. Chang (B) Division of Pediatric Immunology and Allergy, Joe DiMaggio Children’s Hospital, Hollywood, FL 33021, USA e-mail: [email protected] Division of Rheumatology, Allergy and Clinical Immunology, University of California Davis, Davis, CA 95616, USA © Springer Nature Singapore Pte Ltd. 2020 C. Chang and Q. Lu (eds.), Epigenetics in Allergy and Autoimmunity, Advances in Experimental Medicine and Biology 1253, https://doi.org/10.1007/978-981-15-3449-2_1

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1.1 Introduction The realization that DNA sequence is not the sole determinant of clinical phenotype was a result of the observation that identical twins, who carry the same DNA, are often disease discordant, whereby one of the twins is sick and the other is healthy (Fraga et al. 2005; Javierre et al. 2010; Costello et al. 2000). The term “epigenetic” was first proposed by Waddington (1939), who introduced the term “epigenetic landscape” to describe the molecular and biologic mechanisms that transform a genetic trait into a visualized phenotype. This encompasses the idea of the genotype and the phenotype (Esteller 2008; Rideout et al. 2001). Modulation of gene expression is a way that the DNA sequence can be regulated leading to stimulation or suppression of pathways or molecules that may lead to health or disease. Currently, DNA methylation is a well-characterized and intensely studied epigenetic modification tracing back to the research done by Mahler and Griffith in 1969, who showed that DNA methylation may play an important role in the function of long-term memory (Bird 2002). Besides DNA methylation, other epigenetic modifications include histone modifications, miRNA and nucleosome accessibility (Fig. 1.1). The continuous interest in epigenetics has resulted in discoveries of a role for epigenetics in diseases ranging from autoimmune diseases to cancer, congenital disease, mental retardation, endocrine diseases, pediatric diseases, neuropsychiatric disorders, and many others (Fraga et al. 2005; Javierre et al. 2010). Fig. 1.1 Primary mechanisms of epigenetic modifications include DNA methylation, histone modifications, miRNA, and nucleosome accessibility

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1.2 The Science Behind Epigenetics The central dogma in genetics is the doctrine that information in our cells flows only in one direction—from DNA to RNA to proteins (Portela and Esteller 2010). It was an absolute dogma that has now been essentially debunked, due to the role of the environment in modulating the expression of genes. A new term, “epigenetic”, literally meaning outside of or above the gene, has become one of the hottest and newest emerging fields in the scientific world. Epigenetics does not involve the biochemical alteration in DNA sequences, rather, it turns on or off different genes that can make us susceptible to developing disease. Epigenetic research aims to unearth how environment, social condition, psychosocial factors, and nutrition affect an individual’s expression of genetic information (Fig. 1.2). In multicellular organisms, variable phenotypes may result from the same genotype because of the potential ability of epigenetic markers appearing during development to be passed on to offspring (Kaminsky et al. 2009). Researchers have already found that the phenomenon of division and differentiation of single cell during embryogenesis is tightly associated with epigenetics (Meissner et al. 2008). The result is that monozygotic twins have the same genetic information, but may have a different epigenetic profile, determined by the environment in which they live and grow, leading to differences in health and disease phenotype (Kaminsky et al. 2009). Theoretically, a cloned animal, with genetic material from the same donor, can potentially develop a different disease from the donor (Costello et al. 2000). Epigenetics can be part of the answer to variable phenotypes and plays a crucial role in cell division and differentiation. Fig. 1.2 The interaction among epigenetics, genetics, and the environment

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1.3 Epigenetics and Human Disease The three main mechanisms of epigenetics are DNA methylation, histone modification, and miRNA. These mechanisms are responsible for the initiation and maintenance of epigenetic silencing and regulation of the gene expression profile and are cornerstones of a series of cellular processes, including cell differentiation, gene expression, X chromosome inactivation, embryogenesis, and genomic imprinting (Holliday and Pugh 1975; Riggs 1975). Unveiling the relationship among these components has rapidly and surprisingly resulted an improved understanding of regulation of gene expression. Furthermore, disruption of an epigenetic profile can have a significant impact on cellular function, which can lead to dysregulation of gene expression and can potentially lead to the occurrence and development of “epigenetic disease”. An aberrancy in DNA methylation is a common manifestation of epigenetic disease. Methylation occurs at the 5 -position of a cytosine residue, which is regarded as a fundamental gene silencing mark (Holliday and Pugh 1975). This cytosine residue can be methylated and maintained by numerous DNA methyltransferases (DNMTs), which play an important role in the silencing of transcription factors, as well as defense against expression of endogenous retrovirus genes and repression of transposable elements (Roulois et al. 2015). The addition of a methyl group to the untouched C-5 position of a cytosine by DNMTs during DNA replication contributes to the occurrence of de novo DNA methylation (Jones and Baylin 2002). The methylation occurring in 5 -CG-3 (CpG) can easily be deaminated spontaneously to the thymine, while the unmethylated CpGs can be converted to uracil. The expected number of CG pairs in the human genome is about 20% (Jones 2012). The observed number is often lower than the expected number, due to a high mutation rate for methylated CpG sites. Some promoter regions enriched with CG, named CpG islands, are at least 200 bp and are greater than 55% conserved throughout evolution. Maintaining the primary epigenetic status is fundamental to maintaining normal development. Disruption of this balance can lead to an aberrant epigenetic landscape on the basis of time and place. The DNA located at some promoter regions, when methylated, may cause heritable transcriptional silencing. The hypermethylation occurring at some important genes, such as p16INK4A, CDH1, DAPK, p14ARF, can contribute to the tumorigenesis (Esteller 2007). Histone modification is another key mechanism of epigenetics (Fig. 1.3). Histone complexes are composed of two unstable dimers H2A, H2B and a tetramer of H3 and H4, wrapped by 147 bp of DNA to form the nucleosome (Schotta et al. 2004). The histone complex facilitates the condensation of genomic DNA and has an impact on post-transcriptional modification. Several modifications, such as acetylation, methylation, ubiquitination, phosphorylation, and sumoylation, occur on the conserved lysine at the histone tails (Nakayama et al. 2001; Yuen and Knoepfler 2013). Histone acetylation and deacetylation are essential for gene regulation. Acetylation generally leads to active transcription, whereas hypoacetylation is an indicator of

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Fig. 1.3 Histone modifications include acetylation, methylation, ubiquitination, phosphorylation, and sumoylation

inactive transcriptionally. Histone methylation can indicate both active and inactive transcription, and the state of mono-, di-, and trimethylation has different effects. Methylation is facilitated by the enzymes known as histone methyltransferases (HMT). Histone modification to H3 is the most well studied and characterized. The diand trimeric forms of H3K4 and H3K36 are frequent targets of histone modification and lead to activation of transcription. In contrast, H3K92/3 and H3K27me2/3 modification lead to gene silencing. It should be noted that the histone component H3K9 is found primarily in a gene-poor region, such as telomeres and centromeres, and is a permanent marker for the formation of heterochromatin. This histone component is also associated with X chromosome inactivation and gene repression at promoter regions (Nakayama et al. 2001). Conversely, the H3K27 is generally found in gene-rich regions and acts as a temporary marker correlating with the development of regulators (Santenard et al. 2010). Studies show that histone H3 mutations are associated with giant bone cell tumor and chondroblastoma and have also been found to be a mutation of high frequency in high-grade gliomas in children (Schwartzentruber et al. 2012). Any mutation of histone-associated enzymes may contribute to the development of diseases, such as cancers, autoimmune diseases, endocrine diseases, and psychologic disorders. Mature miRNA is another key player in epigenetics. miRNA is a class of noncoding small RNA, about 22 nucleotides in length. MicroRNA are complementary to single or a series of messenger RNA (mRNA). It cannot be translated into protein, rather their main function is to downregulate gene expression in different ways, including mRNA cleavage, translational inactivation, and deadenylation to produce a mitotically heritable result (Tufarelli et al. 2003). Emerging evidence indicates that miRNAs play significant roles in cell division, differentiation, and development. Abnormalities in miRNA are associated with a wide variety of human diseases,

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including cancer, autoimmune diseases, and cardiac diseases (Calin et al. 2002). Consequently, miRNAs are becoming extremely useful as clinical biomarkers, and diagnostic tools have been developed especially in the field of cancer. In addition, miRNA play a crucial role in many other biological systems. An example would be in cardiology. Through regulation of gene expression, miRNAs play a significant role in regulating cardiac function or dysfunction, including cardiac rhythm, ventricular wall integrity, contractility, and myocyte growth.

1.4 The Clinical Application of Epigenetics One of the personal human challenges in health and disease has to do with uncertainty. In the vast majority of cases, there is no single test that will definitely provide an answer for patients. Patients often need multiple studies, which take a significant amount of time, and this adds to the anxiety of seeing a physician. The promise of epigenetic is that it can provide new insights into clinical development of diagnostic and therapeutic methods and bridge the gap between effects of the environment and host genetics. Epigenetics has the potential to be used as biomarkers for the detection and diagnosis of disease, disease monitoring, and response to treatment. In the past few decades, pharmacoepigenetics has attracted much interest and epigenetic drug (epidrug) development has achieved significant advancement.

1.4.1 Epigenetic Biomarkers The discovery and utilization of biomarkers have the potential to impact patient management and clinical outcomes (Garcia-Gimenez et al. 2017). Biomarkers may be directly related to pathogenesis or may be surrogate markers or important for disease prognostication or monitoring. Some biomarkers may also be potential therapeutic targets or may indicate where the search for such targets should commence (CostaPinheiro et al. 2015; Dirks et al. 2016). The identification of potential markers is only the first step, as these markers must be validated and confirmed as a reliable and statistically acceptable reflection of the disease. Epigenetic markers have already been incorporated into clinical application and are being used in the prevention, diagnosis, and treatment of cancers, autoimmune diseases, as well as neurological and cardiac disorders. There are several advantages of epigenetic biomarkers. First, the biomarkers indicate a new direction in which molecular markers correlate with genetic and the environmental factors which contribute to the development of diseases (Lorincz 2011). What epigenetics does is to provide a functional biomarker which does not depend on DNA sequence alone. The epigenetic biomarker, especially those related to DNA methylation, falls outside of the DNA and RNA sequence based testing and may provide an alternate stability profile (Garcia-Gimenez et al. 2017). Epigenetic

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biomarkers can be checked in blood, tissue, body fluid as well as secretions which are commonly sampled during procedures and surgeries. Furthermore, any disruption of epigenetics can be checked in the context of the genome and even prior to or at the very early stage of the disease. This property is unique compared to the RNA and protein-based tests because RNA and protein abnormalities appear at relatively late stages and often in low quantities or concentration.

1.4.2 Epigenetic Therapy Epigenetic therapy is a new treatment option utilizing epigenetic drugs (epidrug) or less obviously, non-pharmacological techniques of clinical management (Fig. 1.4). Recent research in epigenetics now offers an attractive way to target the epigenetic mechanism caused by cancers, autoimmune diseases, cardiac disorders, and mental illness. Large numbers of molecular inhibitors have been developed over the past several decades. The United States Federal Drug Administration (FDA) approved the first epidrugs azacytidine (5-AZA) and decitabine (5-AZA-CdR) in 2004 for the treatment of leukemia (Egger et al. 2004). These drugs are in fact DNA methyltransferase inhibitors, thereby categorized as epigenetic modifiers, which can reprogram the epigenetic profile and potentially reverse the disease. They are now indicated in the treatment of hematologic malignancies, including acute myeloid leukemia (AML), myelodysplastic syndromes (MDS), and chronic myelomonocytic leukemia (CMML). Reprogramming and reshaping the epigenetic profile by reducing DNA

Fig. 1.4 Epidrugs for the treatment of human diseases. Several epidrugs have been approved for clinical application, and many epidrugs are undergoing clinical trials

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Table 1.1 A variety of epidrugs are already approved for clinical use or are undergoing clinical trials Drug HDACi Azaci dine Decitabine Guadecitabine HDACi Vorinostat Belinostat Panobinostat Pracinostat HDMi GSK2879552 INCB059872 Tranylcypromine HMTi Tazemetostat MAK683

Disease

phrase

clincal applica on

CMML,AML and MDS CMML,AML and MDS AML

clincial prac ce For the treatment of haematological malignancies clincial prac ce For the treatment of haematological malignancies Phase III clinical trial Recruited AML pa ents

CTCL PTCL HIV-1 AML

clincial prac ce clincial prac ce Phase I/II clinical trial Phase III clinical trial

Relapsed/refractory SCLC Advanced malignancies Bipolar depression

Phase II clinical trial Recruited SCLC pa ents Phase I/II clinical trial Recruited AML/MDS pa ents Phase IV clinical trial Recruited bipolar depression pa ents

Refractory B cell (NHL) DLBCL

Phase I/II clinical trial Recruited NHL pa ents Phase I/II clinical trial Recruited DLBCL pa ents

For the treatment of CTCL For the treatment of PTCL Recruited HIV pa ents Recruited AML pa ents

methylation levels, especially on tumor suppressor genes, may lead to normalization of the gene expression profile (Table 1.1). Histone acetylase inhibitors are another compelling class of epidrugs (Nagaraja et al. 2017). Panobinostat has been approved for the treatment of multiple myeloma (MM), Belinostat has been used in the treatment of refractory or relapsed peripheral T cell lymphoma (PTCL), and several clinical trials using sodium phenylbutyrate for Huntington disease and Vorinostat for HIV-1 are undergoing (Vojinovic et al. 2011). Other oncology research is focusing on the combination treatment of HDAC and DNMT inhibitors for AML, glioma, breast cancer, and CMML, thereby demonstrating a synergistic effect (Brocks et al. 2017) between two forms of epigenetic mechanisms. Drug resistance remains a problem (Grasso et al. 2015). EZH2, one of the components of polycom-repressive complex 2 (PRC2), is a histone K27 methyltransferase. Recent studies on the EZH2 inhibitor have shown an arrest of cell growth by its ability to remove residual PRC2 (Mohammad et al. 2017). In a recent trial, an EZH2 inhibitor, tazemetostat, has been tested to treat refractory B cell lymphoma (NHL) (Morera et al. 2016). Another team is using MAK683, an inhibitor of embryonic ectoderm development protein (EED), to treat nasopharyngeal carcinoma and diffuse large B cell lymphoma (DLBCL) (Chiappella et al. 2017). Epidrugs have showed promising effects in both clinical practice and preclinical and clinical trials. Scientists are not only focusing on the enzymes that generate or create epigenetic markers (readers), but also on the enzymes that wipe out epigenetic markers (erasers) and proteins that edit epigenetic markers (writers).

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1.5 Epigenetic in Diseases 1.5.1 The Role of Epigenetics in Cancer Epigenetic aberration is a common feature of cancer, characterized by hypermethylation at specific promoter regions and global DNA hypomethylation, and/or either loss or gain of acetylation or methylation of histone proteins (Liang and Weisenberger 2017). Disruption of chromatin is crucial for nucleosome positioning, DNA wrapping, accessibility of chromatin to transcription factors, and regulation of gene expression. Silencing of tumor suppressor genes and activation of oncogenes are the hallmarks of epigenetic aberrancy (Fig. 1.5). The dysregulation of the epigenetic profile plays a key role in carcinogenesis. Likewise, the dynamic and reversible character of epigenetic modulation is an attractive feature for novel clinical treatment modalities.

1.5.1.1

AML

AML is a malignant tumor that arises from abnormal hematopoietic stem cells, characterized by massive proliferation of neoplastic precursor tumor cells, which causes hematopoietic aberrancies and alters bone marrow homeostasis. Current clinical protocols have limited options, involving intensive chemotherapy (Lavallee et al. 2016), and/or using poorly sourced stem cell transplantation (Powles et al. 1980). Despite promising results over the last few decades, AML is still a devastating disease in over half of young patients and almost 80% of elderly patients due to relapse and drug resistance, leading to increased morbidity and mortality (Adelman et al. 2019; Burnett et al. 2011). Aberration of the epigenetic landscape contributes to the development and the regulation of AML. Recurrent somatic mutations occur in specific genes that play a crucial role in epigenetic modulation, but epigenetic dysregulation is

Fig. 1.5 Epigenetic mechanism in cancers which are induced by both DNA methylation and histone modifications can be reversed by inhibitors of epigenetic modifiers

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a more likely mechanism compared to the recurrent mutations alone. Consequently, there is an urgent need to unearth the epigenetic mechanisms and pathogenesis of AML in order to achieve better patient management. DNA Methylation Aberrant DNA methylation is a hallmark of cancer, with global hypomethylation at repetitive elements, and hypermethylation occurring in the promoter regions that are enriched with CpG islands. Emerging evidence shows that for leukemogenesis, the disruption of DNA methylation occurring outside of CpG island is equally important as those within CpG island regions, and that hypomethylation and hypermethylation contribute equally to oncogenesis. Recent studies show that myeloid malignancies are accompanied by recurrent mutations occurring at epigenetic modifiers including Tet2 and DNMT3A, which are associated with hypomethylation and hypermethylation. Unearthing the interaction of these DNA methylation modifiers can help to elucidate the mechanism of AML. DNMT3A is a DNA methylation enzyme that can produce de novo methylation at CpG loci, and it is a common target of somatic mutations. These mutations occur in almost 40% of cytogenetic AML patients and about 20% of T-AML patients (Shlush et al. 2014). DNMT3A is viewed as a marker of early stage leukemia and may be beneficial in monitoring early events in AML. Increasing evidence has shown that DNMT3A mutations which occur in AML may appear in the T lymphocytes from the same individual. Recent research has also demonstrated that elderly people can carry the DNMT3A mutation without evidence of hematologic malignancy, showing that these mutations may be involved in clonal hematopoiesis and can contribute to leukemogenesis (Bond et al. 2019). The mutation occurring in DNMT3A leads to an arginine substitution, which results in a reduction in enzyme activity (Russler-Germain et al. 2014). DNMT3A mutated mice showed dynamic DNA methylation patterns occurring in both regions of hypomethylation and hypermethylation. Normal DNMT3A is critical for HSC self-renewal and cell differentiation in adult wild-type recipient mice (Liu et al. 2005). DNMT1 is a key player in the fate of leukemia cells, and a deficiency of DNMT1 in a mouse model was associated with reduced DNA methylation with reduction of the capacity of tumor suppressor genes to reactivate (Mizuno et al. 2001). The ten-eleven translocation (TET) family is another important target of DNA methylation through the transformation of 5-methyl-cytosine (5-mc) to 5hydroxymethylcytosine (5-hmc). About 30% of AML patients have mutations in TET2, which leads to reduced 5-hmc levels (Cimmino et al. 2017). The association between TET mutations and poor prognosis of AML patients has been reported. Increased capacity of self-renewal, over-proliferation of hematopoietic stem and progenitor cells (HSPC), and increased cell differentiation have been observed in TET2 deleted mice. In about 30% of AML patients, mutations frequently occur in isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2). Mutated TET and mutated IDH are mutually exclusive in adult AML. IDH can convert isocitrate into α-ketoglutarate naturally, but 2-hydroxyglutarate (2-HG) results from mutated IDH. This metabolite can

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compete with α-ketoglutarate and function as an inhibitor of TET2. Furthermore, the global hypermethylation signature in AML is associated with mutated IDH1/IDH2, and the overlapping hypermethylation signature has been observed in patients with mutated TET2. Murine models show that the level of 2-HG is increased in mutated IDH and the population of HSPC is expanded. Mouse findings were also consistent with those in AML patients (Cimmino et al. 2017). Histone Modification Histone acetyltransferases (HAT) and histone deacetylases (HDACs) are the primary mediators of histone acetylation and deacetylation, respectively. HAT is involved in sporadic translocation in AML patients (Izutsu et al. 2001). The myeloid oncoproteins, including PML-RARA and EVI-1, can interplay with either major complexes or scaffold proteins which aberrantly recruit HDACs. This results in abnormal chromatin condensation and remodeling, with the sites near transcription factors being more affected. HMTs are involved in translocation in AML, and HMT mutations occur in components of PRC2 and mixed-lineage leukemia (MLL) proteins (Basheer et al. 2019). The most common MLL protein, KMT2A, can modify H3K4 and transcriptionally activate targeted genes. MLL-induced translocations occur in about 10% of AML patients. Abnormal patterns of H3K79 methylation have been observed in MLLtransformed AML patients, and several related genes are also overexpressed. EZH2 can stimulate the di- and trimethylation of H3K27 and is generally considered to be a repressive modifier in numerous types of malignancies. Intriguingly, EZH2 mutations result in functional silencing in ALL, but the mechanism remains unclear. Other components, including SUZ12 and EED, play an important role in the leukemogenesis. Mutations of these components can lead to loss of function in ALL (Sinha et al. 2015). miRNA Aberrant activity of certain miRNAs can disrupt hematopoiesis and trigger leukemogenesis (Liu et al. 2019). miRNA can perform as either tumor suppressor or oncogenic agents, and while many new miRNAs are being found to have epigenetic activity each year, there are many that probably have not even been identified. The most studied miRNA in AML is Let-7, which is known for its tumorsuppressive property in various types of cancers. It functions by targeting a number of different oncogenes, including KRAS, HMGA2, MYC, and IMP1, and plays a role in adult AML. Let-7b is also downregulated in pediatric AML patients, and it is associated with dysregulation of the oncogene c-Myc, indicating that both solid tumors and hematologic neoplasia may have abnormal expression of Let-7 (Pelosi et al. 2013). Another well-known miRNA is miR-29, which is downregulated in MLL-mediated AML. The main function of miR-29 is induction of apoptosis and regulation of the cell cycle. Studies in mice support that miR-29 can induce apoptosis and inhibit tumor cell growth (Garzon et al. 2009). Oncogenic miRNAs such as miR-126 play a significant role in cancer. Overexpression of miR-126 in stable leukemia cell lines demonstrates inhibition of apoptosis

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and improved cell survival. AML patients also may show high levels of miR-24, and overexpression of miR-24 blocks the synthesis of mitogen-activated protein kinase phosphatase 7, promoting cell growth in AML (Organista-Nava et al. 2015).

1.5.1.2

Lung Cancer

Lung cancer is the leading cause of tumor-related death worldwide and is responsible for nearly 30% of cancer-related deaths, which is significantly more than the other top five cancers, including colorectal carcinoma, breast and prostate cancer. Despite medical advances, lung cancer continues to have a high mortality and low survival rate. Environmental tobacco smoke continues to be an important risk factor. Lung cancer can be clustered into two groups, small cell lung cancer (SCLC) and nonsmall cell lung cancer (NSCLC). The latter group can be further categorized into two types, squamous cell lung cancer and adenocarcinoma. The abnormal initiation and progression of lung cancer may be caused by the interplay of genetic disruption and dynamic epigenetic aberrancies. Epigenetics plays a key role and is an attractive target for the study of lung cancer and the development of new treatments. DNA Methylation Studies of the abnormal epigenetic profile seen in lung cancers can improve our understanding of lung tumorigenesis. Aberrations in DNA methylation is a key factor that contributes to the initiation and development of lung cancer by silencing tumor suppressor genes. DNA hypermethylation at promoter genes is considered an early event, and about 3% of functional genes carrying CpG-rich regions are deactivated in advanced stages of lung cancer (Teixeira et al. 2019). Three DNMTs are widely studied, all of which are overexpressed in lung cancer. The expression of DNMT1 is increased at the early stage of lung cancer, and it can silence the expression of P16INK4A and RASSF1A. DNMT3B is also a key participant in the pathogenesis of lung cancer and is associated with poor prognosis. The interaction of these DNMTs establishes abnormal DNA methylation patterns and represses the expression of tumor suppressor genes. Numerous tumor suppressor genes are affected and silenced, including MGMT, CDH13, DAPK, and APC genes. The inactivation of RASSF1A occurs in about 40% of squamous cell carcinomas and almost 80% of small cell lung cancers (Giri and Aittokallio 2019). Histone Modification Global H3 methylation and H2A acetylation have been observed in both SCLC and NSCLC. Gene activation caused by the H3K9 methyltransferase SETDB1 has been observed in lung carcinogenesis and increases invasiveness of cancer cells and cell proliferation by regulation of the WNT pathway. ERK1/2 activation, induced by upregulation of the H3K36 modifier KDM2A, promotes invasiveness and cell growth and is associated with a poor prognosis (Gardner et al. 2017). There are other metastasis-associated genes activated through upregulation of H2F3A, increasing

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tumor invasiveness resulting in poor outcomes in early stages of lung cancer. Likewise, upregulation of H4K8 acetylation and hypoacetylation of H3K12/H4K16 have been reported to occur in squamous cell carcinoma (Roper and Sheng 2019). miRNA Downregulation of dicer has been observed in NSCLC and correlates with poor prognosis. A mouse lung cancer model showed that dicer deletion led to tumor development and lower survivor rates (Szczyrek et al. 2019). miR199, miRNA101, and miRNA 126 are dysregulated in rat models in the early stage of lung cancer and are downregulated in human NSCLC patients as well. miRNA-let plays a crucial role in cell apoptosis and the cell cycle; downregulation of let-7 promotes cell division in lung cell lines and upregulation inhibits cell growth. Xenograft mouse model studies show similar results. A study of smokers who suffered from NSCLC found that polymorphisms in let-7 correlate with increased death risk (Del Vescovo and Denti 2015). miR-17-92 regulates cell apoptosis. Deactivation of let-7 and overexpression of MYC are common findings in lung cancer, leading to the upregulation of miR-17-92, overexpression of E2F protein, and increased lung carcinogenesis. Furthermore, miR-17-92 increases genomic instability and RB repression in SCLC cell lines. RB repression results in DNA damage by inducing the expression of y-H2AX (Zhang et al. 2018).

1.5.1.3

Pediatric High-Grade Glioma

In the past few decades, medical advances have greatly improved the survival rates of a number of pediatric cancers. This is not true for pediatric high-grade glioma (pHGG). Neurogenic tumors remain the leading cause of pediatric cancer, and pHGG is the leading cause of neurogenic tumors. It primarily affects the pons, brain stem, and cerebellum, with a survival rate lower than 1% (Donaldson et al. 2006). About 80% of pHGG is associated with histone H3 mutations, where K27 lysine is substituted by methionine (H3K27M) (Schwartzentruber et al. 2012). Treatment of pHGG is limited to surgery and radiation, with effective chemotherapy currently unavailable. Research targeting epigenetics provides a potential novel alternative to current treatment modalities. DNA Methylation DNA methylation patterns of pHGG show hypermethylation at CpG-rich promoter regions, leading to deactivation of tumor suppressor genes. H3K27M mutations commonly occur in pHGG affecting the midline structures and are associated with few O6 -methylguanine-DNA methyltransferase (MGMT) methylation changes, dismal results, and poor prognosis (Wu et al. 2012; Taylor et al. 2014). Similarly, H3G34R/V mutations are associated with a poor prognosis, whereas IDH1 mutations have no significant impact on survival rates compared to the wild type. H3G34R/V mutations are commonly associated with hemispheric pHGG with MGMT methylation

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enrichment (Fang et al. 2018). The methylation profile of three proliferative oncogenes, pedGBM-RTK1, pedGBM-RTK2, and pedGBM-MYCN, are associated with poor prognosis. DNA methylation profiles present important information that can be used to determine treatment and prognosis. Histone Modification An H3 mutation is identified as an oncohistone. Nearly 80% pHGGs harbor the H3.3K27M mutation, which has already been introduced (Schwartzentruber et al. 2012). H3K27I is another mutation that occurs in H3.3, where a lysine is substituted by an isoleucine. Furthermore, H3G34R/V, another variant of pHGG, involves substitution of glycine 34 to either arginine or valine. Mutations of H3.1 and H3.2, including HIST1H3B and HIST1H3C, are common events leading to histone variations named H3.1K27M and H3.2K27M, respectively. Mutations of H3.3 K27M and G34R/V occur exclusively in pHGG and show unique DNA methylation patterns and gene expression profiles. Interestingly, these two types of mutations in H3.3 often occur simultaneously with mutations in other genes. For example, nearly 30% of the K27M mutations are associated with an ATRX mutation and approximately 60% of mutations occur in conjunction with a TP53 mutation. Likewise, G34R/V mutations have ATRX and TP53 mutation as well, but the PDGFRA mutation has been found in the same individuals (Yuen and Knoepfler 2013). Together, this evidence suggests that mutations in H3 are an important risk factor and contribute to the pathogenesis of pHGG. Scientists have found that HDAC inhibitors have a promising effect on the treatment of pHGG (Grasso et al. 2015; Pang et al. 2009). According to this study, a combination of HDAC inhibitors, BRD4 and CDK7 blockers are a better strategy to overcome drug resistance (Nagaraja et al. 2017). EZh2 inhibitor, another inhibitor of histone modification, can remove PRC2 and inhibit cell growth and may be a promising therapeutic method for the treatment of pHGG (Mohammad et al. 2017). miRNA Studies of miRNA in pHGG are lacking compared to adult gliomas. The expression of miR-34 and miR-21 are upregulated, while miR-129 and miR-124 are downregulated in pHGG. Several miRNAs are involved in the regulation of gene expression through the MAPK pathway, involving regulation of BRAF-KIAA1549 (Pang et al. 2009). A xenograft mouse model of miR-487 showed inhibition of colony formation and downregulation of nestin and PROM1 genes. Other miRNA, including miR-204, miR-1296, miR-1224, miR-10a, and miR-34c, are downregulated, and miR-527, miR-769-3, and miR-200A are upregulated in pHGG (Riddick and Fine 2011).

1.5.2 The Role of Epigenetics in Immune Diseases The etiology of autoimmune diseases remains unclear. Although genome-wide association studies (GWAS) are now widely available, they have failed to reveal a clear genetic pathophysiology of autoimmune diseases. Scientists now appreciate that the

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Fig. 1.6 Epigenetic modifications dysregulate gene expression on different types of immune cells and trigger autoimmune diseases

epigenome plays a critical role to initializing and stimulating autoimmune diseases (Fig. 1.6). Disruption of DNA methylation and histone modification leads to abnormal epigenetic profiles. Epigenetic aberration in autoimmune disease results in breaking self-tolerance, thus triggering autoimmunity. The epigenetics of autoimmune diseases is discussed in Chaps. 7–13 of this book.

1.5.2.1

Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease characterized by overactivation of the immune system and production of excessive autoantibodies. These antibodies may attack self-tissues or organs and are a potential cause of SLE. However, even with the medical advances of the past decades, the mechanism of SLE remains unclear. Epigenetics may provide new insights to elucidating some of the factors leading to the breakdown of tolerance. DNA Methylation DNA methylation is a key player in the pathogenesis of SLE. Altered DNA methylation in SLE is characterized by global hypomethylation on CD4+ T cells involving the extracellular signal-regulated kinase (ERK) signaling pathway. In murine models, studies have shown dysregulation of this pathway leading to downregulation of DNMT1 and overexpression of methylation-associated autoimmune genes.

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Hypomethylation in CD4+ T cells results in upregulation of relevant genes. Studies have found that CD11a (ITGAL), CD40LG, CD70 (TNFSF7), and perforin are all upregulated in lupus patients and are positively correlated with disease activity. It has been found that the promoter region of these genes is significantly hypomethylated in lupus T cells, compared to controls and patients with inactive lupus (Lu et al. 2002, 2007; Oelke et al. 2004). Similarly, lupus models were successfully induced after CD4+ T cell from healthy individuals were stimulated with phytohemagglutinin (PHA), followed by treatment with any of the DNA methylation inhibitors, including 5-aza, procainamide, hydralazine (Deng et al. 2003). The promoter regions of these genes are hypomethylated and the corresponding genes are greatly upregulated. Mice injected with either procainamide- or hydralazine-treated CD4+ T cells develop a lupus-like disease, which shows loss of methylation at promoter regions of some targeted genes and produces autoreactive antibodies. Histone Modification Abnormal histone modification is a key contributor to the pathogenesis of SLE. Active SLE patients show downregulation of global H3 and H4 acetylation in CD4+ T cells, with the acetylation level being negatively associated with disease activity (Coit et al. 2013). SLE murine models demonstrate that spleen cells have a low level of acetylation in H3. The use of HDAC inhibitors, such as suberoylanilide hydroxamic acid or trichostatin A, successfully treated splenomegaly and glomerulonephritis in SLE. In vitro, the acetylation level of histones H3 and H4 greatly improved after the use of HDAC inhibitors, with a decrease in the level of a number of cytokines, including IFN-γ, IL-6, IL-10, and IL-12. HAT mutations in a mouse model led to a propensity to develop lupus-like diseases, with positive anti-dsDNA autoantibodies, glomerulonephritis, and low survivor rates (Mishra et al. 2003). miRNA miRNAs function by regulating the transcription of mRNAs. Peripheral blood mononuclear cells (PBMCs) in SLE patients show an abnormal expression of miRNA. Disruption of miRNAs involving the ISG and TLR pathway is considered a key risk and contributes to the pathogenesis of SLE (Yan et al. 2014). Previous work demonstrated that miR-146a, which negatively regulates the IFN pathway, contributes to disease pathogenesis. Recent studies have demonstrated that an abnormal expression of LYN induced by miR-30a in B cells has an important role in SLE. In MRL/lpr murine models, DNMT1 was decreased by upregulation of miR-148a and miR-21, leading to a DNA hypomethylation pattern. Overexpression of miR17-92 has been shown to lead to lupus in animal models. Mice knockdown (Wang et al. 2018) studies demonstrated a slow progression of lupus and better prognosis. miRNAs can also be used as biomarkers in clinical application, are associated with SLE disease activity index (SLEDAI), and are a good predictor of disease activity (Khoshmirsafa et al. 2019).

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Rheumatoid Arthritis

Rheumatoid arthritis (RA) is a chronic relapsing autoimmune disease, characterized by aberrant targeting of joint linings by the immune system. RA leads to bilateral joint erosion, including knees, hands, or shoulders. The symmetric characteristic is useful to distinguish RA from other forms of arthritis. In RA, disruption of a normal epigenetic profile by DNA methylation, histone modifications, and miRNA is commonly detected in stromal and immune cells. Epigenome aberration affects multiple inflammatory and matrix-associated pathways and contributes to the pathogenesis of RA. DNA Methylation RA has a similar DNA methylation pattern as SLE, showing global hypomethylation of T cells and monocytes. Demethylation occurs in the promoter region of CD40L on silenced X chromosomes, leading to overexpression of CD40L, which contributes to the development of RA (Lu et al. 2007). CTLA-4 is hypermethylated at specific sites in Treg cells in RA patients, leading to a decrease in the expression of CTLA-4. Subsequent studies found that methotrexate decreases FoxP3 DNA methylation levels in Treg cells. Upregulation of CTLA-4 results from Foxp3 reactivation, which leads to normalization of Treg cell function. Aberrant methylation patterns also occur in PBMCs. Demethylation of IL-10-related genes greatly increases expression of IL-10 in PBMCs (Khoshmirsafa et al. 2019), whereas abnormal methylation of IL-6-related genes in PBMCs results in downregulation of IL-6. Loss of global methylation also occurs in synovial fibroblasts, CXCL12 and TBX5 in RA (Cecchinato et al. 2018). Histone Modification Dysregulation of several histone modifiers is a common feature of RA. Conflicting results have been found between expression of HATs and HDACs in synovial fibrocytes and activity of RA patients, probably caused by different criteria of recruited RA patients. Recent studies discovered that the expression of HDAC1 and HDAC2 is associated with and regulates TNF in synovial fibrocytes (Angiolilli et al. 2017). However, the expression of HDAC5 is negatively associated with IL-6 expression as well as disease activity. Recent work shows that SIRT1 is upregulated in RA synovial fibrocytes, leading to overexpression of IL-6 and IL-8 and reduction of apoptosis. Scientists studied the histone methylation status at the promoter regions of matrix metalloproteinases (MMP) in RA synovial fibroblasts and found that the active marker H3K4me3 was upregulated and the inactive marker H3K27me3 was downregulated in the promoter regions of MMP-1 and MMP-9. An arthritis mouse model using the HDAC inhibitor Givinostat demonstrated a reduction in cytokine levels and improvement in the prognosis of RA (Angiolilli et al. 2018). miRNA Early studies of miRNAs in RA found that expression of miR-155 and miR-146a is upregulated in RA synovial fibroblasts. Subsequently, larger studies showed that miRNA-155 is overexpressed in various tissue and immune cells, such as CD14+

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cells derived from synovial fluid, B cells, macrophages, and PBMCs. Likewise, miRNA-146a is upregulated in PBMCs and CD4+ T cells. The association between miR-155 expression in PBMCs and swollen joints indicates that miR-155 promotes the progression of RA by triggering production and recruitment of cytokines. MiR124a has been observed to be downregulated in RA patients. MiR-223 was found to be overexpressed in CD4+ T cells, synovial fibroblasts, and synovial fluid (Dunaeva et al. 2018) in RA patients.

1.5.2.3

Multiple Sclerosis

Multiple sclerosis (MS) is a chronic relapsing autoimmune disease involving the nerves of brain and spinal cord, leading to axonal degeneration and demyelination. The mechanism of MS remains unclear. Multiple studies discovered disrupted epigenetic profiles in immune system components which lead to demyelination and recurrent inflammation that contributes to the pathogenesis of MS. DNA Methylation Previous studies using a murine model for MS, namely, experimental autoimmune encephalomyelitis (EAE), found that T-bet/H2.0-like homeobox (Hlx), which is regulated by MBD2, plays an important role in the pathogenesis of MS. IFN-γ, expressed Th1 and natural killer (NK) cells, is in turn regulated by T-bet. The Hlx gene coordinates with T-bet to regulate the expression of IFN-γ. MeCP2, a member of the MBD family, is capable of myelin repair and remyelination when combined with brain-derived neurotrophic factor (BDNF) (KhorshidAhmad et al. 2016). Expression of Dnmt1, TET2, and 5hmC is greatly depressed in MS, and abnormal DNA methylation profiles at the promoter region of specific genes has been observed in PBMCs from patients with MS. Studies have also shown that the DNA methylation levels of HLADRB1 in CD4+ T cells correlate with the risk of developing MS (Tang et al. 2019). Histone Modification Disruption of histone modification is a key factor in the initiation and progression of MS. Studies have shown that histone methylation is critical for the development of the M2-macrophage phenotype. The upregulation of H3K4me3 and downregulation of H3K27me2/3 have been observed at the promoter region of M2 marker genes. Overexpression of Jmjd3 removes H3K27me2/3 and affects the M2 phenotype from macrophages. HDACs are associated with differentiation of CD4+ T cells and secretion of cytokines by regulating histone patterns (Sun et al. 2018a). Furthermore, HDAC inhibitors suppress the immune system and inhibit the inflammatory process. HDAC inhibitors play a role in inhibition of cell growth of CD4+ T cells and blocking of the production of IFN-y. HDAC inhibitors decrease T helper (Th) cell associated pro-demyelinating cytokine formation in macrophages, such as TNF-α, IL-12, and IL-6. Consequently, HDAC inhibitors affect Th1–Th2 conversion and Treg proliferation and can help alleviate symptoms of MS by suppressing systemic immune

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responses (Faraco et al. 2011). Upregulated histone acetylation in oligodendrocytes is associated with inhibition of cell differentiation, resulting in damaged remyelination in MS. In addition, histone deacetylation upregulates the transcriptional profile of oligodendrocytes in the context of myelination and remyelination. miRNA The expression of miR-326, correlating with the production of IL-17 in Th17 cells, plays an important role in the initiation and development of MS. MiR-326 is upregulated in Th17 cells and can decrease the expression of Ets-1, leading to an increase in Th17 differentiation (Du et al. 2009). Furthermore, miR-155 has been shown to be able to regulate Th17 cells by controlling the suppressive effects of Jarid2, which functions as a recruiter of PRC2. EAE murine models show upregulation of let-7e in CD4+ T cells, amplifying the function of Th1 and Th17 cell and increasing IL10 activity, leading to an increase in the severity of EAE. Scientists have shown that overexpressed miR-128 and miR-27b exist in naïve cells and miR-340 overexpression occurs in CD4+ memory T cell. These miRNAs favor differentiation of Th1 and abrogate differentiation of Th2 cells. Decreased expression of miR-320a has been found in B cells, leading to overexpression of MMP-9 (Yang et al. 2018).

1.5.3 Role of Epigenetics in Endocrine Diseases The endocrine system comprises endocrine glands that generate the fundamental hormones that act on various organ systems, regulating cell proliferation, differentiation, metabolism, and tissue function. Studies have found that epigenetic modifications bridge the gap between genetic and environmental factors in modifying endocrine function and have a great impact on the endocrine system by regulating gene expression of endocrine networks. Disruption of epigenetics contributes to the pathogenesis of endocrine diseases.

1.5.3.1

Type 2 Diabetic Mellitus

Type 2 diabetes mellitus (T2DM) is a chronic endocrine disease which results from inactive responses of insulin to high blood glucose caused by damaged capacity in insulin-responsive tissues or organs and is associated with deficient β-cell compensation. Epigenetics play a key role in differentiation of endocrine cell and performance of islet cells. Epigenetic modifications affect the proliferation and development of β-cells and contribute to the pathogenesis of T2DM. DNA Methylation Abnormal insulin secretion of pancreatic islets contributes to the pathogenesis of T2DM. Hypermethylation at the promoters of transcription factor Pdx1, Ppargc1a as well as insulin-associated genes negatively controls the expression of mRNA.

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Genome-wide Infinium450K array has identified over 1000 CpG sites and genes, including Tcf7l2, Pde7b, Cdkn1a, and Kcnq1, that have a different DNA methylation pattern in T2DM (Kodama et al. 2018). In T2DM, the promoter of Cdkn1a and Pde7b is hypermethylated, resulting in downregulation of these two genes and reduction of transcription activity of β-cells and abnormal secretion of insulin. Another study demonstrated that there is a significantly higher number of hypomethylated CpGs in T2DM compared to normal controls. Aberrant DNA methylation patterns in islets of T2DM have been observed in both PBMC of T2DM and β-cell lines during hyperglycemia, suggesting that changes in DNA methylation is a key factor in the pathogenesis of T2DM. Researchers have found that the promoter of insulin-like growth factor-binding protein 1 IGFBP1 and IGFBP7 is hypermethylated in PBMCs (Drogan et al. 2016). In addition, global hypermethylation has been observed in B cells and natural killer cells in T2DM. Metabolic abnormalities also arise from liver, adipose tissue, and skeletal muscle, possibly resulting from aberrant DNA methylation patterns in T2DM. Previous T2MD murine models revealed that the promoter of hepatic glucokinase (Gck) and L-type pyruvate kinase (LPK) is hypermethylated and associated with disease initiation and progression. Recent studies indicate that hypermethylation of ubiquinone oxidoreductase subunit B6 (NDUFB6) decreases the expression of NDUFB6, leading to changes in insulin sensitivity (Kacerovsky-Bielesz et al. 2009). Histone Modification Histone tail modification is a critical regulator for the pathogenesis of T2DM. Recent studies indicate that histone hyperacetylation plays an important role in glucose pathway regulation and insulin secretion, implicating HAT and HDAC as key players that modulate T2DM gene expression (Bocchi et al. 2019). HNF-4 acetylation regulates DNA binding and is associated with gene activation. T2DM murine models show that CBP enhances insulin responses and increases glucose tolerance in heterozygous mice. The transcription factor PDX1 regulates gene expression of proinsulin. Several studies show that HDAC inhibitor treatment leads to downregulation of proinflammatory cytokines, such as IL-6, IL-8, ICAM-1, and MIF. In T2DM cell lines or murine models, the methyltransferase Set7 is associated with diabetic complications. Set7 methyltransferase combines with H3 tails to promote H3K4me1 binding to the promoter of RELA. Polymorphisms in SUV39H2, one of the H3K9 methyltransferases, alter inflammatory cytokine expression and have been found to play a role in T2DM (Syreeni et al. 2011). miRNA miRNAs play a role in the regulation of β cell proliferation, cell differentiation, insulin secretion, and insulin resistance in T2DM. miRNAs function as pivotal components in glucose homeostasis. Disruption of miRNA leads to interference of electrical excitation of the β cell membrane, affecting insulin production, development of pancreatic cancer, and regulation of glucose metabolism (Wu and Miller 2017). Repression of miR-124a is important for β cell development and secretion pathway

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regulation through upregulation of Foxa 2 and GTPase Rab 27a, leading to reduction of insulin secretion in islet cells of T2DM patients. Overexpression of miR-34a regulates survival of β cells and apoptosis of MIN-6 cells in both mouse and human T2DM (Wu et al. 2019; Li 2014). Animal models show that miR-375 is upregulated in T2DM and is responsible for β cell proliferation and development by regulating several growth-associated genes in pancreatic β cells (Li 2014).

1.5.3.2

Graves’ Disease

Graves’ disease (GD) is an autoimmune disease caused by excessive autoantibody binding to thyrotropin receptors. Hyperthyroidism is the most common clinical manifestation. Increasing evidence demonstrates that epigenetic modifications occurring as a result of environmental exposures lead to dysregulation of gene expression, contributing to the pathogenesis of GD. DNA Methylation Studies have shown that global DNA hypomethylation occurs in GD, leading to an immune response against thyroid tissue. Analysis of the DNA methylation profile in patients with GD revealed hundreds of genetic regions, including the genes DNMT1, ICAM1, CTLA4, and MECP2, with altered DNA methylation patterns (Guo et al. 2018). There are over 300 methylated regions in CD4+ T cells and over thousands of methylated regions in CD8+ T cells, with many genes involved in T cell immune signaling pathways. Previous studies have shown that hypermethylation of TSHR correlates with GD. Polymorphisms in methionine synthase reductase (MTRR), as well as DNMT1, are associated with DNA hypomethylation and increased susceptibility to GD. Polymorphisms of 5,10-Methylenetetrahydrofolate reductase C677T contribute to the development of GD (Mao et al. 2010). Histone Modification Lower levels of histone H4 acetylation and higher levels of HDAC1 and HDAC2 in the PBMCs of patients with GD have been observed (Sarumaru et al. 2016). Genome-wide studies reveal that H3K4me3 and H3K27ac are downregulated at T cell signaling associated genes in GD. Furthermore, H2A.X, a histone phosphorylated protein, was found to be dysregulated in T cells and thyrocytes in a GD murine mouse model. Dysregulation of TG caused by IFN-α enriches methylation of the Lys-4 residue in H3, which can trigger GD. IFN-α is a T cell secreted cytokine, which during viral infection leads to upregulation of H3K4me1 and H3K4me3 in thyrocytes (Coppede 2017). Recent studies have found that H2B has the capacity to identify DNA fragments in autoimmune thyroiditis, leading to upregulation of immune response genes. Polymorphisms of histone-associated genes contribute to the development of GD. SIRT1, an HDAC, has been associated with an overexpression of autoantibodies in GD.

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miRNA The most studied miRNA in GD is miR-146a (Zheng et al. 2018a). Repression of IL-1R-associated kinase 1 mediated by MiR-146a-5p triggers antigen presentation by dendritic cells (DC). MiR-155-5p mediates transcription factors and immune response molecules, by targeting SOCS1 and STAT3, leading to functional aberrancies in T helper or dendritic cells. Dysregulation of miR-155-5p and miRNA-146a5p thereby erodes the immune microenvironment and breaks immune tolerance. In addition, MiR-346 negatively regulates the expression of Bcl-6 and activates CD4+ CXCR5+ T cells and is decreased in GD. Several overexpressed miRNAs, including miR-183-5p and miR-22-3p, and other repressed miRNAs, such as miR-660-5p, miR-101-3p, and miR-197-3p, have been observed in thyrocytes in patients with GD. miR-125a-5p is repressed in PBMCs of patients with GD, whereas miR-30a–5p and miR-519e-5p are significantly upregulated, and miR-19b-3p and miR-146a-5p are downregulated in Treg cells, which contribute to the development of GD (Qin et al. 2015).

1.5.3.3

Pituitary Adenomas

Pituitary adenomas (PA) are benign brain tumors, characterized by the release of high levels of hormones, including prolactin, growth hormone, and thyrotropin. Although genetic mutations are known to occur in PAs, recent studies demonstrate that altered epigenetic profiles may also contribute to the initiation and progression of tumorigenesis. DNA Methylation DNMT1 induces DNA methylation and alters the expression of the neuronatin (Nnat) gene (Yacqub-Usman et al. 2012). Overexpression of DNMT3b has been observed and can produce de novo DNA methylation. The promoter of DNMT3b is hypomethylated in PA compared to normal controls. In pituitary adenoma cell lines, repressed DNMT3B leads to activation of retinoblastoma protein (RB). Loss of RB in the mouse results in tumors arising from the intermediate lobe of the gland. Infinity HM450K array analysis revealed that p15(INK4b), p16(INK4a), RB1, and p27(Kip1) are hypermethylated and inactivated, and that about 90% of patients with PA showed altered DNA methylation patterns and dysregulated gene expression (Yao et al. 2017). Histone Modification Downregulation of BMP-4 caused by altered histone modifications has been demonstrated in PA (Yacqub-Usman et al. 2012). In PA patients, high levels of H3K9 acetylation positively regulate tumor immigration and invasiveness by targeting the MIB-1 (Ki-67) gene, as well as p53. Histone modification of melanoma-associated antigens (MAGE) and hematopoietic stem cell chromatin remodeler were found to be greatly overexpressed in PA. Upregulation of MAGE interacts with FGFR2, leading to hypomethylation of promoter regions and de-repression of targeted genes.

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HDAC regulates pituitary tumor-transforming gene (PTTG) and leads to a high level of PTTG expression (Wierzbicka-Tutka et al. 2016). Increased acetylation of PTTG promoter has been observed, upregulating PTTG expression, resulting in an unfavorable outcome by modulating the signaling pathways of c-Myc and FGF2. Recent studies showed that dysregulation of Ikaros mediates the acetylation removal at the promoter of GH, restricting access to the Pit-1 activator. In PA patients, IK6, an isoform of Ikaros without a DNA binding domain, has a negative effect on gene expression, resulting in upregulation of H3 acetylation with overexpression of antiapoptotic Bcl-XL, contributing to the development of PA (Ezzat et al. 2003). miRNA Overexpression of miR-493 and miR-122 has been observed in PA patients compared to normal controls. Decreased expression of let-7a, miR-15a, and miR-16, miR-21, and miR-141 has been found in PA as well (Nemeth et al. 2019). Upregulation of miR-26a modulates cell proliferation by targeting AtT20. Abnormal expression of miR-128 and miR-26b results in dysregulation of gene expression by targeting PTEN-AKT in GH-correlated PA. Furthermore, the interaction between downregulated let-7 and high-mobility group AT-hook2 (HMGA2) results in Ki-67-associated cell proliferation, invasiveness, immigration, and tumor growth, which contributes to the pathogenesis of PA. Decreased miR-23b and miR-130b have been shown to occur in PA. Upregulation of these two miRNAs arrests cell growth in PA cell lines (Leone et al. 2014).

1.5.4 The Role of Epigenetics in Respiratory System Diseases 1.5.4.1

Asthma

Asthma is a chronic and relapsed inflammatory lung disease, characterized by recurring and reversible airway constriction as well as bronchospasm. Despite recent advances in pharmaceuticals for asthma, the pathogenesis of asthma remains incompletely elucidated, and thousands of people still die from asthma every year. It is reasonable to believe that since asthma is a disease that is significantly impacted by environmental exposures, and since asthma is not a monogenic disease, epigenetics can help answer how regulation of gene expression may play a role in the risk of developing asthma as well as variable phenotypes of asthma (Fig. 1.7). The epigenetics of allergic diseases, including asthma, is discussed in Chaps. 4–6 of this volume. DNA Methylation Studies have shown that epigenetic modification plays an important role in T cell differentiation and have shown that altered DNA methylation contributes to the pathogenesis of asthma. Two arginase genes (Arg1 and Arg2) play a role in nitric oxide production, and altered DNA methylation in the promoter of these molecules has

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Fig. 1.7 Epigenetic modifications regulate gene expression and contribute to the pathogenesis of asthma

been associated with pediatric asthma (Li et al. 2006). DNA methylation at the promoter of Alox12 has been found to correlate with persistent bronchospasm. Abnormal DNA methylation patterns in Treg cells and altered DNA methylation of Foxp3 have been shown to occur in patients suffering from asthma with or without exposure to air pollution (Li et al. 2018). Polluted air contributes to decreased chemotaxis of Treg cells. Environmental tobacco smoke (ETS) also contributes to the development of asthma. Altered DNA methylation of Pcdh-20 has been found in sputum samples of asthma patients after comparing the asthma smoker to control smoker groups, and Pcdh-20 interacts with Pax-5α to increase the risk of asthma. Diet is another factor that may also affect the epigenetic profile in asthmatics. Pregnant mice were fed with high and low methylation diets, and ovalbumin was used to stimulate the offspring. The offspring of the mothers fed with high methylation food showed higher IgE and more severe bronchial inflammation compared to the group on the low methylation diet. Abnormal DNA methylation patterns have been observed in CD11 DC cells of baby mice with vertical transmission from the mother. A murine asthma model showed hypermethylation occurring in the promoter region of IFN-γ and overproduction of IFN-γ in CD4+ T cells. Furthermore, loss of DNMT3A in CD4+ T cells overexpresses IL-13 and reduces DNA methylation at the promoter of IL-13, leading to aggravation of bronchial inflammation and overexpression of IgE (Yu et al. 2012). Histone Modification Asthma patients have higher expression of H4 acetylation compared to normal controls, which correlates with a reduction in HDAC activity and overexpression of inflammation-associated genes (Royce and Karagiannis 2014). Furthermore, airway inflammation in asthma patients can be controlled by glucocorticoids by regulating the expression of histone acetylation. Several studies have shown that modification

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of histone acetylation can be achieved in glucocorticoid-resistant asthma patients, and these modifications can reverse the glucocorticoid resistance. Recent studies have demonstrated that TGF-β2 can inhibit expression of ADAM33, a gene which has been cited as having a role in the pathogenesis of asthma, resulting in downregulation of histone acetylation of H3 and H4, as well as histone hypermethylation of H3K9 (Khaleva et al. 2019). miRNA Dysregulation of miRNA in CD8+ T cells of asthma patients has been observed, and expression levels correlate with disease severity. Downregulation of miR-146a and miR-146b in T cells, as well as decreased miR-28-5p, has been observed in CD8+ T cells in asthma patients (Comer et al. 2014). A number of animal studies have also shown that miRNAs play a crucial role in the pathogenesis of asthma. Animal models have shown that inhibition of miR-126 can block Th2 activity by modulating the expression of MyD88. In addition, repression of miR-145 can block inflammatory pathways, decrease mucous secretion, and downregulate Th2 cytokines. Multiple studies have shown that members of the let-7 family are upregulated after stimulation by allergens. Since let-7a stimulates the expression of IL-13, let-7a inhibitors may lead to remission of the inflammatory response (Chen et al. 2019).

1.5.4.2

Chronic Obstructive Pulmonary Disease

Chronic obstructive pulmonary disease (COPD) is characterized by limited airflow and irreversible impaired airway structure and globally is one of the leading causes of death. Epigenetic aberration plays a key role in the pathogenesis of COPD. DNA Methylation Environmental tobacco smoke (ETS) is an important factor contributing to the development of COPD, possibly as a result of its role in aberrant DNA methylation. A genome-wide DNA methylation study found that over 300 CpGs sites are associated with pathogenesis of COPD and have a great impact on the reduction of lung function (Bermingham et al. 2019). In addition, studies of innate immune cells in COPD patients showed that aberrant DNA methylation patterns and the severity of disease correlate with smoking status. Murine COPD models sensitized to smoke also demonstrate abnormal DNA methylation patterns and altered gene expression profiles. DNA methylation at the promoter of p16 is positively associated with the severity of smoking (Sundar et al. 2018). Smoking can alter the expression level of NRF2, corresponding to the DNA methylation alteration in PBMCs inpatients with COPD. Loss of DNA methylation of A1AT is a risk factor for the development of COPD. Murine models sensitized to smoke have shown that overexpressed hypomethylation of HDAC occurs in COPD, resulting in cilium degeneration and dysregulation of mucus clearance.

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DNMT expression is affected by smoke in COPD. Smoke exposure downregulates the expression of DNMT1 and upregulates DNMT3B in COPD (Qiu et al. 2018). Abnormal DNA methylation patterns after smoke exposure induce gene silencing by targeting PRC2. RUNX3, an anti-tumor gene, is regulated by PRC2 and is positively correlated with duration of smoking and methylation status. Histone Modification Upregulation of inflammation-associated genes, including AP-1 and NF-κB, induces the overexpression of cytokines by upregulating acetylation levels of histones in COPD patients (Sun et al. 2018b). Upregulation of NF-κB has been observed in COPD patients. A murine COPD model has shown that AP-1 and NF-κB are upregulated by ETS. TNF-α and other inflammatory cytokines can then trigger the inflammatory response by altering the expression of NF-κB, leading to massive production of IL-8. Abnormal histone phosphorylation stimulated by smoke has been found to activate MSK1 in both humans and mice models. MSK1 interacts with p65, a member of NF-κB family, and is downregulated by post-transcriptional modification of phosphorylation and acetylation of H3 and H4. Studies have found that inflammatory cytokines and chemokines can be negatively controlled by HDACs (Lai et al. 2018). HDAC3 deacetylates p65 and negatively modulates expression of NF-κB. Furthermore, the expression of HDAC is reduced in PBMCs and airway tissue from smoking derived COPD patients. Impaired activity and reduced expression of HDACs are associated with disease status, although there is relative stable expression of HDAC5 and HDAC3. In smokers with COPD, HDAC2 activity decreases in small but not large airways. Downregulation of DJ-1 and NRF2 is correlated with disease status in COPD patients. Murine studies revealed that DJ-1 knockdown inhibits the activity of NRF2 and downregulates the expression of antioxidant genes (Malhotra et al. 2008). miRNA Recent studies have found that miRNAs can trigger lung inflammation, and abnormal miRNA activity can contribute to the development of COPD. Studies have found that smoking has a repressive effect on the expression of miRNA, and that miRNAs are significantly downregulated in smokers with COPD compared to normal controls (Szymczak et al. 2016). Abnormal expression of miR-452 is involved in the dysregulation of MMP12. Altered expression of miRNAs plays an important role in the TGF-β and Wnt pathways, which are crucial for the initiation and progression of COPD (Heijink et al. 2016). Studies have also demonstrated that miR-181d, miR-30c, and miR-638 expression may play a role in the pathogenesis of COPD by regulating oxidative stress.

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Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disorder with dismal prognosis and few therapeutic options. IPF is characterized by progressive fibrosis and an irreversible decline in lung function. The pathogenesis and mechanism remain unknown. Epigenetic changes may shed light on the pathophysiology of IPF. DNA Methylation Studies have shown that hypermethylation at the promoter of Thy-1 downregulates Thy-1 in IPF, resulting in proliferation of fibroblasts and impaired lung function. The methylation status at the promoter of a-SMA in different cells, including myofibroblasts and fibroblasts, is associated with a-SMA gene expression (Tzilas et al. 2019). DNMT inhibitors have a repressive effect on DNMT activity and activate the expression of a-SMA. Recent studies show that a-SMA can bind to MeCP2, altering the expression of a-SMA in fibroblast cells in the lung (Coward et al. 2014). Fibroblast apoptosis is affected by the methylation levels of PTGER2 and ARF, and hypermethylation in the promoter decreased the expression level of these genes in IPF. PTGER2 can upregulate the activity of DNMT3a and increase the methylation level, resulting in upregulation of genes that arrests cell growth in fibroblasts. IPF patients have a loss of methylation and an increase in the level of TP53INP1 expression (Sanders et al. 2012). It has been shown that PDGF, NOTCH1, and CASZ1 alter DNA methylation and gene expression, contributing to the pathogenesis of IPF. Histone Modification Loss of acetylation of histone at the promoter of apoptosis and anti-fibrosis genes, such as CXCL-10 and COX-2, can reduce gene expression and decrease protein activity, leading to the proliferation of fibroblasts and impeding normal apoptosis in IPF. Studies have found that a histone deacetylase, Sirtuin, mediates the degradation of p21 proteasomal and abolishes the senescence mediated by TGF-β in bronchial epithelial cells (Korfei et al. 2018). The histone deacetylase inhibitor can be performed as an antagonist of TGF-β1 and inhibits fibroblasts’ differentiation into myofibroblasts, leading to decreased production of collagen. IPF animal models have shown that a histone deacetylase inhibitor can activate the expression of Thy-1 in fibroblasts. Furthermore, histone deacetylase inhibitors block differentiation pathways regulated by TGF-β1 and collagenation in pulmonic fibroblasts. A novel histone deacetylase inhibitor, SpA, can arrest cell growth and block the differentiation of cells that contribute to IPF (Davies et al. 2012). miRNA Mir-29, let-7d, miR21, and miR154 are upregulated in IPF patients compared to normal controls (Mizuno et al. 2017). A murine IPF model shows that let-7d has a protective function by blocking the pathway of epithelial to mesenchymal transition mediated by Smad-3. Let-7d can be blocked by an miRNA inhibitor, leading to a decrease in the expression of epithelial cells and an increase in the expression of mesenchymal markers in epithelial cells (Pandit et al. 2010). miR-154 has been found

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to be overexpressed in IPF patients (Milosevic et al. 2012). Introduction of miR154 into fibroblasts increases cell growth by activating the WNT pathway. Human and animal studies also have shown that miR-21 and miR-29 are upregulated in fibroblasts, and that inhibition of these miRNAs can modulate TGF-β1 and reduce fibrosis.

1.5.5 The Role of Epigenetics in Dermatologic Disorders Dermatologic diseases vary extensively in symptoms and physical appearance. Some manifestations may be benign, and others may be life-threatening. Genetic and environmental factors both play a role in the pathogenesis of dermatologic disorders. Recently, large-scale studies have shown that disrupted epigenetic profiles can trigger the initiation and progression of dermatologic diseases.

1.5.5.1

Psoriasis

Psoriasis is a dermatologic disorder involving the accelerated proliferation of keratinocytes. Clinically, skin presents red and rough patches covered with excessive silver scales. The etiology and mechanism of psoriasis remain unclear, but it is thought to be an autoimmune disease, although no autoantibody has been identified. The epigenetics of psoriasis is discussed in detail in Chap. 8. DNA Methylation Global hypomethylation in CD4+ T cells and hypermethylation in PBMCs have been observed in psoriasis patients. Studies have found that DNMT1 is overexpressed in PBMC in psoriasis patients compared to normal controls (Zhang et al. 2010). Downregulation of MeCP2 and MBD2 has been observed in PBMCs from patients with psoriasis. Loss of methylation has been detected at the promoter of SHP-1, which is important for the cell growth. An isoform of SHP-1 has been found to be overexpressed in psoriasis patients compared with normal controls (Ruchusatsawat et al. 2006). The promoter of p16 has been found to be demethylated and the expression of p16 upregulated in mononuclear cells from psoriasis patients. Loss of methylation of p15 and p21 has occurred in psoriasis patients, resulting in arrest of hematopoietic cell growth. Studies have found that the promoter region of a tumor suppressor gene, p14ARF, is heavily hypermethylated and the expression level downregulated in psoriasis patients (Chaturvedi et al. 2003). Genome-wide studies have identified over hundreds of genes that are hypermethylated in psoriasis, of which about 100 are associated with the X chromosome. Immune-associated genes, such as TLR-7 and IRAK1 on the X chromosome, are hypermethylated in T cells. A recent study revealed that the methylation status of CpG sites can be categorized into different

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groups in CD4+ T cells of psoriasis patients, and many of these genes are associated with regulation or expression of cytokines and chemokines (Coit et al. 2019). Histone Modification Psoriasis patients have been demonstrated to have global H4 hypoacetylation in PBMCs, with the level of H4 acetylation associated with PASI scores as well as disease activity. Upregulation of HDAC1, EZH2, and SUV39H1 and downregulation of HATs, SIRT1, and CBP have been observed in psoriasis (Zhang et al. 2011). Studies have also found that SIRT1 can arrest cell growth and induce cell differentiation of keratinocytes by inhibiting the activity of E2F1 (Fan et al. 2019). E2F1, a member of the E2F family, can function as an activator or repressor of genes. The activated pathway of E2F is responsible for hyperproliferation and impaired apoptosis, while the repressed pathway of E2F correlates with a reduced cell growth rate. In psoriasis patients, downregulation of SIRT1 may be responsible for the overgrowth of keratinocytes. Studies have shown that HDAC inhibitors may be a potential therapeutic epidrug for the treatment of psoriasis. miRNA Recent studies have found that about 10 miRNAs are repressed and 40 miRNAs are overexpressed in psoriasis patients compared to normal controls, and almost all of these miRNAs are involved in the pathogenesis of psoriasis (Hawkes et al. 2016). Upregulation of miR-146a can mediate the expression of TNF, which may trigger initiation and progression of psoriasis. Repression of miR-125b can mediate the expression of FGFR2. MiR-21 is negatively correlated with T cells apoptosis and is overexpressed in psoriasis patients. MiR-31, which is regulated by TGF-1, is upregulated in keratinocytes of psoriasis patients. Collagen IV is regulated by miR-135b. Inhibition of miR-135b inhibits keratinocyte proliferation. In psoriasis patients, miR-424 is significantly downregulated, leading to excessive proliferation of keratinocytes by activating cyclin E1 and MEK1 (Tsuru et al. 2014). Some psoriasis patients have been treated with anti-TNFα. Recent studies have shown that levels of miRNAs involved in the regulation of inflammation are altered in the serum of patients with psoriasis. Upregulation of miR-210 has been observed in CD4+ T cells in psoriasis, and it can inhibit the expression of FOXP3 and facilitate the development of autoimmunity (Wu et al. 2018).

1.5.5.2

Systemic Sclerosis

Systemic sclerosis (SSc) is an autoimmune disorder of connective tissue, characterized by an accumulation of collagen and persistent thickening and stiffening of the skin, caused by impairment of small blood vessels and accumulation of collagen. DNA Methylation Studies have already shown that SSc is characterized by global DNA hypomethylation in CD4+ T cells and upregulated autoimmune-disease-associated genes, such as

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NLRP1. It has also been found that DNA methylation modifiers, including DNMTs and MBDs, play a role in SSc. Hypomethylation in the promoter regions of CD40L and CD70 in CD4+ T cells and upregulation of the genes have been observed in patients with SSc (Yalcinkaya et al. 2016; Hedrich and Rauen 2012). A murine model demonstrated that loss of methylation occurs at the promoter of CD40L, resulting in overexpression of the gene and fibrosis. In addition, abnormal DNA methylation and overexpressed CD40L appear only in female SSc patients, mainly because CD40L is located on the X chromosome. In contrast, DNA methylation levels of fibroblasts in patients with SSc are increased compared to normal controls, correlating with upregulation of the DNA methylation modifiers, DNMT1, MECP2, and MBD1 (Dees et al. 2014). Hypermethylation has been found to occur in the promoter of FLI1, which results in reduced synthesis of collagen. Downregulation of this gene by DMNT inhibitors can decrease the amount of fibrinogen in the fibroblasts of SSc patients. As in other diseases previously discussed, components of the Wnt pathway may be hypermethylated, leading to reduced expression of Wnt pathway antagonists SFRP1 and DKK1, thus triggering fibrosis. From a therapeutic standpoint, DNMT inhibitors may activate these genes and repair Wnt signaling, thus blocking fibrosis. Studies have also shown that the promoter of BMPR2 is hypermethylated and the gene is downregulated, contributing to the pathogenesis of pulmonary hypertension in SSc patients (Gilbane et al. 2015). Histone Modification HDAC inhibitors can induce acetylation and downregulate the expression of FN1 and COL1A1, both of which contribute to fibrosis. Besides inhibiting gene expression of collagen synthesis in SSc, HDAC inhibitors can also activate the expression of profibrotic genes, including CTCF and ICAM-1, which can impact the development of fibrosis in SSc (Pang and Zhuang 2010). The expression of p300, a histone acetyltransferase, is upregulated in fibroblasts of SSc patients, and it acts to increase fibrosis along with Egr1 and TGF-β in SSc. Studies have also demonstrated that inhibition of H3K27me3 can block collagen production and decrease fibrosis induced by TGF-β in SSc. Altered acetylation levels of H3 and H4 have been observed in B cells in patients with SSc. Acetylation levels of H4 are increased and there is a loss of methylation of H3K9. These alterations impact SUV39H2 and HDAC2, induce dermatologic fibrosis, and increase severity of disease (Wang et al. 2013). miRNA Upregulated miR-21 increases the expression of fibrosis-associated genes, including COL1A1 and FN1, by modulating the expression of SMAD7 in fibroblasts of SSc patients. Studies have also found that miR-21 is upregulated in other fibrotic diseases, including pulmonary fibrosis and dermatologic fibrosis. In contrast to miR-21, miR29 has a negative impact on fibrosis (Bagnato et al. 2017). Downregulation of miR-29 has been found in SSc and other diseases in which fibrosis is a feature. Downregulated miR-29 leads to a decrease in the expression of COL1A2 and COL3A1, leading to an increase in the level of ECM proteins and triggering the development of fibrosis in SSc.

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Decreased let-7a increases the level of collagen I in SSc, and a murine SSc model demonstrated that an increase in the expression of let-7a inhibits fibrosis. miR-196a functions as an inhibitor of collagen production under the regulation of TGF-β. Downregulation of miR-196a leads to excessive production of collagen and the development of fibrosis in SSc patients. The expression of miR-129-5p is mediated by IL-17A and downregulated by TGF-β signaling (Nakashima et al. 2012).

1.5.5.3

Melanoma

Melanoma results from aberrant proliferation and differentiation of melaninproducing cells called melanocytes and is one of the most malignant cancers with poor prognosis. The etiology of melanoma still remains unknown, but ultraviolet (UV) light exposure increases the risk of disease. DNA Methylation The DNA methylation pattern of melanoma is similar to other types of cancer, characterized by global hypomethylation and specific promoter hypermethylation, leading to tumor suppressor gene silencing and oncogene activation, resulting in tumorigenesis. One study found that melanoma patients can be classified into several groups based on different DNA methylation patterns, as in the case with colorectal cancers. Colorectal cancer can be classified into several groups based on CpG island methylator phenotype (CIMP), and the same process can be applied to melanoma (Tanemura et al. 2009). CIMP status is dependent upon mRNA transcription and protein translation. A recent study assigned mutations in IDH1 and ARID2 into high CIMP groups. Another study found that genetic mutations correlate with an altered epigenetic profile, leading to dysregulation of gene expression. Hypermethylation at the promoter of RASSF1A results in the deactivation of encoded genes, which occurs in about 60% of melanoma cases. But this is only found in advanced stages of melanoma, suggesting that methylated RASSF1A may be a good marker for monitoring the progression of melanoma. Loss of p16 resulting from methylated CDKN2A has been observed in melanoma, and this leads to melanocyte hyperproliferation (Li et al. 2019). DNA hydroxymethylation is another important mechanism which contributes to the pathogenesis of melanoma (Fig. 1.8). 5-hydroxymethylcytosine (5hmC) is produced through enzymatic action of TET family proteins. Melanoma has a low 5hmC level compared to normal controls, and the level is associated with tumor stage, suggesting a potential role as a biomarker for the prognosis of melanoma (Bonvin et al. 2019). Another study found that several TET genes as well as IDH2 are deactivated, contributing to the downregulation of 5hmc. A murine melanoma model showed that TET2 insertion can restore expression of 5hmc, indicating that it may be an attractive therapeutic target for the treatment of melanoma. Histone Modification Downregulation of H3K27ac and upregulation of H3K27me3 have been observed in melanoma, which leads to an increase in the expression of SOX10 (Cronin et al.

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Fig. 1.8 Global loss of 5hmc in melanoma can be a biomarker for the diagnosis of melanoma

2018). A SOX10 knockout model demonstrated a slower melanoma growth rate compared to wild-type controls. SAHA, an HDAC inhibitor, induced acetylation of H3 and H4 at CDKN2A, leading to a depression of p14ARF. A murine melanoma model showed that in advanced stages of melanoma, mH2A is downregulated due to DNA hypermethylation and reduced expression of mH2A2, leading to an increase in migratory capacity. Abnormal expression of E2F and BRD2, which binds to H2A.Z.2, is associated with increased malignant potential of melanoma. Knockdown of this altered histone variant downregulates the expression of these encoded genes, including E2F and BRD2. HDAC6 regulates the expression of STAT3, which is responsible for the expression of PD-L1, suggesting that combination treatment of HDAC inhibitors and immunotherapy may be a treatment option (Lombard et al. 2019). Studies have found that Temozolomide, a chemotherapy drug commonly used in melanoma by targeting MGMT, often encounters drug resistance in melanoma patients. A study using HDAC inhibitors to treat chemo-resistance melanoma patients found that the acetylation level was upregulated at the promoter region of MGMT, although the expression level of this gene was not changed (Chen et al. 2016). miRNA miRNAs can function as either tumor suppressive or onco-miRNAs to regulate the development of melanoma. MiR-31, functioning as a tumor suppressor miRNA, represses tumor growth by inhibiting EZH2 expression. Downregulation of miR-31 has been observed in melanoma, leading to overexpression of EZH2 and contributing to hyperproliferation of the tumor (Zheng et al. 2018b). Previous studies identified that miR17 was overexpressed and miR-25 is underexpressed in metastatic samples of melanoma, and thus it can potentially be developed as a biomarker for melanoma.

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Dysregulated miRNAs, including miR-26a, miR-221, and let-7a, are involved in regulating cell apoptosis, cell growth, and tumor metastasis, all of which contribute to the initiation and progression of melanoma (Romano et al. 2017).

1.5.6 Role of Epigenetics in Cardiovascular Diseases Cardiovascular diseases (CVD) that may be under the influence of epigenetic regulation include atherosclerosis, angina, myocardial infarction, cardiomyopathy, heart arrhythmia, and congenital heart disease. CVD is one of the leading causes of death worldwide.

1.5.6.1

Atherosclerosis

Atherosclerosis is characterized by irreversible inflammation created by the persistent accumulation of plaques. The blockage of vessels is associated with plaque-induced inflammation, ultimately leading to hypoxia and ischemia. Reprogrammed epigenetic profiles may play a role in the pathogenesis of atherosclerosis. DNA Methylation Studies have found that the DNA methylation pattern in atherosclerosis is different from that of cancer and autoimmune disease and is characterized by global DNA hypermethylation. Genome-wide studies have found that DNA methylation is positively correlated with the severity and disease grade of atherosclerosis, suggesting that the global DNA methylation pattern may be able to be used to monitor the progression of disease. Studies have also shown that the DNA methylation in cardiovascular diseases is modulated by inflammation-associated genes, such as TLR2. Epithelial cells treated with low-density lipoprotein (LDL) showed overexpressed DNMT1 and hypermethylation at the promoter of KLF2, which is an antiinflammatory gene. Suppression of KLF2 induces the development of inflammation (Tabaei and Tabaee 2019). DNMT inhibitors induce hypomethylation and have a positive effect on KLF2. The promoter of KLF4 can be methylated by overexpressed DNMT3A, leading to downregulation of KLF4 and vascular inflammation. In addition, the DNA methylation profile of coronary artery disease is characterized by global DNA hypermethylation in PBMCs, triggering an inflammatory process. A murine atherosclerosis model shows that 5-aza alleviates atherosclerosis (Cao et al. 2014). Histone Modification Using immunohistochemistry, it was demonstrated that the histone repressive marker H3K27me3 was downregulated in vascular smooth muscle cells (Wierda et al. 2015). The expression of JMJD3 was increased, and along with a decrease in the expression of H3K27me3 led to de-repressed target genes.

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An atherosclerosis model showed that GSK-J4, an inhibitor of JMJD3, can downregulate inflammation-associated cytokines and chemokines, including TNF-α. HDAC5 and HDAC7 have a negative effect on the expression of KLF4 in epithelial cells, and the upregulation of HDACs can suppress KLF4 expression and contribute to the pathogenesis of atherosclerosis (Zheng et al. 2015). Another study found that HDAC3 knockout leads to upregulation of IL-4-associated genes, leading to the activation of anti-inflammatory effects, reversing atherosclerosis. A murine model demonstrated that lipopolysaccharides failed to induce inflammation and release cytokines after HDAC9 knockout (Azghandi et al. 2015). Another study revealed that upregulated HDAC can be stimulated chemically in small muscle cells and that epigenetic inhibition can disrupt abnormal cell proliferation and apoptosis, leading to inhibition of the development of atherosclerosis. miRNA Studies have showed that miRNAs play a crucial role in the pathogenesis of atherosclerosis. Recent studies have shown that miRNAs can regulate the accumulation and function of HDL and LDL, and the levels of lipoprotein. miR-128-1 and miR301b have been found to have an impact on the regulation of lipoprotein-associated genes, including ABCA1 and LDLR (Laffont and Rayner 2017). Dysregulation of miR-148a plays a role in lipoprotein metabolism by targeting these genes. The use of an miR-148a inhibitor can potentially upregulate the expression of ABCA1 and LDLR, leading to upregulated HDL-C and downregulated LDL-C. An abnormal level of cholesterol is a risk factor for atherosclerosis. miR-223 plays a role in cholesterol synthesis by activating ABCA1. A murine miR-223 knockout model showed upregulated HDL-C and cholesterol. miR-33 can also regulate the expression of ABCG1 and ABCA1 by targeting SREBP1, which plays a role in cholesterol metabolism. Altered miR-33 can affect cholesterol levels, contributing to the pathogenesis of atherosclerosis (Ouimet et al. 2017). In addition, let-7 g can deactivate inflammation-associated genes, such as TGF-β and LOX-1 by inhibiting SIRT1 and TGF-β. A murine model showed that downregulated let-7 g levels can increase expression of PAI-1, leading to endothelial inflammation (Wang et al. 2017).

1.5.6.2

Hypertension

Hypertension is characterized by persistent increased blood pressure. Hypertension is one of the leading public health issues worldwide and is a main risk factor for stroke, hypertensive nephropathy, and hypertensive ophthalmopathy. The mechanism of hypertension still remains unknown, but the pathogenesis is believed to be multifactorial. Epigenetics plays an important role in the pathogenesis of hypertension. DNA Methylation A genome-wide study was conducted on about 10,000 hypertensive individuals and normal controls identified dozens of CpGs sites that are involved in the pathogenesis

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of hypertension (Han et al. 2016). Loss of methylation at the promoter of TLR4 and Alu results in upregulation of encoded genes, contributing to the pathogenesis of hypertension. Abnormal DNA methylation of 11βHSD2 can dysregulate the expression of its encoded genes, leading to disruption in the regulation of mineralocorticoids (Bailey 2017). A murine hypertension model revealed that loss of methylation occurs in the promoters of AT1aR and NKCC1, which are regulators of the Na+ channel, leading to increased blood pressures. The DNA methylation pattern is globally downregulated and blood pressure is decreased by ACE inhibitors. Hypoxia can lead to a decrease in the DNA methylation levels of AGT and ACE1 in endothelial cells, resulting in increased blood pressure and decreased heart rate. Histone Modification Studies have found that upregulation of HDAC can decrease H3 and H4 activity and block the WNK4 pathway, leading to downregulation of WNK4 (Lee et al. 2018). Downregulation of WNK4 may play a role in the development of hypertension. A murine hypertension model revealed that exposure to high salt can decrease expression of LSD-1, resulting in loss of methylation of both H3K4 and H3K9, dysregulation of eNOS, and the initiation and progression of hypertension. Another murine hypertension model showed that Af17 knockout can upregulate the level of H3K79me2, leading to a decrease in sodium levels and resolution of hypertension. Yet another animal study revealed that upregulated β2-adrenergic receptors can deactivate WNK4, decrease the expression of HDAC8, and upregulate the level of histone acetylation, contributing to the pathogenesis of hypertension (Li et al. 2017). miRNA miR-126 is a key player in the development of endothelial cells. Dysregulated miR126 can disrupt vascular integrity and affect vascular function. Deleted miR-126 is associated with damage to blood vessel structure and function, which contributes to the pathogenesis of hypertension (Yuan et al. 2019). Abnormal expression of miR-217 can target eNOS and FOXO1 of endothelial cells. Upregulated miR-143 has been observed in hypertensive patients, and inhibition of miR-143 can decrease blood pressure. A murine model found that decreased miR-181 is associated with hypertension (Han et al. 2018). Studies have shown that upregulated miR-637, miR122, and let-7 correlate with hypertension. miR-27a and miR-150 are decreased and miR-92 and miR130 are increased in hypertensive patients compared with healthy controls (Nemecz et al. 2016).

1.5.6.3

Heart Failure

Heart failure (HF), or congestive heart failure (CHF), is one of the leading causes of death worldwide. Currently available drugs are limited to slowing the progression of the disease. The mechanism of HF remains unclear. Altered epigenetic profiles may play a role in the pathogenesis of HF.

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DNA Methylation A genome-wide study revealed that loss of methylation at the promoter region can upregulate encoded genes, such as GLUT1, in HF (Li et al. 2017). This study also identified several genes associated with angiogenesis, including PECAM-1 and ARHGAP24, which are modulated by DNA methylation status. Studies have also found that altered DNA methylation patterns have an impact on the expression of ADORA2A. Upregulated DNMT1 increases methylation levels of SERCA2a by targeting TNF-α signaling pathways. A study on murine HF models demonstrated that DNMT3 knockout mice have impaired cardiac function. A recent study found that DNMT3B is the main DNMT in cardiomyocytes, and the disease develops rapidly in DNMT3B knockout models, suggesting it plays a crucial role in the initiation and progression of HF (Nuhrenberg et al. 2015). Histone Modification Studies have found that HDACs are key players in the development of HF (Evans and Ferguson 2018). HDAC5 and HDAC9 regulate cell proliferation in HF models. Deletion of these HDACs can accelerate the growth rate of cardiomyocytes by targeting and regulating the expression of Mef2c, resulting in the hypertrophy seen in HF. Furthermore, deleted HDAC4 murine models show cardiac muscle cell hyperproliferation, leading to the cardiac hypertrophy and the development of HF. In a HDAC2 knockout model, hypertrophy of cardiac muscle is ameliorated, while reintroduction of HDAC2 can accelerate cardiac muscle hypertrophy and contribute to the development of HF (Yoon et al. 2018). Emerging studies show that SIRT1 and SIRT3 have a positive effect on HF. P300, a HAT, and associated CBP genes function as a hypertrophic stimulator in the development of HF. Pharmaceutically inhibited p300 and CBP attenuate the progression of cardiac hypertrophy, and reintroduction of p300 and CBP stimulates the hypertrophy. Altered histone methylation of H3K4me3 and H3K9me3 has been observed in patient samples and murine models of HF. Upregulated JMJD2A can reduce the expression of H3K9me3 and H3K36me3 by targeting FHL1, leading to the proliferation of cardiomyocytes. JMJD2A deletion decreases the level of hypertrophy, suggesting that JMJD2A plays a key role in the pathogenesis of HF (Zhang et al. 2011). miRNA Studies have found that decreased miR-1 is associated with cardiac hypertrophy, and reintroduction of miR-1 can alleviate the development of cardiac muscle hypertrophy in a murine HF model (Al-Hayali et al. 2019). Studies have demonstrated that miR-1 functions by targeting several genes, including IGF-1, GATA4, and NCX1. Several muscle-associated miRNAs, including miR-133 and miR-378, are downregulated in HF patient samples. Furthermore, miR-23, miR195, and miR199 are upregulated in HF patients compared to normal controls (Vegter et al. 2016). Studies have shown that upregulated miR-195 and miR-499 can downregulate the expression of MO25 and HMGA. The latter two facilitate cell apoptosis, thus inhibition of these will result in

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cardiac hypertrophy in HF. Murine HF models have shown that overexpressed miR499 activates the WNT pathway, resulting in cardiac hypertrophy. Murine studies have also shown that upregulated miR-199b targets Dyrk1a and contributes to the pathogenesis of HF (da Costa Martins et al. 2010).

1.5.7 The Role of Epigenetics in Gastrointestinal Tract Diseases 1.5.7.1

Gastric Cancer

Gastric cancer is one of the most aggressive cancers, with poor prognosis, and is one of the leading causes of death worldwide. Studies have found that both genetic background and environmental factors play an important role in the development of gastric cancer. Epigenetics is the bridge between genetics and the environment that can also contribute to the pathogenesis of gastric cancer. Emerging evidence demonstrates that altered epigenetic profiles can modulate gene silencing or activation that leads to the development and progression of gastric cancer. DNA Methylation Altered DNA methylation patterns have been identified in gastric cancer. Gastric cancer patients demonstrate hypermethylation in promoter regions and global hypomethylation of repetitive elements. Abnormal DNA methylation patterns occur at both advanced stages and early stages of gastric cancer. H. pylori (HP) is an important factor in the pathogenesis of gastric cancer, and the interaction between HP infection and DNA methylation is a hotspot in gastric cancer research (Maeda et al. 2017). Studies have found that high DNA methylation levels correlate with HP infection in gastric cancer, and eradication of HP infections is associated with a decrease in DNA methylation in gastric cancer (Maekita et al. 2006; Miyazaki et al. 2007). Genome-wide studies have revealed that the oncogenes HAND1 and FLNC are activated in gastric cancer. Tumor suppressor genes, including p16, COX- 2, and MGMT, have been found to be downregulated by DNA hypermethylation at their promoter regions in gastric cancer. These genes are associated with cell proliferation, DNA damage repair, and apoptosis. Studies have found that altered DNA methylation patterns at the promoter of these genes dysregulate the encoded genes and contribute to the pathogenesis of gastric cancer. For example, hypermethylated homeobox D10, also known as HoxD10, which plays a role in cell apoptosis, has been observed in gastric cancer, leading to downregulation of the gene and aberrant apoptosis and gastric cellular hyperproliferation in gastric cancer. Studies have also found that 5mc and 5hmc are closely associated with gene expression, and that 5mc is downregulated in gastric cancer patients compared to normal controls. Decreased 5mc is correlated with dismal prognosis in gastric cancer (Necula et al. 2015).

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Histone Modification Early studies showed that an increase in H3K9me3 was associated with an aggressive course and dismal prognosis in gastric cancer. It has also been found that gastric cancer cells are sensitive to EZH2 inhibitors in vitro. Further analysis revealed there is abnormal accumulation of H3K27me3 and that PRC2 is a target of the epidrug Tazemetostat, suggesting that it may be a potential therapeutic target for the treatment of gastric cancer (Choi et al. 2014). Recent studies found that both DNA methylation and histone modification aberrations contribute to the pathogenesis of gastric cancer. It has been shown that EZH2 interacts with DNMTs to increase DNA methylation levels in a series of genes, such as MT1F, BHMT, and ACSL1. Furthermore, H3K27me3 regions are frequently hypermethylated in AGS127, a gastric cancer cell line. The co-existence of hypermethylation and histone modification, including downregulated H3K9ac and upregulated H3K9me3, has been observed at the promoter of MLH1, leading to downregulation of the encoded gene. After treatment with a DNMT inhibitor, the expression of MLH1 is restored. This was not true with the HDAC inhibitor, but combination treatment has a synergistic effect on gene expression, suggesting that DNA methylation is the foremost player in deactivating this gene, and histone modification may also play an important role in this pathway (Guo and Yan 2015). miRNA miRNAs can be categorized into tumor suppressive and oncogenic miRNAs, both of which are involved in the regulation of gene expression. Studies have found that overexpressed miR-106b can target and decrease the expression of CDKN1B and BCL2L11, which are involved in cell apoptosis, leading to cancer cell hyperproliferation in gastric cancer (Zhu et al. 2019). A murine gastric cancer model showed that miR-16, miR-126, and miR-106a are associated with drug resistance. Genome-wide studies identified several miRNAs, including miR-99a, miR-202, and miR-133a, that are upregulated in gastric cancer. Decreased miR-let7 may be a clinical biomarker for the prognosis of gastric cancer. Another study revealed that dysregulated miRlet7, miR-21, and miR-99a can target PKM2 and PTEN and play an important role in the pathogenesis of gastric cancer (Wang et al. 2015). Furthermore, miRNAs can interact with DNA methylation, contributing to disease initiation and progression. Dysregulated miR-331-3p can target HER2, leading to hyperproliferation of cancer cells in gastric cancer, suggesting it plays a key role in the pathogenesis of gastric cancer.

1.5.7.2

Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is a systemic and chronic autoimmune disease. The major inflammatory bowel diseases include Crohn’s disease (CD) and ulcerative colitis (UC). IBD may affect the entire digestive tract, but most commonly involves the small intestine and the colon. IBD adversely impacts quality of life and is often

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life-threatening. Genetic variation and environmental factors play significant roles in IBD. Altered epigenetic profiles bridge the gap between genomic and environment factors. DNA Methylation Studies have found that hypermethylation occurs in the promoter of TRAF6, causing a decrease in gene expression in PBMCs in patients with CD and UC. Genome-wide studies showed that the promoters of AATK, BGN, and SERPINA5 are hypermethylated in inflamed mucosa samples of CD compared to normal controls, and the expression of encoded genes is deactivated (McDermott et al. 2016). Altered DNA methylation patterns occurring in the promoter of DOK2 have been observed, which can regulate cell growth. Thus, dysregulated expression of this gene results in abnormal cell proliferation. The promoter of CDH1 is hypermethylated and the gene is downregulated in inflamed tissue samples of CD and UC. On the other hand, normal areas demonstrate no such changes, suggesting that this dysregulation contributes to the pathogenesis of CD and UC. A recent study revealed that FANCC, THRAP2, and GBGT1 are methylated only in inflamed mucosa of CD, but not in UC, and normal areas show no significant change in methylation of these genes, indicating that methylation may play a key role in the initiation and progression of CD (Cooke et al. 2012). Histone Modification Studies have shown that the interaction between histone modification and gut microbiome is critical for the pathogenesis of IBD. The gut microbiome can produce a small molecule, n-butyrate, which functions as a HDAC inhibitor (Chang et al. 2014). A recent study demonstrated that bacteria in the gut can metabolize propionate, and the resulting metabolite plays a role in regulating gene expression of PPARγ and Gpr43. The levels of HDAC are also downregulated, suggesting that HDAC inhibitors can be a marker of inflammation in CD and UC (Felice et al. 2015). Helminths have been found to negatively regulate cell differentiation by targeting the HDAC level. miRNA Several miRNAs, including miR-21, miR-16, and miR-594, were found to be overexpressed in inflamed mucosal samples from CD patients compared to samples from normal areas in CD patients and in healthy controls, suggesting that these miRNAs participate in the pathogenesis of CD (Soroosh et al. 2018). Genome-wide studies have shown that miR-106a, miR23b, and miR-191 are upregulated, while miR-629 and miR-19b are downregulated in both CD and UC (Ni et al. 2018). Another study compared active CD, inactive CD, and normal controls and found that miR-126, miR-9, and miR-130a, are overexpressed and were only found in active patients, but not in inactive patients and normal controls, suggesting that these miRNAs may be a good marker for the treatment and that they may contribute to the initiation and progression of CD. In both human and murine models, it has been shown that expression of miR-141 is repressed in patients with CD. The study found that miR141 can target CXCL12β to modulate migration of leukocytes in the inflamed area,

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and that dysregulated miR-141 plays an important role in the pathogenesis of CD. Various miRNAs, including let-7b, miR-30e, miR-16, and miR-192, are upregulated in PBMCs from CD patients, indicating that they may contribute to the pathogenesis of IBD (Moein et al. 2019).

1.5.7.3

Hepatic Cirrhosis

Hepatic cirrhosis is a degenerative disorder characterized by normal liver tissue being replaced by fibrosis tissue. Hepatitis B and C and alcohol abuse are the most common causes of cirrhosis. In cirrhosis, hepatic stellate cell (HSC) is converted into myofibroblasts and accelerates fibrosis, but the mechanism of cirrhosis is still incompletely elucidated. Epigenetics plays a role in the pathogenesis of cirrhosis (Fig. 1.9). DNA Methylation Genome-wide studies in patients with cirrhosis have shown that the DNA methylation of 10% of all genes is altered, which results in either gene activation or deactivation (Urabe et al. 2013). MeCP2, a DNA methylation modifier, binds to the promoter

Fig. 1.9 Epigenetic modifications take part in the gene expression in hepatic stellate cells

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of PPARγ , and then induces gene repression of H3K9me3, resulting in silencing of the expression of PPARγ , activating HSC and triggering fibrosis (Urabe et al. 2013). A murine study showed that the expression of αSMA, a marker of fibrosis, is decreased in HSCs of MeCP2 knockout mice. Furthermore, MeCP2 activates the expression of fibrosis-associated genes by targeting the histone modifier, ASH1. This leads to an increase in expression of αSMA, TIMP1, and collagen I, contributing to the pathogenesis of cirrhosis. Another study showed that the DNA methylation pattern at the promoter of PPP1R18 and HoxA2 is associated with the severity of disease. Human cirrhosis samples and murine models demonstrated upregulation of DNMT3A and DNMT3B and downregulation of TET, leading to alteration of the DNA methylome profile in HSCs. Knockdown of these DNA modifiers leads to inhibition of fibrosis, suggesting that these DNA modifiers play a key role in the initiation and progression of cirrhosis (Oh et al. 2007). Histone Modification Upregulation of HDAC has been observed in cirrhosis samples and animal models, and pharmaceutical inhibition of HDAC can decrease expression of HDAC and attenuate hepatic stellate cell proliferation (Khan et al. 2016). Studies have also found that HDAC inhibitors can repress the expression of fibrotic genes and inhibit cell growth, leading to attenuation of fibrosis. Murine studies have revealed that alcohol exposure can increase levels of H3K9ac and MLL1, resulting in extensive activation of fibrosisassociated genes. Furthermore, murine studies have shown that JMJD1A knockdown mice overexpress H3K9me2 at the promoter of PPARγ , increasing the expression of profibrogenic genes and accelerating fibrosis. Recent studies have demonstrated that HMT inhibitors can also attenuate fibrosis (Jiang et al. 2015). miRNA Numerous miRNAs have been studied in cirrhosis (Starlinger et al. 2019). The most studied miRNA in cirrhosis is the miR-29 family. Studies have shown that the expression of miR-29 is downregulated by NFκB and TGFβ in activated HSC. Human cirrhosis samples and murine models have demonstrated that the expression of miR-29 is decreased, and that it is regulated by TGF-β. An increase in the expression of miR-29 decreases production of collagen I. Collagen I contributes to the pathogenesis of cirrhosis. Upregulated miR-29a reduces cell growth and fibrosis by targeting fibrosis-associated genes in HSC. Furthermore, studies revealed that miR-29a can inhibit the expression of DNMTs, including DNMT3B and DNMT1, resulting in demethylation of targeted genes and downregulation of fibrosis-associated genes in HSC. A recent study demonstrated that miR-29 can regulate IGF-1 and PDGF-C, leading to inhibition of mitosis and migration capacity (Deng et al. 2017).

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1.6 Discussion Epigenetics is a rapidly developing field, although the clinical application of epigenetics is still in its early stage. However, there are several epidrugs and biomarkers that have been approved by FDA and are already widely used in clinical practice. Oncology and autoimmune disorders are the main fields targeted by epigenetic studies, although epigenetic aberrations can affect any disease or organ system. Novel epigenetic-based technologies, such as the infinium humanmethylation450K (HM450K), whole genome bisulfite sequencing (WGBS), methylated DNA immunoprecipitation (MeDIP), and chromatin immunoprecipitation sequencing (ChIP-Seq), have helped in the development of this field. Along with the explosion of epigenetic studies, large amounts of complicated and cumbersome data have been generated. Luckily, the ability to analyze such “big data” is now available as a result of rapid technological advances in computing power. Entire bioinformatics departments have been established in academic institutions to tackle these issues. Furthermore, a number of databases, including the Cancer Genome Atlas (TCGA) and the Encyclopedia of DNA Elements (ENCODE), are continually adding population-based data to help better understand disease pathogenesis. All of these resources have contributed to the development of epigenetics. Numerous epigenetic challenges remain unmet. Multiple studies have demonstrated that an altered epigenetic profile can disrupt biological pathways and play a key role in the pathogenesis of human diseases. But translating this knowledge to clinical applications remains a significant problem. Biomarkers are being identified, but they are often of low sensitivity and specificity, rendering them poor surrogates to track disease status. Furthermore, variable and non-standardized patient samples pose problems due to the sample heterogeneity of epigenetic modifications (Morente et al. 2008). Clearly, further studies are required to answer these questions regarding the role of the epigenetic landscape on human health. The role of epigenetics in cell destiny, including differentiation, proliferation, apoptosis, and metabolism is still incompletely understood. Detailed analysis of DNA methylation, histone modification, and miRNAs in healthy and diseased human subjects is necessary for better understanding of the mechanism of diseases. Clarifying the interplay among genetic variation, environmental factors, and epigenetic aberration is critical to understanding the initiation and progression of human diseases.

1.7 Conclusion Genetic variations and environmental factors only contribute a portion of the risk for developing disease. Epigenetic modification can be influenced by environmental factors and provides hereditable but reversible changes in gene expression in the absence of DNA sequence changes. Great efforts have been focused on the epigenetic

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study of human diseases in the past decades, and this has resulted in the development of new innovative strategies for the diagnosis, monitoring, prognostication, and management of diseases. Extensive studies on DNA methylation, histone modification, and miRNAs have contributed to a better understanding of the pathogenesis of human diseases. It has been found that an altered epigenetic profile that is associated with the development of a disease state can be taken advantage of in a clinical setting, as these changes can be used as biomarkers in some cases. Epigenetic changes may also be reversed pharmaceutically, and hence the development of agents that affect DNA methylation or histone modifications, as well as miRNAs that can change gene expression. Discoveries that address epigenetic disruption put us on the cusp of fulfilling the promise of personalized medicine and tailored therapy that has been a holy grail for clinical practitioners for many years now. From the first epidrug for the treatment of hematological malignancies approved by the FDA, new emerging epigenetic medications and biomarkers are continually being tested in clinical trials. Other technological advances such as high throughput and highly sensitive means of analyzing epigenetic changes, optimized databases, and the computing ability to analyze large datasets are invaluable tools to achieving these goals.

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Chapter 2

The Development of Epigenetics in the Study of Disease Pathogenesis Matlock A. Jeffries

Abstract The study of epigenetics has its roots in the study of organism change over time and response to environmental change, although over the past several decades the definition has been formalized to include heritable alterations in gene expression that are not a result of alterations in underlying DNA sequence. In this chapter, we discuss first the history and milestones in the 100+ years of epigenetic study, including early discoveries of DNA methylation, histone posttranslational modification, and noncoding RNA. We then discuss how epigenetics has changed the way that we think of both health and disease, offering as examples studies examining the epigenetic contributions to aging, including the recent development of an epigenetic “clock”, and explore how antiaging therapies may work through epigenetic modifications. We then discuss a nonpathogenic role for epigenetics in the clinic: epigenetic biomarkers. We conclude by offering two examples of modern state-of-the-art integrated multiomics studies of epigenetics in disease pathogenesis, one which sought to capture shared mechanisms among multiple diseases, and another which used epigenetic big data to better understand the pathogenesis of a single tissue from one disease. Keywords Epigenetics · History of epigenetics · Integrative analysis

2.1 The History and Discovery of the Basic Mechanics of Epigenetics 2.1.1 Experimental Observations: Setting the Stage for the Discovery of Epigenetic Mechanisms To set the stage for our later discussion of the epigenetic underpinnings of disease pathogenesis, we will first review the history of the discovery of epigenetic control M. A. Jeffries (B) University of Oklahoma Health Sciences Center, Oklahoma Medical Research Foundation, Oklahoma City, OK 73118, USA e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 C. Chang and Q. Lu (eds.), Epigenetics in Allergy and Autoimmunity, Advances in Experimental Medicine and Biology 1253, https://doi.org/10.1007/978-981-15-3449-2_2

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mechanisms and the field of epigenetics more generally. Epigenetics in its contemporary form, the focus of this book, has only emerged since the 1990s; in fact, the consensus modern definition, “stably heritable phenotype resulting from changes in a chromosome without alterations in the DNA sequence” was formulated at a Cold Spring Harbor meeting in 2008 (Berger et al. 2009). Prior to this, the term “epigenetic” was used with widely disparate meanings. The word itself has been in English language use since the seventeenth century, having been used by Harvey in Exercitationes (1651) and Anatomical Exercitations (1653), with the definition “the additament of parts budding one out of another.” The subsequent history of epigenetics as we presently understand it is inevitably linked with the history of genetics, itself emerging out of historical analyses of evolution, development, and inheritance. No discussion of the history of epigenetics is complete without reference to the theories of the French zoologist Jean-Baptiste Lamarck (Fig. 2.1). At half-past noon on the May 17, 1802, he gave the first lecture of his course on invertebrate zoology

Fig. 2.1 Jean-Baptiste Lamarck. Credit Wellcome Library, London, Wellcome Images

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at the Museum of Natural History in Paris, where he set forth an unprecedented (and later debunked) theory explaining the incremental development and differentiation of all life forms on earth. His theories, now known simply as “Lamarckian evolution”, were based on two major themes. First, he posited that the environment gives rise to changes in animals; he offered as examples the presence of teeth in mammals, the absence of teeth in birds, and the loss of sight in moles. The second principle argued that life was structured in an orderly manner, and that different parts of all bodies made possible the organic movement of animals (Eb 1895). Lamarck’s ideas on evolution are held as grand examples of theories of inheritance of acquired characteristics, also known as “soft inheritance”, later supplanted by the infamous descriptions of inheritance and natural selection put forth by Gregor Mendel and Charles Darwin, respectively, in the mid-1800s. Although discredited as a viable theory of evolution throughout the twentieth century, Lamarck’s underlying ideas regarding environmental contributions to phenotypic characteristics (and the heritability thereof) have seen a resurgence in modern times with recent descriptions of transgenerational epigenetic inheritance. The first concepts we would recognize as related to modern epigenetics were formulated in the late nineteenth century with Fleming’s discovery of chromosomes and their behavior during animal cell division in 1879. Subsequent work by a variety of investigators cemented the notion of chromosomes as the quintessential substrate of inherited information. Most convincingly, in 1911 Thomas Hunt Morgan demonstrated sex–chromosome genetic linkage of several Drosophila genes (Morgan 1911), which was quickly followed by the first maps of individual genes arranged in a linear fashion occupying specific locations on each chromosome (Sturtevant 1913). Questions remained, however, regarding the ways in which this “hard” genetic information was used to direct the developmental programs which lead to cellular differentiation and the diversity of phenotypes seen in multicellular life forms. It quickly became apparent that chromosomal nucleic acid codes alone were inadequate to carry all developmental information, since similar amounts and organization of this material was present in widely disparate cell types. As an example, Hermann Joseph Muller in 1930 described a class of Drosophila mutations which involved the displacement of large portions of genetic material from its rightful place to another chromosome (a phenomenon we would later understand as balanced translocations) (Muller 1930) resulting in unexpected phenotypic variations; particularly, the observation of mottled eyes. He initially attributed this to “genetic diversity of the different eye-forming cells,” but later research including Hannah et al. in the 1950s went on to demonstrate that this variegation arose when rearrangements inserted particular genes into regions of the chromosome with variable staining density. These regions would come to be known as heterochromatin, which we now understand to be differentiated from evenly staining chromosomal regions (euchromatin) by the density of DNA-packaging elements, directed by epigenetic modification (Hannah 1951). It was about this time (1939) when Conrad Waddington, the Buchanan Professor of Genetics at Edinburgh University, altered the Greek word epigenesis, defined as a theory of development in which the early embryo

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existed in an undifferentiated state, to epigenetics, which he defined as the implementation of cellular genetic programming for development (Waddington 1939). This view was reflected in his later book The Epigenetics of Birds, which provides an account of the embryological development of chicks (Waddington 1952). He is also credited with the term epigenotype, which he defined as “the total developmental system consisting of interrelated developmental pathways through which the adult form of an organism is realized” (Waddington 1939). Although admittedly broad, this definition strikes a familiar chord when applied to our modern understanding of epigenetics, where, at least at a cellular level, epigenetic controls may indeed be well defined as the set of interrelated transcriptional control programs which dictate and ensure the proper terminal differentiation of cells in a particular tissue. Simultaneous to and along the same lines as Waddington, seminal works were published establishing and refining the ideas behind phenotypic divergence during organism development at a cellular level. It became evident, for example, that phenotypically distinguishing features, once established, were clonally inherited to daughter cells. The mechanisms underlying these observations were unclear. Initially, it was proposed that these phenotypes were maintained by the presence or accumulation of particular biochemical reactions, suggested by the physicist Max Delbruck in 1949. In this model, self-stabilizing stimulatory and inhibitory mechanisms could theoretically lead to substantial phenotypic divergence, which could be passed on from parent to daughter cell. This theory ran into a problem, however, with the discovery that protein-free DNA could carry this information, first by Avery et al. in 1944 (the “Transforming Principle”) (Avery et al. 1944), later by Hershey and Chase in 1952 (Hershey and Chase 1952), and further reinforced with the infamous description of the structure of DNA by Crick at Cold Spring Harbor in 1953 (Watson and Crick 1953). At the same time, a pivotal study in northern leopard frogs by Robert Briggs and Thomas King was published (Briggs and King 1952) in which they demonstrated that a nuclear transplant from a frog blastula into an enucleated frog egg cell results in the normal development of an embryo, which argued that the “essential material” for complex organism development was indeed contained in the nucleus. Although discoveries since that time have cemented the concept of a fully differentiated cell having the same genetic makeup as an embryonic cell, this was not self-evident until as late as 1970. It was in this year that a pivotal study done by Laskey and Gurdon demonstrated the transfer of nuclear material from several adult somatic Xenopus frog cell sources (around 1–2% of transplanted nuclei, likely representing endogenous tissue pluripotent cells) into enucleated eggs resulted in embryos that developed into feeding larval stages (Laskey and Gurdon 1970). Other work soon revealed that cellular fates and phenotypic characteristics were heritable throughout cellular differentiation. For example, Ernst Hardon in 1965 showed that imaginal disc cells from Drosophila (regions of embryonic tissue present in fly larvae that subsequently develop into well-defined adult structures; i.e., two per wing, etc.), were still able to develop into their requisite structures on transplantation into fly larvae, even after being passaged through multiple generations of adult flies (Hadorn 1965).

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2.1.2 Getting to the Substance of the Matter: Discoveries of Physical Mechanisms of Epigenetic Control Building on prior observations, a number of scientists made key discoveries in the mid-twentieth century that would help explain how these cellularly heritable gene expression patterns were made possible. First were investigations into the mechanisms underlying X-chromosome inactivation, the process by which one of two X chromosomes in females is randomly selected to more or less fully transcriptionally “shut down”. Ohno demonstrated in 1959 that the “sex chromatin”, a female-specific chromosome first discovered by Barr and Bertram (1949), and still commonly bearing the eponymous title Barr Body, was, in fact, an X chromosome which had been densely packaged (Ohno et al. 1959). Lyon and colleagues in 1961 went on to demonstrate that the selection of X chromosome for condensation into a Barr Body from the paternal or maternal genetic material was a random process, providing further evidence that the mechanism of inactivation of genetic material was the most important component, not any preexisting underlying difference in genetic code (Lyon 1961). DNA-binding proteins, histones chief among them, had long been recognized as associated with nucleic acids, having first been described by Kossel (1884), which, incidentally, earned him the 1910 Nobel Prize in Physiology or Medicine. The husband-and-wife research team Steadman and Steadman in 1950 described variations in histone proteins isolated from different tissues, initially incorrectly ascribing these differences to variation in their constituent amino acids, but nonetheless correctly surmising the importance of what would later be defined as histone posttranslational modifications in contributing to the regulation of gene transcription (Stedman and Stedman 1950). In their letter to Nature in 1950, they stated: It has always been a puzzle to us, how the physiological functions of the cell nuclei in the same organism can differ from one cell-type to another when they all contain identical chromosomes and hence identical genes. …The demonstration…that some of the basic proteins present in cell nuclei are certainly cell-specific leads to the hypothesis that one of their physiological functions is to act as gene suppressors. (Steadman and Steadman 1950)

Soon though, the field of gene transcription shifted toward cis-acting regulatory elements and transcription factors (see below) It was thereafter generally assumed that histones were passively acting packaging proteins that served only to suppress gene transcription, even though evidence existed that extensive genomic regions with an open chromatin conformation did not, in fact, exist (Clark and Felsenfeld 1971). Further disagreement came with the description of posttranslational modifications of histone proteins were in 1964 by Mirsky and Allfrey. Importantly, they demonstrated that acetylated histones were associated with more active gene transcription than their non-acetylated counterparts (Allfrey et al. 1964), suggesting that certain histones were required for gene activation, rather than a straightforward removal of histone proteins. Several additional posttranslational modifications of proteins were discovered in the ensuing years, including methylation and phosphorylation, although their associated cellular functions remained elusive. It would not be until the

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mid-1990 s that the binding of transcriptional regulators to post-translationally modified histone proteins would elevate their status to bona fide epigenetic modifications (Hecht et al. 1995). Among the seminal works at this time, Taunton and colleagues in 1996 demonstrated that a mammalian histone deacetylase was closely related to a protein previously described as a transcriptional repressor in yeast (Taunton et al. 1996). Furthermore, Brownell et al. in 1996 showed that a histone acetyltransferase from the ciliate protozoan Tetrahymena was homologous to the yeast regulatory protein Gcn5 (Brownell et al. 1996), proving definitively that histone post-translational modification enzymatic activity was correlated with gene transcription regulation. The regulatory potential of modifications of the DNA molecule itself was put forth by Holliday and Pugh (1975) and Riggs (1975) in 1975, who proposed (correctly, in retrospect) that methylation of DNA nucleotides could at least partially account for Barr Body chromosomal inactivation. It is important to note here that methylation of cytosine DNA residues had been previously reported in the literature more than 20 years earlier in 1951, by Wyatt et al., although the function of the modification was unknown at the time (Wyatt 1951). In a remarkably prescient description of what would later come to be identified as an epigenetic control mechanism, Holliday and Pugh wrote: Since the ultimate control of development reside in the genetic material, the actual program must be written in base sequences in the DNA. It is also clear that cytoplasmic components can have a powerful or overriding influence on genomic activity in particular cells, yet these cytoplasmic components are, of course, usually derived from the activity of genes at some earlier stage of development. A continual interaction between cytoplasmic enzymes and DNA sequences is an essential part of the model to be presented. (Holliday and Pugh 1975)

They further correctly hypothesized that the chemical modification of DNA by methylation at cytosine residues in cytosine–guanosine (CpG) pairs is added by both a set of de novo enzymes (the DNA methyltransferases DNMT3a and DNMT3b) and a separate maintenance enzyme required to copy epigenetic marks to daughter cells during division (the DNA methyltransferase DNMT1), first described some 20 years later in 1982 and 1983, respectively (Jähner et al. 1982; Bestor and Ingram 1983). Furthermore, they also correctly pointed out that these modifications are reversible, a necessary function for any organism to react in a bidirectional fashion to environmental manipulation, although the enzymes responsible for DNA demethylation were not described and validated until some three decades later (Tahiliani et al. 2009; Ito et al. 2010; Ko et al. 2010). These observations gave the first depictions of sequence-specific epigenetic mechanisms by which transcriptional patterns could be set and transmitted through cellular generations. It is here that we first encounter evidence of the nascent field of epigenetics intersecting with studies of human disease pathogenesis. In his 1979 paper entitled “A New Theory of Carcinogenesis”, Holliday argued that repair of damage to DNA induced by known carcinogens could lead to loss of epigenetic information; specifically, that “replacement” DNA would lose any preexisting methylation marks and, if in the right gene, might partially explain tumorigenesis (Holliday 1979). Although not entirely accurate, an epigenetic basis for malignancy, and epigenetic aberrations within known oncogenes and near chronic-disease-associated susceptibility alleles

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is now a well-studied phenomenon. There were two lines of evidence then uncovered that unequivocally linked methylation of cytosine DNA residues to gene expression and confirmed previous hunches about DNA methylation and X-chromosome inactivation. The first was the discovery of bacterial restriction enzyme pairs (known as isoschizomers) where one enzyme was methylation-sensitive; that is, one enzyme which would cut double-stranded DNA at a particular position regardless of the methylation status of an included cytosine, whereas another would cut at the same sequence only when cytosine residues were in a single methylation state. An example of this can be seen in the pair MspI and HpaII; both cut GCGC motifs, but Msp I requires the middle cytosine to be methylated. Several studies in the late 1970s and early 1980s soon leveraged this technique to demonstrate that genes with DNA methylation of their respective promoter regions were inactive, whereas unmethylated promoter regions were associated with active gene expression (Doerfler 1981). The second line of evidence came soon thereafter, with the discovery that the nucleoside analogue 5-azacytidine. When incorporated into cellular DNA, it inhibits the activity of DNA methyltransferases, leading to reductions in DNA methylation levels globally and subsequent increases in gene expression levels, including reactivation of genes located on the inactive X chromosome (Jones 1985). An obvious question then became the focus of the epigenetics field: how are DNA methylation marks (or histone posttranslational modifications) targeted to the right genomic locations within a cell at the right time? This final fundamental topic in epigenetic regulation began to be answered in the late 1980 and 1990s, when intermediate factors that possess both DNA localization domains as well as binding sites for chromatin- or DNA methylation-altering enzymes were described. Of particular historical importance in this context included the description of the myogenic differentiation factor MyoD by Davis et al. (1987), Weintraub et al. (1989). MyoD is a transcription factor that binds to the enhancer regions of hundreds of myogenic genes and recruits various histone posttranslational modifiers, including p300, LSD1, G9a, and HDAC1; in this way, it functions as a “bridge” between short-term gene activation or repression and long-term epigenetic modification to produce a particular transcriptional phenotype driving myogenic differentiation. In 1994, Pazin and colleagues induced gene activation in Drosophila embryo chromatin extract by mixing with yeast activator GAL4, fused with the transcriptional activation region of the herpes virus protein VP16 (Pazin et al. 1994). They demonstrated that gene activation occurred via an ATP-dependent mechanism, and was accompanied by reorganization of nucleosomes within the chromatin. These findings would later be clarified with the discovery of nucleosome remodeling complexes, including SWI/SNF (Peterson and Herskowitz 1992) and NURF (Mizuguchi et al. 1997), which have subsequently been shown to bind themselves to other protein sequences (like Dri ARID) which provide sequence specificity to their gene transcription modulatory activity (Sun et al. 2015). These discoveries have become particularly important over the past decade or two as investigators have begun identifying alterations in various epigenetic-targeting effectors in association with human disease. Take, for example, the description by Sawalha and colleagues in 2008 of genetic mutations in the methylcytosine-binding protein 2 (MECP2) gene which increase the risk of systemic lupus erythematosus

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(Sawalha et al. 2008); MECP2 functions to bind methylated DNA and direct further histone posttranslational modification to “turn off” genes, as well as recruiting the maintenance DNA methyltransferase DNMT1 during cellular division, maintaining fidelity of epigenetic marks. Koelsch, Sawalha, and colleagues went on to show that overexpression of MECP2 in a mouse model altered all three major domains of epigenetic control: DNA methylation, noncoding RNA (discussed in detail below), and histone posttranslational modification (Koelsch et al. 2013).

2.1.3 A New Epigenetic Role for RNA We have until this point focused on DNA and protein as the central players in the epigenetic regulation space; however, we must not ignore the role of RNAs, which had a bit of a late start but have nonetheless more recently risen to epigenetics fame. Coincident with the discoveries of DNA in the mid-twentieth century, the “central dogma” of molecular biology emerged; that is, the concept that DNA encodes RNA which, in turn, is “read” by ribosomes to produce proteins. The first glimpse of a potential regulatory role of RNA was found in 1966, when Warner and colleagues identified a complex group of nuclear RNAs aside from what was then termed “ribosomal precursor” RNA, which they termed “heterogeneous nuclear RNA” or hnRNA (Warner et al. 1966). At the same time, researchers identified retrotransposons, large areas of repeated elements within DNA in multiple species across several domains. Integrating this information, Roy Britten and Eric Davidson published “Gene Regulation for Higher Cells: A Theory” in Science Magazine, which outlined their theory that higher organisms contained extensive RNA networks which regulated gene transcription (Britten and Davidson 1969). The next big discovery occurred in 1997 with the demonstration of noncoding regions interspersed among coding regions in messenger RNA, areas they termed “introns” (Berget et al. 1977; Chow et al. 1977). Unfortunately, it was erroneously assumed that the noncoding portions of these transcripts represented “junk” RNA, and little additional work was done on these noncoding RNA regions in the ensuing decade. This thinking radically changed, however, with the landmark discovery in 1993 by Ambros and colleagues of the regulatory nature of small (~22 nucleotides in length) bits of RNA. Working in C. elegans, they found that the gene lin-4 encoded two small RNAs, one 22 and the other 61 nucleotides, which bound to a repeated sequence element in the 3 untranslated region of lin-14 mRNA, which codes the LIN-14 protein, critical for C. elegans development. They further demonstrated that this antisense RNA–RNA interaction was tightly inversely correlated with LIN-14 expression, suggesting that this small RNA was indeed regulating the gene (Lee et al. 1993). The world of noncoding RNA grew much larger with the discovery in 1998 of the RNA interference pathway in both C. elegans (Fire et al. 1998) and plant species (Waterhouse et al. 1998), discoveries which would lead to the awarding of the Nobel Prize for Physiology or Medicine to Fire et al. (1998). This RNA interference pathway had been suggested in plants by the process of transgene silencing,

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a mechanism described in the early 90s which has been subsequently identified as RNA-directed DNA methylation (see the previous discussion of this epigenetic control) (van der Krol et al. 1990; Wassenegger et al. 1994). Scientists then identified the presence of double-stranded RNA, and the fact that these were processed into short fragments (small interfering RNA, or siRNA) upon viral infection of plant cells. Subsequently, endogenous dsRNA precursors were identified, as were the cellular proteins responsible for their processing (including Argonaute, Drosha, and Dicer) (Bernstein et al. 2001; Doi et al. 2003; Lee et al. 2003; Basyuk et al. 2003) in the early 2000s. Although it was initially thought that these noncoding RNAs functioned more or less exclusively by binding messenger RNA and targeting it for degradation (thereby downregulating gene expression), later studies demonstrated that certain siRNA processing machinery, particularly Argonaute, was expressed not only in the cytoplasm, but in the nucleus (Ahlenstiel et al. 2012; Ameyar-Zazoua et al. 2012). This curious observation led to later demonstrations that these short RNAs can direct other forms of epigenetic modulation within the nucleus; incidentally, by recruiting a variety of histone posttranslational-modification enzymes, including the aforementioned polycomb complex (Kim et al. 2006). Over the past decade a large range of noncoding RNAs have been identified, all with distinct regulatory pathways, many of which involving direct epigenetic modulation of a target gene. For example, long noncoding RNAs are intricately linked with paternal imprinting (the process by which the redundant copies of each gene, either maternal or paternal in origin, are inactivated) (Sleutels et al. 2002; Thakur et al. 2004). Interestingly, X chromosome inactivation is also partially directed by the coating of the nascent chromosome in a short noncoding RNA known as the X-inactive specific transcript (X-ist), which, in turn, recruits Polycomb repressive complex 2 (PCRC2), which trimethylates lysine 27 of histone 3 (H3K27me3), a repressive histone mark. The expression of X-ist itself is epigenetically regulated by a variety of other lncRNAs (review, Lee and Bartolomei 2013). Several novel functions of miRNAs have been proposed, and several new classes of larger noncoding RNA with important transcriptional significance have been recently described, including Piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), and others.

2.2 Epigenetics Moves Mainstream and Meets the Clinic Now that we have outlined a historical perspective of the discovery of epigenetics, we will next move to describe how our knowledge of these fundamental mechanisms have expanded and, in some cases, radically changed our understanding both of normal cellular processes and of disease pathogenesis. As an example, we will first explore the epigenetic changes underlying the normal aging process, then introduce the concept of an epigenetic “clock”, a topic that has received much attention in the recent literature. We will then discuss the epigenetic effects of antiaging interventions. Epigenetics has not only been studied in the context of disease pathogenesis however; especially from a clinical standpoint, epigenetic biomarkers hold great

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promise, and will be discussed. Finally, though this chapter focuses heavily on a historical view of epigenetics, we will then close with examples of how modern epigenetic, transcriptomic, and proteomic tools are being used along with modern computational approaches in the modern age to help make sense of the massive quantities of data being generated through increasingly detailed looks at each of these “-omics” domains.

2.2.1 The Epigenetics of Aging We will start with the epigenetics of aging, a normal process that nonetheless contributes to the development of a large number of chronic diseases. As we have previously detailed, a robust and relatively error-free epigenetic regulatory system is required for the normal development of a multicellular organism, as tissue types arise from embryonic multipotent cells, and particular transcription patterns must be set epigenetically to allow for appropriate tissue differentiation throughout organism development and cellular replenishment or maintenance throughout life. One could imagine, then, that reductions of cellular “plasticity” caused by loss of or improper epigenetic regulation, could substantially affect many fundamental biological processes. There is now a large body of literature which supports the notion that epigenetic aberrancies occur as part of normal aging, and that these may predispose to the development of a variety of diseases. In this section, we will discuss a few of the general epigenetic modifications that have been associated with aging, and a relatively new epigenetic paradigm (the epigenetic clock) that may have important implications in our understanding of epigenetic aging and disease susceptibility. Many of the epigenetic changes previously observed during aging are outlined in Table 2.1 and an overview of epigenetic changes in aging is presented in Fig. 2.2. A global example is generalized loss of histones, a feature which has been noted in organisms from yeast to humans (Dang et al. 2009; O’Sullivan et al. 2010). This loss of histones is associated with the total number of divisions a particular cell has undergone, similar to telomere shortening. The loss can be dramatic; for example, in aged yeast, ~50% of overall histone loss can be seen (Hu et al. 2014). Unsurprisingly, this histone loss renders DNA more accessible to transcription globally, and, in this example, led to the induction of all known yeast genes. Conversely, artificially increasing histone protein production results in extended lifespan in yeast (Freser 2010). Interestingly, during senescence, a pathogenic state in which cells cease to divide but continue to be metabolically active, and produce a variety of harmful inflammatory cytokines, histone genes undergo unique alternative splicing of their requisite genes to produce senescence-specific histone proteins (Rai et al. 2014). Another epigenetically mediated mechanism underlying aging and age-related diseases are reductions in chromatin stability, which can be pathogenic in two fundamental ways. First, age-dependent decreases in chromatin stability, linked with reductions in histone proteins and appropriate chromatin packaging, can make the genome more susceptible to mutations. Additionally, less stable chromatin can reduce

Function

Transcriptional repression/activation

Epigenetic mark

5-mC

No global change

Global decrease and local increases Minor global increase, local increases, and some local decreases Local increases and some local decreases

Increase (LINEs), local decreases and rare local increases No global change

Cellular (senescence) Organismal

Organismal

Organismal

Organismal

Change in epigenetic mark with aging

Organismal (Werner syndrome)

Aging paradigm

Table 2.1 Epigenetic changes during aging. Adopted from Benayoun et al. (2015)

Cortex

Sperm

Small intestine, colon, lung, liver, spleen, brain, blood, kidney and muscle

HSCs

Fibroblasts

MSCs

Change observed in tissue or cells

WGBS

Pyrosequencing (LINEs) Beadchip arrays

Pyrosequencing MCAM Beadchip arrays

RRBS WGBS

Immunostaining WGBS Chromatography

RRBS

Method of detection

(continued)

M. musculus H. sapiens

H. sapiens

H. sapiens M. musculus

M. musculus

H. sapiens M. musculus M. auratus

H. sapiens

Species

2 The Development of Epigenetics in the Study … 67

Function

Transcriptional activation

Unclear

Core chromatin component

Core chromatin component

Core chromatin component

Epigenetic mark

5-hmC

mCH (where H represents A, C, or T)

Histone H2A

H2B

H3

Table 2.1 (continued)

Decrease

Decrease and changes in occupancy

Organismal (replicative lifespan)

Decrease

Organismal Cellular (senescence)

Decrease

Decrease

Organismal (replicative lifespan) Cellular (senescence)

Decrease

Cellular (senescence)

Minor global decrease

Minor global decrease

Organismal Organismal

Minor increase (SINEs and LTRs)

Change in epigenetic mark with aging

Organismal

Aging paradigm

Yeast cells

Epidermis and fibroblasts

Muscle stem cells

Fibroblasts

Yeast cells

Fibroblasts

Cortex

HSCs

Cerebellum

Change observed in tissue or cells

Western blot MNase–seq

Immunostaining Western blot SILAC–MS

Transcriptional profiling

Western blot

Western blot

Western blot

WGBS

HPLC–MS

Immunostaining Chemical tagging and sequencing

Method of detection

(continued)

S. cerevisiae

H. sapiens

M. musculus

H. sapiens

S. cerevisiae

H. sapiens

H. sapiens M. musculus

M. musculus

M. musculus

Species

68 M. A. Jeffries

Function

Core chromatin component

Component of heterochromatin

Component of heterochromatin

Component of heterochromatin

Component of heterochromatin

Epigenetic mark

H4

macroH2A

HP1

HP1α

HP1β

Table 2.1 (continued)

No change

Organismal

Increase

Decrease

Organismal Cellular (senescence)

Decrease

Organismal (HGPS and Werner syndrome)

Remodeling

Increase

Organismal Organismal

Increase

Cellular (senescence)

Decrease

Decrease

Organismal

Cellular (senescence)

Change in epigenetic mark with aging

Aging paradigm

Fibroblasts

MSCs

Fibroblasts and MSCs

Head, gut, and fat cells

Lung and liver

Fibroblasts

Fibroblasts

Head

Soma, whole male flies and muscle stem cells

Change observed in tissue or cells

Immunostaining Western blot

Western blot

Immunostaining Western blot

Immunostaining ChIP–chip

Immunostaining Western blot

Immunostaining Western blot

Western blot SILAC–MS

Western blot (normalization to total protein or DNA)

Western blot (normalization to tubulin) Transcriptional profiling

Method of detection

(continued)

H. sapiens

H. sapiens

H. sapiens

D. melanogaster

M. musculus

H. sapiens

H. sapiens

D. melanogaster

C. elegans D. melanogaster M. musculus

Species

2 The Development of Epigenetics in the Study … 69

Function

Component of heterochromatin

Enriched in euchromatin along gene bodies, involved in transcriptional repression

Enriched along gene bodies, involved in transcriptional repression

Enriched in heterochromatin regions, involved in transcriptional silencing

Epigenetic mark

HP1γ

H3K9me1

H3K9me2

H3K9me3

Table 2.1 (continued)

Decrease

Decrease Increase and remodeling Decrease

Cellular (senescence) Organismal Organismal

Decrease

Organismal Organismal (HGPS and Werner syndrome)

Decrease

Cellular (senescence)

Increase

Decrease

Organismal Cellular (senescence)

Decrease

Change in epigenetic mark with aging

Organismal (HGPS)

Aging paradigm

Fibroblasts and soma

Head

Fibroblasts

Fibroblasts and MSCs

Whole male flies

Fibroblasts

Fibroblasts

Fibroblasts

Fibroblasts

Change observed in tissue or cells

Immunostaining Western blot

Western blot ChIP–chip

SILAC–MS Western blot

Immunostaining Western blot ChIP–seq

Western blot

Western blot SILAC–MS

Western blot SILAC–MS

Immunostaining

Immunostaining

Method of detection

(continued)

H. sapiens C. elegans

D. melanogaster

H. sapiens

H. sapiens

D. melanogaster

H. sapiens

H. sapiens

H. sapiens

H. sapiens

Species

70 M. A. Jeffries

Function

Enriched in euchromatin along gene bodies, involved in transcriptional repression

DNA repair and genomic stability

Enriched in pericentric heterochromatin

Enriched in euchromatin along gene body, involved in transcriptional activation

Epigenetic mark

H3K27me3

H4K20me2

H4K20me3

H3K4me2

Table 2.1 (continued)

Decrease Increase and remodeling

Organismal Organismal

Increase

Organismal Global increase and remodeling

Decrease

Cellular (senescence)

Organismal

Increase

Organismal (HGPS)

Increase

Remodeling

Cellular (senescence)

Cellular (senescence)

Decrease and remodeling

Change in epigenetic mark with aging

Organismal (HGPS and Werner syndrome)

Aging paradigm

Cortex

Liver and kidney

Fibroblasts

Fibroblasts

Fibroblasts

Brain, muscle stem cells and HSCs

Soma

Fibroblasts

Fibroblasts and MSCs

Change observed in tissue or cells

ChIP–seq

Liquid chromatography

Western blot SILAC–MS

Western blot Immunostaining

Western blot SILAC–MS

Immunostaining ChIP–seq

Western blot

ChIP–seq

Immunostaining ChIP–seq

Method of detection

(continued)

M. mulatta

R. norvegicus

H. sapiens

H. sapiens

H. sapiens

N. furzeri M. musculus

C. elegans

H. sapiens

H. sapiens

Species

2 The Development of Epigenetics in the Study … 71

Function

Enriched in euchromatin at promoters, involved in transcriptional activation

Enriched in euchromatin along gene body, involved in transcriptional elongation

DNA replication, DNA damage response, and nucleosome assembly

Epigenetic mark

H3K4me3

H3K36me3

H3K56ac

Table 2.1 (continued)

Minor global increase and remodeling

Organismal

Decrease Decrease

Cellular (senescence) Organismal (replicative lifespan)

Minor global decrease, remodeling

Decrease and remodeling

Organismal

Organismal

No change

Organismal

No global change and remodeling

Remodeling

Cellular (senescence)

Organismal (replicative lifespan)

No global change

Change in epigenetic mark with aging

Organismal (Werner syndrome)

Aging paradigm

Yeast cells

Fibroblasts

Soma and head

Yeast cells

Neurons, HSCs and muscle stem cells

Head

Soma

Fibroblasts

MSCs

Change observed in tissue or cells

Western blot

Immunostaining Western blot

Western blot ChIP–chip ChIP–seq

ChIP–seq

ChIP–seq

ChIP–chip

Western blot

ChIP–seq

ChIP–seq

Method of detection

(continued)

S. cerevisiae

H. sapiens

C. elegans D. melanogaster

S. cerevisiae

H. sapiens M. musculus

D. melanogaster

C. elegans

H. sapiens

H. sapiens

Species

72 M. A. Jeffries

Regulation of telomere silencing and regulation of chromatin compaction (?)

Enriched in euchromatin along gene body, involved in transcriptional elongation

H4K16ac

H4K12ac

Increase

Decrease

Organismal (replicative lifespan) Organismal Decrease upon contextual fear conditioning

Decrease

Cellular (senescence)

Organismal

Decrease

Change in epigenetic mark with aging

Organismal (HGPS)

Aging paradigm

Hippocampus

Liver and kidney

Yeast cells

Fibroblasts

Fibroblasts and liver

Change observed in tissue or cells

Western blot

Western blot

Western blot

Western blot

Immunostaining Western blot

Method of detection

M. musculus

H. sapiens M. musculus

S. cerevisiae

H. sapiens

M. musculus

Species

RRBS reduced representation bisulfite sequencing, WGBS whole genome bisulfite sequencing, HPLC high-performance liquid chromatography, SILAC stable isotope labeling by amino acids, ChIP chromatin immunoprecipitation

Function

Epigenetic mark

Table 2.1 (continued)

2 The Development of Epigenetics in the Study … 73

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Fig. 2.2 A model for epigenetic changes observed in aging. Adopted from Benayoun et al. (2015)

the precision of transcription. The second major mechanism whereby epigenetically mediated mechanisms can affect chromatin stability is by making the epigenetic state of chromatin itself unstable, a process known as epimutation (Chong et al. 2007). Much like mutations in underlying genomic material, epimutations are passed on to daughter cells and increases in epimutation rate are linked to the number of cellular divisions; therefore, epimutations increase throughout life, as first described by Holliday (1987). These are driven by a number of factors, the first being errors in DNA and epigenome repair (Burgess et al. 2012). Furthermore, much like chronic inflammatory signaling seen in autoimmune diseases, chronic DNA damage signaling can cause pathogenic recruitment of a variety of histone- and DNA-methylation modifiers and induce inappropriate chromatin remodeling (Burgess et al. 2012), creating a feedback loop, resulting in ever-increasing local chromatin instability. This is modeled well in a genetic disease known as Werner syndrome, a deficiency in DNA helicase (the DNA “unwinding” enzyme) in mesenchymal stem cells, which leads to permanent aberrations in chromatin arrangements including global decreases in histone 3 lysine 9 trimethylation (H3K9me3), histone 3 lysine 27 trimethylation (H3K27me3), among others (Zhang et al. 2015). Age-associated epigenetic changes can also lead to increases in DNA transposition, which has potentially pathogenic effects. Up to 80% of the genome consists of transposable elements; themselves not encoding proteins,

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but possessing the ability to regulate proximate genes. It has been previously demonstrated that transposable elements induce instability of the surrounding genome when actively transcribed; this transcription is normally reduced with suppressive epigenetic marks, especially histone 3 lysine 9 trimethylation; however, the expression of transposable elements increases with age and cellular senescence, and has been linked with human disease, particularly, diseases of the central nervous system (De Cecco et al. 2013; Reilly et al. 2013; Wood and Helfand 2013). At a more granular level, global reductions in DNA methylation are seen in with aging, a feature noted decades ago by Wilson and Jones in 1983, who demonstrated that primary human, mouse, and hamster cells had substantially decreased global methylation levels when cultured in vitro over time compared to early passages and immortalized cell lines (Wilson and Jones 1983). Global hypomethylation induces genomic instability as well as leading to increases in gene expression of a variety of genes thought to promote tumorigenesis (Cruickshanks et al. 2013). Substantial changes in DNA methylation patterns associated with age are seen, however, when comparing gene islands, where aging tends to result in decreased methylation, whereas CpG sites within promoters tend to become hypermethylated with age, particularly in genes associated with development and differentiation (Maegawa et al. 2010; Day et al. 2013). Importantly, the rate of age-associated epigenetic changes can vary among individuals. This concept was perhaps best illustrated by Fraga and colleagues (2005). They examined the epigenomes of lymphocytes (including DNA methylation and histone acetylation patterns) of a large cohort of monozygotic twins in Spain. They found that the epigenetic patterns of twins diverged according to their age; 50-yearold twins had substantial differences, whereas 3-year-old twins were nearly indistinguishable. These differences were, as one would expect, correlated strongly with lifestyle; twins who were younger, had similar lifestyles, and had spent most of their lifetimes together had the least DNA methylation changes throughout their genome, whereas twins who were older, had divergent lifestyles, and spent less of their lifetimes together had the most-divergent DNA methylation patterns. Importantly, these epigenetic differences were correlated with changes in gene expression patterns, and the differences persisted across a variety of tissue types. Although the full consequences of altered DNA methylation states associated with aging have not yet been worked out, there are suggestions that epigenetic alterations are associated to specific transcription factors’ binding sites, and that this may contribute to gene misregulation during aging, as highlighted by Sun et al. in hematopoietic stem cells (Sun et al. 2014). This can have direct implications in the development of age-related diseases; cancer, for instance. An article published in 2010 by Teschendorff et al. (2010) examined targets of polycomb group proteins (PCGTs), which are epigenetically repressed in multipotent cells including human embryonic and adult stem cells (Lee et al. 2006). DNA hypermethylation of PCGTs occurs at a higher rate (~12-fold) than at other genomic locations in the development of cancer. Teschendorff first identified significant linear correlations between age and DNA methylation of PCGTs (increases in methylation associated with age) irrespective of cancer status, in multiple tissues,

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including whole blood, lung, cervix, and mesenchymal stem cells, among others. Interestingly though, the DNA methylation levels of these age-related PCGTs were even higher in cancer tissue, suggesting an exacerbation of the underlying DNA methylation changes caused by aging. This was bolstered by this age-related PCGT hypermethylation signature’s ability to discriminate preneoplastic from normal cells.

2.2.2 The Concept of an Epigenetic Clock In recent years, many additional investigators have sought to define the pattern of epigenetic (and particularly, DNA methylation) changes that occur during aging, and how these may be associated with or predictive of pathogenic disease states. Chief among them is Steve Horvath of the University of California—Los Angeles. His seminal article in 2013 defined a multi-tissue algorithmic predictor of biological age based on a calculated “methylation age”, defined from ~8000 healthy human tissues and cell types (Horvath 2013) (Fig. 2.3). This initial algorithm was an attempt by Horvath to produce an algorithm that could accurately predict a patient’s biologic age based on DNA methylation information quantified using Illumina’s genomewide DNA methylation arrays (see subsequent chapters on epigenetic measurement methods), an important point to remember when considering later works seeking to define differences in this DNA methylation “clock” associated with chronic diseases. Using a machine learning approach, his final algorithm leveraged the DNA methylation values of 353 CpG sites to predict an epigenetic age, which was highly accurate with an average Pearson correlation coefficient 0.97 and median absolute error of 2.9 years; importantly, accurate correlations were made using this same algorithm across a variety of tissue types, including whole blood, a variety of brain samples, normal breast tissue, buccal cells, cartilage, dermal fibroblasts, epidermis, head and neck tissue, kidney, lung, mesenchymal stromal cells, stomach, thyroid, and others. There are a couple of notes of particular importance in his study. First and most interestingly, his algorithm was quite well validated in mixed peripheral blood samples. This is surprising given that this tissue is composed of a variety of cell types which have remarkably different lifespans; for example, monocytes live several weeks, whereas CD4+ memory T cells can live decades. DNA methylation age values were concordant even when examining these cell lines individually. The second observation is that his algorithm is applicable to nonhuman primates; interestingly, it correlated best with chronological age in chimpanzees, but somewhat less well in gorillas, likely reflecting a larger evolutionary distance. Finally, as one would predict, the DNA methylation age of induced pluripotent- and embryonic stem cells are very close to 0, indicating that they do not display any substantial epigenetic aging. This work has subsequently been extended by both Horvath and others to include the study of alterations of the epigenetic clock in a plethora of human diseases (Table 2.2). The aforementioned Werner syndrome, a disease whose character-

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Fig. 2.3 The DNA methylation-based epigenetic ‘clock’ is a continuous readout of cellular, tissue, and organismal aging. Adopted by Chen et al. (2016)

istics include many of the clinical signs of accelerated aging, is indeed associated with accelerated epigenetic aging of peripheral blood cells (Maierhofer et al. 2017). A number of central nervous system disorders exhibit accelerated epigenetic aging. Among these are Parkinson’s disease patients (Horvath and Ritz 2015) and Alzheimer’s disease (Levine et al. 2015b). In the latter case, accelerated epigenetic aging was found in the pathogenically affected organ itself (measured on dorsolateral prefrontal cortex samples), and was individually associated with a variety of neuropathological measurements, including the presence of diffuse plaques, neuritic plaques, amyloid load, cognitive functioning, and memory. In another fascinating study, Levine, Horvath, and colleagues examined methylation aging in blood samples drawn at baseline in a group of roughly 2000 patients as part of the Women’s

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Table 2.2 Conditions linked to alterations in the epigenetic clock. Adapted from Chen et al. (2016) Condition

Source of DNA

Age estimator

Alzheimer disease

Prefrontal cortex

Horvath’s clock

Amyloid load and neuropathology

Prefrontal cortex

Horvath’s clock

Blood pressure (systolic)

Blood

Hannum’s clock

Body mass index

Liver

Horvath’s clock

Cancer

Blood

All clocks

Cardiovascular disease

Blood

DNAm PhenoAge

Coronary heart disease

Blood

DNAm PhenoAge

Cellular senescence (oncogene-induced)

Various

Horvath’s clock

Centenarian (offspring status)

Blood

Horvath’s clock

Cholesterol, HDL (not LDL)

Blood

Hannum’s clock and DNAm PhenoAge

Cognitive performance

Blood and brain

Horvath’s clock and DNAm PhenoAge

C-reactive protein

Blood

All

Diet (carotenoids)

Blood

Hannum’s clock and DNAm PhenoAge

Dementia

Blood

DNAm PhenoAge

Down syndrome

Blood and brain

Horvath’s clock

Education

Blood

Hannum’s clock and DNAm PhenoAge

Exercise (recreational)

Blood

Hannum’s clock and DNAm PhenoAge

Frailty

Blood

Horvath’s clock and DNAm PhenoAge

Gender

Blood and brain

All

Gestational week

Blood and brain

Horvath’s clock

Glucose

Blood

All

Huntington disease

Blood and brain

Horvath’s clock

Income

Blood

Hannum’s clock and DNAm PhenoAge

Insulin levels

Blood

All

Menopause

Blood and saliva

Horvath’s clock

Mortality (all-cause)

Blood

All

Obesity

Liver and blood

All clocks

Osteoarthritis

Cartilage

Horvath’s clock

Parkinson disease

Blood

All

Pubertal development

Blood

Horvath’s clock (continued)

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Table 2.2 (continued) Condition

Source of DNA

Age estimator

Sleep

Blood

Hannum’s clock

Smoking

Blood

DNAm PhenoAge

TERT expression

Blood and fibroblasts

Horvath’s clock

Triglycerides

Blood

All

Walking speed

Blood

DNAm PhenoAge

Werner syndrome

Blood

Hannum’s clock and Horvath’s clock

HDL, high-density lipoprotein; LDL, low-density lipoprotein. ‘Age estimator’ indicates whether the effect was measured using the multi-tissue 353 CpG methylation-based age estimator, also known as Horvath’s clock (Horvath 2013), the single-tissue (blood) 71 CpG methylation-based age estimator, also known as Hannum’s clock (Hannum et al. 2013), or the DNA methylation-based phenotypic age (PhenoAge) measure based on 513 CpGs (Levine et al. 2018)

Health Initiative, 43 of which went on to develop lung cancer during an almost 20year follow-up period, their hypothesis being that individuals with naturally occurring “slowing” of the epigenetic clock would be protected against the oncogenic effects of carcinogens like cigarette smoking. They found that, indeed, baseline acceleration of the epigenetic clock was associated with the development of cancer; surprisingly, in all groups, including patients who were former- or never-smokers (Levine et al. 2015a). This effect was even stronger in chronologically older individuals (above 70 years of age). These studies offer the intriguing possibility of a generally increased susceptibility to a variety of chronic diseases based on epigenetic mechanisms, above and beyond those associated with specific diseases, genes, and pathways, which will be discussed in subsequent chapters. Horvath and colleagues have gone on to demonstrate premature epigenetic aging in a variety of chronic diseases and factors previously associated with chronic disease, including prenatally acquired HIV infection (Horvath et al. 2018), coronary heart disease (Horvath et al. 2016), menopause (Levine et al. 2016), cartilage of osteoarthritis patients (Vidal-Bralo et al. 2016), increases in body mass index, waist circumference, and fasting glucose (Grant et al. 2017). Furthermore, and of particular importance to the theme of this book, Irvin et al. have identified associations between accelerated epigenetic aging and a variety of inflammatory cytokines, including interleukin-6, C-reactive protein, and tumor necrosis factor-alpha (Irvin et al. 2018). In essentially all of the epigenetic aging literature to date, it appears that accelerations in preexisting aging-associated DNA methylation changes are associated with the onset of disease, indicating that potential future therapies directed at slowing or reducing epigenetic aging may be of benefit for prevention of chronic disease. Finally, this concept of an epigenetic clock (and of accelerations or decelerations of epigenetic aging) have been suggested as the most

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promising molecular estimator of biologic age in a recent review, which pitted epigenetic clocks against transcriptomic-based, proteomic-based, metabolomic-based, and composite biomarkers, as well as telomere length (Jylhävä et al. 2017).

2.2.3 Epigenetic Effects of Antiaging Interventions If aging, one of the strongest risk factors for most chronic diseases, is mediated to a large extent by widespread epigenetic changes, it stands to reason that interventions that slow or reverse the biological effects of aging might be acting through epigenetic mechanisms. A few studies have been published recently which do indeed indicate that this is the case, and serve to reinforce the notion that epigenetic states generally are plastic and potentially reversible. This concept that will no doubt be increasingly important in the near future as we continue developing the ability to modify epigenetic states in a site-specific manner. As an example of antiaging epigenetic modification, we will highlight a 2017 article by Maegawa and colleagues (2017). In this study, they examined wholeblood DNA methylation patterns in a genome-wide fashion from young and old individuals from three species with widely disparate maximum lifespans: mice and rhesus monkeys fed either a “normal” diet or a calorie-restricted one, and human samples (Fig. 2.4). They describe several interesting findings. First, they quantify the

Fig. 2.4 Cross-species comparison of DNA methylation drift and aging. a Correlations of methylation % and age across the lifespan of mouse, monkey, and human. b Association of normalized (% per year) DNA methylation drift and maximum species longevity. Adopted from Maegawa et al. (2017)

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rate of epigenetic “drift”; that is, the average percent change in methylation rates per year of life. There was a very strong inverse correlation between the rate of epigenetic drift and the species maximum longevity, suggesting that age-related drift in DNA methylation may have a role to play in limiting the lifespan of a particular species. Next, they confirm that these changes in DNA methylation were indeed correlated with change in gene expression, suggesting that these changes are functional, rather than innocent bystanders. Finally, they examined in great detail what occurs to DNA methylation patterns when mice and monkeys have their food calories reduced by 40% and 30%, respectively. Caloric restriction has been previously demonstrated in many studies to have antiaging (or, at least, life-extending) properties (review, Fernández-Ruiz 2017). In the case of mice, caloric restriction (CR) was started in young adulthood (0.3 years of age) and continued throughout their 2–3-year lifespan, whereas in monkeys, CR began in middle age, and data analyzed at 22–30 years of age. DNA methylation analysis of whole-blood samples showed that old-CR animals were much more like young animals, and regular-diet animals were in a separate cluster. This effect was most pronounced at CpG sites which were unmethylated in young animals, and were more pronounced in mice, which had caloric restriction begun earlier on relative to their total lifespan than in monkeys. These epigenetic effects were best explained by a substantial reduction in epigenetic drift. Finally, they went on to examine the tissue specificity of these changes using samples from a variety of organs, including spleen, bone marrow, liver, kidney, small intestine, and large intestine, and found that this phenomenon of epigenetic drift reduction with calorie restriction was present in most tissues, exceptions being kidney and liver. This study has several direct implications on the study of epigenetics in chronic diseases and, perhaps most importantly, offers evidence that at least some of the diseasereducing benefits seen in interventions that increase lifespan may occur through epigenetic modulation.

2.3 Epigenetic Modifications as Biomarkers of Disease So far in this chapter, we have focused on epigenetic modifications and their association with the disease from a pathogenesis standpoint. Another application of epigenetic study that has garnered more attention in the past few years is the potential of epigenetic modifications as biomarkers of the presence or progression of a particular disease. In this section, we will offer several examples of recently described epigenetic biomarkers of some of several important human diseases, and, when appropriate, discuss the advantages of using epigenetic biomarkers over other traditional methods of diagnosing and monitoring disease progression. The field of oncology has seen the most interest in epigenetic biomarkers, where markers fall into one of three major categories: early or initial diagnosis, risk stratification, and prediction of treatment response. Take, for example, colorectal cancer, the second leading cause of cancer-related deaths in the US behind lung and bronchial cancer (Siegel et al. 2011). The gold standard method for colon cancer screening

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at present is a colonoscopy procedure, whereby precancerous polyps can be identified and removed. This method has indeed reduced significantly colorectal cancer incidence and mortality (Schoen et al. 2012); however, an estimated 6% of colonoscopies detect advanced adenomas, and around 1% detect frank adenocarcinoma (Ferlitsch et al. 2011). Furthermore, the colonoscopy procedure itself is associated with nontrivial morbidity and is both expensive and burdensome for patients, who must undergo significant preparatory work the day before the procedure, receive conscious sedation during the procedure, etc. Clearly, a less invasive, more accurate, and earlier diagnostic biomarker for colon cancer would be desirable. Colon cancer occupies a unique position from an epigenetic standpoint in that much epigenetic analysis has already been done on cancerous and precancerous colon lesions (polyps, which are removed as part of screening colonoscopies) and the distinguishing epigenetic features have been well described (Lao and Grady 2011). Building on these data, several studies have suggested epigenetic biomarkers for both diagnosis and evaluation of the future risk of colon cancer. For example, hypermethylation of the MGMT gene has been strongly associated with the future likelihood of colon cancer development, even in grossly normal colon tissue, and has been suggested as a key early factor in carcinogenesis (Menigatti et al. 2009; Lang 2011). More recently, Luo and colleagues have reported that the DNA methylation pattern of a panel of six genes (AOX-1, RARB2, RERG, ADAMTS9, IRF4, and FOXE1) in a much more accessible biomarker fluid (peripheral blood cells) was highly associated with colorectal cancer (Luo et al. 2016). To date, at least two epigenetic biomarker panels have been FDA approved for colorectal cancer diagnosis including ColoVantage (a predictor using methylation of SEPT9 in peripheral blood) and ColoSure (a predictor using methylation of the vimentin gene in fecal samples). Another example of recent epigenetic biomarker development can be found in prostate cancer, a disease that has seen much controversy in recent years. This mostly stems from the prostate-specific antigen (or PSA) test, a previously widely used biomarker for the presence of prostate cancer, which led to what many experts feel is an overly aggressive biopsy- and treatment-paradigm in a disease that is frequently indolent in nature. The PSA test is a poor marker for a number of reasons, including a non-definitive cutoff for positivity, a nontrivial rate of PSA elevations without detectable prostate cancer, and a suboptimal rate of false-negative results (Castle 2015). Like colon cancer, much has already been described regarding the specific epigenetic changes that are associated with the transition from precancerous to malignant prostate tissue (Ruggero et al. 2018). A number of noninvasive prostate cancer epigenetic screening methods have been published, including APC gene methylation screening in urine (Jatkoe et al. 2015), CHD13 in serum (Wang et al. 2014), and ERBeta in serum (Brait et al. 2017). Unlike colorectal cancer, however, there have to date been no FDA-approved epigenetic biomarkers for the diagnosis of prostate cancer. Germane to this book on rheumatic disease are recent studies examining epigenetic biomarkers in systemic lupus erythematosus (SLE). One would expect, given that autoimmune diseases are driven to a substantial degree by alterations in circulating inflammatory cells, that peripheral blood-based epigenetic biomarkers might

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be both related to the underlying biological pathogenesis and easily accessible for clinical application; indeed, the search for epigenetic biomarkers in peripheral blood cells has been quite fruitful in several autoimmune diseases. Lupus is an interesting and important target for novel biomarker development; it is a quite heterogeneous disease characterized by autoantibody production against a variety of nuclear targets, affecting almost every body system. The diagnosis of lupus is notoriously difficult, but very important, as delayed diagnosis can lead to substantial irreversible organ damage (Fortin et al. 1998). Currently available laboratory markers for lupus have substantial limitations, including mismatches in sensitivity and specificity. An article by Zhao and colleagues in 2015 offers a good example of diagnostic biomarker development in lupus (Zhao et al. 2016). First, they screened peripheral blood mononuclear cell DNA methylation patterns from lupus patients, healthy controls, and non-lupus autoimmune rheumatoid arthritis and Sjogren’s syndrome patients, and an independent validation cohort of lupus patients and healthy controls for potential disease-associated biomarkers using an Illumina genome-wide DNA methylation array (see subsequent chapter on methods for epigenetic quantitation). They identified differentially methylated sites within the IFI44L gene as highly associated with the presence of lupus; then, they examined two specific locations within this region in a much larger group of patients as part of a discovery cohort, using a different method (bisulfite pyrosequencing). They went on to confirm the sensitivity and specificity of the DNA methylation values of these two CpG sites in multiple validation cohorts, including among the same ethnic group (Chinese) and among a different ethnic group (Europeans). Remarkably, these methylation sites had quite high sensitivity and specificity for the diagnosis of lupus, in the 90% range for both among Chinese, and in the 70–80% range for both in Europeans. Furthermore, they were able to accurately differentiate lupus from both rheumatoid arthritis and Sjogren’s syndrome patients. A subsequent study by Coit et al. (2015) identified a single CpG within the CHST12 gene of naive T cells from lupus patients as highly associated with the presence of lupus nephritis, a manifestation of SLE which is difficult to detect without an invasive biopsy, with a sensitivity of 86% and specificity of 71%. Other studies have similarly noted strong associations with certain clinical manifestations and disease indices with alterations in DNA methylation of easily accessible tissues. These include IL10 and IL12 hypomethylation correlation with lupus disease activity scores (Lin et al. 2012), IL6 methylation correlation with lupus disease activity, prediction of flare, and serum complement levels (Mi and Zeng 2008; Tang et al. 2014), FOXP3 methylation association with disease activity (Horwitz 2008), and retroviral element HERV-E and HERV-K methylation association with both disease activity and the presence of a variety of autoantibody specificities (Okada et al. 2002; Piotrowski et al. 2005). Another area of biomarker research where epigenetics can play a strong role is in predicting the response to particular therapies. In rheumatoid arthritis (RA), for example, we are fortunate to have dozens of effective “traditional” and biologic medications with more being approved on an almost yearly basis; unfortunately, however, experience has shown that these are not universally effective. Additionally, most of these new drugs take some time to reach peak effectiveness; consequently,

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when a patient has a suboptimal response within the first weeks of treatment, it is nearly impossible to determine whether this represents a failure of the therapy or simply a delayed response. Given the substantial cost of these treatments, a need clearly exists for biomarkers that can help stratify RA patients and predict whether or not they will respond to a particular drug or class of drugs. Traditional non-biologic synthetic disease-modifying drugs (DMARDs) may actually partially work by inducing epigenetic changes, as highlighted by de Andres and colleagues in 2015, who outlined substantial DNA methylation changes induced by treatment with one of these drugs, methotrexate, in RA patients (de Andres et al. 2015). Although this is a relatively new field, an article by Plant and colleagues in 2016 demonstrated the usefulness of peripheral blood epigenetic patterns to predict clinical responses in RA patients subsequently treated with the antitumor necrosis factor-alpha drug etanercept (Plant et al. 2016). In this study, they performed an epigenome-wide association analysis (EWAS). The discovery cohort included 36 pretreatment whole-blood samples from RA patients who later had a poor response to etanercept by a well-validated clinical disease activity index after three months of treatment and compared this with 36 pretreatment whole blood samples from patients who later had a very good response to etanercept (clinical disease activity index in remission after three months of therapy). They identified five CpG sites with significant differential methylation between responders and nonresponders; intriguingly, all five demonstrated reduced methylation among good responders compared to poor responders. Interestingly, two of the top five, and four of the top 15 most differentially methylated CpG sites between groups were located within exon 7 of the LRAP1 gene; they went on to demonstrate that three genetic single nucleotide polymorphism mutations were highly correlated with the DNA methylation levels of two of these CpGs, indicating that epigenetic and genetic mechanisms in LRAP1 interact to produce a good or bad TNF inhibitor response in RA patients. This sort of interaction, known as methylation quantitative trait loci or meth-QTL, has in recent years been demonstrated as quite important in a variety of clinical phenotypes and disease states, and will likely be even more intensely studied as the field moves toward whole-genome and—epigenome studies, collectively known as “big data”, which will be discussed in the following final section of this chapter.

2.4 Epigenetics in the Modern World: Using Big Data to Understand the Pathogenesis of Complex Diseases in the Present Day In the final section of this chapter, we will move from a historical perspective of epigenetics to discuss the state-of-the-art in epigenetics research, as well as offer some glimpses into the future of epigenetics research as it relates to chronic disease research generally, and disorders of the immune system specifically. As technology has advanced and allowed researchers to generate increasingly intricate maps of both

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genetic risk and epigenetic associations in chronic disease states, new techniques have been developed to make sense of this massive amount of data. Several studies have been recently published, including in the field of rheumatology, which seeks to computationally synthesize large genetic, epigenetic, proteomic, and transcriptomic datasets in key cell types and draw conclusions regarding the ways in which these— omics domains interact regionally to contribute to the development of the disease. In a way counterintuitively, large, detailed data sets and complex computational analysis have also allowed researchers to take a step back and draw more general conclusions about the genes, organ systems, and pathways that are altered in chronic diseases generally. As the cost of complete genomic sequencing and base-specific wholegenome epigenetic analyses continue to fall, we will no doubt see more of these integrated analyses in the future; hopefully offering a more complete understanding of the fundamental processes underlying disease pathogenesis driven by machinelearning-driven insights, and perhaps offer novel treatment strategies. A nice example of this computationally driven view of the integration of underlying genetic sequence and epigenetic modification in the development of autoimmune diseases generally can be found in an article by Farh et al. (2015). In this study, they collected genome-wide association study (GWAS) data from 39 independent, wellpowered GWAS studies representing a variety of complex systemic diseases from published datasets. They then clustered diseases based on shared genetic susceptibility loci in order to produce a map relating the diseases to each other on a genetic level; remarkably, many disparate disorders shared a number of similar features. For example, 69% of single nucleotide polymorphisms (SNPs) collected in their metaanalysis were shared among at least two autoimmune diseases. Next, they developed a novel computational approach to estimate the probability that SNPs associated with multiple autoimmune diseases represented a causal SNP as opposed to an “innocent bystander”, a method they termed Probabilistic Identification of Causal SNPs (PICS). Next, they generated immune cell subtype-specific “maps” (including, for example, CD4+ and CD8+ T cell subsets, B cells, and monocytes) based on both data generated within their laboratory and data previously published through the NIH Epigenomics Project and the Encyclopedia of DNA Elements (ENCODE, a publicly accessible research project aiming to identify and catalogue all functional elements within the human genome), including a 56 cell types. They computed a genome-wide map of histone posttranslational modification regulatory elements and then clustered individual cell types based on these patterns. Finally, they inferred the cell types most likely driving particular autoimmune diseases by overlaying these two datasets; that is, they looked for cell types in which disease-specific genetic mutations were located in regions known to be epigenetically “active” (Fig. 2.5). This allowed them to guess which cell types are most likely involved in specific autoimmune disease. Several of the associations were predictable; for example, both T-cell stimulation and B cells shared enrichment of epigenetically active enhancers. Interestingly, these SNPs were also common within generalized stimulus-dependent enhancers; epigenetically active enhancers from unstimulated T cells did not overlap with these SNPs. Further, and a good example of the complexity of epigenetic regulation, they found that many disease-

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Fig. 2.5 Cell-type specificity of human diseases, inferred from epigenetic mapping. Adopted from Farh et al. (2015)

and cell-type-associated SNPs were located within regions which regulated the transcription of noncoding RNAs, another epigenetic control mechanism. In the end, they estimate that genetic changes in enhancer regions producing mixed genetic– epigenetic effects overall account for around ~60% of all disease-associated genetic variants (Houseman et al. 2012; Martino et al. 2012). The next problem, of course, is identifying how these genetic/epigenetic interactions within enhancer regions in specific immune cell subsets are actually contributing to disease risk or pathogenesis. For example, the most obvious potential explanation is that these changes conspire to alter gene regulation, inducing overexpression or underexpression or, intriguingly, interrupting the appropriate regulation of the gene in question, allowing it to be turned on or off at inappropriate times. They investigated this possibility by modeling how these variations (be they genetic or epigenetic) alter the binding of transcription factors. Although they did find enrichment of PICS SNPs within or proximate to many transcription factor binding sites, these represented only a minority (around 7%), and was more or less the percentage one would expect to find at random from non-disease-related SNPs. Unfortunately, the authors were unable to give a definitive pathophysiologic mechanism, although they speculate that future

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research to better define the structure and function of gene enhancers, which the majority of these sites fell within, may allow a better understanding. As outlined above, one would expect that this sort of analysis would also give us another important bit of information: the cell types which are most likely to be involved in a particular disease based on this genetic/epigenetic inference. The authors compared their list of likely “causal” SNPs for a given disease with the histone “fingerprint” of a wide variety of cell types included in both the NIH Epigenomics Project and ENCODE datasets mentioned above. Several of these associations were expected; for example, migraine disease and Alzheimer’s were both predicted to involve brain tissue, just as inflammatory bowel diseases like ulcerative colitis mapped to gastrointestinal tissue. Some were more surprising, however. For example, systemic lupus erythematosus, Kawasaki disease (a form of large vessel autoimmune vasculitis), and primary biliary cirrhosis all mapped mostly to B cells. One can imagine large genetic/epigenetic screens such as this one being used in the future to help researchers narrow down the increasingly large field of potential players in a particular condition for more in-depth large-scale-omics analyses; future similar studies may also allow researchers to predict the most likely involved cell types to study for potential therapeutics. Multi-omics, integrated computational analyses can also be quite informative when tasked with closely examining a single pathogenic tissue. As an example of this, in 2018 Steinberg and colleagues published an integrative and multi-omics analysis of cartilage from osteoarthritis (OA) patients, and offers a good example of how such state-of-the-art studies can be used to distill enormous amounts of data to actionable targets. In their study, they collected osteochondral samples from patients undergoing total knee joint replacements, both eroded and intact sections from within the same joint, as well as control cartilage samples from non-OA individuals, in both a discovery and two replication cohorts. They then set out do examine proteins that were differentially present in the two disease states using liquid chromatography-mass spectrophotometry (LC-MS) technique, mRNA gene expression using RNA-Seq, and epigenetic patterns (specifically, DNA methylation) using Illumina’s genomewide DNA methylation microarray system. As expected, they found a large number of differences in each domain; 209 proteins were differentially abundant, 349 genes were differentially expressed from an mRNA perspective, and 271 differentially methylated regions were identified from an epigenetic perspective (Fig. 2.6). The important next step, which has only been possible with technological and computational advances over the past few years, was the integration of these data across multiple-omics domains. They found 49 genes which differed in at least 2 domains, and three genes that exhibited significant evidence for OA involvement across all three domains: aquaporin 1 (AQP1), the collagen 1 gene (COL1A1), and CLEC3B gene, which encodes tetranectin, a regulator of fibrinolysis. All three of these genes were upregulated at both a protein and mRNA level, and also exhibited reduced DNA methylation at all CpG probes associated with them included in the Illumina arrays. Interestingly, of the 49 genes with differential regulation across at least 2 domains, fully one third had not been previously implicated in OA pathogenesis.

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Fig. 2.6 Overview of genes identified as associated with osteoarthritis in human cartilage from a multi-omics perspective. Adopted from Steinberg et al. (2017)

An important consequence of this sort of multi-omics domain is the ability of researchers to hone in on potentially important, but previously unrecognized, avenues for treatment. In this study, they applied their list of 49 genes with cross-domain association with OA to Drugbank (Law et al. 2014), a comprehensive databank which lists information on drug targets, and identified ten drugs which had actions on nine of the 49 dysregulated proteins, all of which already had Food and Drug Administration marketing authorization for use in human patients. Some were expected, including non-steroidal anti-inflammatory drugs, but a few were novel, including vitamin K1 (phylloquinone), an antipsychotic/antiemetic (trifluoperazine), and a drug used to treat elevated cholesterol (ezetimibe), among others. As technology continues to develop, and the costs of performing this sort of global analysis drops, future epigenetic studies will no doubt more and more frequently include just this sort of large, multi-omics approach to data analysis, and will likely substantially benefit patients by identifying previously unrecognized druggable targets in various epigenetically driven diseases.

2.5 Summary In this chapter, we have highlighted the history of the discovery of epigenetic control mechanisms, which in many ways paralleled the discovery of the DNA code itself. We then highlighted a few ways in which epigenetics has changed the way we think about both basic biological processes and the pathogenesis of the complex human

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disease. We began with a discussion of the epigenetics of “normal” aging, and went on to discuss the recent development of an epigenetic “clock”. Alterations in the rate of epigenetic aging have been demonstrated to be associated with a variety of chronic human diseases; furthermore, interventions that slow aging also appear to slow the rate of epigenetic aging, suggesting that antiaging interventions may have widespread epigenetic effects. We then discussed a few examples of a nonpathogenic role for epigenetics in clinical medicine: the development of epigenetic biomarkers both for the presence of disease, but also as predictors of response to particular therapies. Finally, we exampled two examples of complex, modern epigenetic studies, which leverage massive amounts of data from multiple biological domains to infer the ways in which epigenetic modifications affect gene expression at a transcriptomic, proteomic, and whole-organism level. The ways in which epigenetic mechanisms have contributed to our understanding of disease pathogenesis is nothing short of remarkable; given its meteoric rise in importance over the past 100+ years, there is no doubt that the study of epigenetics in human disease has a bright future indeed.

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Chapter 3

Epigenetic Methods and Twin Studies Angela Ceribelli and Carlo Selmi

Abstract Genomic predisposition fails to fully explain the onset of complex diseases, which is well illustrated by the largely incomplete concordance among monozygotic twins. Epigenetic mechanisms, including DNA methylation, chromatin remodeling, and non-coding RNA, are the link between environmental stimuli and disease onset on a permissive genetic background in autoimmune and chronic inflammatory diseases. Autoimmune diseases now include almost 100 conditions and are estimated to cumulatively affect up to 5% of the world population with a healthcare expenditure superior to cancer worldwide. Many advances in medicine have been made to treat these conditions but there are still gaps, and an innovative and efficient therapy is needed. Systemic autoimmune diseases include rheumatoid arthritis, systemic lupus erythematosus, systemic sclerosis, Sjogren syndrome, polymyositis, and dermatomyositis. Monozygotic twins discordant for any disease offer an ideal study design as they are matched for many factors, including genetic variation and this is a real advantage for epigenetics study. We will herein discuss the available data in the epigenetic differences leading to disease discordance in MZ twins for systemic lupus erythematosus, rheumatoid arthritis, and systemic sclerosis. Keywords DNA methylation · microRNA · Autoimmunity · Autoantibody · Rheumatoid arthritis

A. Ceribelli · C. Selmi (B) Humanitas Clinical and Research Center—IRCCS, via Manzoni 56, 20089 Rozzano, Milan, Italy e-mail: [email protected] A. Ceribelli e-mail: [email protected] C. Selmi BIOMETRA department, University of Milan, Milan, Italy © Springer Nature Singapore Pte Ltd. 2020 C. Chang and Q. Lu (eds.), Epigenetics in Allergy and Autoimmunity, Advances in Experimental Medicine and Biology 1253, https://doi.org/10.1007/978-981-15-3449-2_3

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3.1 Introduction It is becoming increasingly clear that genetic predisposition is insufficient to explain the onset and the pathogenic mechanisms of systemic autoimmune rheumatic diseases (SARDs) (Meda et al. 2011). In fact, the concordance rates of rheumatic diseases are consistently lower than 50% in monozygotic (MZ) twins that share an identical genetic background, thus additional factors play a role in SARDs onset and pathogenesis (Selmi et al. 2012). Environmental factors that may trigger SARDs are still uncertain, spanning from chemicals to infectious agents, but none can explain why each peculiar rheumatic disease develops in a subject at a particular time point during a person’s lifetime. The term “exposome” has been coined recently to describe all those environmental factors, both exogenous and endogenous, which we are exposed to in our life (Bogdanos et al. 2013), and environmental wide association studies (EWAS) have been proposed to investigate the effect of environment on the onset of SARDs and other conditions (Bogdanos et al. 2013). Epigenetics may represent the missing link between genetic predisposition and the onset of autoimmune diseases, and it is represented by mechanisms such as DNA methylation, histone changes, and microRNAs expression, contributing to the epigenome and characterizing specific diseases (De Santis and Selmi 2012). For these reasons, applying epigenetic methods to the study of SARDs may be important to better understand disease mechanisms and to identify ideal targets for new personalized treatments as suggested by similar data in cancer patients (De Santis and Selmi 2012). In this chapter, we will describe the most common epigenetic methods used in the study of SARDs, and the results obtained from epigenetic studies in sets of twins affected by different rheumatic conditions.

3.2 Epigenetic Methods Applied to Rheumatic Diseases The term “epigenetics” refers to the analysis of heritable changes that do not involve alterations in the DNA nucleotide sequence (Dupont et al. 2009). A vast number of epigenetic modifications happen during our lifespan to maintain good health. Epigenetic changes can modify the expression of specific genes without changing nucleotides, and they occur fundamentally both during development and our entire lifespan. The onset of specific diseases may thus depend on the changes that affect not only specific genes, as in the case of cystic fibrosis, but also epigenetic modifications such as DNA methylation, histone modifications, and microRNA analysis (Dupont et al. 2009) which are thought to be involved in multifactorial conditions such as SARDs (De Santis and Semi 2016). DNA methylation and histone changes are the two major changes contributing to the epigenome of a cell, and their role has been studied in the last two decades in diseases such as Systemic Lupus Erythematosus (SLE) (Ballestar et al. 2006). In

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SLE, global and gene-specific DNA methylation changes have been demonstrated to occur, and histone deacetylase inhibitors reverse the altered expression of multiple genes involved in the onset and pathogenesis of SLE (Ballestar et al. 2006). DNA methylation occurs in CpG dinucleotides at the 5 position of cytosine in the promoter region, causing functional consequences such as transcriptional repression, and tissue-specific genes may be silenced by promoter methylation (Ballestar et al. 2006). The three main types of DNA methyltransferases (DNMTs) involved in genomic DNA methylation are DNMT1, DNMT3A, and DNMT3B. The first one, DNMT1, mainly replicates existing methylation patterns and maintains DNA methylation, while DNMT3A and DNMT3B are involved in establishing new DNA methylation markers and they are called de novo DNA methyltransferase (Pan et al. 2010). The high incidence of twin pairs in which only one of the twins has SLE supports the hypothesis that environmental factors and their effect on epigenetics can affect the onset of the disease. It has been shown in SLE patients that the epigenetic deregulation of genes can contribute to or increase apoptosis and exacerbate the activation of T and B cells (Ballestar et al. 2006). This has been demonstrated by experiments showing that DNA extracted from T cells of SLE patients is hypomethylated compared with the DNA obtained from T cells of normal controls (Pan et al. 2010). However, it is not clear how hypomethylation can finally lead to the onset of SLE and its different clinical and laboratory features (Pan et al. 2010). Further support to the role of DNA methylation in SLE is demonstrated by the effects of DNA demethylation induced by drugs (i.e., 5-azacytidine, procainamide and hydralazine) that are known be responsible for a lupus-like disease (Ballestar et al. 2006). Beside these mechanisms, in recent decades a strong evidence has emerged in support of a role of microRNAs (miRNAs) in several rheumatic diseases from SLE to systemic sclerosis (SSc) (Chouri et al. 2018; Ciechomska et al. 2017; Rossato et al. 2017; Zhou et al. 2017; Christmann et al. 2016; O’Reilly 2015) and Sjogren ¨ Syndrome (SjS) (Yan et al. 2019; Talotta et al. 2019; Wang-Renault et al. 2018). MiRNAs are single-stranded, endogenous non-coding RNAs that can regulate up to 90% of protein-coding genes, and they play a central role in several biological processes including those related to immune and autoimmune responses (Bartel 2004). MiRNAs biogenesis starts in the nucleus and it continues in the cytoplasm, and they are processed by several enzymes from the pri- to the pre-miRNAs status until they are loaded into the argonaute (Ago) proteins that are able to generate the RNAinduced silencing complex (RISC) which allows miRNAs to bind to their targets (Yoda et al. 2013). The mature miRNA finally interacts with the 3 -UTR of its specific messenger RNA (mRNA) to regulate gene expression, thus activating its epigenetic influence on the function of specific disease genes (Carthew and Sontheimer 2009) (Table 3.1). Modifications of the miRNAs profile and resultant up- or down-regulation of affected genes have been described in several autoimmune conditions, including SARDs, and their role as biomarkers is a very active field of research nowadays. Their identification has changed the way we approach genetic and epigenetic predisposition to diseases, as variations in miRNA expression levels in the circulation or in different cells and tissues are disease-specific and they may contribute to the onset of disease.

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Table 3.1 Main epigenetic alterations observed for DNA methylation and miRNAs expression in patients with systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), and systemic sclerosis (SSc) SLE

RA

DNA methylation alterations

MiRNAs altered expression

Hypomethylation of T cells DNA

miR-146a, miR-181, miR-186, miR550-3p are the most relevant to SLE susceptibility

DNA demethylation induced by “lupus-like disease” drugs

Alterations on X-chromosome: responsible for female predominance?

ACPA (+) RA patients have differentially methylated regions compared to ACPA (-) RA twins (i.e., EXOSC1 gene)

miR-155, miR-143 and miR-145, miR-146a, miR-132, miR-16 are the most promising in RA pathogenesis and therapeutic targets

Influence of smoking on epitope homozygosity SSc

Hypermethylation of CpG islands on FLI1 gene promoter region, inducing collagen transcription

MiRNAs activating collagen deposition by SSc fibroblasts: miR-335, miR-180, miR-132, miR-27b, miR-16, miR-15b

Pathologic hypermethylation of Rasal1 promoter region activating fibroblasts and fibrogenesis

MiRNAs stimulating TGF-beta signaling: miR-132

Ko of DNMT3 activated ERK1/2 pathway for fibroblasts regulation

MiRNAs stimulating B cell response: miR-150

We are still lacking the evidence from functional studies which demonstrate the link between altered miRNAs and disease onset, but single nucleotide polymorphisms (SNPs) in predicted miRNA target sites have been shown to alter miRNAs function, thus possibly contributing to disease development.

3.3 Epigenetic Twin Studies in Rheumatic Diseases Twin studies are very powerful tools in the era of epigenetic studies to understand the reasons for disease susceptibility and clinical manifestations (Selmi et al. 2012). In fact, they allow for discriminating whether a complex disease is induced by genetic or environmental factors, in particular in MZ twins that share an identical genetic background. Quite simplistically, a disease with a high concordance rate between MZ twins is believed to have a stronger genetic predisposition, while low concordance rates support an environmental trigger (Bogdanos et al. 2012; Generali et al. 2017). Findings obtained from twin studies suggest the possible role of environmental factors such as infectious agents or chemicals in autoimmune diseases (Selmi et al. 2012), and they may act through (i) breakdown of immune tolerance mediated by polyclonal B cell activation; (ii) direct effects of changing the adaptive and innate immune responses; (iii) modifications of self-antigens (post-translational); and (iv) alterations of DNA methylation as part of epigenetics (Selmi et al. 2012).

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In RA patients it is known that the two class II human leucocyte antigen (HLA) alleles DR4 and DR1 are major genetic contributors to the disease, but their role accounts only for approximately 60% of variation in RA disease susceptibility (MacGregor et al. 2000; Messemaker et al. 2015). We recently demonstrated that human collagen T and B cell epitopes can activate T cell memory response in both HLA-DR4 positive MZ twins discordant for RA, while CD4+ cells are activated only in the RA twin. We also noticed that post-translationally modified collagen epitopes, citrullinated and carbamylated, induce the production of IL-17 in the twin with RA, while IL-4 and even more IL-10 are produced in the healthy twin (De Santis et al. 2016). However, different post-translation modifications in epitopes associated with RA and a specific TCR repertoire both contribute to the T cell response in RA patients, along with DRb1*04 alleles (De Santis et al. 2016). Apart from this genetic predisposition that accounts only partially for the onset of RA, it is clear that epigenetics plays an important role in these patients. In fact, MZ twins with RA and with positive anti-citrullinated protein antibodies (ACPA) have differentially methylated regions compared to ACPA negative twins, and these changes are evident in particular in proximity of the EXOSC1 gene (Gomez-Cabrero et al. 2016; Nevius et al. 2016). Several environmental factors have been proposed as crucial for onset of RA via their influence on epigenetic changes contributing to the disease (Svendsen et al. 2013), but the most well-known factor is smoking, which is strongly associated with RA in MZ twin pairs (OR 12, 95%CI 1.78e513) (Silman et al. 1996). We further note the association of smoking with serum ACPA and the observation that the shared epitope homozygosity significantly increases the risk of developing RA (Pedersen et al. 2007). Of note, smoking also manifests a high concordance rate in MZ compared to DZ twins (Whitfield et al. 2007), and most of the variability in ACPA positive RA twins has been accounted for by non-shared or stochastic environmental factors rather than shared environmental and genetic factors (Hensvold et al. 2015). As for miRNAs altered expression in RA patients, several promising miRNAs have been described in the last decades for their pathogenic and possibly therapeutic function (Ceribelli et al. 2011), and among them the most promising seem to be miR-155, an important regulator of immune cells both in humans and mice (Su et al. 2017), miR-143 and miR-145 that are able to modulate the activity of RA synovial fibroblasts (Hong et al. 2017), and miR-146a, miR-132, and miR-16 which are overexpressed in PBMCs of RA patients and are able to influence TNF-alpha expression (Pauley et al. 2008). Another condition in which epigenetics and twin studies have become promising in recent years is SLE, a condition associated with variable heritability, with pairwise concordance rates of 11–50% in MZ twins (Deapen et al. 1992; Block et al. 1975, 1976). The relative risk for a twin to develop SLE compared to the other twin is estimated to be 315, while for parents and siblings the RR is 11–23 (Kuo et al. 2015). However, the clinical phenotype of SLE patients is very heterogeneous and it is not clear what factors influence the appearance of a phenotype or the other, as heritability accounts for up to 43.9%, shared environmental factors up to 25.8%, and non-shared environmental factors up to 30.3% (Kuo et al. 2015). Genetics play a

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significant role in SLE development, and several loci and genes have been reported to be associated with SLE onset (i.e., IRF5, PTPN22, CTLA4, STAT4, and BANK1), even though none is enough for triggering SLE (Ghodke-Puranik and Niewold 2015). Thus, epigenetic changes are involved in the susceptibility to SLE and may play a role in disease onset and pathogenesis similarly to genetic predisposition. This has been clearly demonstrated by epigenetic studies on DNA methylation showing the presence of an altered profile of micro- and long non-coding RNA that is altered on the inactive X-chromosome, thus suggesting a possible explanation of female prevalence of SLE (Odhams et al. 2017). Data on X-chromosome inactivation and differences in X monosomy between SLE women and controls are still inconclusive, and this area of analysis on epigenetics still needs further studies (Invernizzi et al. 2007, 2008). Another epigenetic mechanism studied in SLE patients is represented by miRNAs, as altered expression patterns have been identified in different cell types in SLE patients compared to controls (Dai et al. 2007). Seventy-two lupus susceptibility genes have been analyzed and shown to play a role in SLE, as they contain potential multiple target sites for over 140 conserved in mammals microRNAs (Vinuesa et al. 2009). In particular, three miRNAs, namely, miR-181, miR-186, and miR-590-3p are considered as the most relevant to SLE susceptibility, as they target over 50% of all lupus susceptibility genes (Vinuesa et al. 2009) and are considered significantly related to SLE disease predisposition. Several other miRNAs have been reported in recent years as associated with SLE onset, and one of the most studied is miR-146a which seems to be correlated to specific disease manifestations (i.e., anemia) through its influence on STAT1, a critical signaling molecule that influences the production of type-1 interferon (I-IFN), CCL2, and CXCL10, which are upregulated in SLE (Dominguez-Gutierrez et al. 2014). Besides RA and SLE, another rheumatic disease in which epigenetic studies in twins are becoming more and more important is Systemic Sclerosis (SSc) (Generali et al. 2017). SSc is a rare autoimmune disease which can develop in several different phenotypes, a diffuse form and a limited one based on the extent of skin fibrosis, and it is characterized by peculiar autoantibody production that has both a diagnostic and prognostic value (Singh et al. 2019). Only limited data are available on twin studies in SSc, but these show a marginal pairwise concordance in both MZ and DZ twins, of 4.2% and 5.6%, respectively, with higher concordance rates for ANA which is estimated to be 90% and 40%, respectively (Feghali-Bostwick et al. 2003). However, the difficulty in studying SSc is also related to the heterogeneity of clinical and laboratory features of the disease, even though epigenetic studies are adding knowledge to this condition, in particular DNA methylation (Bossini-Castillo et al. 2015) and miRNAs expression analysis (Aslani et al. 2018). In detail, the DNA methylation profile of skin biopsies of SSc patients has shown hypermethylation of CPG islands in the FLI1 (Friend leukemia integration-1) gene promoter region, which is important for its function in suppressing the collagen transcription via the sp-1-dependent pathway (Czuwara-Ladykowska et al. 2001; Wang et al. 2006). Thus FLI1 functions as a negative regulator of the extracellular matrix and it is regulated by epigenetic modification of CpG islands in SSc fibroblasts (Wang et al. 2006). Other epigenetic findings have shown that long-term exposure of kidney fibroblasts

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to TGF-beta, a profibrotic factor, leads to the activation of the enzyme DNMT1 and to the pathologic hypermethylation of the Rasal1 promoter region thus activating fibroblasts and fibrogenesis (Bechtel et al. 2010). The enzyme DNMT3 is crucial instead in silencing pathways of regulatory genes, as shown by the fact that knocking down DNMT3 results in the inhibition of expression of the Ras association domain family 1 isoform A (RASSF1A) expression, responsible for the activation of the ERK1/2 signaling pathway fundamental for the regulation of fibroblast formation in SSc patients (Tao et al. 2014). As for the role of miRNAs in SSc, we can divide miRNAs in two main groups: miRNAs which activate collagen production by SSc fibroblasts (i.e., miR-335, miR-150, miR-132, miR-27b, miR-27a, miR-16, and miR15b) and those that influence SSc pathogenesis through TGF-beta signaling (i.e., miR-132) and B cell response (i.e., miR-150) (Aslani et al. 2018; Huang et al. 2015).

3.4 Conclusions Despite the remarkable progress in the understanding of the etiology of SARDs, several unanswered questions remain with regard to the pathogenesis and preventive strategies for various conditions, particularly SLE, RA, and SSc. A better understanding of the genomic susceptibility and the epigenetic changes may help to identify subjects at increased risk of developing overt disease in the presence of serum autoantibodies and possibly establish preventive measures. In fact, susceptibility genes identified in the past years cannot fully explain the high degree of heritability of SARDs suggested by twin studies, and the epigenetic modifications inherited by the next generation might in part be responsible for this discrepancy. Furthermore, somatic epigenetic modifications may be triggered by diverse environmental exposures and change the individual disease susceptibility. Numerous limitations have to be kept in mind when interpreting methylation studies, especially if studies are performed on a complex tissue, as every cell type has its unique epigenome. In addition, changes in DNA modifications caused by the microenvironment (e.g., inflammatory and hypoxic microenvironments or the microbiome) that are only transient in nature (i.e., not corresponding to the original definition of epigenetics) may also be identified. Although their discovery will not help as biomarkers to identify individuals at risk for SARDs, the mechanistic understanding of the pathways involved in these “epigenetic” modifications may contribute to a better understanding of disease pathogenesis and can help to discover novel drug targets. Ultimately, the study of twins remains a powerful tool in the investigation of individual determinants of complex disease onset. Acknowledgements This work was supported by the Italian Ministry of Health grant PGR00771 for the Italy–China collaboration.

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Selmi C, Leung PS, Sherr DH, Diaz M, Nyland JF, Monestier M et al (2012b) Mechanisms of environmental influence on human autoimmunity: a National Institute of Environmental Health Sciences expert panel workshop. J Autoimmun 39:272–284 Silman AJ, Newman J, MacGregor AJ (1996) Cigarette smoking increases the risk of rheumatoid arthritis. Results from a nationwide study of disease-discordant twins. Arthritis Rheum 39:732–735 Singh D, Parihar AK, Patel S, Srivastava S, Diwan P, Singh MR (2019) Scleroderma: an insight into causes, pathogenesis and treatment strategies. Pathophysiol: Off J Int Soc Pathophysiol 26:103–114 Su LC, Huang AF, Jia H, Liu Y, Xu WD (2017) Role of microRNA-155 in rheumatoid arthritis. Int J Rheum Dis 20:1631–1637 Svendsen AJ, Kyvik KO, Houen G, Junker P, Christensen K, Christiansen L et al (2013) On the origin of rheumatoid arthritis: the impact of environment and genes—a population based twin study. PLoS One 8:e57304 Talotta R, Mercurio V, Bongiovanni S, Vittori C, Boccassini L, Rigamonti F et al (2019) Evaluation of salivary and plasma microRNA expression in patients with Sjogren’s syndrome, and correlations with clinical and ultrasonographic outcomes. Clin Exp Rheumatol 37 Suppl 118(3):70–77 Tao H, Yang JJ, Chen ZW, Xu SS, Zhou X, Zhan HY et al (2014) DNMT3A silencing RASSF1A promotes cardiac fibrosis through upregulation of ERK1/2. Toxicology 323:42–50 Vinuesa CG, Rigby RJ, Yu D (2009) Logic and extent of miRNA-mediated control of autoimmune gene expression. Int Rev Immunol 28:112–138 Wang Y, Fan PS, Kahaleh B (2006) Association between enhanced type I collagen expression and epigenetic repression of the FLI1 gene in scleroderma fibroblasts. Arthritis Rheum 54:2271–2279 Wang-Renault SF, Boudaoud S, Nocturne G, Roche E, Sigrist N, Daviaud C et al (2018) Deregulation of microRNA expression in purified T and B lymphocytes from patients with primary Sjogren’s syndrome. Ann Rheum Dis 77:133–140 Whitfield KE, King G, Moller S, Edwards CL, Nelson T, Vandenbergh D (2007) Concordance rates for smoking among African-American twins. J Natl Med Assoc 99:213–217 Yan T, Shen J, Chen J, Zhao M, Guo H, Wang Y (2019) Differential expression of miR-17-92 cluster among varying histological stages of minor salivary gland in patients with primary Sjogren’s syndrome. Clin Exp Rheumatol 37 Suppl 118(3):49–54 Yoda M, Cifuentes D, Izumi N, Sakaguchi Y, Suzuki T, Giraldez AJ et al (2013) Poly(A)-specific ribonuclease mediates 3 -end trimming of Argonaute2-cleaved precursor microRNAs. Cell Rep 5:715–726 Zhou B, Zhu H, Luo H, Gao S, Dai X, Li Y et al (2017) MicroRNA-202-3p regulates scleroderma fibrosis by targeting matrix metalloproteinase 1. Biomedicine & Pharmacotherapy = Biomedecine & Pharmacotherapie 87:412–418

Part II

Allergic Diseases

The study of epigenetics in allergic diseases trails that of cancer and autoimmune diseases. However, in recent years, this has gained momentum as an area that may prove to be very helpful in understanding the pathogenesis of allergic diseases. The fact that allergic diseases are generally not monogenic in nature, but polygenic, along with the lack of information of the role that individual genes play in the mechanism of the disease makes it an exciting arena for the study of epigenetics. It is likely that the turning on and off of multiple genes in a network of pathways under the influence of the environment may prove to be the ultimate cause of allergic diseases, but our understanding of how these networks are inter-related is still in its infancy. The following three chapters are on epigenetics in allergic rhinitis and asthma, food allergy and atopic dermatitis.

Chapter 4

The Role of Genetics, the Environment, and Epigenetics in Atopic Dermatitis Zhanglei Mu and Jianzhong Zhang

Abstract Atopic Dermatitis (AD) is a common inflammatory disease with a genetic background. The prevalence of AD has been increasing in many countries. AD patients often have manifestations of pruritus, generalized skin dryness, and eczematous lesions. The pathogenesis of AD is complicated. The impaired skin barrier and immune imbalance play significant roles in the development of AD. Environmental factors such as allergens and pollutants are associated with the increasing prevalence. Many genetic and environmental factors induce a skin barrier deficiency, and this can lead to immune imbalance, which exacerbates the impaired skin barrier to form a vicious cycle (outside–inside–outside view). Genetic studies find many gene mutations and genetic variants, such as filaggrin mutations, which may directly induce the deficiency of the skin barrier and immune system. Epigenetic studies provide a connection between the relationship of an impaired skin barrier and immune and environmental factors, such as tobacco exposure, pollutants, microbes, and diet and nutrients. AD is a multigene disease, and thus there are many targets for regulation of expression of these genes which may contribute to the pathogenesis of AD. However, the epigenetic regulation of environmental factors in AD pathogenesis still needs to be further researched. Keywords Atopic Dermatitis · Epigenetics · Genetics · Skin barrier · Filaggrin

4.1 Introduction Atopic Dermatitis (AD) is a common chronic inflammatory skin disease. Patients often present with pronounced itching and chronically relapsing dermatitis. AD may affect one-fifth of the population in many countries, especially in developed countries. AD typically begins during infancy or early childhood, and children with AD have a predisposition to develop asthma and allergic rhinitis. This progression is commonly referred to as the “atopic march”. The interaction of genetic and environmental factors Z. Mu · J. Zhang (B) Department of Dermatology, Peking University People’s Hospital, Beijing, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 C. Chang and Q. Lu (eds.), Epigenetics in Allergy and Autoimmunity, Advances in Experimental Medicine and Biology 1253, https://doi.org/10.1007/978-981-15-3449-2_4

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plays an important role in the development of AD. The pathogenesis of AD shows two marked features, skin barrier dysfunction and immune imbalance. However, the exact mechanism of AD etiology remains to be determined.

4.2 Prevalence The prevalence of AD varies between different countries and regions, and the prevalence changes over time. Since 1999, The International Study of Asthma and Allergies in Childhood (ISAAC) has carried out three-phase surveys for AD prevalence in many countries. Phase Three (1999–2004) showed that the prevalence continued to vary and had changed in different countries and regions of the world (Odhiambo et al. 2009). The prevalence seemed to have reached a plateau of about 20% in the countries with the highest prevalence. For the age group 6–7 years, the data showed the prevalence ranged from 0.9% in India to 22.5% in Ecuador. Higher prevalence was more common in Oceania, and lower prevalence was generally more common in the Indian Subcontinent, the Eastern Mediterranean region, and Northern and Eastern Europe. For the age group 13–14 years, the data showed the prevalence ranged from 0.2% in China to 24.6% in Columbia with the highest values in Africa and Latin America. The global summary prevalence value for ISAAC Phase Three is higher than the comparable value for Phase One (7.9 vs. 6.1%) in the 6–7 year age group, but is lower than Phase one (7.3 vs. 8.8%) in the 13–14 year age group. In adults, the prevalence of AD ranges from 2.1 to 4.9% in Canada, U.S., Europe and Japan, and decreases with age (Barbarot et al. 2018). A family history of atopic diseases, such as eczema, AD, allergic rhinitis and asthma, maybe a relevant risk factor for the offspring. It is estimated that approximately 70% of patients with AD have a positive family history. In a U.K. cohort study, there was a strong association between parental eczema and childhood AD: odds ratio 1.69 (95% CI 1.47–1.95) for maternal eczema only, 1.74 (95% CI 1.44–2.09) for paternal eczema only, and 2.72 (95% CI 2.09–3.53) for eczema in both parents (Wadonda-Kabondo et al. 2004). In an Italian cohort study, parental history of AD and/or asthma was associated with an increased risk of AD (RR 1.5, 95% CI 1.1–2.0) (Parazzini et al. 2014). A German birth cohort study showed that at the age of 20, 18.5% of the subjects with allergic parents had 2 or 3 concurrent allergy diseases as compared to only 6.3% of those with nonallergic parents (Gough et al. 2015). In addition, twin studies showed that the pairwise concordance rate was 0.72–0.86 in monozygotic and 0.21– 0.23 in dizygotic twin pairs (Larsen et al. 1986; Schultz Larsen 1993). Relative to the general population, there is a sevenfold increased risk of AD in the co-twin of an affected monozygotic twin, compared with a threefold increased risk in the co-twin of an affected dizygotic twin (Thomsen et al. 2007).

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4.3 Clinical Features Pruritus is often the main symptom of AD patients, who often have generalized skin dryness. Eczematous lesions typically show age-related morphology and distribution. In infants, the lesions are generally acute, mainly on the face and the extensor surfaces of the limbs. From age 1 to 2 years onwards, the skin lesions show polymorphous manifestations, particularly in flexural folds. If presenting early in infancy, AD generally may improve significantly by about 5 years of age in about 50% of patients, even as asthma or allergic rhinitis begin to appear. Adolescents and adult patients often present with lichenified and excoriated plaques of the flexural regions, wrists, ankles, and eyelids. The types of AD lesions depend on the stage of the disease. Acute lesions show diffuse erythematous patches and oozing papulovesicles; subacute lesions appear red, dry, and scaly; chronic lesions have scaly patches and plaques with excoriation and lichenification. Some nonspecific clinical features such as hyperlinear palms and soles are mainly seen in patients with filaggrin (FLG) mutations or ichthyosis vulgaris (Weidinger and Novak 2016).

4.4 Diagnosis AD is a difficult disease to define because it has a wide spectrum of dermatological manifestations. As a result, there is a disagreement about the definition of some features. During the past decades, various lists of diagnostic criteria for AD have been proposed. In 1980, Hanifin and Rajak prompted the first diagnostic criteria for AD (Hanifin 1980). The criteria include four major and 23 minor criteria and are often used in clinical trials. However, there are some tests that are not often used in routine clinical practice, and are not suitable for population-based studies. U.K. diagnostic criteria were proposed in 1994 by Williams et al., including one mandatory and five major criteria (Williams et al. 1994). The U.K. diagnostic criteria are all noninvasive and designed for clinical and epidemiological studies, and now it is the most extensively validated. In 2016, we carried out a hospital-based study and proposed Chinese diagnostic criteria for adolescent and adult AD (Liu et al. 2016). The criteria must have “symmetrical eczema/dermatitis for more than 6 months,” plus one or more of the following: “personal and/or family history of atopic diseases,” and “elevated total serum IgE level and/or positive allergen-specific IgE and/or eosinophilia.” The criteria are simple and sensitive for the diagnosis of AD in Chinese adults and adolescents.

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4.5 Pathogenesis The pathophysiology of AD is complex and multifactorial, involving elements of genetics, environmental factors, microbiota, skin barrier dysfunction, and immune imbalance. Initially, both a defective epidermal permeability and a predisposition to secondary infection were well-accepted features of AD. These abnormalities were widely assumed to reflect the downstream consequences of a primary immunologic abnormality (inside–outside view). However, Elias et al. proposed that the permeability-barrier abnormality in AD is not merely a phenomenon but rather the driver of disease activity (outside–inside–outside view) because: (1) the extent of the permeability-barrier abnormality parallels severity of disease; (2) both clinically spared skin sites and skin cleared of inflammation for as long as 5 years continue to display significant barrier abnormalities; (3) emollients may improve the disease; and (4) specific replacement therapy for prominent lipid abnormalities involved in AD not only repairs the permeability-barrier abnormality but also constitutes effective anti-inflammatory therapy (Elias et al. 2008). Presently, there is accumulating evidence in support of the outside–inside–outside view.

4.5.1 Skin Barrier The function of the skin barrier is largely dependent on the stratum corneum (SC), the outermost layer of the epidermis. The SC formation follows a regulated process of keratinocyte differentiation. In the stratum granulosum (SG), keratinocytes start to produce keratohyalin granules and lamellar bodies. Keratohyalin granules contain intracellular components of the SC (i.e., FLG, loricrin, and keratin filaments), and lamellar bodies contain extracellular components (i.e., lipids, corneodesmosin, and kallikreins). In the SC, keratinocytes become flattened and denucleated, and their membranes are replaced by the cornified envelope (CE). At the transition from SG to SC, lamellar bodies are secreted into the intercellular space between the corneocytes and filled with lipids (Egawa and Kabashima 2016). The CE is a specific structure formed beneath the cell membranes of corneocytes, comprising highly cross-linked proteins anchored by extracellular lipids. This structure acts as a vital physical barrier of the SC. In keratinocytes, envoplakin, periplakin, and involucrin become cross-linked to each other by transglutaminase (TG) 1 and TG5. These are rigidly linked in the CE, and provide mechanical stability to the corneocytes. In the SG, loricrin and small proline-rich proteins are cross-linked by TG3, and then they are cross-linked to the involucrin scaffold by TG1 and TG5. FLG plays a pivotal role in the function of the skin barrier. In the SG, FLG is produced as a polymer of 10–12 linked repeats of FLG monomer (profilaggrin) and stored in keratohyalin granules. At the transition to the SC, profilaggrin is cleaved to FLG monomers by proteases. The FLG monomers are attached to keratin filaments. At the upper layer of the SC, FLG becomes dissociated from the keratin filaments,

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and then FLG are degraded to free amino acids, including glutamine, arginine, and histidine. These amino acids are converted into urocanic acid (UCA) and pyrrolidine carboxylic acid (PCA) by caspase 14, calpain 1, and bleomycin hydrolase. UCA and PCA are involved in maintaining the acidic environment of the skin. UCA may partly protect the skin from UV damage, and PCA is a major constituent of natural moisturizing factors (NMF), which are responsible for skin hydration. The intercellular lipids are composed of a heterogeneous mixture of ceramides, free fatty acids, and cholesterol, which are produced in the SG and stored in lamellar bodies. During the transition to the SC, these lipids are secreted into the extracellular space, and form lipid lamellae in the intercellular space between corneocytes. Adhesion of adjacent corneocytes is dependent on the corneodesmosome. In the corneodesmosome, desmoglein-1 (DSG-1) and desmocollin-1 interact with plakoglobin and plakophilins, which bind to envoplakin and periplakin. The envoplakin and periplakin heterodimers are cross-linked to the involucrin scaffold to bind keratin filaments. The corneodesmosin is an important modulator of corneodesmosomal adhesion. It is stored in the lamellar bodies and secreted into the intracellular space of the SC to interact with cadherin proteins and support their adhesion. Tight Junctions (TJs) are other structures required for the integrity of the skin barrier. TJs are composed of transmembrane proteins (i.e., claudin and occludin families) and several cytosolic scaffold proteins. In the skin, TJs seal adjacent keratinocytes in the SG and form a barrier for water and solutes. It is speculated that TJs may have both the function of inside–outside and outside–inside barrier to ions. Corneocyte desquamation is an important aspect of SC homeostasis, and this process is mainly regulated by a proteolytic cascade of KLK-related peptidases: KLK-5, KLK-7, and KLK-14. These proteases are members of a family of serine proteases. With trypsin-like activity, KLK-5 and KLK-14 can cleave desmoglein. KLK-7, with chymotrypsin-like activity, can hydrolyze corneodesmosin and desmocollin. KLK-5 is capable of activating KLK-7, KLK-14, and itself, suggesting that KLK-5 maybe a primary regulator of the KLK cascade (Cork et al. 2009). The activity of these proteases is pH-dependent with optimum activity at slightly alkaline pH. Their activity is also strictly regulated by the protease inhibitors, including lymphoepithelial Kazal-type 5 serine protease inhibitor (LEKTI), which is encoded by serine protease inhibitor Kazal-type 5 (SPINK5). LEKTI is composed of 15 potential serine proteinase inhibitory domains against KLKs. KLKs and LEKTI are stored in lamellar bodies and delivered into the intercellular space at the SG–SC interface, where the pH is near neutral. Under the neutral environment, the activity of KLK-5 and KLK-7 is inhibited by LEKTI. When the pH is more acidic, the inhibitory function of LEKTI is reduced.

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4.5.2 Skin Barrier and AD The skin barrier function is impaired in AD and is characterized by an increase in transepidermal water loss (TEWL) and microbial infections. The barrier dysfunction plays an important role in initiating and/or exacerbating AD.

4.5.2.1

FLG in AD

There is a large cluster of genes involved in the epidermal differentiation process located on chromosome 1q21, referred to as the epidermal differentiation complex (EDC). The EDC includes FLG, loricrin, involucrin, small proline-rich proteins (SPRRs), S100A family, S100-fusion protein family and CE proteins. FLG mutations cause a change in the expression of FLG and thereby affect skin barrier function. In human subjects, FLG mutations are associated with the arise of AD and ichthyosis vulgaris. The prevalence of FLG mutations in patients with AD ranges from 25 to 50% in Northern European and Asian populations (Sandilands et al. 2007; Nomura et al. 2007). The p.R501X and c.2282del4 are two loss-of-function mutations in the FLG gene, and they show the strongest association for AD. The two loss-of-function variants are carried by about 9% of Europeans (Palmer et al. 2006). In Asians, FLG P478 S and C3321delA are risk factors of AD, the atopic march and recurrent skin infection. In African populations, loss-of-function mutations in FLG2, but not FLG, are associated with increased risk for AD in children (Margolis et al. 2014). FLG mutations are a major predisposing factor and the most significant risk factor for the development of AD, particularly in patients who have early-onset AD and those with persistent AD. Meta-analyses involving thousands of patients confirmed the association of FLG mutations and AD with an overall odds ratio ranging from 3.12 to 4.78 (Rodriguez et al. 2009; van den Oord and Sheikh 2009). The null mutations of FLG in part are involved in about 50% of moderate-to-severe AD patients, but only about 15% of mild to moderate AD may be explained by FLG mutations (Brown and McLean 2009). Compared with AD patients without FLG mutations, patients with FLG mutations have a more persistent course of disease and erythema is more common. In AD patients with allergic sensitization, FLG is considered as the first strong genetic factor. In the mouse model, FLG deficiency alone was shown to decrease the threshold for inflammation following the application of irritants or haptens, and repeated hapten exposure induced severe AD-like manifestations (Scharschmidt et al. 2009). It is hypothesized that FLG mutations drive allergic diseases via increased allergens penetration through the defective barrier. In children with FLG mutations and cat exposure, an increased risk of developing AD appears in the first year of life. FLG mutations were also reported to increase the risk of IgE-mediated peanut allergy. Loss-of-function mutations in FLG confer an overall risk of 1.48–1.79 for asthma, which is limited to those who have AD or a history of the disease (Weidinger et al. 2008; Henderson et al. 2008).

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There is some controversy on the role of FLG in the pathogenesis of AD. One study indicated that FLG null mutations could not predict food allergy, as defined by positive skin prick or specific IgE testing (Tan et al. 2012). In addition, a large number of AD patients do not have FLG mutations, and about 40% of individuals with FLG mutations do not have AD. It appears that FLG mutations may contribute to AD, but it is not sufficient to induce AD alone.

4.5.2.2

SPINK5, LEKTI, and KLKs in AD

SPINK5 and LEKTI play an important role in epidermal barrier homeostasis, including stratum corneum desquamation, lipid barrier construction, and cornified CE. Netherton syndrome, caused by SPINK5 mutations, manifests as severe dermatitis, allergic rhinoconjunctivitis, asthma, and a high serum IgE level. SPINK5 also contributes to the regulation of proteolysis in keratinocyte differentiation and the generation of normal epithelium, and LEKTI is involved in maintaining normal skin permeability. Polymorphisms of SPINK5 are associated with the development and severity of AD in certain populations. The defective function of SPINK5 induces the increased proteolytic activity within the epidermis, as well as enhanced TSLP expression. In the LEKTI-deficient mouse model, KLK-5 induced AD-like skin lesions through the stimulation of protease-activated receptor 2 (PAR-2) (Briot et al. 2009). E420K LEKTI variant is a risk factor for AD via an increase in TSLP expression (Fortugno et al. 2012). Skin pH contributes to skin barrier homeostasis, cell adhesion in the SC, and antimicrobial activity. FLG mutations and external factors may raise skin pH, and the activity of SPINK5, LEKTI, and KLKs largely depends on the skin pH. The elevated pH induces KLKs activation. KLKs can hydrolyze desmoglein, corneodesmosin, and desmocollin, which lead to skin barrier dysfunction. In addition, KLK-5 may activate PAR-2, which upregulates the expression of cytokines, such as TSLP.

4.5.2.3

Lipids and AD

There are defective lipids in the skin of AD patients, with altered expression of enzymes which are involved in the biosynthesis of free fatty acids and ceramides. In the SC, the composition of intercellular lipids is altered in AD patients. In AD skin lesions, short-chain ceramides are increased, leading to aberrant lipid organization and defective skin barrier function, and are associated with AD severity independent of FLG mutations. Researchers have demonstrated that altered composition of stratum corneum intercellular lipids correlates with Staphylococcus aureus (S. aureus) colonization status in AD. Additionally, it has been reported that synthetic omegahydroxyceramides enhances the integrity of the stratum corneum, and accelerates the recovery of damaged skin barrier function by stimulating differentiation (Behne et al. 2000). Lowe et al. also reported that routine lipid replacement reduces the incidence

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of AD during the active treatment period by approximately fifty percent (Lowe et al. 2018). Therefore, the lipid matrix in the cornified layer may play a crucial role as part of the skin barrier.

4.5.2.4

Other Molecules of Skin Barrier and AD

Several transcriptomics studies have reported that IVL, LOR, and LCE2B, and the cell–cell adhesion protein CDSN are significantly downregulated in AD skin lesions. One case-control study showed that a 24-bp deletion in SPRR3 was associated with AD in European cohorts (Kelsell and Byrne 2011). However, there is a discrepancy. A German cohort study did not find the associations in evaluating polymorphisms across 21 EDC genes, except for FLG (Stemmler et al. 2009). In Caucasians, the deletion of LCE3B and LCE3C genes is not associated with AD (Bergboer et al. 2010). The claudin family is a type of TJs transmembrane protein. In claudin1-deficient mice, the skin manifests severe dehydration and increased epidermal permeability without any abnormalities in the SC proteins or lipids. CLDN-1 haplotype-tagging SNPs are associated with AD in the North American population, and expression of claudin-1 was markedly reduced in the non-lesional skin of AD (De Benedetto et al. 2011). The claudin-1 level was inversely correlated with serum IgE level and eosinophils. In addition, IL-4 and IL-13 also enhance keratinocyte claudin-1 expression. Loss-of-function mutations in DSG1, which encodes the desmosome protein desmoglein-1, causes severe dermatitis and multiple allergies in humans. CDSN expression is downregulated by cytokines, including IL-4, IL-13, IL-22, IL-25, and IL-31. In addition, CDSN deficiency resulted in lethal-skin barrier disruption in a mouse model, and enhanced viral penetration in an organotypic skin model (Leclerc et al. 2009). TMEM79 plays a role in the lamellar granule secretory system. A homozygous mutation of TMEM79 is responsible for a spontaneous AD-like phenotype in flaky tail mice (Sasaki et al. 2013). Moreover, a missense SNP of human TMEM79 is significantly associated with AD. Several other genes including LAMA3, OVOL1, and ACTL9 have been reported to be associated with AD (Bin and Leung 2016).

4.5.3 Immune Imbalance of AD 4.5.3.1

Innate Immunity in AD

AD patients are characterized by increased S. aureus colonization and/or infections with a loss of microbial diversity during flares. AMPs, including β- defensin family (hBD-1, 2, and 3), cathelicidins, psoriasin, and ribonuclease (RNase) 7, are crucial for the clearance of microbial pathogens and in maintaining epidermal barrier function.

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In the skin, keratinocytes are the major source of AMPs which are synthesized in the SG, packaged into lamellar bodies, and then excreted into the SC. AMPs may directly interact with pathogens, or modulate the immune response to kill or inhibit the growth of pathogens. AMPs attach to negatively charged phospholipids on the cell walls of pathogens, resulting in membrane destabilization and physical disruption. In skin, AMPs link the innate and adaptive immunity via chemotaxis of DCs and T-cells and maturation and activation of DCs. AMP expression is impaired in AD patients, which may be one of the causes of S. aureus overgrowth and plays a role in the initiation and exacerbation of AD. In AD lesions, hBD-2 and LL-37 expression are decreased. IL-4 and IL- 13 inhibit the expression of hBD-2 and hBD-3, and indirectly inhibit hBD-3 and LL-37 production. However, some studies showed that the induction of hBD-2, hBD-3, and LL-37 was not impaired in AD, and AMP function may be disturbed (Harder et al. 2010; Schittek 2011). In addition, several SNPs of human β-defensin 1 (DEFB1) gene have been found to be associated with AD, and some SNPs correlate with disease severity, hypereosinophilia and specific IgE (Liang et al. 2016). Mutations in toll-like receptors (TLRs) and nucleotide-binding oligomerization domain-like receptors (NLRs) lead to susceptibility to skin infections by microbial pathogens. TLR2 can bind to bacterial lipoteichoic acid, which then induces immunologic responses. Many studies found that TLR2 polymorphisms are associated with AD. The TLR2 polymorphisms R753Q and A-16934T have been found in severe AD patients and in AD patients with other concomitant atopic diseases. TLR2 R753Q and TLR4 D299G mutations have been found in Italian children with severe AD (Salpietro et al. 2011). The TLR2 R753Q mutation modulates the innate and adaptive immune systems via regulation of cytokine production (IL-2, IL-6, IL-8, and IL-12) and alteration of TLR2 and CD36 expression in AD patients. However, a recent study showed that the TLR2 (R753Q and A-16934T) SNPs are not associated with AD in a group of Turkish patients (Can et al. 2017). The TLR4 A-896G mutation was associated with severe AD patients and with complications. Three TLR6 polymorphisms (rs5743794, rs6531666, and rs5743798) have been found in AD children. The TLR9 promoter polymorphism C-1237T has been reported in patients with intrinsic AD. Several NLRs gene polymorphisms in CARD4, CARD12, CARD15, NALP1, NALP12, and NOD1 have also been reported in AD patients. NOD2, a ligand for muramyl dipeptide derived from S. aureus, is also involved in the pathogenesis of AD. The NOD2-deficient mice exhibit increased susceptibility to S. aureus infection in the skin, and polymorphisms of the NOD2 gene are associated with AD (Deshmukh et al. 2009). A disintegrin and metalloproteinase domain-containing protein 17 (ADAM17) maintains skin barrier homeostasis via promoting basal activation of Notch and EGFR signaling. ADAM17 deficient mice manifest AD-like lesions with increased TSLP expression. Zinc finger protein 750 (ZNF750) is expressed in epidermal suprabasal layers and increases in conjunction with keratinocyte differentiation. The ZNF750 gene also regulates epidermal terminal differentiation markers, including FLG and SPINK5. A dominant mutation in ZNF750 has been reported to be associated

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with seborrheic dermatitis and psoriasis-like manifestations. However, the role of ADAM17 in human AD and the relationship between ZNF750 and AD has not been fully elucidated.

4.5.3.2

Th2 Cells and Th2 Cytokines in AD

It is widely accepted that the Th2 phenotype is a critical characteristic of the pathogenesis of AD. Th2 cytokines, such as IL-4, IL-5, and IL-13 are significantly increased in lesional and non-lesional skin in the acute phase of AD. It has been demonstrated that the risk of developing AD increases when higher levels of IL-4 and IL-13 in cord blood were found. IL-4 transgenic mice have been reported to develop AD-like skin lesions spontaneously. IL-13 is a major stimulator of inflammation and tissue remodeling at sites of Th2 inflammation. In clinical trials, dupilumab, a monoclonal antibody which binds to the shared alpha subunit of the receptor for IL-4 and IL13, improves signs and symptoms of AD. In addition, IL-4 and IL-13 influence the innate immune response in AD by downregulation of AMPs. IL-4 and IL-13 are also known to affect lipid and defending expression in the skin barrier unrelated to FLG defects, connecting the barrier defects directly to the immune system. In addition, mepolizumab, a humanized antibody against IL-5, led to only modest improvements in moderate-to-severe AD (Oldhoff et al. 2005). Linkage studies show that different loci are distinctly associated with different phenotypes of AD, indicating a possible separate genetic basis for different forms of AD. IL-4 and IL-13 play a pivotal role in AD. Several distinct polymorphisms of IL-4, IL-13, IL-4 receptor alpha (IL-4RA), IL-5 receptor alpha (IL-5RA), and IL-13 receptor alpha (IL-13RA) have been associated with AD in different populations. A cytokine cluster at 5q31.1 includes IL-4/KIF3A and IL-13/RAD50 and is related to IL-13 expression. The signal transducer and activator of transcription 6 (STAT6) is a key transcription factor in IL-4- and IL-13-mediated responses. STAT6 variants have been found to be associated with allergic diseases. Other cytokine variants have also been identified in AD, including IL-2, IL-5, IL-6, IL-7, IL-9, IL-10, IL- 12, IL-13, IL-18, and IL-31.

4.5.3.3

Th1 Cells and Th1 Cytokines in AD

In the chronic phase of AD, there is a Th1-biased immune response. The switch from Th2 to Th1 may be attributable to the predominant type of DCs. Th1 cells are characterized by the production of IFN-γ, IL-12 and IL-2, TGF-β1, and other cytokines, which are found to be decreased or increased in AD. Some cytokines, such as IL-11 and TGF-β1, seemed to be responsible for tissue remodeling and fibrosis in chronic AD. IFN-γ is reduced in acute AD. However, in chronic AD lesions, IFN-γ acts as a promoter of chronic inflammation, as well as a strong stimulant of tissue remolding. In addition, IFN-γ may induce keratinocyte apoptosis and upregulate the expression of

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FLG in AD. IL-12, another Th1 cytokine, promotes the development and proliferation of T-cells and NK cells, and induces IFN-γ production. IL-12 is elevated in chronic lesions but not acute lesions of AD. Deficiency of IL-12 attenuates inhibition of IL-4 and IL-18, which may increase eosinophils and IgE levels involved in a Th2 type immune response.

4.5.3.4

Th22 Cells and IL-22 in AD

Th22 and associated markers are increased in acute AD with intensification in chronic lesions. IL-22 is produced mainly by Th22 cells, but can also be produced by Th17 cells and NK cells. High levels of expression of IL-22 has been observed in chronic AD but not in psoriasis or normal controls. IL-22 levels are positively associated with the severity of AD, and IL-22 may promote epidermal hyperplasia in AD (Nograles et al. 2009). IL-22 expression may also be induced by staphylococcal enterotoxin B and α-toxin from S. aureus. IL-22 exerts a synergistic effect with IL-17, and together these two cytokines regulate AMPs in the epidermis, such as hBD-2 and hBD-3, as well as matrix metalloproteinase. IL-22 may inhibit the differentiation of keratinocytes and promote their migration. In addition, IL-22 downregulates FLG and profilaggrin processing enzyme expression, and then exaggerates the epidermal barrier dysfunction in AD.

4.5.3.5

Th17 Cells and IL-17 in AD

Th17 cells have the capacity to produce IL-17, IL-22, and IL-26. In AD patients, Th17 cells are increased both in the peripheral blood and acute lesions, with the percentage of cells correlating with the AD severity. In acute AD, IL-17 is highly expressed, but IL-17 expression is reduced, or even undetectable in the chronic phase (Souwer et al. 2010). IL-17 serves to promote inflammation through stimulating keratinocytes to produce cytokines, such as GM-CSF, TNF-alpha, IL-8, CXCL-10, and VEGF. IL17 may also induce specific B cells to produce antigen-specific IgE, indicate a role for IL-17 in the pathogenesis of acute AD. Deficiency in Th17 cells is thought to be partially responsible for the susceptibility to chronic bacterial infection in AD. IL-17 can induce S100 protein and pro-inflammatory cytokine expression, which are responsible for eosinophil- and neutrophil-mediated inflammation. In mice with OVA leading to AD-like model, epicutaneous sensitization may induce the cutaneous expression of IL-17 and IL-17-producing T cells in the draining lymph nodes and spleen, and increased serum IL-17 levels. In an AD-like mouse model with repeated hapten application, IL-17A is necessary for the development of skin inflammation, IL-4 production, and IgE induction (Mizutani et al. 2015). In addition, IL-17A is detected in the AD-like dermatitis of flaky tail mice.

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Dendritic Cells (DCs) in AD

As one type of professional antigen-presenting cells, DCs capture antigens, allergens, and microbes, and prime naive T cells into immunogenic or tolerogenic subsets. In the skin, Langerhans cells (LCs) reside in the epidermis, and dermal DCs are found in the dermis. LCs may induce Th2 responses to drive naive CD4 T cells into Th2 cells. LCs are also responsible for the initiation of AD under the influence of TSLP. It is reported that in the AD-like mouse model upon epicutaneous sensitization with OVA, LCs are essential to the induction of clinical manifestations and IgE elevation via the action of TSLP (Nakajima et al. 2012). There is a decreased number of plasmacytoid DCs in AD lesions, and this may be associated with a lack of chemoattractant for plasmacytoid DCs. The reduced number of plasmacytoid DCs, which is crucial in immune responses against viral infections, may contribute to susceptibility to viral infections in AD skin.

4.5.3.7

Mast Cells in AD

Mast cells are bone marrow-derived cells that undergo maturation in tissues. Mast cells and basophils can be sensitized by IgE via the high-affinity IgE receptor (FcεRI). The binding of FcεRI and IgE induces mast cells to release three classes of molecules: (1) preformed chemical and protein mediators, such as histamine, serotonin, heparin, and major basic protein; (2) lipid mediators, such as prostaglandins, leukotrienes, and platelet-activating factor (PAF); (3) preformed and/or de novo synthesized growth factors, cytokines, and chemokines, such as TNF-α, TGF-β, IL-4, IL-5, IL-10, IL-12, and IL-13. Mast cells regulate the recruitment and function of multiple cell types involved in the formation of skin lesions in AD. Mast cells can modulate the differentiation of naive T cells, as well as their activation and migration by chemotactic factors and adhesion molecules on endothelial cells. They also induce Th2 polarization through the suppression of IL-12 production and play roles in B cell development and IgE synthesis. Mast cell-derived chemokines induce the recruitment of eosinophils and the production of pro-inflammatory cytokines in keratinocytes. The number of mast cells is normal in acute AD lesions but is significantly increased in chronic lesions. In an AD-like mouse model, the degranulation of mast cells has been shown to correlate with the severity of AD (Zhao et al. 2006). Histamine and tryptase produced by mast cells play a role in pruritus and the secondary skin barrier defect. The chemokine CCL1 is upregulated specifically in the serum of patients with AD. In addition, TSLP in AD patients can activate mast cells to produce Th2 cytokines. Despite all these above effects of mast cells, the precise mechanism of mast cells in AD is still unclear.

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Eosinophils in AD

Eosinophils are derived from CD34+ hematopoietic progenitor cells in the bone marrow. IL-3, IL-5, and GM-CSF are important cytokines in eosinophil generation, maturation, and differentiation. Eosinophils are found in lesional skin and peripheral blood eosinophilia is present in many patients with AD. Eosinophilic infiltration into tissue had also been shown to correlate with disease severity of AD. Eosinophils play an important immunoregulatory role by secreting many cytokines and chemokines. The level of IL-16 is significantly higher in patients with AD (Frezzolini et al. 2002). Moreover, IL-16 has been shown to induce the exacerbation of AD. The Th2 cytokines, IL-4 and IL-13, increase eosinophil recruitment to eczematous skin by enhancing CCL26 (eotaxin-3) production by keratinocytes. Eotaxin-1, also called CCL11, is an important chemokine for eosinophil recruitment and contributes to inflammation in AD. Eotaxin levels are increased in the blood of patients with AD and eotaxin is expressed in AD lesions. RANTES/CCL5 is also a potent chemoattractant for eosinophils. High levels of CCL5 protein have been found in the scales of AD lesions. Moreover, serum CCL5 levels are significantly increased in patients with AD, although they do not correlate with clinical scores of patients.

4.5.3.9

TSLP in AD

TSLP is an IL-7-like cytokine initially identified in the culture supernatant of a thymic stromal cell line. TSLP is mainly produced by keratinocytes and other epithelial cells. Recent studies found that other cells such as mast cells, fibroblasts, and dendritic cells can also produce TSLP (Mu et al. 2014). TSLP exerts its biological functions by binding to a heterodimeric receptor consisting of the IL-7 receptor alpha-chain (IL-7Rα) and the TSLP receptor chain (TSLPR). TSLPR is expressed on a variety of cell types, including T cells, B cells, dendritic cells, and monocytes. Pro-inflammatory cytokines, Th2-related cytokines, and IgE induce or enhance expression of TSLP in keratinocytes. Skin barrier injury, increased epidermal endogenous protease activity, decreased epidermal barrier function also contribute to TSLP expression. In addition, environmental factors such as TLR ligands, danger-associated molecular patterns, virus, allergens, helminths and chemicals can trigger TSLP production. TSLP expression is increased in the skin from AD patients, and serum TSLP concentration is elevated in AD children. TSLP overexpression in keratinocytes induces the spontaneous development of an AD-like disease in mice. TSLP triggers DCmediated Th2 inflammatory responses and induces the production of IL-4, IL-5, IL-13, and TNF-α. TSLP also stimulates DCs to release CCL17 and CCL22, which can attract and expand T cells that produce IL-5 and IL-13. In addition, TSLP can promote Th2 responses through its actions on mast cells, epithelial cells, macrophages, and basophils (Han et al. 2017). TSLP thus plays an important role in the Th2 skewing response in AD.

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Other Molecules of the Immune System in AD

The IL-1 family of cytokines also contributes to the pathogenesis of AD. Members of this family include IL-1α, IL-1β, IL-18, and IL-33. IL-1α, IL-1β IL-18, and IL-1R antagonist levels are increased in the uninvolved skin of patients with moderateto-severe AD. IL-18R1/IL-18RAP is involved in the pathogenesis of AD and is a biomarker of AD severity. IL-33 and the receptors, ST2 and IL-1RAcP, are increased in lesional skin of AD patients. The IL-33/IL-1RL1 axis triggers the release of several pro-inflammatory factors and induces systemic Th2-type inflammation. IL-18 gene variants are associated with the development of AD. Chemokines are also involved in the immune response of AD. Polymorphisms of RANTES have been reported to be associated with AD, and G-401A is associated with allergen sensitization. Although eotaxin SNPs in the promoter and exon regions are not associated with AD, two SNPs in the promoter had been found to be associated with serum IgE. It has been reported that eotaxin SNPs were found in Italian children with extrinsic AD. Haplotypes of the histamine receptor H4 (HRH4) have been found to be associated with AD. Copy numbers of the HRH4 gene are associated with AD in Chinese populations. In studies from Asia, several polymorphisms of FcεRI have been found to be associated with high serum IgE levels and AD. Some loci on chromosome 3q21 have been implicated in both AD and allergic sensitization. CD80 and CD86 that induce the activation of Th2 lymphocytes and mediate allergic inflammation have also been mapped to this region. IL-1RL1, MHC, and IL-13 have also been associated with AD and asthma. C11orf30 is associated with AD, asthma, and allergic rhinitis. C11orf30, SLC25A46, and IL-1RL1 have been found to be related to sensitization and allergic diseases.

4.5.4 Interaction of Skin Barrier and Immune Function in AD In AD patients, both affected and unaffected skin are abnormal and in a chronic mild state of inflammation. The impaired skin barrier allows for increased antigens or irritants to be absorbed and enter the skin, leading to sensitization and inflammation. A primarily Th2 polarized response results in different tissues injure and further aggravates the skin barrier damage (Fig. 4.1). It has been shown that damage to the SC modulates the production of cytokines and chemokines by keratinocytes. For instance, tape stripping upregulates TSLP levels in the skin, which polarizes skin DCs to elicit a Th2 type immune response. Skin barrier deficiency may lead to an increase in skin pH, which induces KLKs activation and subsequent inflammation, such as elevated TSLP. Therefore, under certain conditions, the skin barrier abnormality is the primary cause in the development of AD.

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Fig. 4.1 The possible mechanisms of AD. Genetic defects or mechanical injury can induce skin barrier dysfunction, which facilitates the penetration of allergens and microbial pathogens into the skin. The allergens and pathogens lead to the immune imbalance, especially a Th2 polarized response via different cell types, such as DCs. The immune response can exacerbate the impaired skin barrier. In addition, elevated skin pH may activate KLKs to induce skin barrier damage and Th2 response via TSLP

DCs in AD patients have increased high-affinity receptors for IgE, and the binding of antigens and IgE receptors results in an inflammatory cascade. After allergen exposure, DCs induce the release of cytokines promoting Th2 cell differentiation in the impaired skin barrier. TSLP, mainly from keratinocytes, stimulates DCs and drives the subsequent Th2 response. Thus, DCs may be the link between allergen exposure and inflammatory lesions. Th2 responses may induce skin barrier dysfunction through the following mechanisms (1) IL-4 and IL-13 inhibit protein expression of keratinocyte differentiation, especially FLG; (2) IL-4 may inhibit ceramide synthesis; and (3) DSG-3 expression is also inhibited by IL-4 (Elias et al. 2008). In addition, the impaired skin barrier is often accompanied by microbial infection, such as S. aureus, which further decreases the strength of the barrier via inflammation and degradation by serine proteases.

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The above observations indicate that the primary skin barrier dysfunction in AD can stimulate downstream inflammatory mechanisms that may further compromise skin barrier function, creating a potential outside–inside–outside pathogenic loop in AD.

4.5.5 Environmental Factors The increasing prevalence of AD is hard to explain by genetics alone. In fact, our life and living environment is continuously undergoing changes with time. It is well accepted that environmental factors are major components in the development and exacerbation of AD. Factors are diverse and include allergens, soap and detergents, and pollutants. Other factors that may increase the risk of developing AD include type of daycare exposure, delivery during childbirth (i.e., vaginal vs. cesarean section), weight at birth, breast-feeding, diet (i.e., dietary intake of fish and omega-3 fatty acid), level of parental education, place of dwelling (i.e., rural vs. urban setting), socioeconomic status, smoking, and pets, but data is sometimes variable and inconclusive (Chiesa Fuxench 2017). Allergens play a pivotal role in the pathogenesis of AD, for instance, many AD patients are sensitized to house dust mite (HDM). It is noted that allergen patterns shift with age. In infants, food allergens play a role in severe AD, but inhalant allergens and microbials may be more important in older individuals. A study showed that grass-allergen-sensitized adults with AD have worsening of their cutaneous symptoms after being exposed to grass pollen (Werfel et al. 2015). In patients without elevated IgE or clinical allergy, HDM can trigger AD-like lesions through nonallergic mechanisms. These include (1) HDM increases keratinocyte proliferation; (2) HDM increases expression of IL-22Ra and CCL17/thymus and activation-regulated chemokine (TARC) in the keratinocytes; and (3) the protease Der p1 may induce TSLP expression of keratinocytes. In fact, HDM and cockroach allergens both facilitate barrier breakdown and activate PAR-2. One study showed a higher percentage of samples with HDM from AD patients compared with that of controls, however, there was no difference in their percentage in bedding or clothing between the groups (Teplitsky et al. 2008). This result indicates that the allergen may exacerbate or trigger AD lesions under impaired skin barrier conditions. In modern life, detergents are widely used in cleaning skin. However, detergents may irritate the skin, leading to skin scaling, dryness, tightness and roughness, erythema, and swelling. The use of soap and detergents is one of the most common causes of irritant contact dermatitis of the hands and can trigger flares of AD (Cork et al. 2009). For instance, sodium lauryl sulfate is a standard irritant in the patch test. The detergents often increase TEWL, decrease the skin lipids and raise the skin pH. The elevated skin pH activates KLKs to impair the skin barrier and induce the inflammation. In addition, washing with the soap may decrease the thickness of the

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SC. It is for this reason that many guidelines of AD treatment recommend that AD patients do not use soap or detergents for washing and bathing. The prevalence of AD is higher in areas with hard water and high chlorine concentration. Water hardness is a measure of the amount of calcium carbonate (CaCO3 ) dissolved in water. A study showed that CaCO3 and chlorine levels are strongly correlated, and high domestic water CaCO3 level is associated with an increased risk of AD in infancy. However, the effect of increased chlorine levels was uncertain (Perkin et al. 2016). It is speculated that hard water may contain irritant chemicals, and a larger amount of soap or detergents are required when washing with hard water (Danby et al. 2018). Some common industrial pollutants also are external factors related to the health of skin with and without AD (Ahn 2014). Airborne formaldehyde increases TEWL and skin pH, and it is speculated that formaldehyde may induce cell death and Th2 cytokines and other pro-inflammatory cytokines. Air pollutants are associated with a rise in allergic-type diseases in general, because air pollutants may directly affect the immune response and increase the risk of atopic disease. Exposure to benzene and other chemicals may increase IL-4 expression and Th2 polarization, leading to AD. Painting or new furniture increases the future possibility of AD in children. Other related pollutants include particulate matter 10 (PM10), nitrogen oxide compounds, carbon monoxide, and tobacco smoke. The effects of environmental pollution may partly explain the disparities in the prevalence of AD in children raised in urban and rural environments. Studies have reported an association between vitamin D insufficiency and diseases such as cardiovascular diseases, osteoporosis, and some cancers. Serum 25(OH)D level is mainly associated with consumption of fatty fish, use of vitamin D supplements, area of uncovered skin, use of tanning bed, consumption of margarine and preference for sun (van der Meer et al. 2008). A systematic review showed that there is a link between serum vitamin D levels and severity of AD in children; however, there was weak evidence supporting the improvement of AD with vitamin D supplementation (Huang et al. 2018). A recent study showed that vitamin D can decrease the allergic phenotype of circulating DCs in children with AD, and oral vitamin D supplements reduced expression of surface-bound IgE on pDCs in these children (Cristi et al. 2019). The exact mechanism of vitamin D in the pathogenesis of AD needs further research.

4.6 GWAS in AD There have been large-scale GWASs of AD performed in European, Chinese, Japanese, and Korean populations. More than 30 susceptibility loci have been identified, which are primarily involved in epidermal barrier abnormalities and immune dysregulation.

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In 2009, the first GWAS study of AD identified that rs7927894 on chromosome 11q13.5, located 38 kb downstream of C11orf30 is involved in AD (Esparza-Gordillo et al. 2009). About 13% of European individuals are homozygous for rs7927894[A], and their risk of developing AD is 1.47 times that of noncarriers. In 2011, a GWAS study of AD in the Chinese Han population reported two new susceptibility loci, 5q22.1 and 20q13.33 (Sun et al. 2011). The 5q22.1 region contains TMEM232 and solute carrier family 25, member 46 (SLC25A46), and the TSLP gene is located adjacent to the involved region. The 20q13.33 region contains the TNF receptor superfamily, member 6b (TNFRSF6B) gene that encodes decoy receptor 3 (DCR3). DCR3 is a secreted protein belonging to the TNF receptor family (TNFRSF) and it binds to LIGHT (TNFSF14), which is a target for asthma airway remodeling. In 2011, a meta-analysis of GWAS studies identified a total of three novel risk loci: 5q31.1 (KIF3A/IL4/IL13), 11q13.1 (OVO homolog-like 1, OVOL1), and 19p13.2 (actin-like 9, ACTL9) (Paternoster et al. 2011). The 5q31.1 region contains a clustered family of Th2 cytokine genes, including IL-13 and IL-4. The 11q13.1 locus contains OVOL1, which regulates the growth of embryonic epidermal progenitor cells and represses c-myc transcription. The 19p13.2 region contains the “a disintegrin and metalloproteinase with thrombospondin motifs 10” (ADAMTS) and ACTL9 genes. ADAMTS proteins play a role in connective tissue remodeling and extracellular matrix turnover. In 2012, a GWAS study in the Japanese population identified eight novel regions of interest: 2q12 (IL1RL1/IL18R1/IL18RAP), 3p21.33 (GLB1), 3q13.2 (CCDC80), 6p21.3 (MHC region), 7p22 (CARD11), 10q21.2 (ZNF365/EGR2), 11p15.4 (OR10A3/NLRP10), and 20q13 (CYP24A1/PFDN4) (Hirota et al. 2012). The 2q12 region contains the receptors of the IL-1 family cytokines (IL1RL1, IL18R1, and IL18RAP). The IL-1 family cytokines, including IL-1α, IL-1β, IL-18, and IL-33, play pivotal roles in innate immunity and contribute to the pathogenesis of AD. The 3p21.33 region is adjacent to the CCR4 gene, which encodes a Th2associated chemokine receptor for CCL22 and CCL17/TARC. Serum TARC levels are useful for the evaluation of the disease activity of AD. CCR4 is a skin-homing receptor of Th22 which is important in chronic AD. The region at 3q13.2 contains CCDC80, which is involved in the induction of C/EBP α and peroxisome proliferatoractivated receptor (PPAR). The region at 7p22 contains CARD11, which encodes CARMA1 has a critical role in the regulation of JunB and GATA3 and subsequent production of Th2 cytokines. The region at 10q21.2 contains early growth response protein 2 (EGR2), a T cell anergy-associated transcription factor involved in the negative regulation of T cell proliferation and inflammation. The region at 11p15.4 contains NLRP10, which is essential to initiate adaptive immunity and plays a role in the control of fungal infection. The region at 20q13 includes CYP24A1, which encodes a mitochondrial cytochrome p450 superfamily enzyme. The protein acts as a degradation enzyme of 1,5- dihydroxyvitamin D3.

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In 2013, an immunochip analysis for AD revealed four new susceptibility loci: 4q27 (IL-2/IL21), 11p13 (PRR5L), 16p13.13 (CLEC16A/DEXI), and 17q21.32 (ZNF652) (Ellinghaus et al. 2013). The 4q27 region contains the IL2 and IL21 genes. The TNF receptor associated factors (TRAF6) (11p13), recombination-activating gene 1 (RAG1) (11p13), RAG2 (11p13), suppressor of cytokine signaling 1 (SOCS1) (16p13.13), and nerve growth factor receptor (NGFR) (17q21.32) genes are located adjacent to those associated regions. In just this year, a GWAS study on childhoodonset AD confirmed five loci: 1q21, 2q22, 5q31(RAD50/IL13), 6p21 (MHC region), and 11q13 (LRRC32) (Weidinger et al. 2013). The linkage disequilibrium (LD) patterns across the regions are consistent with single effect loci on chromosomes 2q22 and 11q13. The 1q21 region coincides with the FLG locus. In 2015, a GWAS study was performed in the Korean population for recalcitrant AD. The study found new loci: 2p24.3 (neuroblastoma amplified sequence, NBAS), 6q22.33 (thymus-expressed molecule involved in selection, THEMIS), 10p14 (GATA3), 13q21.31 (protocadherin 9, PCDH9), and 15q24.3 (S-phase cyclin A-associated protein in the ER, SCAPER) (Kim et al. 2015). NBAS is expressed in epidermal skin cell, and it has not previously been implicated in skin inflammatory diseases. THEMIS mutation is associated with impaired function of Treg cells and Th2 skewed inflammation in an inflammatory bowel disease animal model. PCDH9 is associated with asthma, rheumatoid arthritis, and total serum IgE levels. GATA3 is an important regulator of T-cell development and promotes the production of IL-4, IL-5, and IL-13 from Th2 cells. In 2017, a multi-ancestry GWAS study was carried out to examine 11 new susceptibility loci in the Chinese Han population based on the previous GWAS (Cai et al. 2017). The results showed that CD207 may be a new susceptibility gene for AD.

4.7 Epigenetics and AD In many countries or regions, the prevalence of AD has increased rapidly in recent years. This is seen in the large increase in the prevalence over a period of 5–10 years in countries between the two ISAAC surveys. The prevalence is not accounted for by changes in genetic variation alone, because genetic factors unlikely change in such a short time. The phenomenon is thought to be due to environmental factors such as industrialization, modern lifestyle, pollutants, and others. There is increasing evidence showing that environmental factors regulate gene expression through genomic DNA modifications and miRNAs mechanisms. For example, tobacco exposure, dietary pattern, and environmental pollutants may induce DNA methylation or changes in miRNA expression. These epigenetic mechanisms are associated with the diversity and distinct pathogenesis of AD, including skin barrier related structures and pivotal immune factors (Fig. 4.2).

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Fig. 4.2 The epigenetic mechanisms of AD. Environmental factors, such as smoking, pollutants, nutrients, and microbes, may cause epigenetic modifications (DNA methylation, histone modifications, and miRNAs), which induce skin barrier dysfunction or immune imbalance involved in AD pathogenesis

4.7.1 Epigenetic Studies on the Skin Barrier To explore whether FLG gene variants and adjacent differential DNA methylation synergistically act on the development of AD, a whole-population birth cohort study established on the Isle of Wight in 1989, in which 1456 children were enrolled with follow-up for 18 years (Ziyab et al. 2010), was conducted. The prevalence of AD was 15.2 and 9% of the subjects carried FLG variants R501X, 2282del4 and S3247X. Of the 10 CpG sites within the FLG gene, the methylation level of CpG site “cg07548383” had a significant interaction with FLG variants on the risk for AD. At 86% methylation level, FLG haploinsufficient subjects had a 5.8-fold increased risk of AD compared to those with wild type FLG genotype (Ziyab et al. 2013). In 2014, there was one epigenome-wide association study using integrated epigenetic and transcriptomic analysis in adult AD patients (Rodriguez et al. 2014). There were 28 AD patients and 29 healthy controls in whom methylation of DNA from the lesional or non-lesional epidermis, whole blood, T cells and B cells was studied. The study showed that significant DNA methylation differences in a total of 19 CpG

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sites, and correlation with altered transcript levels of genes were observed between epidermal lesions from AD patients and healthy control epidermis. These genes are predominantly associated with keratinocytes differentiation, proliferation and innate immune response, including S100A genes located within the EDC, KRT6A and KRT6B genes encoding keratins located within the keratin clusters, and OAS1, OAS2, and OAS3, belonging to a family of proteins regulated by IFN and innate immune response. However, the study showed there was no significant methylation difference of CpG sites within the FLG gene, and methylation patterns were not associated with FLG genotypes. In addition, there were no significant DNA methylation differences between AD patients and healthy controls in whole blood, T cells and B cells, indicating blood maybe not an ideal surrogate for skin tissue. There was also one cohort study investigating whether prenatal smoke exposure induces DNA methylation of cord blood (Wang et al. 2013). In 150 children, methylation of CpG sites within the TSLP gene was significantly associated with prenatal tobacco smoke exposure and AD. High smoke exposure can lead to TSLP 5’CpG island hypomethylation. In addition, the hypomethylation of TSLP DNA in cord blood was positively correlated with elevated TSLP protein expression, which activated DCs and promoted the development of AD. These results indicated that TSLP hypomethylation in cord blood is positively associated with childhood AD accompanied by prenatal smoke exposure. Interestingly, another study investigated whether TSLP expression is regulated by aberrant DNA methylation modification of the TSLP promoter in the lesional skin of AD patients (Luo et al. 2014). There were 10 children with AD and 10 healthy controls, and the results showed that the TSLP gene promoter was demethylated in lesional skin from patients, and inhibition of DNA demethylation induced TSLP overexpression in cultured keratinocytes. These results confirmed that TSLP is methylation sensitive, and that DNA hypomethylation contributes to TSLP overexpression in skin lesions of AD patients. Development of the skin barrier is regulated by a complex network of sequencespecific transcription factors and epigenetic modifiers. There was one study exploring the role of histone H2A deubiquitinase Mysm1 in the skin using Mysm1-deficient mice and skin-derived epidermal cells (Wilms et al. 2018). The results showed that there was skin atrophy with reduced thickness and cellularity of epidermis, dermis, and subcutis in Mysm1-deficient mice, and p53 was a potential mediator inducing increased pro-apoptotic and anti-proliferative gene expression. The deficiency of zinc may induce manifestations of skin barrier injury, and the zinc transporter ZIP10 is required for epidermal development (Bin et al. 2017). The study showed that ZIP10 was predominantly expressed in the epidermis and hair follicles, and ZIP10 depletion induced epidermal malformation via downregulation of the activity of the epigenetic enzyme, histone acetyltransferase (HAT), in a reconstituted human skin model (Bin et al. 2019). In addition, ZIP10 and HATs were closely linked with the regulation of genes involved in epidermal homeostasis, particularly filaggrin and metallothionein. Sun exposure is an important environmental factor inducing skin diseases. Studies have examined the influence of sun exposure on the epigenetic status of genes in

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human skin (Da Silva Melo et al. 2015; Silva et al. 2017). However, these studies showed that sun exposure induced no changes in DNA methylation or hydroxymethylation status in miR-9-1, miR-9-3, miR-137, MMP9, KRT14, KRT19, or MTHFR genes.

4.7.2 Epigenetic Studies on the Immune System One study explored the relationship between epigenetic regulation of hBD-1 and defects in the innate immune system in the pathogenesis of AD (Noh et al. 2018). The study showed DNA methylation of 14 CpG sites within the hBD-1 5 region in normal human epidermal keratinocytes, which induced about an 86% reduction in promotor activity, and affected hBD-1 transcriptional regulation. In lesional skin, methylation frequencies at the CpG 3 and CpG 4 sites within hBD-1 promotor were higher than in normal skin. Treg cells play an essential role in the immune response toward a proallergic or tolerant state. Foxp3 is regulated by DNA methylation of its transcriptional regulatory regions. Demethylation of the Treg specific demethylated region (TSDR) corresponds with the stability of FOXP3 in Treg cells. Prenatal environmental factors, such as maternal allergy, maternal cytokine production, and exposure to tobacco smoke may modify DNA methylation of the FOXP3 locus in cord blood (Hinz et al. 2012). Children with low Treg numbers at birth, detected by means of demethylation of TSDR, might be at a higher risk for developing AD or sensitization to food allergens in the first years of life. In AD patients with high IgE levels, the DNA cytosine methyltransferase 1 (Dnmt1) transcripts in peripheral blood mononuclear cells are significantly lower (Nakamura et al. 2006). The overexpression of FcεRI on monocytes and DCs contributes to the development of AD. A study obtained monocytes from the blood of 10 AD patients and 10 healthy controls and global DNA methylation levels were measured (Liang et al. 2012). The results showed that AD patients have a global DNA hypomethylation and locus-specific hypomethylation at FCER1G, and the hypomethylation of FCER1G was inversely associated with its expression. Thus, demethylation of specific regulatory elements within the FCER1G locus contributed to FcεRI overexpression on monocytes in AD patients. In the fetus, epigenetic regulation can be biased against Th1-mediated immunity to prevent harmful cell-immune responses. The IFN-γ (IFNG) gene is hypermethylated in resting neonatal CD4+ cells compared with adult CD4+ cells (Sun et al. 2013). After birth, exposure to a diverse range of microbiota promotes necessary upregulation of Th1 immune responses via epigenetic modification. The alterations of commensal bacterial communities are associated with allergic disease. For example, the children who experienced early antibiotics treatment are at an increased risk of developing allergic diseases. However, the epigenetic mechanisms contributing to the pathogenesis of AD remain unclear.

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Changes in dietary patterns may partially explain the increasing prevalence of allergic diseases in industrialized countries. Potential mechanisms are epigenetic changes, including DNA methylation. Dietary methyl donors are necessary for the one-carbon metabolic pathway that produces S-adenosyl-methionine (SAM), which is the universal methyl donor that is essential for the DNA methylation process. Vitamin B12 and betaine, additional agents from the diet, are also necessary for methionine synthesis, which is another important step in DNA methylation. Therefore, differential intake of these nutrients may lead to differences in DNA methylation and ultimately alter gene expression. In mouse models, in utero supplementation of a diet high in methyl donors (i.e., folic acid, choline, and vitamin B12) resulted in increased atopic disease in the exposed progeny, which is associated with increased methylation of the Runt-related transcription factor (Runx3) gene and decreased expression of Runx3 (Hollingsworth et al. 2008). Runx3 is negatively related to allergic airway disease. However, the results of the studies investigating prenatal and postnatal dietary methyl donor intake or status have been mixed. Exposure to environmental pollutants has been identified as a factor that can alter epigenetic status in the offspring and be associated with allergic diseases. Altered methylation at the ACSL3 gene promoter was associated with maternal airborne polycyclic aromatic hydrocarbon (PAH) exposure and parent-reported asthma in children prior to age 5 (Perera et al. 2009). A follow-up study reported that maternal PAH exposure was associated with increased promoter methylation of IFNG in cord blood DNA. In vitro, exposure of noncytotoxic doses of PAH increased IFNG methylation and reduced expression of IFNG in Jurkat cell lines. Another study found that polyaromatic hydrocarbons such as benzo(a)pyrene, derived largely from the combustion of organic material, such as fossil fuels, coal, wood, and tobacco, are associated with increased serum IL-4 level in children with asthma (Chowdhury et al. 2017). However, benzo(a)pyrene decreases global DNA methylation by inhibition of DNA methyltransferase expression and interferes with the assembling of the methylation. Children with prenatal tobacco exposure had a global hypomethylation at AluYb8 repeat elements in buccal cells collected from mouth swab. In addition, diesel exhaust can lead to the hypermethylation of CpG sites in the IFNG gene promoter and hypomethylation of the IL-4 gene promoter (Liu et al. 2008). Some studies showed there was no or weak association between vitamin D and global DNA methylation. In 2013, a genome-wide methylation study of severe vitamin D deficiency in African American adolescents demonstrated increased methylation of CYP2R1 and decreased methylation of CYP24A1 in vitamin D deficient individuals (Zhu et al. 2013). In postmenopausal women supplemented by vitamin D, methylation status of responders (increased serum 25(OH)D after supplementation) was compared to nonresponders (Zhou et al. 2014). Both responders and nonresponders were found to have lower methylation levels of CYP24A1. Although previous studies showed that gene polymorphism of CYP24A1 was associated with AD in adults, the exact role of methylation levels of CYP24A1 in the pathogenesis of AD remains unclear.

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4.7.3 miRNAs in AD miRNAs are involved in many biological processes, including cell proliferation, differentiation, apoptosis and signal transduction, and organ development. In 2012, one study compared global miRNA expression in healthy skin of controls (n = 4) and lesional skin of AD patients (n = 3). The results showed that 44 miRNAs were significantly different between AD and healthy controls (34 downregulated and 10 upregulated miRNAs), and miR-155 was significantly upregulated in infiltrating T cells in AD skin lesions (Sonkoly et al. 2010). The study also indicated that healthy skin had relatively low miR-155 levels in comparison with other organs. It was found that dermal infiltrating cells expressed miR-155 and that CD4+ T cells were the main cell type responsible for increased miR-155 levels in skin lesions. Environmental factors, such as dust mite and staphylococcal superantigens, can induce miR-155 expression in atopic skin. MiR-155 can promote T cells activation and downregulate CTLA-4 expression, leading to maintenance of a chronic inflammatory state. Another study showed that miR-155 can be induced by LPS and that IL-10 is its target gene (Quinn et al. 2014). For maternal tobacco smoke exposure during pregnancy, the expression of miR-155 was decreased in cord blood but not in maternal blood, and miR-155 expression was not associated with Treg cell numbers (Herberth et al. 2014). In addition, the expression of miR-155 was also increased in the blood of children with moderate-to-severe AD (Bergallo et al. 2017). Maternal tobacco exposure during pregnancy was correlated with high miR-223 and low Treg cell numbers, and the children with low Treg cell numbers at birth had a predisposition to AD during the first 3 years of life (Herberth et al. 2014). Another study showed that miR-223 was increased in the whole blood cells in AD patients, and histamine-N-methyltransferase (HNMT), a major histamine degradation enzyme, was increased in AD patients and AD mouse models (Jia et al. 2018). Although there was one binding site in the 3 -untranslated region of the HNMT gene for miR-223, HNMT was not influenced by miR-223. It was speculated that miR-223 is involved in AD via upregulating HNMT indirectly to degrade the excessive histamine. A Chinese study showed that miR-203 and miR-483-5p are significantly increased in the serum of children with AD compared with healthy controls (Lv et al. 2014). The serum miR-483-5p level is significantly associated with AD and allergic rhinitis and/or asthma. However, miR-203 in urine is markedly decreased in children with AD compared with healthy children. The decreased miR-203 in urine is associated with an abnormal level of serum IgE in AD patients. These results indicated that increased miR-483-5p in serum predicts comorbidity of other atopic conditions, and decreased miR-203 in urine is a biomarker for disease severity. In AD patients, the level of miR-151a is not markedly different in the lesions, however, miR-151a in the plasma is upregulated, and miR-151a can inhibit Th1 cytokines and IL12RB2 expression (Chen et al. 2018). IL12RB2 plays a role in Th1 differentiation progress and immune response. This study indicates that miRNA studies should consider differences in tissue source. In cultured keratinocytes, miR-143 suppressed the downregulation of skin barrier related proteins (FLG, involucrin, and loricrin)

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induced by IL-13 via targeting of IL-13Rα1 (Zeng et al. 2016). Another study found that miR-323-3p expression is increased in peripheral blood mononuclear cells from asthma patients, but the expression is not changed in AD patients (Karner et al. 2017). Another study found that miR-17-5p, miR-20a, miR-21, miR-106b, and miR146a expression are upregulated in both AD and psoriasis skin lesions, and that miR-122a, miR-133a-133b, miR-133b, miR-215, and miR-326 are downregulated in the two diseases (Sonkoly et al. 2007). In AD and psoriasis lesions, the similar expression of miRNAs is consistent with common clinical features of the diseases (Table 4.1).

4.7.4 Epigenetics Studies in AD Patients To explore the role of epigenetics in the pathogenesis of AD patients, one should consider several factors. First, the objective of the study should be determined. Second, which type of samples, blood, skin lesions or other materials, should be collected from patients? Third, which epigenetic marks should be evaluated? Epigenetic research may study the role of external factors in the development of AD, or changes in epigenetic marks after exposure to external factors, or detection of the epigenetic profiles in AD patients. One study investigated the relationship between parental atopy history and tobacco exposure and development of AD in children (Hinz et al. 2012). Another study found miRNA changes in maternal and cord blood after tobacco exposure (Herberth et al. 2014). Two studies used cord blood to study the relationship between parental atopy history and tobacco exposure with AD in children (Hinz et al. 2012; Herberth et al. 2014). Whole blood also can be collected to detect DNA methylation or miRNA expression (Ziyab et al. 2013; Bergallo et al. 2017; Jia et al. 2018). However, there are so many cell types in the whole blood, which may give rise to variable results. Furthermore, some studies extracted monocytes or peripheral blood mononuclear cells from the whole blood for examination (Liang et al. 2016; Karner et al. 2017). In others, serum or plasma was the medium studied (Lv et al. 2014; Chen et al. 2018). Skin barrier dysfunction is the main pathophysiological feature of AD. Skin encounters the external environment, and external stimuli may directly affect the skin and induce aggravation of the disease. Compared with blood cells or serum and plasma, skin lesions may possess different characteristics. Lesional skin from AD patients was collected to study TSLP methylation and miRNA expression changes (Sonkoly et al. 2007; Luo et al. 2014). Even then, lesional skin also consists of many cell types, such as keratinocytes, lymphocytes, and dendritic cells. There was one study which involved collecting lesional epidermis to detect DNA methylation, which showed significant methylation differences (Rodriguez et al. 2014). After collection of blood or lesional skin samples, one can detect DNA methylation, modifications of histone or miRNAs with gene-specific analysis (qualitative and quantitative), global methylation/modification analysis or genome-wide scans. Other studies examined global DNA methylation or miRNA profiles to find more

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Table 4.1 The role of epigenetics in AD Cell/tissue types

Epigenetic alterations

Findings

References

Cord blood

TSDR methylation in Foxp3

Parental atopy history, particularly maternal hay fever and paternal asthma, maternal cytokines (IL-13, IL-17E, and IFN-γ) and maternal smoking/exposure to tobacco smoke during pregnancy were related to lower Treg numbers in cord blood with TSDR methylation. During the first year of life, children with lower Treg numbers at birth had a higher risk to develop AD and sensitization to food allergens

Hinz et al. (2012)

Monocytes

FCER1G methylation

Demethylation of FCER1G induced FcεRI overexpression on monocytes in AD patients

Liang et al. (2012)

Whole blood

FLG methylation

FLG DNA methylation increased AD risk

Ziyab et al. (2013)

Lesional skin

TSLP methylation

Promotor hypomethylation of the TSLP gene was found in AD skin lesions

Luo et al. (2014)

Lesional epidermis

DNA methylation

There were significant methylation differences between lesional epidermis from AD patients and healthy control epidermis

Rodriguez et al. (2014)

Lesional skin

miRNA profiling

Upregulation: miR-17-5p, miR-20a, miR-21, miR-106b, and miR-146a Downregulation: miR-122a, miR-133b, miR-133a-133b, miR-215, and miR-326

Sonkoly et al. (2007)

Lesional skin

miR-155

miR-155 was significantly upregulated in infiltrating T cells in AD skin lesions

Sonkoly et al. (2010)

miR-155 expression was increased in the children with moderate-to-severe AD

Bergallo et al. (2017)

Blood

(continued)

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Table 4.1 (continued) Cell/tissue types

Epigenetic alterations

Findings

References

Cord blood

miR-223

Maternal tobacco exposure during pregnancy was correlated with high miR-223 and low Treg cell numbers

Herberth et al. (2014)

miR-223 and histamine-N-methyltransferase was increased in AD patients

Jia et al. (2018)

Whole blood cells

Serum and urine

miR-203 and miR-483-5p

miR-203 and miR-483-5p were significantly increased in the serum of children with AD, but miR-203 was decreased in the urine of Children with AD. miR-203 in urine was a biomarker for the disease severity

Lv et al. (2014)

Peripheral blood mononuclear cells

miR-323-3p

miR-323-3p expression was increased in peripheral blood mononuclear cells from asthma patients, but the expression was not changed in AD patients

Karner et al. (2017)

Plasma and lesional skin

miR-151a

miR-151a was not markedly different in the lesions. However, miR-151a in the plasma was upregulated

Chen et al. (2018)

and new specific sites associated with the development of AD (Sonkoly et al. 2007; Rodriguez et al. 2014). In addition, the epigenetic marks of key molecules in the pathogenesis of AD, such as filaggrin and TSLP, have been found (Ziyab et al. 2013; Luo et al. 2014).

4.8 Conclusion AD is a common heterogeneous inflammatory disease with a genetic predisposition. The pathogenesis of AD is characterized by skin barrier dysfunction and immune imbalance. The normal skin barrier represents a first line of defense. The barrier structures consist of SC, FLG, intercellular lipids, corneodesmosomes, and TJs. The normal barrier function is also dependent on the activity of proteases, skin pH, and external factors. When the skin barrier is impaired because of the many factors, allergens, irritants, and pathogens that can penetrate the skin, this leads to inflammation.

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The mechanism and manifestation of immune dysfunction vary between acute and chronic stages of AD. These changes eventually induce or exacerbate skin barrier dysfunction. In the end, the above process forms a positive feedback loop. Genetic studies show that there are many gene mutations or genetic variants. For instance, FLG mutations are common in people from different countries and regions. The genetic variants of the skin barrier and immune system may directly induce the deficiency of skin barrier and immune system. The prevalence of AD in some countries or regions has increased significantly in the past few decades, and it has been speculated that environmental factors and epigenetics may play pivotal roles in AD. Some studies have shown that there is abnormal epigenetic regulation in skin barrier and immune function in AD triggered by environmental factors. However, the relationship between environmental factors and the development of AD is still incompletely understood, and elucidation of the mechanisms of epigenetics in AD needs further research.

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Chapter 5

The Epigenetics of Food Allergy Christopher Chang, Haijing Wu, and Qianjin Lu

Abstract Food allergy is a global health problem, particularly in developed countries. It is mainly mediated by Th2 cell and IgE produced by B cells. While the pathogenesis of IgE-mediated food allergy is quite straightforward, the factors that lead to the development of food allergies at any age in children and adults are unclear. Recent studies have revealed that genetics, epigenetics, and environmental exposures contribute to the development of atopy. In this chapter, we discuss the interplay between these three key elements, reveal how epigenetic modifications may mediate genetic susceptibility of food allergies, and explain why epigenetic modifications may be the key in environmental factors mediated-gene expression, leading to the loss of immune tolerance and eventually, the initiation of food allergies. It should be noted that the study of the role of epigenetics in food allergy is still in its infancy, and lags behind research on epigenetics in other fields such as cancer and autoimmune diseases. One of the reasons for this may be the extreme complexity and variability of clinical presentation of food allergy, ranging from less severe forms such as oral allergy syndrome to full-blown anaphylaxis. Research on early exposure has disrupted the previous thinking of avoidance of food allergies to prevent sensitization in children, instead leading to recommendations that early introduction to foods may, in fact, induce tolerance. However, clear and unequivocal guidelines on how to approach this in the clinical setting have not been developed. The coming of the

C. Chang (B) Division of Pediatric Immunology and Allergy, Joe DiMaggio Children’s Hospital, Hollywood, FL 33021, USA e-mail: [email protected] Division of Rheumatology, Allergy and Clinical Immunology, University of California Davis, Davis, CA 95616, USA H. Wu · Q. Lu Department of Dermatology, Hunan Key Laboratory of Medical Epigenomics, Second Xiangya Hospital, Central South University, Changsha, Hunan, China e-mail: [email protected] Q. Lu e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 C. Chang and Q. Lu (eds.), Epigenetics in Allergy and Autoimmunity, Advances in Experimental Medicine and Biology 1253, https://doi.org/10.1007/978-981-15-3449-2_5

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epigenetic era in food allergies is to provide better understanding of pathogenesis of food allergy, as well as providing therapeutic and preventive strategies for this very common condition. Keywords Gene regulation · Gene expression · microRNA · DNA methylation · Food allergy · Histone modification · Microbiome · Immune intolerance

5.1 Introduction Over the past few decades, there has been a dramatic rise in allergic diseases, including allergic rhinitis, asthma, atopic dermatitis, and food allergy. This has been especially prevalent in developed countries. Within undeveloped countries, allergic diseases have also been on the rise but in specific areas of higher socioeconomic status. For example, the rates of allergies in modernized regions such as Shanghai are far greater than those in the poorer western regions of China such as Xinjiang. It is now well accepted that allergic diseases arise out of a genetic predisposition that is modulated by the environment, and that it is through epigenetic modulation that these environmental exposures exert their influence. The epigenetics of allergic rhinitis, asthma, and eczema are discussed in Chap. 6 of this book. In this chapter, we will limit our discussion to the epigenetics of food allergy. While the term food allergy is sometimes used very loosely, with many different connotations, the precise scientific definition is an IgE-mediated response to a food allergen. IgE-mediated reactions are the hallmark of the Type 1 hypersensitivity reactions, and is the most commonly seen of the four types of hypersensitivity reactions defined by the classic Gel and Coombs classification system that was proposed in 1963. The term immediate signifies that these reactions occur quickly after exposure, usually within the first hour and most commonly within the first half-hour. Multiple organ systems can be affected, with the skin being the most commonly affected in up to 90% of reactions. Skin manifestations may include most commonly hives, but flushing can also occur, and these signs are commonly associated with swelling and pruritus. Other system involvement can accompany the skin signs or occur in the absence of skin manifestations. Gastrointestinal symptoms frequently occur, including abdominal pain, diarrhea, or vomiting. Respiratory signs and symptoms include cough, wheezing, respiratory distress, and edema of the upper airway. The cardiovascular system can be targeted during an anaphylactic episode to food, resulting in anaphylactic shock resulting from mediator release from mast cells that leads to increased vascular permeability, vasodilation, and bronchoconstriction. Anaphylaxis may in some cases lead to cardiovascular collapse and death, which is why it is crucial that patients with a food allergy have epinephrine available at all times. Epinephrine autoinjectors come in several different forms, and the patients need to be educated on how to use them. Despite the common erroneous practice of using steroids and antihistamines to treat anaphylaxis, epinephrine is the only form of treatment that will

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reverse the course of anaphylaxis and it is critically important that patients understand this. Epinephrine is the first line, and with few exceptions, the only effective mode of therapy for the treatment of anaphylaxis. Anaphylaxis can be caused by various triggers. Foods constitute about a third of all cases of anaphylaxis. The other major triggers are medications and venom stings, but it is important to know that in about 30% of cases, anaphylaxis is idiopathic. Food induced anaphylaxis is associated with the worst outcomes, because they are the most common, and because they often occur in the field under suboptimal conditions for treatment. Most anaphylaxis episodes due to foods result from peanut and tree nut allergies. A genetic predisposition to food allergies is evident based on the observation that allergies do seem to run in families, but there is no specific gene that by itself confers a predisposition to develop allergies. It is more likely that food allergy is a multi-gene or polygenic phenomenon. A genetic predisposition is not in itself sufficient to develop allergies. There also must be an environmental influence. In addition, a genetic predisposition may lead to a variety of phenotypes of food allergies, depending on the environmental exposure. Environment can also modulate the specific response to a food allergy and may determine the level of security and the clinical manifestations of an individual’s food allergy. The development of a food allergy is a complex process, the mechanism of which is not completely known. It is particularly humbling when one realizes that even in this age of tremendous advances in pathophysiology of health and disease, clinical scientists have yet to decipher whether or not or when, exposure to food in early life may lead to sensitization or tolerance. For years, the recommendation by professional groups had been to avoid food to prevent food anaphylaxis, which makes sense if one is already sensitized, but recently, the recommendation has changed to encourage early exposure. The challenge is even if we know that early exposure leads to the development of tolerance, we do not know when this occurs in any given person. Timing is thus important, and we have yet to gain sufficient knowledge to make overreaching recommendations on when and how to introduce foods to prevent the development of allergies, so-called “primary prevention”. The LEAP study and subsequent EAT study seem to suggest that early exposure helps to build tolerance. Assuming that the principles of genetics and the environmental are known, namely, that any individual has a specific genetic predisposition to developing food allergies that are modulating in some way by the environment, how does the environment impact the development of allergies. This is where epigenetics comes in. Epigenetics is the turning on or turning off of genes by alteration of the structure of the DNA and its accompanying proteins, not the DNA sequence. This switching on and off of genes is usually done at the promotor regions. It is only recently that the role of epigenetics in the development of food allergies is beginning to be researched.

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5.2 Biological Processes in Food Allergy The pathophysiology of food allergy involves loss of immune tolerance, in which the immune system mounts a reaction to innocuous antigens, such as food proteins (Berin and Mayer 2013; Syed et al. 2013). The mechanisms of tolerance are complex and involve positive and negative selection in both the central and peripheral immune systems. However, why certain people are unable to develop tolerance to certain antigens, while others do, is not clear. Accumulating evidence indicates that antigenpresenting immune cells, such as dendritic cells (DCs) (Ruiter and Shreffler 2012), as well as macrophages (Kumar et al. 2013), and regulatory T cells (Treg) (Palomares 2013), contribute to suppression of an inappropriate immune response and maintain peripheral tolerance. In food allergy, exposure to food antigens initiates and promotes a Th2-skewed immune response and generates food antigen-specific IgE antibodies produced by B cells (Kumar et al. 2013; Quake and Nadeau 2015). Although quantification of IgE antibody levels in serum has been proposed as an index to reflect the possibility of individuals who are likely to show clinical reactions to egg, peanut, fish, or milk (Chokshi and Sicherer 2016), there is no good discrimination between those who are sensitized versus allergic. The level of specific IgE, as well as the size of a skin testing response to a specific food, only provides a probability that the patient is actually allergic to that food via a Type 1 hypersensitivity mechanism. The size of such reactions or the level of specific IgE provides no information on the severity of a possible reaction. Food testing is notoriously inaccurate, with large numbers of false positives and negatives. The detection of specific IgE only represents sensitization and not clinical allergy (Klemans et al. 2015). The main source of IgE antibodies is from B cells, and result from the interaction of B cells and various forms of T helper cells such as Th2 and Tfh cells (Prussin et al. 2009). IL-4, 5 and 13 are cytokines that help facilitate this interaction and also help induce mediator release from mast cells causing the specific pathophysiologic changes of an allergic reaction. IL-9 from Th9 cells has also been shown to be expressed differentially by children with peanut allergy and sensitization (Brough et al. 2014a), suggesting an important role of IL-9 in food allergy. More evidence for the involvement of IL-9 can be found from a mouse study in which mice intestinal mast cells express IL-9 and promote experimental food allergy depending on IL-9 production (Chen et al. 2015). In addition to effector T cells, regulatory T cells are also critical for food allergy. In mouse models, injection of Treg cells can inhibit food allergy, and in a food allergy mouse model, an impairment of Treg function has been observed (Noval Rivas et al. 2015), indicating that food allergy is a failure of Treg cells. The process of immune response to food allergy is shown in Fig. 5.1.

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Fig. 5.1 The biology of food allergy. The generation of an IgE-mediated response to a food allergen requires sensitization via presentation of the allergen to the T-cell receptor. T cells then stimulate B cells to produce antigen-specific IgE. Upon re-exposure, the IgE recognizes the food allergen and binds to it. Cross-linking of allergen bound IgE on the surface of mast cells leads to the production of mediators that induce an allergic response

5.3 Genetics 5.3.1 Family History The role of family history in the development of allergies and food allergies has been extensively studied. A population-based study performed in Australia evaluated 5276 one-year old infants. Five hundred and thirty-four of them carried a food allergy diagnosis. The study found that having one immediately family member with a history of allergy led to a mild increase in the risk of developing food allergy (OR 1.4, 95% CI 1.1–1.7), but having two immediately family members with allergy led to a significantly higher risk of developing food allergy (OR 1.8, 95% CI 1.5– 2.3) (Koplin et al. 2013). Sicherer and Sampson reviewed the data in 2018 and identified a selection of genetic and environmental factors that may impact the risk of developing food allergies. These included race/ethnicity, gender, familial history, and the microbiome (Sicherer and Sampson 2018). In the 2016 study by Gupta et al. (2016), it was found that 66% of siblings of a proband with food allergies would be sensitized to foods, but only 13.7% were clinically allergic (Gupta et al. 2016).

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5.3.2 Genes Involved in Food Allergy Twin studies in food allergy have revealed that a substantial component of allergic risk is inherited. Seventy-five twin pairs were recruited for a twin study in peanut allergy, but 17 pairs were excluded due to the unconvincing peanut allergy histories. Out of 14-monozygotic pairs, 9 were found to be concordant for peanut allergy. In 44 dizygotic pairs, only three were found to be concordant for peanut allergy. This study indicates that the heritability of peanut allergy is 81.6%, suggesting that there is a strong genetic influence on peanut allergy (Sicherer et al. 2000). In another twin study, 354 pairs of dizygotic Chinese twins and 472 pairs of monozygotic Chinese twins were evaluated for sensitization to five aeroallergens and nine foods. The authors used structural equation models to calculate the best fit for correlation between foods and environmental allergens. They found that correlation of sensitization was high for two aeroallergens (cockroach and dust mite, 0.83) and two foods (peanut and shellfish, 0.58), and they estimated that the contributions to sensitization ranged from 0.51 to 0.68 for heritability and 0.32–0.49 for the environmental (Liu et al. 2009). Several genes have been reported to be associated with food allergy. The filaggrin gene, for example, encodes profilaggrin, which is an epidermal protein that is proteolytically cleaved into filaggrin monomers. This process occurs in keratinocytes within the stratum corneum of the skin. There are two studies that have shown a positive association between mutations in the filaggrin gene and sensitization to foods (Venkataraman et al. 2014; van Ginkel et al. 2015). However, in other studies, this association has only been revealed with regard to sensitization to peanut (Asai et al. 2013). A study reported an association between early-life environmental peanut exposure and an increased risk of peanut allergy in children with filaggrin mutations, suggesting that peanut allergy may develop following the transcutaneous sensitization (Brough et al. 2014b). It should be noted that this association has only been reported with IgE sensitization to peanut and not other allergens (Johansson et al. 2017). Genome-wide Association Studies (GWAS) have been conducted to better understand the genetics of food allergy. Changes in DNA methylation within the HLA-DR and-DQ regions have been associated with peanut allergy (Hong et al. 2015). In another GWAS study, filaggrin gene null variants have been further confirmed to increase susceptibility to food allergy in children (Hirota et al. 2017). In addition, polymorphisms in immune-related genes, such as IL10, IL13, STAT6, SPINK5, FOXP3, have been shown to be associated with food allergy (Li et al. 2016; Hemler et al. 2015). Several monogenic disorders also show a high incidence of atopy and food allergy, such as dedicator of cytokinesis 8 deficiency, LoeysDietz syndrome, and STAT3-hyper-IgE syndrome (Tuano et al. 2015; Carter and Frischmeyer-Guerrerio 2018).

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5.4 The Environment 5.4.1 The Effect of Early Introduction of Foods In a 2010 survey from the United Kingdom, 45% of mothers of infants between 8 and 10 months of age reported avoiding giving their infant a particular food. The rates varied depending on the food, and was 48% for nuts, 14% for eggs, 10% for dairy, and 6% for fish (Payne and Quigley 2017). As mentioned earlier, new evidence has shown that early introduction of peanut, egg, and cow’s milk may prevent the onset of food allergy (Du Toit et al. 2008; Koplin et al. 2010; Katz et al. 2010). In another trial, 1303 breast-fed infants were recruited at the age of 3 months and randomly assigned to early introduction of peanut, cooked egg, cow’ milk, sesame, whitefish, and wheat. The results showed that the consumption of 2 g per week of peanut or egg was associated with lower prevalence of allergy than with less consumption, indicating that the protective effects of early introduction of allergenic foods may be dose-dependent (Perkin et al. 2016). Studies on early exposure to foods such as the LEAP and the EAT study confirm a postnatal environmental influence on the development of primary sensitization to foods.

5.4.2 The Microbiome Microbial diversity is believed to be an important factor in the primary prevention of food allergy. There is also evidence showing that pet exposure in early life may be a protective factor against food allergy (Noval Rivas et al. 2015). Pet ownership contributes to a high microbial diversity in our living environment (Fujimura et al. 2010). More interesting is that dust from pet-owning households has been found to prevent experimental asthma in mice (Fujimura et al. 2014). Additional evidence for an effect of microbial diversity can be derived from studies of fetal stool. The fetal gut is believed to be sterile; however, several studies have revealed the presence of microbiota in the first infant stool (meconium). This suggests that microbial colonization of the fetal gut may begin in utero (Gosalbes et al. 2013; Moles et al. 2013). In meconium, four major bacteria (Actinobacteria, Bacteroides, Firmicutes, and Proteobacteria) have been found, and it has been shown that low microbial diversity in early infancy is associated with atopic dermatitis (Abrahamsson et al. 2012). In a more recent study, fecal microbial samples have been tested by 16S rRNA sequencing. Increased levels of Clostridium and Anaerobacter and reduced levels of Bacteroides and Clostridium XVIII have been found in infants with food allergy (Ling et al. 2014). In the American Gut project, 1879 individuals were recruited. A significantly decreased microbial richness and alpha diversity were reported in individuals with peanut or tree nut allergy compared with non-allergic controls (Hua et al. 2016). More interesting is that commensal bacteria have been found to regulate

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the production of IgE. In a food allergy inducing model, germ-free mice display higher levels of IgE. However, raising these mice together with mice with a diverse microbiota in early life suppresses the IgE and prevents the development of food allergy in the germ-free mice (Cahenzli et al. 2013). Clostridium species and other bacteria strains have been found to induce Treg cells in the gastrointestinal tract and contribute to the reduction in food allergy (Faith et al. 2014; Atarashi et al. 2013).

5.5 Epigenetic Research in Food Allergies There are only a few studies that address the association of epigenetics and food allergy. It is well accepted that CD4+ T helper cells help facilitate the allergic response. CD4+ cell proliferation and activity maybe under the control of epigenetic regulation and may thereby influence the development of allergies. In a recent study, the genome-wide DNA methylation profiles consisting of about 450,000 CpGs on CD4+ T-cells were studied in a birth cohort of twelve 12-month-old children who were diagnosed with IgE-mediated food allergy. The CD4+ methylation profiles at birth and at 12 months of age were compared. It was discovered that there were 136 differentially methylated probes at birth which increased to 179 at 12 months. It was also found that there were 92 allergy-associated non-SNP DNA methylation probes found at birth when the subjects were disease-free. It was postulated that these may play a role in the development of allergies over time. The differentially methylated genes were related to the MAP kinase pathway. While the data did not prove involvement in the pathogenesis of allergy, it is highly likely that dysregulation of DNA methylation in MAP kinase-involved signaling may lead to anomalous T cell function leading to a breakdown in the development of tolerance in children with food allergy (Martino et al. 2014). Another study found that DNA methylation may play a role in sustained unresponsiveness in patients who underwent oral immunotherapy through the induction of antigen-specific Treg cells and DNA hypomethylation of the Foxp3 gene (Syed et al. 2014). This study looked at 43 patients with peanut allergy, of whom 23 were receiving peanut oral immunotherapy and 20 were receiving standard of care over a period of 24 months. It was found that FOXP3 methylation was reduced throughout the treatment period. They also showed that sustained unresponsiveness correlated with a persistent FOXP3 demethylated state, whereas those patients who became re-sensitized experienced a return to higher methylation of FOXP3. Another study was a GWAS in food allergy involving 2759 participants from the United States. In this study, it was shown that differential DNA methylation of HLA-DR and-DQ gene regions can identify and support genetic risk factors for the development of peanut allergies (Hong et al. 2015). In this study, peanut, milk, and egg allergic patients were studied. Peanut allergy-specific loci were found in the HLA-DQ and DR regions at 6p21.32, tagged by rs9285596 and rs7192. These

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single-nucleotide polymorphisms were found to have differentiated DNA methylation at multiple CpG sites. Rs7192 and rs9275596 were associated with a population attributable risk of 21% and 19%, respectively. In another epigenetic related study in children, polyclonal activation of naive CD4+ T cells through the T cell receptor has been found to result in reduced lymphoproliferative responses with food allergy. In addition, it was shown that the expression of the cell cycle-related targets, including MYC and E2F transcription factor networks was decreased, and that the reduced lymphoproliferative response was tied to remodeling of DNA methylation at inflammatory (IL1R, IL18RAP, CD82) and metabolic (RPTOR, PIK3D, MAPK1, FOXO1) genetic loci. Infants who have sustained food allergy in later childhood show cumulative increases in epigenetic disruption of T cell activation genes and reduced lymphoproliferative responses compared to children who “outgrow” their food allergy. This data demonstrates that epigenetic dysregulation in the early stages of signal transduction through the T cell receptor complex occurs specifically in pathways modified by gene-environment interactions in food allergy (Martino et al. 2018). More interesting is that DNA methylation has been proposed as markers to predict clinical reactivity in food-sensitized infants (Martino et al. 2015). In this study, 58 food-sensitized infants were recruited, and genome-wide DNA methylation profiling was conducted on the blood samples from these infants. Ninety-six CpG sites were identified to predict clinical outcomes. In addition, these 96 CpG sites can serve as biomarkers with an accuracy of 79.2% using a calculated diagnostic score (Martino et al. 2015). Although our knowledge of epigenetic regulation in food allergy is still in its infancy (Table 5.1), there is extensive research on the impact of epigenetic modifiTable 5.1 Epigenetic regulations in food allergy Cell types

Epigenetic modifications

Targeting genes

Consequence

References

CD4+ T cells

DNA Methylation

MAP kinase pathway

Anomalous T cell function

Martino et al. (2014)

Treg cells

DNA Methylation

FOXP3

Reduced Treg cells

Syed et al. (2014)

Whole blood

DNA methylation

HLA-DQ and DR regions

High risk of Food allergy

Hong et al. (2015)

Naive CD4+ T cells

DNA methylation

L1R, IL18RAP, CD82, RPTOR, PIK3D, MAPK1, FOXO1

Reduced lymphoproliferative response

Martino et al. (2018)

Whole blood

DNA methylation

96 CpG

Predict food allergy in infants

Martino et al. (2015)

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cations on autoimmune diseases and cancer. For example, Vitamin D is a chromatin modulator which can alter several immune cells (Andraos et al. 2011). In a mouse study, feeding large doses of peanut at an early age is capable of inducing antigenspecific Treg cells and demethylation of Foxp3 (Wang et al. 2018), which has been reported to be associated with human peanut allergy (Syed et al. 2014).

5.6 Conclusions Compared to autoimmune diseases and cancers, the study of the role of epigenetics in food allergy is still in its infancy. There are so far only a small number of studies investigating DNA methylation levels in food allergies, and there are virtually no studies on the effect of histone modifications or microRNA on food allergy. This is despite some investigators beliefs that epigenetics is the lost link in establishing a better understanding of the prevention of food allergies and the development of tolerance. It is anticipated that the epigenetics of food allergies will undergo increased scrutiny and that more studies will be developed to establish the effects of the environment and the microbiome on the development of food allergies.

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Ling Z, Li Z, Liu X, Cheng Y, Luo Y, Tong X et al (2014) Altered fecal microbiota composition associated with food allergy in infants. Appl Environ Microbiol 80(8):2546–2554 Liu X, Zhang S, Tsai HJ, Hong X, Wang B, Fang Y et al (2009) Genetic and environmental contributions to allergen sensitization in a Chinese twin study. Clin Exp Allergy 39(7):991–998 Martino D, Joo JE, Sexton-Oates A, Dang T, Allen K, Saffery R et al (2014) Epigenome-wide association study reveals longitudinally stable DNA methylation differences in CD4+ T cells from children with IgE-mediated food allergy. Epigenetics 9(7):998–1006 Martino D, Dang T, Sexton-Oates A, Prescott S, Tang ML, Dharmage S et al (2015) Blood DNA methylation biomarkers predict clinical reactivity in food-sensitized infants. J Allergy Clin Immunol 135(5):1319–1328.e1–12 Martino D, Neeland M, Dang T, Cobb J, Ellis J, Barnett A et al (2018) Epigenetic dysregulation of naive CD4+ T-cell activation genes in childhood food allergy. Nat Commun 9(1):3308 Moles L, Gomez M, Heilig H, Bustos G, Fuentes S, de Vos W et al (2013) Bacterial diversity in meconium of preterm neonates and evolution of their fecal microbiota during the first month of life. PLoS One 8(6):e66986 Noval Rivas M, Burton OT, Wise P, Charbonnier LM, Georgiev P, Oettgen HC et al (2015) Regulatory T cell reprogramming toward a Th2-cell-like lineage impairs oral tolerance and promotes food allergy. Immunity 42(3):512–523 Palomares O (2013) The role of regulatory T cells in IgE-mediated food allergy. J Investig Allergol Clin Immunol 23(6):371–382; quiz 2 p preceding 82 Payne S, Quigley MA (2017) Breastfeeding and infant hospitalisation: analysis of the UK 2010 infant feeding survey. Matern Child Nutr 13(1) Perkin MR, Logan K, Tseng A, Raji B, Ayis S, Peacock J et al (2016) Randomized trial of introduction of allergenic foods in breast-fed infants. N Engl J Med 374(18):1733–1743 Prussin C, Lee J, Foster B (2009) Eosinophilic gastrointestinal disease and peanut allergy are alternatively associated with IL-5+ and IL-5(-) T(H)2 responses. J Allergy Clin Immunol 124(6):1326–1332.e6 Quake C, Nadeau KC (2015) The role of epigenetic mediation and the future of food allergy research. Semin Cell Dev Biol 43:125–130 Ruiter B, Shreffler WG (2012) The role of dendritic cells in food allergy. J Allergy Clin Immunol 129(4):921–928 Sicherer SH, Sampson HA (2018) Food allergy: a review and update on epidemiology, pathogenesis, diagnosis, prevention, and management. J Allergy Clin Immunol 141(1):41–58 Sicherer SH, Furlong TJ, Maes HH, Desnick RJ, Sampson HA, Gelb BD (2000) Genetics of peanut allergy: a twin study. J Allergy Clin Immunol 106(1 Pt 1):53–56 Syed A, Kohli A, Nadeau KC (2013) Food allergy diagnosis and therapy: where are we now? Immunotherapy 5(9):931–944 Syed A, Garcia MA, Lyu SC, Bucayu R, Kohli A, Ishida S et al (2014) Peanut oral immunotherapy results in increased antigen-induced regulatory T-cell function and hypomethylation of forkhead box protein 3 (FOXP3). J Allergy Clin Immunol 133(2):500–510 Tuano KS, Orange JS, Sullivan K, Cunningham-Rundles C, Bonilla FA, Davis CM (2015) Food allergy in patients with primary immunodeficiency diseases: prevalence within the US Immunodeficiency Network (USIDNET). J Allergy Clin Immunol 135(1):273–275 van Ginkel CD, Flokstra-de Blok BM, Kollen BJ, Kukler J, Koppelman GH, Dubois AE (2015) Loss-of-function variants of the filaggrin gene are associated with clinical reactivity to foods. Allergy 70(4):461–464 Venkataraman D, Soto-Ramirez N, Kurukulaaratchy RJ, Holloway JW, Karmaus W, Ewart SL et al (2014) Filaggrin loss-of-function mutations are associated with food allergy in childhood and adolescence. J Allergy Clin Immunol 134(4):876–882.e4 Wang M, Yang IV, Davidson EJ, Joetham A, Takeda K, O’Connor BP et al (2018) Forkhead box protein 3 demethylation is associated with tolerance induction in peanut-induced intestinal allergy. J Allergy Clin Immunol 141(2):659–670.e2

Chapter 6

Epigenetics and the Environment in Airway Disease: Asthma and Allergic Rhinitis Andrew Long, Bryan Bunning, Vanitha Sampath, Rosemarie H. DeKruyff, and Kari C. Nadeau Abstract Asthma and rhinitis are complex, heterogeneous diseases characterized by chronic inflammation of the upper and lower airways. While genome-wide association studies (GWAS) have identified a number of susceptible loci and candidate genes associated with the pathogenesis of asthma and allergic rhinitis (AR), the riskassociated alleles account for only a very small percent of the genetic risk. In allergic airway and other complex diseases, it is thought that epigenetic modifications, including DNA methylation, histone modifications, and non-coding microRNAs, caused by complex interactions between the underlying genome and the environment may account for some of this “missing heritability” and may explain the high degree of plasticity in immune responses. In this chapter, we will focus on the current knowledge of classical epigenetic modifications, DNA methylation and histone modifications, and their potential role in asthma and AR. In particular, we will review epigenetic variations associated with maternal airway disease, demographics, environment, and non-specific associations. The role of specific genetic haplotypes in environmentally induced epigenetic changes are also discussed. A major limitation of many of the current studies of asthma epigenetics is that they evaluate epigenetic modifications in both allergic and non-allergic asthma, making it difficult to distinguish those epigenetic modifications that mediate allergic asthma from those that mediate non-allergic asthma. Additionally, most DNA methylation studies in asthma use peripheral or cord blood due to poor accessibility of airway cells or tis-

A. Long · B. Bunning · V. Sampath · R. H. DeKruyff · K. C. Nadeau (B) Division of Pulmonary and Critical Care Medicine, Department of Medicine, Sean N. Parker Center for Allergy and Asthma Research at Stanford University, Stanford, CA 94305, USA e-mail: [email protected] A. Long Department of Pharmacy, Lucile Packard Children’s Hospital, Stanford, CA 94304, USA © Springer Nature Singapore Pte Ltd. 2020 C. Chang and Q. Lu (eds.), Epigenetics in Allergy and Autoimmunity, Advances in Experimental Medicine and Biology 1253, https://doi.org/10.1007/978-981-15-3449-2_6

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sue. Unlike DNA sequences, epigenetic alterations are quite cell- and tissue-specific, and epigenetic changes found in airway tissue or cells may be discordant from that of circulating blood. These two confounding factors should be considered when reviewing epigenetic studies in allergic airway disease. Keywords Asthma · Allergic rhinitis · Heritability · Maternal transmission · Airway disease

6.1 Introduction Asthma and rhinitis are complex, heterogeneous diseases characterized by chronic inflammation of the upper and lower airways and can be allergic and non-allergic in etiology. Symptoms of asthma include wheezing, shortness of breath, chest tightness, and cough, while those of allergic rhinitis (AR) include sneezing, itching, rhinorrhea, and congestion. The prevalence of asthma and AR has steadily increased over the past few decades, with asthma currently affecting approximately 7–11% of the global population (Backman et al. 2017; Pawankar 2014). In the US alone, asthma is responsible for an estimated $50.3 billion in medical costs annually (Nurmagambetov et al. 2018). AR is estimated to affect around 10–30% of all adults and up to 40% of children, with direct annual medical costs estimated at an additional $3.4 billion (Meltzer 2016; Wallace et al. 2008). Allergic asthma is characterized by an allergic immune response to specific allergen triggers found in the environment, including dust mites, pet dander, pollen, food, and mold. Those with an allergic asthma phenotype typically develop the disease earlier in life and frequently present with other comorbid allergic diseases, such as AR, food allergy, or atopic dermatitis, and a familial history of allergies. In allergic asthma and AR, environmental allergen exposure drives the activation and differentiation of allergen-specific type 2 helper T (Th2) cells; the production of interleukin 4 (IL-4), IL-5, IL-9, and IL-13 cytokines; B cell class switching and allergen-specific immunoglobulin E (IgE) production; and IgE-dependent mast cell activation and eosinophil recruitment into the lungs. Other immune cells and cytokines involved include epithelial cells (thymic stromal lymphopoietin, IL-25, and IL-33), natural killer T cells (IL-4 and IL-13), and type 2 innate lymphoid cells (IL-5 and IL-13) (Altman et al. 2018; De Greve et al. 2017; Muraro et al. 2016; van Rijt et al. 2016). The net effect of the underlying pathology is a disease marked by persistent eosinophilic airway inflammation, airway hyper-reactivity and remodeling, and increased levels of Th2-associated cytokines, each contributing to the observed symptoms of asthma (Leomicronn 2017). In contrast to the allergic phenotype, non-allergic asthma generally develops later in life and is often mediated by non-allergenic triggers that exert their effects independent of IgE, including air pollution, cigarette smoke, diesel exhaust particles, obesity, certain drugs, and exercise, among others (Fig. 6.1). The mechanisms underlying non-Th2-associated asthma are poorly defined. Epithelial cells, Th1 cells, Th17

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Fig. 6.1 Asthma is a heterogeneous disease caused by a variety of environmental factors acting in combination with many genes. Asthma has several different forms, including allergic, non-allergic and intrinsic, and these forms can overlap in some patients. Allergen-induced asthma is mediated by Th2 immune responses. Non-allergic asthma can be induced by environmental factors such as cigarette smoke, viral infection, or air pollution. Epigenetic modifications of genes contributing to asthma can be induced by exposure to allergens or environmental exposure and in some cases, these modifications can be passed to future generations

cells, and neutrophils have been shown to mediate asthma and may contribute to this setting. Those with uncontrolled asthma have been shown to possess higher levels of neutrophils and chemokine-attracting cytokines, such as IL-8 and IL-17, in their bronchoalveolar lavage (BAL) fluids (Hosoki et al. 2016). Other proinflammatory cytokines, such as IL-6 and IL-23, have also been indicated in promoting neutrophil recruitment (Halwani et al. 2017). Human neutrophils contain activated nuclear factor-κB (NF-κB), a key driver of allergic inflammation (Ventura et al. 2014). Inhibitors of NF-κB have been shown to ameliorate allergic asthma in mice, (Zhang et al. 2017b) and successful allergen immunotherapy decreases NF-κB in the neutrophils of allergic patients (Ventura et al. 2014). In addition to the potential role of NF-κB, increased levels of tumor necrosis factor alpha (TNF-alpha), a type 1 cytokine, and IL-8, produced by epithelial and Th17 cells, have been observed in the serum of patients with asthma, with higher levels of interferon gamma (IFN-γ) observed in those with severe asthma (Jiang et al. 2018; Raundhal et al. 2015). Although asthma and rhinitis are often classified into an allergic or non-allergic phenotype in a dichotomous fashion, this simplistic method of classification is not without its shortcomings. Despite differences in phenotypic presentation, the classifications are of limited value in predicting an individual’s course of disease or

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response to therapy. Studies have shown a significant range of pathophysiological and clinical overlap among the two forms of asthma, and evidence now supports a link between environmental pollutants and an increase in both the incidence and the exacerbation of allergic disease and asthma (Yang and Schwartz 2012). Newer classification systems for asthma are rapidly evolving, and these strive to account for the heterogeneous nature of the disease by factoring in the complex genetic and environmental interactions driving its course. These newer forms of classification aim to link specific asthma endotypes (variations in the underlying genetic, epigenetic, or other molecular and cellular mechanisms) with specific asthma phenotypes (variations in asthma triggers, disease trajectory, and clinical characteristics) in an effort to better predict, prevent, and alter the course of disease, as well as promote the development of novel, targeted therapies, and personalized medicine (Kim et al. 2010; Muraro et al. 2016). Current evidence suggests the course of allergic disease may be set even before birth, with genetic variance playing a key role in the transmission of risk. Familial studies indicate that asthma occurs in a pattern consistent with heritable factors, with the risk of disease being twice as high in children with both parents affected by asthma compared to those with only one (Vicente et al. 2017). Heritability of asthma and AR have been estimated at between 35% and 95% and 33% and 91%, respectively, highlighting the importance of genetic mechanisms in the inheritance of disease risk (Ober and Yao 2011). Candidate gene studies, linkage studies, and GWAS have identified a number of these asthma-associated genetic variations. In 2007, the first GWAS for asthma identified asthma-associated single-nucleotide polymorphisms (SNPs) within the ORMDL3/GSDMB gene of chromosome 17q21 that have a strong association with childhood-onset asthma (Moffatt et al. 2007). The association between ORMDL3 and asthma has been replicated by numerous studies; however, the role of this gene in asthma remains poorly understood. Between 2007 and 2016, 25 GWAS of asthma were published, the largest with a sample size of 157,242 individuals; however, many of those identified are of unknown function and replication of many of these analyses is difficult due to the heterogeneity of asthma (Vicente et al. 2017). A disintegrin and metalloproteinase glycoprotein 33 (ADAM33) expressed in airway smooth muscle was the first report of a positionally cloned asthma susceptibility gene (Van Eerdewegh et al. 2002). Since its discovery in 2002, the association between ADAM33 polymorphisms, asthma, and bronchial hyperresponsivess (BHR) has been replicated by a number of studies in multiple populations (Jongepier et al. 2004). However, while genetic studies have identified a number of susceptible loci and candidate genes associated with the pathogenesis of asthma and AR, the risk-associated alleles for each gene account for only a very small percent of the overall genetic risk (Li et al. 2015; Ober and Yao 2011). In complex diseases such as allergic disease, cancers, neurologic disorders, and others, it is now thought that epigenetic modifications, including DNA methylation, histone modifications, and non-coding microRNAs, caused by complex interactions between the underlying genome and the environment may account for some of this “missing heritability” and may explain the high degree of plasticity in immune responses (Kuriakose and Miller 2010; Meyers et al. 2014). While the findings of

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epigenome-wide association studies (EWAS) are currently limited relative to those of GWAS, there are increasingly meaningful results in the literature. Unlike genetic variation, changes in the epigenome can occur rapidly in response to environmental exposures and provide a potential explanation for the rapid rise in asthma in allergic disease that has occurred over the last few decades. Epigenetics may also explain age and sex effects in disease and sporadic occurrence and remission of disease. Evidence suggests that epigenetic mechanisms can modify the expression of transcription factors involved in the regulation of T cells (Th1, Th2, and regulatory T (Treg) cells) and other immune cells, ultimately influencing the trajectory of asthma and allergic disease. In this chapter, we will focus on the current knowledge of classical epigenetic modifications, DNA methylation and histone modifications, and their potential role in asthma and AR. We will review epigenetic variations associated with maternal airway disease, demographics, environment, and non-specific associations. The role of specific genetic haplotypes in environmentally induced epigenetic changes is also discussed. MicroRNAs, which are short, “non-classical”, non-coding RNAs that regulate gene expression by targeting mRNAs and preventing protein translation, are beyond the scope of this review, and the reader is directed to other excellent reviews on the topic (Sastre et al. 2017; Zheng et al. 2018). As most epigenetic studies on allergic airway disease have focused on asthma, many of the examples of epigenetic alteration in this chapter are on asthma epigenetics; however, we have included examples of epigenetic studies on AR, when possible. Additionally, although most of the research investigating the role of epigenetics in allergy and AR has focused on DNA methylation, findings describing the role of histone modifications have begun to emerge. Among histone modifications, research has focused on histone acetylation and methylation, and there is a lack of data on other histone modifications, such as phosphorylation, sumoylation, and ubiquitination.

6.2 Epigenetic Variation in the Course of Asthma and Allergic Rhinitis 6.2.1 The Role of Maternal Airway Disease Epigenetic mechanisms associated with the inheritance of risk have recently come to light, including gene imprinting, prenatal modification of DNA methylation, and transgenerational inheritance. Epigenetic marks are not only transferred to daughter cells during cell replication, but they can also be inherited through generations. While the mechanisms of epigenetic inheritance and disease origin are yet to be fully described, evidence increasingly suggests that epigenetic variation associated with a trajectory toward asthma may originate as early as within the womb (DeVries et al. 2017; Gunawardhana et al. 2014a). The risk for allergy and asthma in those with a maternal history of asthma is up to fivefold greater than those with a paternal history (Barrett 2008), and this discrepancy may be explained through a combination

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of parental imprinting, a process during which some genes are epigenetically silenced during gametogenesis, and the modification of the fetal epigenome (Barrett 2008; North and Ellis 2011). Maternal asthma status has also consistently been associated with an increased risk of childhood asthma, with an inverse association between maternal asthma control during pregnancy and risk (Lim et al. 2010; Martel et al. 2009; Paaso et al. 2014). Mouse models of the disease suggest that an increase in asthma susceptibility persists even when the offspring of mothers with an allergic asthma phenotype is genetically and environmentally identical to offspring of healthy parents, providing support for the contribution of non-genetic, non-environmental factors in the transmission of asthma risk. The at-risk offspring display significantly increased airway hyperresponsiveness and inflammation upon allergen sensitization compared to controls; however, these proinflammatory responses are observed to persist across allergens to which the mother was not sensitized, arguing that the transfer of allergenspecific antibodies from the mother plays little to no role in this setting (Hamada et al. 2003). Significant DNA methylation changes have been observed in the peripheral blood of 12-month-old infants with a maternal history of asthma compared to those without, suggesting a role for epigenetic mechanisms in the transmission of risk. These epigenetic differences include several genes involved in key regulatory pathways relating to developmental, metabolic, and inflammatory processes that may contribute to the pathogenesis of asthma (Gunawardhana et al. 2014a). One such change is the significant hypermethylation of CHFR in those born to mothers with asthma. CHFR is an ubiquitin ligase implicated in the downregulation of IL-8 through its inhibition of the NF-κB pathway, and is potentially associated with persistent wheezing in children (Kashima et al. 2009; Morales et al. 2012). Interestingly, while the function of the PM20D1 gene, a carboxypeptidase PM20D1 precursor, is yet to be fully described, its differential methylation has been linked to maternal asthma and atopic status, maternal inhaled corticosteroid use, and maternal serum IgE, suggesting a potential role in the course of asthma. Significant alterations in the expression of these genes via differential methylation may lead to the overexpression of proinflammatory cytokine pathways, the promotion of a proallergenic phenotype, and the development of wheezing in infants, all of which contribute to the development of asthma (Gunawardhana et al. 2014a). Davies et al. demonstrated that increased levels of soluble ADAM33 induced in utero by allergen exposure of allergic mothers caused airway remodeling and enhanced postnatal airway eosinophilia and BHR (Davies et al. 2016). Some studies have suggested that alterations in epigenetic marks may contribute to the environmentally induced effects on ADAM33 expression and this remains under investigation (Yang and Schwartz 2012; Yang et al. 2012). Additional findings have demonstrated associations between maternal asthma status, altered DNA methylation profiles in cord blood mononuclear cells (CBMCs), and the subsequent development of asthma, suggesting the transmission of asthma susceptibility associated with maternal asthma status is indeed a result of epigenetic variations and that the trajectory toward asthma may originate as early as within the womb (DeVries et al. 2017; Gunawardhana et al. 2014a). Significant differences in

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DNA methylation have been observed in the cord blood of children born to asthmatic mothers who develop asthma compared to those who do not, with the most significant differences residing at genes associated with known immunoregulatory and proinflammatory pathways. By mapping these differentially methylated regions (DMRs) with their transcripts in a pathway-based network of asthma-associated methylation alterations at birth, researchers have identified transcription factor SMAD3 as the most connected node within the network (DeVries et al. 2017). SMAD3 has been recognized in multiple GWASs of asthma and is thought to play a role in asthma through its downstream regulation of Th17 and Treg cells (Derynck and Zhang 2003; Ferreira et al. 2014; Martinez and Vercelli 2013; Moffatt et al. 2010). Mean CBMC-associated methylation levels at the SMAD3 promotor were significantly greater in subjects developing asthma by 9 years of age compared to those who remained asthma-free, with a nearly twofold increase in risk for each 10% increase in SMAD3 methylation. This hypermethylation was also significantly associated with increased production of IL-1β, a proinflammatory mediator that is overexpressed in those with non-allergic asthma (DeVries et al. 2017; Hastie et al. 2010; Raedler et al. 2015). IL-1β has been associated with a number of pathological findings that may contribute to the development of asthma, such as increased airway hyperresponsiveness, elevated airway neutrophil counts, and the promotion of Th17 differentiation and expansion (Chung et al. 2009; Tsukagoshi et al. 1994). In contrast to the differences observed among the children of asthmatic mothers, no significant differences in methylation or expression were identified among the children of non-asthmatic mothers or when comparing asthmatic children to non-asthmatic children, independent of maternal asthma status. Ultimately, the epigenetic dysregulations of SMAD3 and IL-1β expression associated with maternal asthma appear to contribute to observed increases in asthma susceptibility by skewing the developing immune system toward the destabilization of the Treg pathway and increased differentiation of proinflammatory Th17 cells (DeVries et al. 2017). These findings provide evidence that epigenetic changes acquired prior to birth contribute to the transmission of risk associated with maternal asthma, and these specific changes may be of use as early predictors of a predisposition for asthma. Despite advances in the identification of potential epigenetic variations that may play a role in the maternal transmission of asthma risk, the mechanisms by which these variations are passed to the child in utero are much less understood; however, some studies suggest the transmission of risk may be mediated through dendritic cells (DCs). DCs in the airway play a critical role in determining how the immune system will respond to inhaled antigens during the initial presentation of the antigen to naïve T cells, with proinflammatory DCs driving the induction of Th2-dependent eosinophilic airway inflammation, goblet cell hyperplasia, and BHR (Hammad and Lambrecht 2006; Lambrecht 2001; Upham and Stumbles 2003). While the mechanisms dictating whether the DC will promote a tolerogenic or proinflammatory response are yet to be fully understood, epigenetic variation inherited through DCs may contribute to its decision. Mouse models comparing DC DNA methylation of offspring born to asthmatic and non-asthmatic mothers have noted significant differences in observed methylation patterns, with the majority of DMRs falling

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within interaction networks focused on the regulation of IL-6, a key inflammatory cytokine implicated in the pathogenesis of asthma via its induction of Th2 cell activity (Lajunen et al. 2016; Mikhaylova et al. 2013). While several genes within the IL-6associated DMRs also showed significant differences in their expression in allergennaïve pups, a vast majority of genes within the underlying DMRs only showed significant transcriptional differences upon sensitization to ovalbumin through a sensitization protocol. Following sensitization, nearly half of the differentially methylated and expressed genes were associated with known networks involved in allergic inflammation and asthma, potentially promoting early-life asthma. These findings argue that epigenetic changes within the DCs of neonatal mice with a maternal history of asthma may lay the groundwork for an environment in which allergen-naïve DCs preferentially promote a proinflammatory, Th2 cell-dominant response upon initial allergen encounter, ultimately driving the initial allergic process and early-life onset of an allergic asthma phenotype. In particular, aberrant regulation of IL-6 associated with these epigenetic changes may be of interest as an early predictor of allergic asthma susceptibility (Mikhaylova et al. 2013). In a murine study, under the influence of maternal AR, neonatal offspring showed increases in cytokines IL-4 and IL-17 and decreases in IL-10. Decreases in Treg cells were also observed. The study suggested that Th2 skewing might be mediated by increases in Foxp3 methylation (Tan et al. 2017). Whether or not these mechanisms are mirrored in the human transmission of maternal asthma risk is not yet known; however, these findings provide a foundation of promising targets for future research.

6.2.2 The Role of Demographic Variation In addition to the increased risk of disease associated with a maternal history of asthma and AR, there is an increasing body of evidence highlighting the association between specific patterns of variation in the epigenome and the development of asthma in pediatric patients. Although causality is difficult to establish, many of the observed patterns have been linked to specific demographic characteristics. Large epigenetic differences between different populations have been observed. A recent study evaluating CpG methylation near the transcription start sites of over 14,000 genes in 180 cell lines derived from one African and one European population found epigenetic differences in about one-third of the population (Fraser et al. 2012). Geographic variability of childhood asthma prevalence were found among neighborhoods in Chicago with predominantly African American neighborhoods having a higher asthma prevalence than predominantly white or Hispanic neighborhoods and this difference was observed even after taking into account cofounding factors such as sex, age, household members with asthma, and neighborhood income (Gupta et al. 2008). A population-based sample of children aged 3 years found that African American children had increased risk of asthma and this risk persisted independent of income levels. To determine if epigenetics can explain the differences in prevalence in asthma in different populations, Chen et al. measured global methylation in peripheral blood mononuclear cells (PBMCs) obtained from children with

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asthma and examined the association between global methylation and socioeconomic status, asthma severity, and race ethnicity. Their study indicated that African American children had higher levels of global DNA methylation than children of other races/ethnicities and that this difference was more pronounced when socioeconomic status and asthma severity were taken into account (Chan et al. 2017). In addition to epigenetic differences across race and socioeconomic status, ageand sex-related changes in disease-associated methylation have also been observed. Recent research by Naumova et al. identified a single regulatory region within the 17q12-q21 chromosomal region (proximal promoter region of the zona pellucida binding protein 2 (ZPBP2)) gene showing statistically higher DNA methylation in females compared to males. Additionally, DNA methylation was observed to be higher in adult males compared to boys. Chromosome region 17q12-q21 has previously been associated with asthma by several independent studies. These results suggest that DNA methylation attenuates the genetic effect of the 17q12-q21 alleles on asthma development (Naumova et al. 2013). Once asthma has manifested in the pediatric population, there is evidence of further change to underlying patterns of methylation, specifically in genes related to immune regulation. In a study of children aged 4–16 years old, significant hypomethylation of 14 unique CpG sites in the whole blood of those with asthma was observed compared to those without; however, these differences were not apparent in cord blood at birth. These associations were further strengthened when purified eosinophils were used as the source of DNA, suggesting a critical role of eosinophil CpG hypomethylation in driving the asthma-associated methylation profiles observed in whole blood. The CpG sites involved suggest an early-life shift of naïve T cell populations toward effector and memory CD8 cells, as well as natural killer cells, with five of the 14 sites having previously been associated with asthma in nasal epithelial cells (Xu et al. 2018). Obesity has also consistently been implicated as a risk factor for asthma (Sutherland 2014). Additionally, altered DNA methylation patterns have been associated with obesity (Dick et al. 2014; Sayols-Baixeras et al. 2017; Soubry et al. 2015). A GWAS of PBMCs from normal weight and obese asthmatic patients showed significant methylation differences between these groups. These differentially methylated regions were associated with T-cell differentiation and increased macrophage activation, factors that have previously been linked to obesity-associated asthma (Rastogi et al. 2013).

6.2.3 The Role of Biologic Variation In addition to disease-related epigenetic variations associated with demographic factors, several changes have been associated with differences in serum levels of IgE. IgE is a key effector molecule involved in mediating allergic reaction. It is associated with asthma severity and BHR, and anti-IgE therapies are currently used in the treatment of moderate-to-severe persistent allergic asthma (Buhl 2003; Oettgen

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and Geha 2001). Several EWAS have demonstrated associations between patterns of DNA methylation and IgE levels, suggesting that susceptibility to IgE-mediated asthma and allergy is driven, in part, through epigenetic means. A recent study conducted by Liang et al. found significant associations between CpG methylation across several genes, particularly LPCAT2, IL5RA, and ZNF22, and IgE levels within Caucasian subjects, including both adult and pediatric populations. Methylation levels were lower in asthma compared to healthy controls and among those with asthma, lower methylation levels were observed in those with high IgE than those with low IgE levels. Notably, these variations in methylation accounted for changes in IgE levels tenfold greater than those observed in studies of SNPs (Liang et al. 2015). Additional research by Chen et al. found similar associations between IgE and the differential methylation of white blood cell DNA obtained from Hispanic children, with specific changes in ZFPM1, ACOT7, and MND1 significantly associated with total serum IgE. Among these genes, both ACOT7 and ZFPM1 have been implicated in the pathogenesis of asthma (Chen et al. 2017). These findings are supported by a recent prospective longitudinal study evaluating DMRs of both cord blood and mid-childhood peripheral blood DNA. The study found 19 methylation marks that were significantly associated with mid-childhood levels of IgE. Further, analysis of methylation changes between cord blood and peripheral blood DNA identified 395 methylation marks in 272 genes associated with mid-childhood IgE, with several of the methylated loci previously associated with asthma (ADAM19, EPX, IL4, IL5RA, and PRG2) (Peng et al. 2018). While it is yet unknown how these specific differences in methylation are induced, the current evidence suggests a clear role for epigenetic variation in the regulation of IgE and potential development of IgE-mediated type-I hypersensitivities and an allergic asthma phenotype.

6.2.4 Disease-Associated Epigenetic Variation of Non-specific Origin While many airway disease-associated epigenetic patterns have been linked to characteristics of the individual, a number of these differential patterns currently remain idiopathic in nature, with no observed association with any individual characteristic. While a potential cause is not yet known, increased levels of IL-2 promoter region methylation in cord blood DNA have been associated with a 1.07-fold increase in the likelihood of severe asthma exacerbations and a 1.12-fold increase in likelihood of hospital admissions for asthmatic wheeze during childhood (Curtin et al. 2013; DeVries et al. 2017). In addition, higher average methylation of CpGs in the AXL gene at birth has been associated with lower mRNA expression of the gene in lung tissue and an increased risk of parent-reported wheezing in children up to 6 years of age, with greater association in females compared to males (Gao et al. 2017). In contrast to each of these patterns, some differences in methylation appear to be

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protective. Higher methylation of GATA3-associated CpGs at birth appears to be associated with reduced risk of asthma in childhood (Barton et al. 2017). In a recent study of African American children with persistent atopic asthma, significant differences in respiratory epithelial cell DNA methylation were observed across 186 genes when compared to those without disease. While the origin of these DMRs is again unknown, the regions included those with established roles in asthma and atopy and correlated well with expected changes in gene expression. Interestingly, the findings were validated in an independent cohort of children with atopic asthma and in an independent population of Caucasian adults with clinical asthma (Yang et al. 2017). While a number of DMRs have been associated with the development of asthma, cohorts of adult patients with asthma have also reported differences in epigenetic patterns associated with the observed clinical phenotype. Research comparing airway smooth muscle cultures obtained from bronchial biopsies in adults with varying disease severity has demonstrated significant variation in the methylation patterns of those with severe asthma, non-severe asthma, and no asthma, primarily in pathways linked to cell proliferation, apoptosis, and endocytosis (Perry et al. 2018). Weighted gene co-expression network analysis has additionally identified four comethylation modules associated with three distinct asthma phenotypes, including severity and inhaled corticosteroid usage, the presence of eosinophils in BAL fluid, and increased fractional exhaled nitric oxide (FeNO) levels (Nicodemus-Johnson et al. 2016a). Of note, the authors were able to associate the pathways and mechanisms by which each differentially methylated module likely promotes the observed phenotype. The findings highlight the value of looking beyond epigenetic variation in single CpG sites, instead of focusing on the net effects of the observed DMRs and the expression of their functional products (Perry et al. 2018). While most research studies have been focused on the influence of differential DNA methylation in airway disease, there is increasing evidence for the role of histone modifications in the course of asthma. Histone acetylation and deacetylation, controlled by histone acetyltransferases (HATs) and histone deacetylase (HDACs), respectively, have been shown to play a critical role in the process of regulation of multiple inflammatory genes. Alterations in HATs and HDACs have been observed in bronchial biopsies and peripheral blood monocytes in patients with asthma (Gunawardhana et al. 2014b; Ito et al. 2002). PBMCs from patients with severe asthma showed diminished corticosteroid sensitivity compared to those from non-severe asthma, and this has been shown to parallel reduction in HDAC activity (Barnes 2013; Hew et al. 2006). MKP1, a steroid-responsive gene, is switched on by corticosteroids through acetylation of histone H4 Lysine residues K5 and K16; however, in some patients with steroid-resistant asthma, K5 acetylation is not observed (Barnes 2013). In human airway smooth muscle cells, release of eotaxin, a potent chemoattractant for eosinophils, is associated with NF-κB binding and histone H4 acetylation of the eotaxin gene promoter region (Nie et al. 2005). Airway smooth muscle cells from asthmatic donors have shown increased histone H3 acetylation, specifically histone H3K18 acetylation, compared to those obtained from healthy controls. Those with asthma were also observed to have significantly increased CXCL8, a CXC

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chemokine that drives steroid-resistant neutrophilic airway inflammation (Clifford et al. 2015). The airway epithelium of asthmatics is abnormal, with dysregulation of genes that are essential for differentiation, proliferation, and inflammation, including epidermal growth factor receptor (EGFR), the N isoform of the transcription factor p63 (Np63), and signal transducer and activator of transcription 6 (STAT6), genes that are essential for differentiation, proliferation, and inflammation. Airway epithelial cells from asthmatics had increased acetylation of H3K18 around the transcription start site of Np63, EGFR, and STAT6 and suggest a complex interaction between histone modifications and gene regulation in asthma (Stefanowicz et al. 2015). In vitro studies using human Burkitt’s lymphoma cells indicate that acetylation of histone H3k9 and H3k27 may regulate IL-4/STAT6-mediated IgE transcription in B lymphocytes, potentially contributing to the pathogenesis of asthma (Fu et al. 2015). In addition to acetylation, histone methylation has also been implicated in the pathogenesis of asthma. Dysregulation of Notch1 has been linked to the pathogenesis of asthma. Overexpression of Notch1 is associated with dysregulation of Th17/Treg cells in peripheral blood of children with allergic asthma (Li et al. 2018). In asthmatic rats, histone modifications (increased acetylation levels of total H3, H4, site-specific H3K9, H3K14, H3K27, H3K18, H4K16, and the trimethylation levels of H3K4, H3K79) of the Notch1 promoter was seen compared to controls and has been shown to affect lung CD4+ T cell differentiation (Cui et al. 2013). Using genome-wide histone modification profiles of T cell subsets isolated from PBMCs of heathy and asthmatic subjects, it was determined that enhancers that gained H3K4me2 marks during Th2 cell development had high levels of SNPs associated with asthma (Seumois et al. 2014).

6.2.5 The Role of Environmental Exposure Research has consistently highlighted a link between environmental exposure to a variety of substances and a differential risk for asthma. While some environments have been shown to play a protective role, maternal exposure to a range of specific environmental triggers, such as air pollution or cigarette smoke, during gestation strongly increases the risk of asthma in the offspring, more so than paternal exposure, suggesting the involvement of an epigenetic mechanism driving such risk (Fig. 6.1 and Table 6.1). Living on a farm and exposure to its associated microbiome has been shown to protect children from the development of asthma and atopy (Ege et al. 2011; Stein et al. 2016). Michel et al. examined the effect of exposure to a farm environment on epigenetic patterns observed across asthma candidate genes and the changes that occurred in them over the first years of life. Cord blood analysis revealed that regions of ORMDL1 and STAT6, genes highly associated with asthma, were significantly hypomethylated in the DNA of farmers’ children compared to those of non-farmers. In contrast, regions of RAD50 and IL13, genes associated with IgE regulation and Th2 differentiation, were hypermethylated in those raised in the farm environment. While

Study (tissue type)

Human CBMCs (Perera et al. 2009)

Species and cell/tissue (Patil et al. 2013)

Cultured human bronchial AECs (Nicodemus-Johnson et al. 2016b)

Murine splenic DCs (Gregory et al. 2017)

Human saliva (Brunst et al. 2013)

Murine airway tissue (Jahreis et al. 2018)

Environmental exposure (time)

Airborne PAH (maternal)

Cigarette smoke (maternal)

IL-13 (postnatal)

DEP (maternal)

DEP (children)

BBP (Pre- and perinatal)

(continued)

↑ Allergic airway inflammation following allergen exposure in offspring

↑ Wheezing/asthma in later life

↑ Methylation of the FOXP3 locus Unspecified; (Phenotypic results of exposure attenuated via DNMT inhibiter in mice)

↑ Percentage of eosinophils and IL-5/IL-13 levels in BAL fluid following allergen sensitization (indicative of transgenerational allergic asthma)

↑ Methylation of IL-4-associated genes, specifically IKBKβ and SOCS5, through F3 offspring ↑ Differential methylation of genes associated with chromatin remodeling factors, specifically SUZ12 and TET1, through F3 offspring

↑ Airflow limitation and airway responsiveness

↑ Methylation of IL-13-associated loci in offspring

Genes clustered into modules correlated with asthma severity and eosinophilia

↑ Parent-reported asthma symptoms in children 1/3 MS patients No difference in SHP-1 methylation between active and stable patients

Methylation assessment method and key findings

Sample source and size (n)

Tissue type

Table 12.1 (continued)

(continued)

Handel et al. (2010a)

Ramagopalan et al. (2008)

Pinto-Medel et al. (2017)

Neven et al. (2016)

Kumagai et al. (2012)

References

12 Epigenetics in Multiple Sclerosis 317

• Genome-wide approach • 30 DMSs identified for RRMS versus HC; 67 for PPMS versus HC; 51 for PPMS versus RRMS • 53% hypermethylated DMSs for RRMS versus HC; 76% for PPMS versus HC; 86% for PPMS versus RRMS

• Genome-wide approach to study effect of smoking on DNA methylation • Smoking caused DNA methylation changes, particularly in known smoking-affected sites, which would attenuate 5 years after smoking cessation • MS patients with known risk factors (female and HLA-DRB*1501 risk haplotypes) showed larger methylation changes affected by smoking • DMS annotation revealed enrichment for autoimmune diseases • Hypomethylation in the top-associated marker of smoking AHRR gene was proportional to smoking load and was reversible after smoking cessation • Demonstrated ↑ AHRR expression in MS patients after smoking

RRMS, n = 18 versus PPMS, n = 8 versus HC, n = 8

Cohort S, n = 50 MS patients stratified for HLA-DRB1*1501+ and HLA-A*02− carriers and non-carriers; Cohort B, n = 132 MS patients without stratification versus HC, n = 135

Gene-specific analysis: MS, n = 28 versus HC, n = 10 Genome-wide analysis: MS, n = 14 versus HC, n = 14

PBMCs

PBMCs

PBMCs, CD4+ and CD8+ T cells

Gene-specific and genome-wide approaches Deconvolution analysis inferred hypomethylation in IL2RA in T cells in MS patients Associated with ↑ IL2RA expression in PBMCs ↑ IL2RA expression in purified CD4+ T cells and CD8+ T cells

• Gene-specific approach • PAD2 expression ↑ in MS, associated with PAD2 promoter hypomethylation • No correlation of PAD2 expression with disease duration EDSS and MRI activity

MS, n = 32 (31 RRMS, 1 SPMS) versus HC, n = 30

PBMCs

• • • •

Methylation assessment method and key findings

Sample source and size (n)

Tissue type

Table 12.1 (continued)

(continued)

Field et al. (2017)

Marabita et al. (2017)

Kulakova et al. (2016)

Calabrese et al. (2012)

References

318 V. S.-F. Chan

• Gene-specific approach • Hypermethylation in exon 1c (alternative promoter) of vitamin D receptor (VDR) in MS patients • VDR mRNA ↑ 6.5-fold in patients

RRMS, n = 23 versus HC, n = 12

MS discordant MZ twins, n = 3 twin pairs

RRMS, n = 17 (10 with and 7 without Natalizumab therapy) versus HC, n = 7

RRMS, n = 30 versus HC, n = 28

RRMS, n = 28 versus HC, n = 22

T cells

CD4+ T cells

CD4+ T cells

CD4+ T cells

CD4+ T cells

• • • •

• • • •

Genome-wide approach ↓ methylation at DMS at HLA-DRB1 ↑ methylation at DMS in HLA-DRB5 11 CpGs at RNF39 in the MHC region of chromosome 6 is independent of HLA-DRB1

Genome-wide approach 74 differentially methylated CpGs with 55 non-HLA and 19 HLA-associated sites in MS patients HLA-DRB1 showed top differential methylation signals 8 of the HLA-associated CpGs clustered to HLA-DRB1 showed ~26% decrease in methylation compared to HCs

• Gene-specific approach • Demethylation in FOXP3 and IL-17A but no difference in IL-13 and IFNγ methylation in Natalizumab-naive MS T cells when compared with HC • No methylation difference in FOXP3 and IL-17A between Natalizumab-treated MS CD4+ T cells and HC

• Genome-wide approach • Only 2–176 DMSs were found among the 2 million CpG dinucleotides between MZ pairs when compared with 800 DMS in unrelated individuals • Limited methylation difference observed between MZ siblings

Methylation assessment method and key findings

Sample source and size (n)

Tissue type

Table 12.1 (continued)

(continued)

Maltby et al. (2017)

Graves et al. (2014)

Janson et al. (2011)

Baranzini et al. (2010)

Ayuso et al. (2017)

References

12 Epigenetics in Multiple Sclerosis 319

• • • •

• Genome-wide approach, locus- and allele-specific validation • Two DMRs found hypomethylated mapped to HLA-DRB1 exon 2 locus in MS when compared with HC • HLA-DRB1*15:01 homozygous carriers exhibited significantly lower methylation, and inversely correlated with higher expression when compared with heterozygous and non-carriers • DRB1*15:01 methylation can exert regulatory properties to drive higher gene expression • 50 risk SNPs were found in 7 DMRs within HLA region that would modify gene expression by Causal Inference Test • Identified a novel protective SNP (rs9267649) with higher methylation in exon 2 of HLA-DRB1 and lowered the gene expression

MS (treatment naïve), n = 16 versus HC, n = 14

RRMS, n = 30 versus HC, n = 28

MS, n = 62 versus HC, n = 20 (monocytes) MS, n = 140 versus HC, n = 139 (whole blood)

CD4+ and CD8+ T cells

CD8+ T cells

Monocytes, whole blood

• • • •

Genome-wide approach 79 differential methylated CpGs (DMS) associated with MS No CpG methylated effect in HLA-DRB1 in CD8+ T cells Distinct DNA methylation profiles from CD4+ T cells

Genome-wide approach Hypermethylation in CD8+ T cells but not CD4+ T cells No evidence of differential methylation in 148 MS-associated risk gene loci No large consistent DNA methylation differences that distinguish patients at different disease status

• Genome wide and gene-specific approach • Highest DMS signals observed in VMP1/MIR21 locus, with ↑ methylation in RRMS when compared with SPMS and HC • Negative correlation with age and miR-21 levels; • Significant upregulation of miR-21 target genes

Discovery cohort: RRMS, n = 12 versus SPMS, n = 8 versus HC, n = 12 Replication set: RRMS, n = 70 versus HC, n = 24

CD4+ T cells

Methylation assessment method and key findings

Sample source and size (n)

Tissue type

Table 12.1 (continued)

(continued)

Kular et al. (2018)

Maltby et al. (2015)

Bos et al. (2015)

Ruhrmann et al. (2017)

References

320 V. S.-F. Chan

• Gene-specific approach • Demethylated myelin oligodendrocyte glycoprotein (MOG) DNA can be detected in patients • Circulating MOG DNA in relapsing MS patients showed higher demethylation index than inactive patients and HCs

• Gene-specific approach • Hypermethylation of LINE1 5 UTR CpGs, particularly CpG sites in L1PA2 subfamily

RRMS in relapse n = 19, versus stable disease, n = 30 versus HC, n = 47

RRMS, in relapse, n = 20 versus inactive disease, n = 20 versus HC, n = 20

MS, n = 24 versus HC, n = 24

cfcDNA

cfcDNA

Dunaeva et al. (2018)

Olsen et al. (2016)

Lehmann-Werman et al. (2016)

Liggett et al. (2010)

References

Abbreviations AHRR, acryl hydrocarbon receptor repressor; BCL2L2, Bcl-2-like protein 2; cfcDNA, cell-free circulating DNA; CDKN2A, cyclin-dependent kinase inhibitor 2A; CTSZ, cathepsin Z; DMRs/DMSs/DMPs, differential methylated regions/sites/positions; DMNT, DNA methyltransferase; EDSS, Expanded Disability Status Scale; FOXP3, Fox-head box P3; HCs, healthy controls; IFN, interferon; LGMN, legumain; LINE-1, long interspersed nuclear element 1; MBP3, myelin basic protein 3; MOG, Oligodendrocyte glycoprotein; MS, multiple sclerosis; MZ, monozygotic; NDRG1, N-Myc Downstream Regulated 1; NEUROG1, neurogenin 1; PAD, protein arginine deiminases; PBLs, peripheral leukocytes; PBMCs, peripheral blood mononuclear cells; PPMS, primary progressive MS; RRMS, relapsing-remitting MS; RUNX, Runt Related Transcription Factor 1; SPMS, secondary progressive MS; SNP, single nucleotide polymorphism; Susceptibility To, 1, SOCS1, Suppressor of cytokine signaling 1; TSS, transcription start site; TETs, Ten-eleven translocation proteins; WM1, Macroglobulinemia, Waldenstrom

• Gene-specific approach • To identify tissue-specific methylation pattern in cfDNA in different disease conditions including diabetes, MS, brain/cardiac injury, pancreatic cancer/pancreatitis • Unmethylated oligodendrocyte-derived DNA fragments from myelin basic protein (MBP3) and unannotated locus WM1 were detected in MS patients in relapse but not in stable patients nor in HCs • Short live unmethylated MBP3 and WM1 cfcDNA reflects acute oligodendrocyte cell death

Methylation array assay for 56 gene promoters 4–8 times higher cfcDNA concentration in MS patients than HC Distinct sets of target methylation can differentiate RRMS(r), RRMS(e) and HC Methylation pattern can differentiate (i) RRMS(r/e) versus HC with >75% sensitivity and >91% specificity; (ii) RRMS(e) and RRMS(r) with >70% sensitivity and 71% specificity

cfcDNA

• • • •

RRMS(r) in remission, n = 30 versus RRMS(e) in exacerbation, n = 29 versus HC, n = 30

cfcDNA

Methylation assessment method and key findings

Sample source and size (n)

Tissue type

Table 12.1 (continued)

12 Epigenetics in Multiple Sclerosis 321

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process, including oligodendrocyte-specific genes MBP and SOX8, as well as genes for cell survival such as BCL2L2 and NDRG1. On the other hand, the hypomethylated genes were mostly associated with lymphocyte-mediated immunity and leukocyte-associated pathways, paving the way to immune-mediated pathology in MS patients. For instance, elevated mRNA levels of proteolytic cathepsin Z (CTSZ) and legumain (LGMN) observed in pathology-free MS tissues may participate in the cleavage of MBP, yielding immunogenic peptides (Beck et al. 2001). Interestingly, DNA methylation also modulates immunogenicity of autoantigens in MS brain tissues. Elevated levels of citrullinated MBP is consistently present in normal appearing white matter in MS brain tissues (Mastronardi et al. 2007; Bradford et al. 2014), and this is possibly due to the hypomethylation in promoter of the citrullination enzyme gene peptidylarginine deiminases 2 (PAD2) (Mastronardi et al. 2007; Yang et al. 2016b). Notably, an increase in PAD2 expression with promoter hypomethylation was also observed in peripheral blood mononuclear cells (PBMCs) of MS patients (Calabrese et al. 2012).

12.3.1.2

Dysregulated DNA Methylation in Circulating Leukocytes in MS Patients

As MS pathology is primarily immune-mediated, it is not surprising to find DNA methylation aberrations in peripheral blood leukocytes of MS patients (Table 12.1). Differential methylation is observed not only between MS patients and healthy controls (HCs) but also between MS patients in different clinical stages of disease. Using genome-wide approach to compare PPMS and RRMS patients, there were 51 DMSs found, 86% of which were hypermethylated (Kulakova et al. 2016). Several independent investigations further revealed a global DNA hypermethylation in the peripheral blood of MS patients, as indicated by the methylation status of several repetitive elements, including the Alu element, the long interspersed nuclear element 1 (LINE-1) and the alpha satellite DNA sequences (SAT-α) (Neven et al. 2016; PintoMedel et al. 2017; Dunaeva et al. 2018), which all together constitute over 30% of the human genome. A lower level of LINE-1 and a higher level of Alu methylation were associated with MS patients having lower disease activity with Expanded Disability Status Scale (EDSS) score ≤2.5 (Neven et al. 2016). Also, high LINE-1 methylation in peripheral blood leukocytes (PBLs) and cell-free circulating DNA (cfcDNA) confers a higher risk for having MS as well as a higher risk for developing clinical activities in IFNβ-treated patients (Pinto-Medel et al. 2017; Dunaeva et al. 2018). Interestingly, a negative correlation between IFNβ treatment duration and percent of LINE-1 methylation was found exclusively in MS patients without clinical activity (Pinto-Medel et al. 2017). Though intriguing, the mechanistic relationship between methylation of these repetitive elements and MS pathogenesis is yet to be elucidated. Genome-wide methylation analyses of circulating leukocytes from patients and HCs reveal striking differential methylation in the top MS-associated locus, HLADRB1 (Graves et al. 2014; Maltby et al. 2017; Kular et al. 2018). Hypomethylation of CpG clusters in HLA-DRB1 in CD4+ T cells from MS patients was shown partially

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dependent on the DRB1*15:01 risk haplotype (Graves et al. 2014). Interestingly, the methylation changes were cell-type specific since CD8+ T cells did not show MSassociated difference in HLA-DRB1 and HLA-DRB5 methylation in the same cohort of patients (Maltby et al. 2015, 2017). Indeed, an independent study also showed distinct methylation patterns between CD4+ and CD8+ T cells, and the methylation pattern was independent of MS disease status (Bos et al. 2015). Consistent with this, no methylation difference in HLA-DRB1*15:01 and HLA-DR5 was observed between MS patients with benign and severe diseases (Handel et al. 2010a). Intuitively, hypomethylation, especially in the DRB1*15:01 risk haplotype, is linked with a higher expression of the gene (Alcina et al. 2012), which in turn confers functional enhancement in antigen presentation. A recent study indeed validated this functional link and showed that DRB1*15:01 homozygous carriers exhibited lower methylation and higher gene expression than the heterozygous and non-carriers (Kular et al. 2018). This team further identified a novel protective single nucleotide polymorphism (SNP) that was associated with higher methylation in exon 2 of HLADRB1 and correspondingly rendered a lower expression of the gene (Kular et al. 2018). Gene-specific approach also revealed methylation differences in non-MHC loci and genes. In general, hypomethylation was found in genes associated with enhanced immune effector functions, including IL2RA and IL17A (Janson et al. 2011; Field et al. 2017), whereas hypermethylation was observed in gene of negative immunomodulatory functions such as SHP-1 (Kumagai et al. 2012). Interestingly, FOXP3, the master transcription factor for regulatory T cells (Treg) differentiation, was also reported to have lower methylation in CD4+ T cells in MS patients (Janson et al. 2011). However, whether these differential methylation patterns in IL17A and FOXP3 in T cells contribute to the disrupted Th17/Treg balance in MS patients is yet to be validated. Two independent studies have revealed the intricate relationship between environmental factors and DNA methylation in MS patients. Vitamin D deficiency and smoking are established risk factors of MS with poor clinical outcomes (Wingerchuk 2012; Lucas et al. 2015). An increase in methylation was found in the alternative promoter at exon 1c of vitamin D receptor (VDR) in T cells of RRMS patients, but this was associated with VDR mRNA upregulation in total blood leukocytes (Ayuso et al. 2017). Although this appears to be in apparent contradiction with the hypothesized role of vitamin D in the development of MS, these findings should be interpreted with cautions as VDR methylation status and mRNA expression were derived from different cell populations, and no experimental evidence was provided to support a cause-and-effect of the two observations. On the other hand, a recent study showed an intriguing exposure–response relationship between smoking and DNA methylation changes in MS patients (Marabita et al. 2017). Comparing genome-wide methylation pattern in MS patients who were never-smokers and ex-smokers within 5-year and beyond 5-year, statistical analyses indicated smoking could potentially impart DNA methylation changes, particularly in known smoking-affected sites and in patients bearing the HLA-DRB*1501 risk haplotypes. From a functional standpoint, the acyl hydrocarbon receptor repressor AHRR was among the top demethylated loci with increased expression after smoking. Also,

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AHRR hypomethylation was proportional to smoking load and was reversible after smoking cessation (Marabita et al. 2017). AHR is a known regulator of cigarette smoke response (Martey et al. 2005). In mice, activation of AHR has been shown to suppress Treg differentiation and promote Th17 cell development, thereby leading to an exacerbated disease in an EAE model (Quintana et al. 2008). This study therefore provides evidence for the functional link between modifiable risk factors, epigenetics changes and pathogenic mechanisms that modulate clinical outcome in MS development.

12.3.1.3

DNA Methylation Modulation in EAE

As in human MS, EAE mice also have aberrations in DNA methylation which can be modulated by environmental factors. For instance, the reduced methylation and increased mRNA levels of Dexras-1, a neuronal nitric oxide synthase downstream target, in the striatum of MOG-induced EAE mice can be reversed by simply housing the mice with environmental enrichment toys and nesting materials (Catanzaro et al. 2016). Also, a number of studies in EAE mice have clearly demonstrated the functional impact of environmental risk factors on DNA methylation through rebalancing the Th17/Treg ratio. The promoter region of the FOXP3 gene was found hypermethylated with reduced transcript level in EAE mice and may lead to a lower Treg frequency, favoring the development of autoimmunity (Noori-Zadeh et al. 2017). The dietary supplement of vitamin D3 (VD3) has been shown to ameliorate disease in EAE animals by regulating Th17 and Treg frequencies (Zeitelhofer et al. 2017; Moore et al. 2018). Transcriptome analysis in CD4+ T cells from 1,25(OH)2 D3 -fed rats reveal a global downregulated expression of targets in the JAK/STAT, ERK/MAPK and PI3K/AKT/mTOR signaling pathways that affect T cell metabolism, activation and differentiation (Zeitelhofer et al. 2017). Mechanistically, VD3 downregulated the global DNA methylation level in T cells by suppressing the expression of Dnmts. In fact, VD3 modulates multiple epigenetic modifiers, including histone acetylation via suppressing the key processing enzymes histone deacetylase genes Hdac1 and Hdac2, as well as upregulation of regulatory microRNAs that target mRNAs related to inhibiting Th17 differentiation (Zeitelhofer et al. 2017). Additionally, calcitriol+VD3 was also shown to promote methionine metabolism through upregulation of the betaine:homocysteine methyltransferase-1 (BHMT1), in a vitamin D receptor (VDR)-dependent manner. BHMT1 is known to transmethylate homocysteine to yield methionine, which in turn can lead to an increase in DNA methylation and modulate the disease course of EAE disease. These calcitriol/VD3fed mice also showed reduction of disease severity with an upregulation in transcripts of Helios, a Treg activity stabilizer (Moore et al. 2018). Overall, these data suggest that VDR signaling in CD4+ T cells can exert effects via multiple epigenetic regulatory pathways to modulate EAE disease. VD3 has been reported to repress CD44 expression in cancer cells (So et al. 2011). Interestingly, a lower CD44 expression in CD4+ T cells may favor EAE attenuation through regulating Th differentiation.

12 Epigenetics in Multiple Sclerosis

325

CD44 activation in T cells promotes Th1/Th17 differentiation through demethylation of the Ifng and Il17a promoters and methylation of the Il4 and FOXP3 promoters, whereas activation of T cells deficient of CD44 reverses these methylation events, leading to disease amelioration (Guan et al. 2011).

12.3.2 MicroRNAs and MS MicroRNAs (miRNAs) constitute a unique family of small non-coding RNAs that represent another layer of epigenetic regulation at the post-transcriptional level. Functionally, the ~22-nucleotide-long mature miRNA in the RNA-induced silencing complex (RISC) binds to complementary sequences, mostly at the 3 -untranslated region (3 -UTR), of the target messenger RNA (mRNA) and mediates translational repression and/or mRNA degradation (Bartel 2009; Huntzinger and Izaurralde 2011). To date, there are over 1900 annotated miRNAs identified in the human genome (http:// www.mirbase.org/). The regulatory network of microRNAs is highly complex since one miRNA can recognize multiple mRNA targets, and an mRNA molecule can be targeted by multiple miRNAs. In the immune system, miRNAs are critical for immune homeostasis and their aberrations can lead to autoimmunity (Mehta and Baltimore 2016; Lam et al. 2018; Yan et al. 2014). For instance, deficiency in the key miRNA processing enzymes Drosha and Dicer in T and B cells results in spontaneous autoimmunity, highlighting the essential role of miRNAs in maintaining self-tolerance (Cobb et al. 2006; Chong et al. 2008; Belver et al. 2010). In MS, overexpression of Dicer, Drosha and its associated microprocessor complex protein DGCR8 were found to be significantly upregulated in peripheral leukocytes (Jafari et al. 2015). On the other hand, B cells from MS patients were shown to have reduced Dicer expression with functional implication in enhancing CD80 and CD86 expression (Aung and Balashov 2015). In EAE mice, dysregulated RISC assembly in infiltrating T cells was shown to contribute to miRNA-dependent proinflammatory Th cell polarization (Lewkowicz et al. 2015). In patients, dysregulated expressions of a multitude of miRNAs have been extensively reported, either by profiling analysis (Table 12.2) or by analysis of a small and specific set of miRNAs (Table 12.3), in a variety of clinical specimens. In the following sections, the regulatory role of miRNAs in MS was reviewed from two different angles: (i) dysregulation of miRNAs in a specific cell type or tissue; and (ii) the role of individual specific miRNA.

12.3.2.1

Dysregulation of MiRNAs in T Cells

As the major effector cells in MS pathogenesis, miRNA dysregulation in CD4+ T cells has attracted much attention in the past decade. MiRNA profiling studies in patient samples (Table 12.2) have revealed upregulation of miR-485-3p, miR-376a, miR-1, miR-497, miR-193a, miR-200b, miR-126, miR-486, miR-17-5p and downregulation of miR-34a in CD4+ T cells in patients with RRMS compared to HCs (Lindberg et al.

Active MS: miR-650; miR-155; miR-326; miR-142-3p; miR-146a; miR-146b; miR-34a; miR-21; miR-23a; miR-199a Inactive MS: miR-629; miR-148a; miR-23a; miR-28; miR-195; miR-497; miR-214; miR-130a; miR-135a; miR-204 miR-25; miR-505; miR-320b; miR-320a; miR-338-3p; miR-181b; miR-125b1; miR-92a; miR-155

MS, n = 16 for active lesions, n = 5 for inactive lesions versus non-neurological disease control samples, n = 9

MS, n = 16 versus non-neurological diseases control, n = 10

Brain, white matter

Brain, cerebral white matter

a miRNA Up-regulated

Patient group versus control group, n = sample size

Tissue source for miRNA profiling

Table 12.2 MiRNA profiling studies in MS patients

miR-7; miR-299-5p; miR-135a; miR-218; miR-129-3p; miR-9; miR-128; miR-130A; miR-126; miR-335; miR-98

Active MS: miR-656; miR-184; miR-139; miR-23b; miR-328; miR-487b; miR-181c; miR-340 Inactive MS: miR-219; miR-338; miR-642; miR-181b; miR-18a; miR-340; miR-190; miR-213; miR-330; miR-181d

a miRNA Down-regulated

• Neurosteroid synthesis enzyme-specific miRNAs miR-338, miR-155 and miR-491 showed bias toward induction in patients • 3α-hydroxysteroid dehydrogenase AKR1C1 and AKR1C2 were targeted and suppressed neurosteroid synthesis machinery • Treatment of allopregnanolone suppress neuroinflammation in EAE mice

• miR-155, miR-34a, and miR-326 target 3 -UTR of CD47 • miR-155 expression can be upregulated by cytokines in astrocytes • Upregulated miRNAs were associated with downregulation of CD47 in active MS lesions

Key findings

(continued)

Noorbakhsh et al. (2011)

Junker et al. (2009)

References

326 V. S.-F. Chan

CSF

MS, n = 53 versus OND control, n = 39

a MS, n = 16 versus HC, n = 5

MS, demyelinated tissue, n = 4 versus myelinated tissue, n =4

Brain, hippocampus

Brain, normal appearing white matter

Patient group versus control group, n = sample size

Tissue source for miRNA profiling

Table 12.2 (continued)

miR-181c; miR-633

miR-223

miR-30d; let-7g; miR-124;miR-24; miR-376; miR-143

a miRNA Up-regulated

miR-922

miR-191; miR-29c, let-7i; miR-449b, miR-125b; miR-324-5p; miR-99a; miR-532-3p; miR-132; miR-151-3p; miR-421; miR-1914; miR-485-5p; miR-517c+ miR-519c

miR-2014; miR-181c; miR-181a, miR-138

a miRNA Down-regulated

• miR-181c and miR-633 differentiated RRMS from SPMS with 82% specificity and 69% sensitivity

• miR-191 negatively correlated with SOX4, FZD4, FZD5, WSB1, BDNF • miRNA target pathway prediction suggested regulation on MAPK signaling, focal adhesion, actin cytoskeleton, adhesion junction, extracellular matrix interaction etc.

• Elevated miR-124 in demyelinated tissue target ionotrophic glutamate receptors AMPA2 and AMPA3 • ↑ miR-124, ↓ AMPA receptors and ↓ memory performance also found in EAE

Key findings

(continued)

Haghikia et al. (2012)

Guerau-de-Arellano et al. (2015)

Dutta et al. (2013)

References

12 Epigenetics in Multiple Sclerosis 327

miR-150; miR-328; miR-30a-5p; miR-645

miR-145; miR-186; miR-664; miR-422a; miR-142-3p; miR-584; miR-223; miR-1275; miR-491-5p

miR-768-3p

miR-16-2-3p

RRMS, treatment naïve, n = 9 versus OND control, n = 5

RRMS, n = 20 versus HC, n = 19

MS treatment naïve, n = 59 (PPMS, n = 18; SPMS, n = 17; RRMS, n = 24) versus HC, n = 37

CIS, n = 25 versus RRMS, n = 25 versus HC, n = 50

CSF

Whole blood

Whole blood

Whole blood

a miRNA Up-regulated

Patient group versus control group, n = sample size

Tissue source for miRNA profiling

Table 12.2 (continued)

miR-20a-5p; miR-7-1-3p

miR-126; miR-454; miR-17; miR-98; let-7f; miR106a; miR-27a; miR-126; miR-140-5p; miR-624

miR-20b

miR-21; miR-199a-3p; miR-191; miR-365; miR-106a; miR-146a

a miRNA Down-regulated

• Reconfirmed underexpression of miR-20a-5p in MS

• 27 miRNAs dysregulated • miR-17 and miR-20a downregulation in all MS subtypes • Knock in/down of miR-17 and miR-20a in Jurkat T modulated T cell activation genes that were also deregulated in MS whole blood

• 165 miRNAs were differentially expressed • miR-145 discriminated RRMS from HC with 89.5% specificity, 90.0% sensitivity and 89.7% accuracy

• Differential expression of miR-150, miR-30a-5p, niR-645 and miR-191 were found in MS patients with lipid-specific oligoclonal IgM bands

Key findings

(continued)

Keller et al. (2014)

Cox et al. (2010)

Keller et al. (2009)

Quintana et al. (2017)

References

328 V. S.-F. Chan

Relapse versus HC: miR-18b; miR-493; miR-599

miR-550; miR-524-3p; miR-223

let-7d; miR-744; miR-93; miR-145

miR-200c; miR-146b; miR-125a

RRMS in relapse, n = 4 versus RRMS in remission, n = 9 versus HC, n = 8

MS, n = 19 versus HC n = 14

RRMS treatment naïve, n = 20 versus HC, n = 21

MS, n = 10 versus HC, n = 10

PBMCs

PBMCs

PBMCs

PBMCs

a miRNA Up-regulated

Patient group versus control group, n = sample size

Tissue source for miRNA profiling

Table 12.2 (continued)

miR-328; miR-199a; miR-152

miR-363; miR-31; miR-876-3p; let-7 g; miR-181c; miR-374a; miR-150

a miRNA Down-regulated

• Six miRNAs were abnormally expressed in Chinese MS patients

• miR-145 in plasma, PBMCs and serum with possible diagnostic value by ROC analysis; • let-7d with positive correlation with IL1B mRNA level

• 104 deregulated miRNAs identified in MS • let-7g and miR-150 with highest rank and validated • Expression correlation analysis identified LKKR1, c9orf109 and CLSPN as potential mRNA targets of let-7 g and miR-150

• miR-18b and miR-599 may be relevant at relapse • miR-96 may be involved in remission • miR-96 may target genes in interleukin and Wnt signaling

Key findings

(continued)

Yang et al. (2014)

Sondergaard et al. (2013)

Martinelli-Boneschi et al. (2012)

Otaegui et al. (2009)

References

12 Epigenetics in Multiple Sclerosis 329

Patient group versus control group, n = sample size

RRMS, n = 11 in IFNβ treatment versus HC, n = 9

RRMS, n = 8 versus HC, n = 10

SPMS, n = 12 versus HCs, n = 12

Tissue source for miRNA profiling

CD3+ T cells

CD4+ T cells

CD4+ T cells

Table 12.2 (continued)

CD4+ T cells: miR-485-3p; miR-376a; miR-1; miR-497; miR-193a; miR-200b; miR-126; miR-486; miR-17-5p

miR-3153

a miRNA Up-regulated

miR-21-5p; miR-26b-5p; miR-29b-3p; miR-1432-3p; miR-155-5p

CD4+ T cells: miR-34a

miR-494; miR-15b; miR-30c; miR-23a; miR-197; miR-1260b; miR-125a-5p; miR-361-5p; miR-320d

a miRNA Down-regulated

• SOCS6 as predicted target and have ↑ expression in MS CD4+ T cells

• Distinct miRNA dysregulation in CD4+ T, CD8+ T and B cells • miR-17-5p, miR-193a and miR-126 expression changed in response to T cell stimulation • miR-17-5p showed expression correlation with its potential mRNA targets of PTEN and PI3KR1

• 23 miRNAs deregulated • miR-494 and miR-197 downregulation validated • Computation matching of DE mRNAs and miRNAs revealed genes enrichment of 21 modules of immune functions • Expression of TNFSF14 as potential target was downregulated in MS

Key findings

(continued)

Sanders et al. (2016)

Lindberg et al. (2010)

Jernas et al. (2013)

References

330 V. S.-F. Chan

miR-629

miR-497

MS Untreated versus treated: miR-551a; miR-19b; miR-191; miR-598; miR-150; BART3-5p; miR-142-5p; BART11-5p; miR-383; miR-106b miR-614; miR-572; miR-648; miR-422a; miR-22

RRMS, n = 8 versus HC, n = 10

RRMS, n = 8 versus HC, n = 10

RRMS treatment naïve, n = 10; natalizumab treated, n = 10 versus HC, n = 10

MS, n = 4 versus HC, n = 4

CD8+ T cells

B cells

B cells

Plasma

miR-29c; miR-107; let-7i; miR-15a; miR-19a; miR-19b; miR-106b

RRMS, n = 12 versus HC, n = 14

CD4+ CD25+ Treg

a miRNA Up-regulated

Patient group versus control group, n = sample size

Tissue source for miRNA profiling

Table 12.2 (continued)

miR-1979

MS Untreated versus HC: miR-25; miR-106b;miR-93; miR-19b; miR-181a (qPCR validated from a list of downregulated 49 miRNAs)

miR-92; miR-135b; miR-153; miR-189; miR-422a

miR-149; miR-30a-3p; miR-497

miR-138-2; miR-324-3p; miR-338-5p; miR-489

a miRNA Down-regulated

• 6 DE miRNAs identified as potential MS biomarkers

• Two clusters miR-106b-25 and miR-17-92, were particularly deregulated • Interaction analysis revealed mRNAs from BCR, PI3K and PTEN pathways were affected • Deregulated viral miRNAs in untreated MS

• Distinct miRNA dysregulation in CD4+ T, CD8+ T and B cells

• Distinct miRNA dysregulation in CD4+ T, CD8+ T and B cells

• miR19-b significantly enriched in CD4+ CD25+ CD127lo Treg versus CD4+ CD25+ CD127+ T effector cells

Key findings

(continued)

Siegel et al. (2012)

Sievers et al. (2012)

Lindberg et al. (2010)

Lindberg et al. (2010)

De Santis et al. (2010)

References

12 Epigenetics in Multiple Sclerosis 331

• miR-191-5p associated with progressive forms of MS • miR-128-3p mostly associated with PPMS

PPMS, n = 18 versus HC, n = 10 Validation cohort: PPMS, n = 31 SPMS, n = 31 versus HC, n = 21

Serum

MS versus HC: miR-191-5p PPMS versus HC: miR-376c-3p, miR-128-3p, miR-24-3p

• miR-15b, miR-23a, and miR-223 levels in direct correlation with EDSS in PPMS

RRMS, n = 8; PPMS, n = 5 versus HC, n = 11

Serum

MS versus HC: miR-15b; miR-23a; miR-223

DE miRNAs identified • RRMS versus HC: miR-22; miR-30e; miR-140-3p; miR-210; miR-500; miR-574-3p • SPMS versus HC:let-7a • RRMS versus SPMS: miR-92a-1; miR-135a; miR-454; miR-500; miR-574-3p • miR-92a-1 and miR-454 significantly associated with EDSS and disease duration

Key findings

RRMS, n = 10 SPMS, n = 9 versus HC, n =9

a miRNA Down-regulated

Plasma

a miRNA Up-regulated

Patient group versus control group, n = sample size

Tissue source for miRNA profiling

Table 12.2 (continued)

(continued)

Vistbakka et al. (2017)

Fenoglio et al. (2013)

Gandhi et al. (2013)

References

332 V. S.-F. Chan

miR-22-3p; miR-660-5p

RRMS, treatment naïve, n = 4 verus IFNβ-treated for 2 years, n = 7

RRMS, n = 9 in relapse, n = 10 in remission versus HC, n = 10 Validation set: RRMS in relapse, n = 33; in remission, n = 30 versus HC, n = 32

Serum exosomes

Serum exosomes

miR-122-5p, miR-196b-5p; miR-301a-3p; miR-532-5p in relapse patients

miR-486-5p; miR-451a; let-7b-5p; miR-320b; miR-122-5p; miR-215-5p; miR-320d; miR-9-3p; miR-26a-5p; miR-142-3p; miR-146a-5p; miR-15b-3p; miR-23a-3p; miR-223-3p

Let-7c-5p; miR-365a-3p

a miRNA Down-regulated

• These 4 miRNAs had significant reduction in patients with gadolinium enhancement in brain MRI • Putative overlapping mRNA targets include STAT3 and AHR

• miR-320a top DE • miR-37a-3p linked with disease progression • miR-199-5p correlated with EDSS

Key findings

Selmaj et al. (2017)

Manna et al. (2018)

Regev et al. (2016)

References

a only the top ten most differentially expressed miRNAs were listed if the number of DE miRNA reported exceeds 10 Abbreviations AHR, aryl hydrocarbon receptor; BCR, B cell receptor; BDNF, brain derived neurotrophic factor; CLSPN, Claspin; CIS, clinically isolated syndrome; CSF, cerebrospinal fluid; DE, differentially expressed; FZD4, Frizzled 4; HC, healthy control; LKK1, Leucine-rich repeat kinase 1; MS, multiple sclerosis; OND, other neurological diseases; PBMC, peripheral blood mononuclear cell; PPMS, primary progressive MS; RRMS, relapsing-remitting MS; SPMS, secondary progressive MS; EDSS, Expanded Disability Status Scale; UTR, untranslated region; ROC, Receiver Operating Characteristic curve; PI3KR1, Phosphoinositide-3-Kinase Regulatory Subunit 1; PTEN, Phosphatase and Tensin Homologue; STAT3, Signal Transducer and Activator of Transcription 3; SOCS6, suppressor of cytokine signaling 6; TNFSF14, TNF Superfamily member 14; Treg, regulatory T cell; SOX4, SRY Box 4; WSB1, WD Repeat And SOCS Box Containing 1

miR-320a; miR-486-5p; miR-320b; miR-25-3p; miR-140-3p, mir-27a-3p ↑ in RRMS compared with PP and SPMS

MS, n = 26 verus HC, n = 20 Validation set: 58 MS, other inflammatory/neurologic diseases, n = 74 versus HC, n = 30

Serum

a miRNA Up-regulated

Patient group versus control group, n = sample size

Tissue source for miRNA profiling

Table 12.2 (continued)

12 Epigenetics in Multiple Sclerosis 333

• miR-233 and 23a ↑ in PBMCs, no changes in miR-15b • All 2 miRNAs ↓ in serum (previously reported • miR-23a rs3745453 C allele ↑ and miR-223 rs1044165 TT genotype↓ in MS • ↑expression in relapsing patients compared with remitting patients and HC • miR-326 expression discriminated relapsing and remitting phases with 100% specificity and sensitivity • In silico analysis indicate miR-26a targets molecules of TGFβ signaling was most statistically relevant • ↑ miR-26a in PBMCs overall MS and in relapse patients • Serum IL-17 in MS, but no correlation between IL-17 and miR-26a

MiR-233 ↑ miR-23a ↑ miR-15b, nd

miR-326 ↑ miR-26a ↑

miR-26a ↑

RRMS versus HC

RRMS, in relapse, n = 20 versus in remission, n = 20 versus HC, n = 20

PBMCs, serum

PBLs

PBMCs

• miR-21 and miR-146a/b ↑ in MS • No difference for miR-150 and miR-155 • No difference in miR-146 rs2910164 variants frequency

miR-121, ↑ miR-146a/b ↑ miR-150, nd miR-155, nd

RRMS versus HC

PBMCs

miR155 ↑ in white matter of MS Inflammatory cytokines can induce miR-155 expression in brain endothelial cells Overexpression → change in cell–cell junctional organization and ↑ permeability Inhibition → prevent cytokine-induced permeability miR-155 targets annexn2, claudin 1, DOCK-1 and syntenin-1 miR-155 negatively regulate BBB function

• • • • • •

miR-155 ↑

MS, n = 6 versus non-neurological disease controls, n =6

White matter, brain endothelial cells

Key findings

miRNA examined

Sample group and size (n)

Sample type

Table 12.3 Studies on specific miRNA dysregulation in MS patients

(continued)

Mahmoud et al. (2017)

Honardoost et al. (2014)

Ridolfi et al. (2013)

Fenoglio et al. (2011)

Lopez-Ramirez et al. (2014)

References

334 V. S.-F. Chan

miR-128 ↑ miR-27a, nd miR-27b ↑ miR-340 ↑

miR-141 ↑ miR-200a ↑

19 DE miRNAs targeting TGFβ pathway

MS, n = 22 versus HC, n = 16 MS, n = 19 versus HC, n = 17

RRMS, n = 15 versus HC, n = 15

RRMS, in relapse, n = 20 versus in remission, n = 20 versus HC, n = 10

MS, n = 22 versus HC, n = 16

Naïve CD4+ T cell Memory CD4+ T

CD4+ T cell

CD4+ T cells

Naïve CD4+ T

miR-15a ↓ miR-16-1 ↓

miRNA examined

Sample group and size (n)

Sample type

Table 12.3 (continued)

• ↑miR-18a; miR-27b; miR-103a; miR-128; miR-141; miR-212; miR-500a; miR628-3p; miR-708; let-7a, let-7b, let-7f • Associated with ↓TGFβR1 and SMAD4 expression, both shown as direct targets of multiple DE miRNAs • Overexpression of these miRNAs suppressed TGFR1 and SMAD4 protein expression • ↓% Treg induction but retained suppressive function

miR-141 and miR-200a ↑ in relapse % CD4+ RORγt+ T ↑ in relapse % CD4+ FOXP3+ T ↑ in remission In silico targetome analysis of these two miRNAs involve TGFβ, mTOR and FOXO pathways • Expression of FOXO3, GATA3 and SMAD2 were reduced in CD4+ T cells in relapse patients • These two miRNAs may inhibit negative regulators of Th17, and promote its differentiation in relapsing MS patients

• • • •

• ↓ in CD4+ T cells but no difference in CD8+ T cells in RRMS • Associated with ↑ BCL2 (known target of miR-15a and miR-16-1)

• Direct suppression of targets: B lymphoma Mo-MLV insertion region 1 homolog (BMI1) and IL-4 (Th2 pathway genes), then leading to downstream GATA3 ↓ • Promote a shift from Th2 to Th1 cytokine • miRNA inhibitors revert Th1 to Th2 cytokine shift (↓ IFNγ, ↑ IL-4 and IL-5) by removing the inhibition on BMI1 and GATA in MS CD4+ T cells

Key findings

(continued)

Severin et al. (2016)

Naghavian et al. (2015)

Lorenzi et al. (2012)

Guerau-de-Arellano et al. (2011)

References

12 Epigenetics in Multiple Sclerosis 335

miR-34a ↑ miR-199a ↓ miR-30c ↑ miR-19 ↑

miR-572 ↓

RRMS, in relapse, n = 20 versus in remission, n = 20 versus HC, n = 11

RRMS, in relapse, n = 20 versus in remission, n = 20 versus HC, n = 20

PPMS, n = 16, versus SPMS; n = 15, versus RRMS, n = 31 versus HC, n = 15

CD4+ T cells

CD4+ T cells

Serum

miR-9-5p ↑ miR-106a-5p↓

miR-27a ↑ miR-214 ↓

RRMS, in relapse, n = 20 versus in remission n = 20 versus HC, n = 10

CD4+ T cells

miRNA examined

Sample group and size (n)

Sample type

Table 12.3 (continued)

↑ miR-34a, miR-30c and miR-19a in relapse ↑miR-199a in remitting phase Their targets possibly involve JAK-STAT, mTOR, TGFβ signaling pathways ↑ in CD4+ RORC+ T cells in relapsing phase ↑ in CD4+ FOXP3+ T cells in remitting phase These 4 miRNAs can differentiate relapsing and remitting phase MS and HC with high specificity and sensitivity

• miR-572 ↓ in overall MS compared with HC • ↑ in SPMS and RRMs in relapse, ↓ in PPMS and RRMS in remission • Correlates with EDSS independently of clinical phenotypes

• • • • • •

• miR-9-5p ↑ and miR-106a-5p ↓ in CD4+ T cells in relapsing MS • RORC↑ in relapsing MS and FOXP3 ↑ in remitting MS CD4+ T cells

• miR-27a ↑ and miR-214 ↓ in CD4+ T cells of relapsing MS patients when compared with remitting patients and HCs • Associated with ↑ IL-17A, IL-23R, RORC, TGFβ and ↓ FOXP3 mRNA → favor Th17 differentiation • In silico mRNA targets analysis suggested miR-27a effect via TGFβ, and miR-224 via mTOR signaling pathways

Key findings

(continued)

Mancuso et al. (2015)

Ghadiri et al. (2018)

Majd et al. (2018)

Ahmadian-Elmi et al. (2016)

References

336 V. S.-F. Chan

Vistbakka et al. (2018)

Niwald et al. (2017)

Ahlbrecht et al. (2016)

References

Abbreviations BBB, blood brain barrier; CIS, clinically isolated syndrome; CSF, cerebrospinal fluid; DE, differentially expressed; DOCK1, dedicator of cytokinesis 1; EDSS, expanded disability status scale; FOXO, Forkhead box O; FOXP3, Forkhead box P3; HC, healthy control; IFN, interferon; JAK, Janus kinase; MS, multiple sclerosis; mTOR, molecular target of rapamycin; nd, no difference; PPMS, primary progressive MS; RORC, RAR-related orphan receptor C; RRMS, relapsing-remitting MS; SPMS, secondary progressive MS; STAT, Signal Transducer and Activator of Transcription; TGF, transforming growth factor; TGFR1, TGF receptor 1

• miR-191-5p and miR-24-3p ↑ in RRMS and PPMS compared with HCs, no difference between • miR-24-3p positively correlates with disability progression index • miR-128-3p, miR-376c-3p no differences found

miR-191-5p↑ miR-24-3p ↑ miR-128-3p nd miR-376c-3p, nd

PPMS, n = 20 RRMS, n = 53 versus HC, n = 27

Serum

• ↓ miR-155 and miR-301a and ↑ miR-326 in MS, with 306 and 301a levels in +ve correlation with Beck Depression Index • Elevation of miR-155 and miR-301a in post-acute phases

miR-155 ↓ miR-326 ↑ miR-301a ↓

RRMS, in relapse, n = 13 versus in remission, n = 23

Serum

• CSF and serum miR-922 were ↑in CIS → RRMS • CSF miR-181c ↑ associated with CIS conversion RRMS, a combination of high CSF miR-181c, young age and >9 MRI lesions has a predictive value of 94%, high specificity 96% for conversion

miR-181c ↑ miR-633, nd miR-922 ↑

CIS conversion to RRMS

Serum, CSF

Key findings

miRNA examined

Sample group and size (n)

Sample type

Table 12.3 (continued)

12 Epigenetics in Multiple Sclerosis 337

338

V. S.-F. Chan

2010). A different set of miRNAs, including miR-21-5p, miR-26b-5p, miR-29b-3p, miR-1432-3p and miR-155-5p, were found to be downregulated in SPMS CD4+ T cells (Sanders et al. 2016). Analyses of specific miRNAs also identified a large number of differentially expressed (DE) candidates; however, there appears to be little overlap in the miRNAs identified by different research groups (Table 12.3). The differences in DE miRNAs identified can be attributed to various confounding factors such as disease stage, drug usage, ethnicity background and miRNA detection methods. However, findings from these studies mostly converge to a common theme on the modulation of Th cell differentiation by miRNAs. The upregulation of miR-128 and miR-27b in naïve CD4+ T cells, and miR-340 in memory CD4+ T cells in MS patients were shown to promote Th1 differentiation through suppressing the expression of their direct targets B-lymphoma MoMLV insertion 1 homologue (BM1) and IL-4, both of which are upstream mediators of GATA3 (Guerau-de-Arellano et al. 2011), a key transcription factor for Th2 responses. Specific microRNA inhibitors can revert the cytokine shift to lowering IFNγ, while producing more IL-4 and IL-5 in CD4+ T cells of patients. On the other hand, dysregulated expression of miR-141, miR-200a (Naghavian et al. 2015), miR27a, miR-214 (Ahmadian-Elmi et al. 2016), miR-9-5, miR-106a-5p (Majd et al. 2018), miR-34a, miR-199a, miR-30c and miR-19 (Ghadiri et al. 2018) were all shown to favor Th17 and Treg differentiation, respectively, in relapsing phases and remitting phases of MS. Many of these miRNAs were shown or implicated to modulate molecular targets in TGFβ (Naghavian et al. 2015; Ahmadian-Elmi et al. 2016), FOXO (Naghavian et al. 2015; Ghadiri et al. 2018), mTOR (Ahmadian-Elmi et al. 2016; Ghadiri et al. 2018) and JAK-STAT (Ghadiri et al. 2018) pathways, such that an increase in the expression of RORC (also referred to as RORγt), the master transcription factor defining Th17 differentiation (Ivanov et al. 2006), was found in CD4+ T cells in relapsing patients. In parallel, higher CD4+ FoxP3+ Treg frequency was observed in association with the dysregulated miRNAs in patients in remission (Naghavian et al. 2015; Ghadiri et al. 2018; Majd et al. 2018). In fact, TGFβ signaling is involved in both Th17 and Treg differentiation and plays a key role in modulating Th17/Treg balance (Hatton 2011). A study by Severin et al. found that 12 miRNAs targeting the TGFβ pathway were upregulated in naïve CD4+ T cells in MS patients (Severin et al. 2016). Phenotypically, this was associated with the reduced expressions of TGF receptor 1 (TGFR1) and its downstream signaling molecule SMAD4, and a lower ability of these naïve CD4+ T cells for Treg induction. The imbalanced Th1/Th17/Treg frequencies and functions are one of the central themes for the pathogenesis and development of MS and EAE. The mechanistic relationship between specific miRNA dysregulation and Th17/Treg in MS is wellillustrated by in vitro cell culture and in vivo animal models. An earlier study investigated the relationship between the upregulated miR-326 in PBLs of patients and the development of MS using EAE mice (Du et al. 2009). miR-326 expression in CD4+ T cells was higher in disease progressive phases than in resting stages in MS patients. In vivo delivery of miR-326 mimics and inhibitory sponges were able to worsen and ameliorate disease, respectively, with a corresponding increase and decrease in Th17 frequency in EAE mice. miR-326 influences Th17 differentiation by directly

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targeting the transcription factor Ets-1, a negative regulator of Th17 differentiation (Moisan et al. 2007). miRNA knockout mouse models also provide much insight. miR-132/212deficient mice were resistant to MOG-induced EAE with reduced incidence and clinical scores that were accompanied by reductions in IFNγ+ and IL-17+ T cells (Nakahama et al. 2013). Instead of the Stat3 and Stat5 pathways, miR-212 was shown to target another Th17 negative regulator Bcl-6. Similarly, delayed EAE onset and reduced disease severity were also observed in miR-181c and miR-223 knockout mice in association with lower Th17 and Th1 frequencies (Satoorian et al. 2016; Zhang et al. 2018). The diminished abilities of dendritic cells (DCs) from miR223−/− mice to produce activation-induced IL-12 and IL-23 may, in part, account for the decrease in Th1 and Th17 cells (Satoorian et al. 2016). In vivo silencing of let-7e also ameliorated EAE with Th1 and Th17 inhibition through unleashing its target IL-10 (Guan et al. 2013). Mice harboring T cell-specific deficiency in miR-17-92 cluster had revealed the action of its components, miR17 and miR-19b, in promoting EAE development via Th17 modulation (Liu et al. 2014). Mechanistically, miR-17 was shown to target a novel Th17 modulator, Ikaros Family Zinc Finger 4 (IKZF4), whereas miR-19b target and suppress PTEN, which in turn promote the PI3K-AKT-mTOR pathway for Th17 differentiation. Collectively, Th17 differentiation in EAE can be promoted through downregulating a number of miRNAs, including miR-20b that targets RORγt and STAT3 (Zhu et al. 2014); miR-15b that targets O-linked N-acetylglucosamine transferase for glycosylation of NF-κB linking to RORγt transcription (Liu et al. 2017b); miR-26a that targets IL-6 (Zhang et al. 2015b); and miR-30a that targets IL-21R (Qu et al. 2016). On the other hand, the upregulation of miR-488, miR-590 and miR-155 that respectively target the known Th17 suppressor proteins tyrosine phosphatase non-receptor type 2 (PTPN2) (Wu et al. 2017), Tob1 (Liu et al. 2017a) and Ets-1(Hu et al. 2013), and miR-155-3p that targets two heat shock protein 40 genes Dnaja2 and Dnajb1 (Mycko et al. 2015) can also promote EAE. Furthermore, pathogenicity of Th17 cell can be modulated by miRNAs in EAE mice. miR-183c upregulation in Th17 cells was shown to enhance its encephalitogenic pathogenicity by promoting the production of IL-17A/F, IL-22, GM-CSF via suppression of FOXO1 (Ichiyama et al. 2016), while IL-17 was shown to downregulate miR-23b which alleviates its suppression of IL-17, TNFα and IL1β-induced NF-κB activation via targeting TAB2, TAB3 and IKKα (Zhu et al. 2012). Comparatively, there are fewer mechanism studies on miRNA regulation of Th1 and Treg in MS and EAE. For Th1, apart from miR-223 (Satoorian et al. 2016) and let7e (Guan et al. 2013) mentioned above, a forced expression of miR-142-5p in CD4+ T cells was shown to promote Th1 differentiation in vitro, possibly through a direct inhibition on suppressor of cytokine signaling 1 (SOCS1) and the TGFβ receptor 1 (TGFBR1) (Talebi et al. 2017). A recent study has also implicated miR-92a in driving Th1 differentiation and responses in EAE (Rezaei et al. 2018). For Treg, an intriguing study showed that let-7i in circulating exosomes of MS patients can inhibit Treg differentiation without affecting Th17 and Th1 (Kimura et al. 2018). The inhibitory effect was shown to be mediated by targeting TGFBR1 and insulin-like growth factor 1 receptor (IGF1R) in naïve CD4+ T cells. On the other

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hand, miR-182 negatively regulates the differentiation of CD4+ FoxP3+ Treg cells and potentiates EAE development in a Foxo1-dependent manner (Wan et al. 2016). miR31 was also shown to be a negative regulator of antigen-induced Treg differentiation in the periphery by targeting the retinoic acid-inducible protein 3 (Gprc5a) (Zhang et al. 2015a). It is noteworthy that miR-17 can potentiate EAE-induced disease through modulation of Treg function without affecting its differentiation (Yang et al. 2016a). Treg suppressive activity was dampened by the expression of miR-17 which can be induced upon IL-6 stimulation. The mechanism was shown to be via targeting Eos, a FOXP3 coregulator that may affect de-repression of genes encoding effector cytokines (Pan et al. 2009). An earlier study, however, showed that Treg-specific deletion of the miR-17-92 cluster had caused exacerbated EAE by reducing Treg accumulation and the ability to produce IL-10 (de Kouchkovsky et al. 2013). Although CD8+ T cells have been shown to have pathogenic role in MS and EAE (Huseby et al. 2012), there are much fewer miRNA studies in this context. To date, only two independent studies reporting the upregulation of miR-16, miR-155, miR-142-3p, miR-629, and downregulation of miR-149, miR-30a-3p and miR-497 in CD8+ T cells of MS patients (Lindberg et al. 2010; Arruda et al. 2015). The role of these miRNAs in CD8+ T cells is yet to be determined.

12.3.2.2

Dysregulation of miRNAs in B Cells

Profiling lymphocyte subsets for DE miRNAs in MS revealed an upregulation of miR-497 and downregulation of miR-92, miR-135b, miR-153, miR-189 and miR422a in purified B cells from patients when compared with HCs (Lindberg et al. 2010) (Table 12.2). A panel of 49 and only downregulated miRNAs were identified in B cells when comparing treatment-naïve MS patients with HCs in an independent study (Sievers et al. 2012). Moreover, upregulation of miR-19b, miR-106b, and 8 other miRNAs were also observed in comparing treatment-naïve with natalizumabtreated patients, suggesting biologics may achieve clinical outcomes in association with miRNAs modulation (Sievers et al. 2012). In silico mRNA target predication and analysis of the two most deregulated miRNA clusters, miR-106b-25 and miR17-92, had identified potential regulatory gene targets of the B cell receptor, PI3K and PTEN pathways, though experimental evidence was not provided in this study. Unlike T cells, functional alterations by miRNAs in MS B cells have only been shown in a few reports. The reduced expression of the key miRNA processing enzyme Dicer in B cells from MS patients was functionally linked with increased expression of costimulatory molecule CD80, which might enhance its function as antigen presenting cells (Aung and Balashov 2015). The overexpression of miR-320a in B cells of MS patients may lead to an increase in the matrix metalloproteinase 9 (MMP9) which may contribute to an increase in blood–brain barrier permeability (Aung et al. 2015). Activated B cells from MS patients also showed an enhanced production of proinflammatory lymphotoxin and TNFα through sirtuin-1 suppression by upregulated miR-132 (Miyazaki et al. 2014). Memory B cells are known to harbor Epstein Barr virus (EBV) in latent stage. Interestingly, three EBV-associated miRNAs were

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found deregulated in B cells of treatment-naïve MS patients when compared with HC, and two other miRNAs, including miR-BART3-5p and miR-BART11-5p, were upregulated when compared with natalizumab-treated patients (Sievers et al. 2012). As EBV miRNAs are known to target host’s genes to modulate immune responses (Wang et al. 2018), it is possible that EBV latency and reactivation in B cells may play a role in MS.

12.3.2.3

Dysregulation of miRNAs in Brain Tissues

Several miRNA profiling studies on MS brain tissue and cerebrospinal fluid (CSF) have uncovered different panels of dysregulated miRNAs in different studies (Table 12.2). Most of the DE miRNAs identified have been implicated to regulate processes related to cell survival and death, neuronal degeneration and repair, inflammation and cellular stress, as well as cell–cell interactions. An earlier report showed that CD47 expression in MS brain tissues was reduced and targeted by the upregulated miR-155, miR-34a and miR-326 (Junker et al. 2009). CD47 is an inhibitory protein that suppresses macrophage activation (Barclay and Van den Berg 2014). Its downregulation in MS brain likely would provide a microenvironment to support inflammation mediated by the resident and infiltrating macrophages. In another study, miR-155, together with miR-338 and miR-491 were found upregulated in relation to the functional targeting of 3α-hydroxysteroid dehydrogenase AKR1C1 and AKR1C2, thereby leading to a suppression of neurosteroid biosynthesis (Noorbakhsh et al. 2011). The impairment in neurosteroidogenesis may contribute to the neuronal deficits in MS patients (Reddy 2010). miR-155 overexpression was also found in neurovascular subunits in MS brain. By targeting the cell–cell complex molecules annexin-2 and claudin-1, and the focal adhesion components DOCK-1 and syntenin-1, this caused a disruption in endothelial cell junctional organization, thereby increasing the permeability of the blood–brain barrier (Lopez-Ramirez et al. 2014). Additionally, this may also promote adhesion and penetrance of peripheral leukocytes by modulating the expression of adhesion molecules VCAM-1 and ICAM-1 (Cerutti et al. 2016). Another study also reported that the 15 DE miRNAs found in normal appearing white matter (NAWM) in MS brain may potentially regulate targets of pathways associated with MAPK signaling, focal adhesion, regulation of actin cytoskeleton, adherens junction as well as extracellular matrix receptor interaction (Guerau-deArellano et al. 2015). Many of these events also affect blood–brain barrier integrity. Along the same direction, miRNA dysregulation in cerebral endothelial cells was also studied using a human cell line mimicked with inflammation by TNFα and IFNγ stimulation (Reijerkerk et al. 2013). Among the 105 DE miRNAs identified, miR-125a-5p downregulation was further verified in MS patient samples and functionally validated that a lower expression would confer reduced VE-cadherin expression with reduced barrier enhancing effect. Conversely, the overexpression of miR-125a-5p reduced TNFα-mediated ICAM-1 expression and monocyte transmigration (Reijerkerk et al.

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2013), indicating that this miRNA plays a positive role in maintaining the integrity of the blood-brain barrier. Apart from modulating the blood–brain barrier function, dysregulated miRNAs also affect neuronal functions. Elevated miR-124 in demyelinated tissues was shown to target ionotrophic glutamate receptors AMPA2 and AMPA3. Functionally, these phenotypic changes were recapitulated in EAE mice in association with a reduced memory performance (Dutta et al. 2013). An intriguing study by Juzwik et al. has recently demonstrated the progressive changes of miRNAs in lumber motor neurons during the disease course of EAE mice (Juzwik et al. 2018). They identified 43 DE miRNAs in a profile screening assay and validated 14 candidates. Putative in silico mRNA target prediction for the 14 miRNAs has found genes related to cell survival and growth via the PI3K/Akt/mTOR pathway, hypoxia-inducible factor (HIF) pathway, as well as genes related to cytoskeletal rearrangement and stress responses.

12.3.2.4

miR-155 in MS

miR-155 is a crucial immunoregulator induced upon activation in many leukocytes (O’Connell et al. 2007; Yin et al. 2008) and its deficiency results in compromised responses in B cells, T cells, DCs, as well as skewing in Th subset development and functions (Rodriguez et al. 2007; Lu et al. 2009). In MS patients, dysregulated miR155 expression can be observed in both the brain tissues and peripheral leukocytes (Junker et al. 2009; Noorbakhsh et al. 2011; Moore et al. 2013; Mameli et al. 2016; Sanders et al. 2016; Niwald et al. 2017). Profoundly, miR-155 deficient mice exhibit delayed disease onset and severity upon EAE induction (Murugaiyan et al. 2011; Zhang et al. 2014). miR-155 likely has multiple roles in MS pathogenesis. In active brain lesions of MS patients and EAE mice, overexpression of miR-155 was found in the neurovascular unit (Lopez-Ramirez et al. 2014), suggesting that miR-155 regulation may extend beyond hematopoietic cells and affect blood–brain endothelial barrier functions. Indeed, miR-155-deficient EAE mice exhibit reduced extravasation of a systemic tracer to CNS (Lopez-Ramirez et al. 2014). Whether the overexpression of miR-155 in MS patients is linked to the haplotype of three disease-associated SNPs in the miR-155 coding region is yet to be determined (Paraboschi et al. 2011). However, its expression in human brain endothelial cells can be upregulated by inflammatory conditions and cytokines such as TNFα and IFNγ in vitro (LopezRamirez et al. 2014; Cerutti et al. 2016). Mechanistically, miR-155 overexpression can induce junctional organization and permeability aberrations in these cells by targeting the cell–cell complex molecules annexin-2 and claudin-1, as well as the focal adhesion components DOCK-1 and syntenin-1(Lopez-Ramirez et al. 2014). miR-155 in brain endothelial cells also promote adhesion of monocytes and T cells, at least in part, by modulating the expression of adhesion molecules VCAM-1 and ICAM-1 (Cerutti et al. 2016). In the immune compartment, overexpression of miR-155 was also observed in myeloid cells and lymphocytes. Circulating CD14+ monocytes and perivascular CD68+ macrophages in active brain lesions from RRMS patients were shown to have elevated miR-155 level

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(Moore et al. 2013). Furthermore, in vitro M1-polarlized macrophages and microglia expressed higher miR-155 when compared with M2- or non-polarized cells, suggesting that miR-155 may be involved in myeloid cell polarization. Transfection of miR-155 mimics in macrophages and microglia promoted inflammatory phenotypes with an increase in TNFα production, CD80 and CD86 costimulatory molecules expression, and enhanced T cell stimulation capacity (Moore et al. 2013). Similarly, CD4+ T cells were shown to have higher miR-155 level in association with proinflammatory properties in murine EAE models and in RRMS patients (Murugaiyan et al. 2011; Zhang et al. 2014; Jevtic et al. 2015). Evidence also shows that miR-155 promotes the development of Th1 and Th17 responses in MS. miR-155-3p was shown to promote Th17 differentiation in EAE mice by targeting two heat shock protein 40 genes, Dnaja2 and Dnajb1 in T cells (Mycko et al. 2015). In the absence of miR-155, EAE alleviation was accompanied by a reduction in Th1 and Th17 responses (Murugaiyan et al. 2011; Zhang et al. 2014). This could be due to the suppressed expression of the Th1/Th17-inducing cytokines including IL-12, IL-6, IL-23 and IL-1β by DCs (Murugaiyan et al. 2011), and/or the diminished ability of CD4+ T cells to produce IFNγ and IL-17 (Jevtic et al. 2015). Furthermore, the specific deletion of miR-155 in autoreactive Th17 cells had rendered them defective in causing EAE as a result of a lowered expression of IL-23Rmediated by Ets-1 activity (Hu et al. 2013). In addition, miR-155 was also shown to target heme oxygenase 1 (HO-1) in encephalitogenic CD4+ T cells to promote infiltration into CNS in a chronic EAE model (Zhang and Braun 2015). Overall, miR-155 mostly functions as a disease-promoting molecule in MS and modulates MS development both at the CNS and immune system levels. It may serve as an attractive target for novel therapeutic development.

12.3.2.5

miR-146a in MS

As miR-146a deficient mice spontaneously develop systemic auto-inflammatory responses, this miRNA is classically considered as a negative regulator of immune function to prevent excessive inflammation and to maintain tolerance (Boldin et al. 2011). However in different EAE models, conflicting findings were reported. In the EAE model with MOG-specific T cell receptor (TCR) transgenic CD4+ T cells, miR146a deficiency in autoreactive T cells rendered a more severe disease course in association with elevated IFNγ and IL-17A levels through enhancing the expression of Th17-differentation factors, including IL-6, IL-21, STAT3 and RORγt (Li et al. 2017). Hence, miR-146a in effector T cells can suppress EAE through modulating Th17 differentiation. Also, miR-146a expression induced in microvessels of MS active lesions and autoantigen-induced EAE mice may negatively regulate T cell adhesion through the inhibition of NF-κB-mediated VCAM-1 and CCL2 expression (Wu et al. 2015). In contrast, miR-146a deficiency in the cuprizone-induced EAE model showed alleviation of demyelination with a reduced infiltration of macrophages, and an increase in oligodendrocyte precursor cells during remyelination (Martin et al. 2018). The mechanism by which miR-146a mediated its pathogenic effect in these mice was

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not clearly shown, though inflammatory molecules such as TNF receptors TNFRI, TNFRII and chemokine CCL2 were reduced in brain lesions in the absence of miR146a. As the cuprizone-induced EAE disease is independent of T cells (Hiremath et al. 2008), it is possible that miR-146a contributes to different functional regulation in immune and non-immune cells in different EAE models. In MS patients, an upregulated miR-146a expression was found in brain lesions (Junker et al. 2009), monocytes (Moore et al. 2013) and PBMCs (Fenoglio et al. 2011), whereas a lower level was reported in CSF (Quintana et al. 2017) and serum exosomes (Manna et al. 2018). Genetically, the miR-146a SNP rs2910164G > C was also demonstrated to be a functional variant with an increased risk of MS in Han Chinese (Li et al. 2015; Park et al. 2016). RRMS patients carrying the rs2910164 C risk allele were shown to have higher miR-146a expression in PBMCs, as well as higher serum levels of TNFα and IFNγ than HCs and non-risk allele-carrying patients (Li et al. 2015). In view of the limited mechanistic studies in human cells, the exact role of miR-146a in MS patients is still unclear and requires further investigation.

12.3.2.6

miR-17-92 Cluster in MS

miR-17-92 cluster is a miRNA gene that encodes 6 miRNAs, including miR-17, miR-18a, miR-19a, miR-19b, miR-20a and miR-92a in a single primary transcript. This cluster of miRNAs is a proven crucial player in regulating the development and function of the immune system (Kuo et al. 2018), and mice overexpressing this cluster die of uncontrolled lymphoproliferative disease (Xiao et al. 2008). The expression of this miRNA cluster in MS patients can be modulated by different treatment regimens (Sievers et al. 2012; Ehtesham et al. 2017; Dolati et al. 2018), suggesting that they may play regulatory roles in disease pathogenesis. In B cells from MS patients, miR17-92 was one of the two clusters that shown to be particularly deregulated; and potential gene targets from the BCR, PI3K and PTEN pathways were implicated (Sievers et al. 2012). However, direct functional evidence is yet to be found. In T cells, its functional role is better defined. In EAE mice, T cell-specific deletion of this cluster led to amelioration of disease via inhibition of Th17 differentiation (Liu et al. 2014). The suppression was found to be mediated specifically by miR17 and miR-19b, which target IKZF4 and PTEN, respectively. IKZF4 is a novel Th17 modulator and its deficiency in mice promotes the development of EAE by amplifying IL-17 as well as IL-2 production (Rieder et al. 2015). PTEN is a negative regulator of the PI3K-Akt-mTOR pathway which controls Th17 differentiation by regulating nuclear localization of RORγ (Kurebayashi et al. 2012). Thus, these two miRNAs favor the development of MS by targeting the negative regulators for Th17 differentiation and function. Counter-intuitively, in MS patients, miR-17 and miR-20a were found to be significantly reduced in peripheral blood, mainly in T cells (Cox et al. 2010; Ehtesham et al. 2017). In vitro knock-in and knock-down studies in a Jurkat T cell line revealed modulation of expression of genes related to T cell activation by miR-17 and miR-20a (Cox et al. 2010). It was subsequently shown that miR-20a can be induced rapidly in primary human naïve CD4+ T cells

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by TCR stimulation with dependence on ERK, NF-κB and Ca2+ signaling (Reddycherla et al. 2015). Overexpression of miR-20a inhibited TCR-mediated signaling with diminished secretion of IL-2, IL-6, IL-8 and most prominently IL-10. However, whether these miR-20-mediated inhibitions in CD4+ T cells are dysregulated in MS patients remains elusive and awaits further exploration. The downregulated miR-20a expression in treatment-naïve RRMS patients was shown to be normalized by IFNβ treatment in patients when compared with HCs (Ehtesham et al. 2017). In silico mRNA target prediction and pathway analysis indicated enrichment in genes of the MAPK signaling pathway, and may provide indirect evidence to support its functional role in MS. For miR-17, elevated expression in CD4+ T cells was observed in untreated RRMS patients and it was downregulated in patients receiving natalizumab treatment (Meira et al. 2014b). An inverse expression relationship was observed between miR-17 and its potential targets PTEN, BIM, E2F1 and p21 in T cells of MS patients, and in miR-17-inhibitor-transfected CD4+ T cells. The negative regulator PTEN and the proapoptotic molecule BIM were indeed shown downregulated in transgenic mice overexpressing miR-17-92 (Xiao et al. 2008). Possibly, dysregulated miR-17 expression in MS CD4+ T cells may also promote T cell activation and proliferation via similar mechanisms. For miR-92a, its expression was found substantially upregulated in MS patients, showing a positive association with EDSS and disease duration (Gandhi et al. 2013). In line with this, miR-92a overexpression in spinal cords of EAE mice was also observed at the peak of disease (Rezaei et al. 2018). In these mice, miR92a overexpression was also found in splenocytes. In vitro transfection of miR-92a mimics to splenocytes led to a skewing of Th1 differentiation and was accompanied by the reduced expression of tuberous sclerosis 1 (TSC1) and dual specificity phosphatase 10 (DUSP10). TSC-1 is a protein that integrates growth signals and drives cell growth along the PI3K/Akt/mTOR pathway and has been shown to regulate the balance between effector and regulatory T cells (Park et al. 2013), whereas DUSP10 is a negative regulator of MAP kinase. Compared with other miRNAs in the cluster, the role of miR-19a is less clear. In RRMS patients, an upregulation of miR-19a, together with miR-30a and miR-34a, was observed in CD4+ T cells with a concurrent increase in CD4+ RORγt+ Th17 frequency during relapse (Ghadiri et al. 2018). However, the exact role of miR-19a in Th17 differentiation has not been described.

12.3.3 Histone Modification and MS Histone modification represents a layer of epigenetics regulation at the post translational level by modulating chromatin structure and recruiting histone modifiers, thereby affecting gene transcription activity. Chromatin comprises packaged nucleosomes which are basic units of 147 base-pair of double-stranded genetic DNA wrapped around an octamer of two copies of the four core histone proteins H2A, H2B, H3 and H4. The linker histone protein H1 mediates inter-nucleosome connection for a higher order of chromatin organization. Histones contain a flexible

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N-terminus (histone tail) which can undergo various types of modification, affecting the accessibility of regulatory proteins for chromatin condensation/decondensation, gene transcription, DNA repair and replication. Histone modification represents the most diverse form of epigenetic regulations, consisting of at least nine distinct types of modifications, including acetylation, methylation, phosphorylation, deimination/citrullination, ubiquitylation, sumoylation, ADP ribosylation, proline isomerization and tail clipping (Bannister and Kouzarides 2011). In this section, we mainly focus on histone acetylation and methylation modifications, the two most prevalent forms of modification reported in MS. A few reports on histone citrullination in MS are also discussed.

12.3.3.1

Histone Acetylation, Methylation and Citrullination

The acetylation of lysine in histone, in particular H3 and H4, is highly dynamic and regulated by the opposing actions of two families of enzymes, namely histone acetyltransferases (HATs) and histone deacetylases (HDACs). By transferring an acetyl group to the lysine (K) residues at the histone tail, acetylation removes the positive charge and reduces the affinity between histones and DNA, thereby increasing the accessibility of transcription factors and RNA polymerase to initiate transcription. Conversely, deacetylation of histone usually results in transcription repression (Shahbazian and Grunstein 2007). There are three main families of HATs, namely general control non-derepressible 5 (Gcn5)-related N-acetyltransferases (GNATs), CREBbinding protein (CBP)/p300 and MYST proteins. For HDACs, there are four classes: class I, II and IV are classical metal-dependent enzymes while the non-classical class III sirtuin families uniquely require nicotinamide adenine dinucleotides for action. The interplay between these diverse HATs and HDACs therefore allows a dynamic and reversible change of activity states both at specific gene loci and at the global level, affecting the overall cellular functional outcomes (Peserico and Simone 2011). In contrast, histone methylation can either enhance or repress transcription depending on the nature of methylated amino acids and the number of methyl group attached. Histone methylation occurs mostly at basic residues lysine (K) and arginine (R) on H3 and H4 by transferring methyl groups donated from S-adenosyl methionine. The most extensively studied histone methylation sites on H3 are lysine at position 4 (K4), K9, K27, K36 and K79; and K20 on H4. Common sites of arginine methylation on H3 are R2, R8, R17 and R26; and R4 on H4 (Greer and Shi 2012). Histone methylation is also regulated by two major types of action-opposing enzymes with high substrate specificity. The histone methyltransferases (HMTs) are further subdivided into three families: the SET domain containing proteins and the Dot-like proteins methylate lysine; whereas PRMT family methylates arginine. There are also three groups of histone demethylases (HDMs): the amine oxidase and Jumonji C (JmjC) domain containing dioxygenases demethylate lysine and a subset of Jmjc lysine demethylases also demethylates arginine (Greer and Shi 2012; Walport et al. 2016).

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Since histone methyltransferases and demethylases exhibit high substrate specificity, functionally, histone methylation can mediate both positive and repressive regulation on gene transcription activity by recruiting specific effector or repressor proteins locally. As such, the location and the degree of methylation would affect the outcome of gene activity. For instance, the tri-methylation of lysine residue at position 4 of H3 (H3K4me3) results in transcription activation, whereas di-methylation of lysine at position 9 of H3 (H3K9me2) is associated with transcriptional silencing (Greer and Shi 2012). The common sites frequently associated with gene activation include H3K4me2/3, H3K36me3 and H3K49me3. On the other hand, H3K9me2/3, H3K27me3 and H4K20me3 are the hallmarks of repression and gene silencing (Kooistra and Helin 2012). Citrullination, also referred to as deimination, is the replacement of the primary amine group (= NH2 ) by a ketone group (= O) in the positively charged arginine, thereby turning it into a citrulline with no net charge. The enzymes arginine deiminases catalyze deimination of free arginine whereas peptidylarginine deiminases (PADs or PADIs) catalyze the citrullination of arginine in proteins. In humans, there are five isotypes of PAD including PAD1, −2, − 3, −4 and −6, among which both PAD2 and PAD4 are known to citrullinate nuclear histone proteins H1, H2A, H3 and H4 (Gyorgy et al. 2006; Christophorou et al. 2014). PAD2 is expressed in a wide spectrum of tissues, including brain, spleen, uterus and skeletal muscle, while PAD4 is detected mainly in immune cells under normal physiological conditions (Wang and Wang 2013). Although the physiological functions of histone citrullination are yet to be fully-defined, it has been shown to regulate gene transcription through various mechanisms including chromatin decondensation and interference of histone arginine methylation (Cuthbert et al. 2004; Wang et al. 2004; Christophorou et al. 2014).

12.3.3.2

Histone Modifications in MS Brain Tissues

The pathogenesis of MS is characterized by the involvement of T cell-mediated inflammatory demyelination, as well as neurodegenerative processes that lead to oligodendrocyte loss, axonal degeneration and reactive gliosis. In brain tissues, various reports have signified the importance of histone modifications, particularly in neurodegenerative events. The RRMS disease course involves demyelination as well as remyelination, which are both epigenetically modulated by HDACs. Naturally, the reduction in remyelination efficiency observed in older mice has been shown to be associated with a reduction of HDAC recruitment, resulting in transcriptional silencing of genes for oligodendrocyte differentiation and myelin synthesis (Shen et al. 2008). As such, high histone acetylation in oligodendrocyte lineage is associated with impaired remyelination. Indeed in progressive MS patients, an elevated level of acetylated histone H3 in oligodendrocytes was observed in association with high levels of TCF7L2 (transcription factor 7 like 2), ID2 (inhibitor of DNA binding 2) and SOX2 (SRY-Box 2), which are transcriptional repressors of oligodendrocytes differentiation (Pedre et al.

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2011). Increased transcript level of the histone acetyltransferase CBP/p300 was also observed in correlation with disease duration. In contrast, oligodendrocytes with marked histone deacetylation were observed in early MS lesions and decreased with disease duration, indicating a shift toward histone acetylation in oligodendrocytes in chronic MS patients. In fact, the dynamic changes of HATs and HDACs during MS progression affect different cellular events in neurodegeneration. This is supported by the observation that treatment with the HDACs inhibitor trichostatin A can improve CNS pathology in EAE mice through upregulation of neuroprotective factors and growth factors, including Igf2 (insulin-like growth factor 2), EAAT2 (glutamate transporter mGLT) and the neuronal integrity gene synaptojanin 2, with a concurrent downregulation of pro-apoptotic E2F1 transcription factor and its targets in the spinal cord (Camelo et al. 2005). The expression of the histone deacetylase SIRT1 was observed in oligodendrocytes, astrocytes, glial cells as well as CD4+ cells in MS plaques (Tegla et al. 2014). In oligodendrocytes, the elevated expression of SIRT1 may protect them from apoptosis in the inflammatory environment since the overexpression of human SIRT1 in CNS of transgenic mice can attenuate EAE disease severity with reduced cell death and demyelination (Nimmagadda et al. 2013). These changes were associated with an increase in brain-derived neurotrophic factor (BDNF) that promotes neuronal survival. Of note, three HDAC-associated SNPs, namely rs2522129 (on SIRT4), rs2675231 (on HDAC11) and rs2389963 (on HDAC9), were found to have the highest predictive values for brain volume changes in MS patients, suggesting that there is a close link between histone modifications and neurodegenerative processes (Inkster et al. 2013). Dysregulation of methionine metabolism that affects histone methylation is also evident in MS patients. The concentration of methionine and its metabolites such as S-adenosylmethionine, betaine and cystathionine were found to be decreased in MS gray matter (Singhal et al. 2015, 2018). In particular, the decrease in betaine, a methyl group donor, correlated with a decrease in histone H3K4me3 in neuron nuclei. Furthermore, the systemic and local concentration of methionine has been shown to have a direct impact on H3K4me3 level in cortical neurons (Singhal et al. 2018). The reduced level of H3K4me3 was functionally linked to the decreased expression of oxidative phosphorylation genes and mitochondrial defects in MS cortexes, indicating its possible involvement in neurodegeneration (Singhal et al. 2015). Histone citrullination also appears to affect MS neurodegeneration process. Compared with control samples from patients with non-neurological diseases, the normal-appearing white matter samples of MS patients had elevated levels of nuclear peptidylarginine deiminase 4 (PAD4) and citrullinated H3 in oligodendrocytes, which may be linked to the elevated TNFα expression in astrocytes (Mastronardi et al. 2006). Similar findings were also observed in transgenic mice expressing CNS-specific TNFα, which in turn induced the expression of PAD4. Interestingly, overexpression of PAD4 alone was not sufficient to drive its nuclear translocation, which required further stimulation from TNFα. However, whether this is of relevance to TNFα-induced apoptosis and demyelination in brain tissue

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is yet to be investigated (Akassoglou et al. 1998). Mechanistically, PAD4-mediated citrullination of H3 arginine 8 of the H3K9me3 was shown to weaken the binding of heterochromatin protein HP1α, a transcriptional repressor of inflammatory cytokines such as TNFα and IL-8. This mechanism has been demonstrated in MS PBMCs, where an upregulation of PAD4 and citrullinated H3R8 was found to be associated with a reduced HPIα recruitment to the promoter region of TNFα, thereby resulting in an augmented TNFα transcription (Sharma et al. 2012). Apart from PAD4, MS brain tissues were also shown to have elevated levels of PAD2 (Wood et al. 2008). Interestingly, mice overexpressing PAD2 in oligodendrocytes exhibited spontaneous demyelination without T cell recruitment. Rather, the pathology was associated with astrocytosis and an increase in TNFα production (Musse et al. 2008). These mice also had elevated PAD4 expression as well as H3 citrullination, suggesting that these two PAD isotypes may act synergistically to promote demyelination in MS via TNFα-mediated mechanisms.

12.3.3.3

Histone Modifications in Immune Cells in MS

As mentioned in earlier sections, a disrupted balance among Th1, Th17 and Treg is central to the deregulated immune responses in MS patients. HDACs have been shown to regulate immune responses of different T cell subsets. For instance, trichostatin A, a class I and II pan-HDAC inhibitor, was shown to shift Th1/Th2 ratio of human antigen-experienced T cells in vitro by upregulating the expression of the Th2-promoting transcription factor GATA-3 and the Th1 negative regulator, sphingosine kinase 1 (Su et al. 2008). This suggests that endogenous HDACs are crucial in maintaining the balance of Th1 and Th2 responses. Also, flingolimod or FTY720, an FDA-approved drug for treating RRMS patients, was shown to bind and inhibit class I HDACs and affect CNS memory functions in vivo (Hait et al. 2014). It was shown to inhibit T cell activation through modulating the activity of transcription factors NFAT-1, AP-1 and NF-κB, which were associated with the enhanced acetylation at H3K9 (Baer et al. 2018). In fact, numerous in vitro and in vivo studies have shown that the HDAC inhibitors (HDACi) have the capacity to promote resolution of inflammation via different routes, including modulation of T effector cell activation and differentiation, enhancement of Treg suppressive functions by increasing FOXP3 stability, as well as suppression of antigen presenting cell function by reducing costimulatory molecules and inflammatory cytokines expression (Akimova et al. 2012). Similar observations were also reported in MS patients and EAE mice. In vivo administration of trichostatin A was shown to ameliorate disease severity in relapsing phases of EAE (Camelo et al. 2005). This was associated with inhibition of a panel of inflammatory target genes such as macrophage inflammation protein 2 (Mip2, involved in chemotaxis), Il12p35 and Il8r (involved in Th1 differentiation and response), as well as Il2rα and Cd28 (involved in T cell proliferation and survival). The use of the GSK-J4, a selective HDACi for JMJD3, also reduced EAE

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severity in mice (Donas et al. 2016). The protective effect was achieved by rendering DCs to a tolerogenic state with reduced costimulatory molecules expression and impaired production of proinflammatory cytokines, such as IL-6, IFNγ and TNF. The increased expression of TGFβ and reduced level of IL-6 promoted Treg generation with enhanced suppressive capacity, thereby mediating certain protective effect in these mice. Intriguingly, a recent study has shown a complete protection from EAE induction in mice with T cell-specific deletion of Hdac1 (Goschl et al. 2018). Despite the induction of STAT1 activity in CD4+ T cells with enhanced Ifnγ and Tbx21 expression in these mice, the protection could be associated with a reduction in Ccr6 and Ccr4 gene expression, thereby suppressing T cell migration to CNS to initiate demyelination. In MS patients, an upregulated HDAC3 expression was observed in PBMCs which, however, were insensitive to trichostatin A treatment and were resistant to p53-associated apoptosis, suggesting that dysregulated HDAC activities may promote abnormal survival of PBMCs in MS (Zhang et al. 2011). SIRT, a non-classical NAD+ -dependent HDAC, is known to regulate a wide spectrum of physiological processes in autoimmune demyelination and neurodegeneration (Martin et al. 2015). In MS lesions, SIRT1 expression was found in infiltrating immune cells in addition to oligodendrocytes and glial cells. Downregulation of SIRT1 in PBMCs of MS patients during relapse was also observed in association with H3K9 acetylation and methylation, and its inhibition can mediate an increase in FasL expression for apoptosis (Tegla et al. 2014). SIRT1 and H3K9me levels are also increased significantly in patients responding to glatiramer acetate treatment (Hewes et al. 2017), suggesting that the latter may function as a negative regulator in modulating MS pathogenesis. In EAE models, SIRT1 appears to have dual roles in disease development. A total knockout of SIRT1 in mice was associated with a more severe EAE via unleashing of anergic T cells (Zhang et al. 2009). It has been shown that SIRT1 was required to keep T cells in an anergic state by inactivating AP-1 transcription activity through its interaction with and deacetylation of c-Jun. On the other hand, specific deletion of SIRT1 in RORγt expressing T cells or inhibition by a chemical inhibitor can ameliorate EAE severity in mice; and SIRT1 has been shown to have a proinflammatory role in promoting Th17 differentiation via RORγt deacetylation (Lim et al. 2015). In both studies, SIRT1-mediated histone modification was not described but could not be excluded. Possibly, SIRT1 also regulates other targets via histone (nor nonhistone) modification in non-Th17 cells to mediate protection in EAE. Furthermore, Th17 differentiation and function are modulated by other histone modifiers. The use of the HDACi vorinostat can ameliorate disease in EAE mice by suppressing Th1 and Th17 functions via inhibition of DCs to express lower levels of costimulatory molecules, as well as Th1 and Th17 polarizing cytokines (Ge et al. 2013). Another HDACi, valproic acid, also reduced brain pathology and disease severity in EAE rats via modulation of encephalitogenic CD4+ T cells with reduced frequency of IL-17 producing cells, possibly through enhancing histone acetylation that suppressed T cell proliferation and differentiation (Castelo-Branco et al. 2014). In fact, the expression of IL-17 in T cells is tightly modulated through costimulatory molecules stimulation. It has been shown that OX40 stimulation represses

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IL-17 expression and reduces EAE via the recruitment of histone methyltransferases G9a and SETDB1, which subsequently leads to methylation at the Il17 locus with the hallmarks of H3K9me2 and H3K9me3 for gene repression and silencing (Xiao et al. 2016). Collectively, Th17 differentiation is tightly regulated through various mechanisms and epigenetic chemical inhibitors likely exert their immunosuppressive effects via multiple targets on different cell types.

12.4 Clinical Application Potential of Epigenetics Regulators in MS Over the past decade, there has been an exponential growth of research to study the roles of epigenetic regulation in MS. Collective findings from numerous research groups not only enable a deeper understanding on the pathogenic mechanisms underlying MS development but also open up a new avenue for identifying molecular targets for the development of biomarkers and novel therapeutics for better patient management. Currently, MS diagnosis, prognosis and clinical management still heavily rely on the assessment on clinical manifestations aided with MRI evaluation of brain lesions load and atrophy, which has proven to be instrumental for its purpose (Kaunzner and Gauthier 2017). However, these assessments are usually indicative of serious deterioration or tissue damages that may not be salvageable. Biomarkers that allow better prediction of MS development in RIS or CIS patients, or one that can predict and correlate well with brain inflammatory and/or degeneration events, particularly at the early phase or remitting phase of disease, are critically needed.

12.4.1 Epigenetic Modifiers as Biomarkers in MS Many studies exploring epigenetic modifiers as biomarkers for MS have been documented, and the majority of them focus on miRNAs (Table 12.4). miRNAs are characteristically attractive biomarker candidates for several reasons. First, circulating and extracellular miRNAs are extremely stable and are resistant to RNase activity as well as harsh extracellular handling conditions (Mitchell et al. 2008). Second, they are readily detected in body fluids like urine, saliva and blood (Weber et al. 2010), which can be sampled repeatedly with minimal invasive procedures for chronic disease monitoring. Third, as discussed above, many miRNAs are validated for their regulatory mechanisms in MS, thus their correlation with clinical parameters and drug response is anticipated to be scientifically justified by their functions. One of the earliest studies of profiling miRNAs in whole blood of RRMS patients had revealed that the differential expression pattern of 48 miRNAs can discriminate MS patients from HCs with over 95% in specificity, sensitivity and accuracy, and miR-145 stood out to be the best single candidate, achieving ~90% in all three

Tissue type

CSF

CSF

Peripheral blood

Peripheral blood

Peripheral blood

Peripheral blood

Biomarker candidate

miR-181c, miR-633

miR-150

miR-145

let-7c, miR-125a, miR-426, miR-320

miR-18a, miR-20b, miR-29a, miR-103

SIRT1 mRNA, H3K9me2 methylation

15

17

19

20

Two cohorts of 142 and 430 patients

53

No. of patients studied

Elevated in RRMS patients versus HCs Higher in CIS converted to RRMS than non-converters Reduced level in CSF but elevated in plasma after natalizumab treatment Levels correlated with CSF cell count, IgG index, and presence of oligoclonal bands

• • • •

2-year longitudinal follow up study Lower SIRT1 expression and lower H3K9me2 in peripheral blood in relapsing patients Higher SIRT1 level in glatiramer acetate responders than to non-responder Predictive for treatment responsiveness: 70% for SIRT1; 71% for H3K9me2

• Longitudinal follow up of peripheral blood miRNAs in relapsing patients at baseline and 1 year after natalizumab treatment • These 4 miRNAs reduced at baseline comparing with HCs, and increased after treatment

• Longitudinal follow up at 6- and 12-month after natalizumab treatment for relapsing MS • Reduced circulating let-7c and miR-125a-5p and elevated miR-462 levels 6 months after treatment • miR-320, miR-320b, miR-629 differentially expressed in association with progressive multifocal leukoencephalopathy at 12 months in 2 patients • Positive correlation of miR-320 level with therapy time

• Discriminated RRMS from HC with 89.5% specificity, 90.0% sensitivity and 89.7% accuracy

• • • •

• Both of these two miRNAs differentiated RRMS from SPMS with 82% specificity and 69% sensitivity

Findings

Table 12.4 Studies on the use of epigenetics modifiers as biomarkers in MS

(continued)

Hewes et al. (2017)

Ingwersen et al. (2015)

Munoz-Culla et al. (2014)

Keller et al. (2009)

Bergman et al. (2016)

Haghikia et al. (2012)

References

352 V. S.-F. Chan

19

28

36

PBMCs

CD4+ T cells

CD4+ T cells

Serum

Serum

Serum

Serum exosomes

miR-155, miR-26a, miR-132

miR-17

miR-126

miR-15b, miR-23a, miR-223

miR-320a, miR-37a-3p, miR-199-5p

miR-24-3p, miR-191-5p, miR-128-3p

miR-122-5p, miR-196b-5p, miR-301a-3p, miR-532-5p

82

80

84

13

20/37/80

PBMCs/plasma/serum

miR-145

No. of patients studied

Tissue type

Biomarker candidate

Table 12.4 (continued)

• These 4 miRNAs differentially expressed in RRMS in patients versus HCs, and downregulated in patients with gadolinium enhancement in brain MRI • Significantly upregulated during relapse

• miR-191-5p and miR-24-3p were overexpressed in both RRMS and PPMS • miR-24-3p correlated with disability progression index • miR-128-3p showed tendency toward predominant expression in PPMS

• miR-320a most differentially expressed between patients and HCs • miR-37a-3p linked with disease progression • miR-199-5p correlated with EDSS

• miR-15b, miR-23a and miR-223 levels in direct correlation with EDSS in PPMS • Possible exploration as diagnostic biomarkers by ROC-curve analysis

• Higher level in CD4+ T cells in untreated relapsing patients • Lower in natalizumab-treated group

• Elevated in CD4+ T cells of untreated relapsing patients • Reduced in natalizumab-treated group

• Longitudinal follow up study • Higher miR-155 and miR-132 in relapsing patients • miR-155 and miR-26a reduced 6 month after natalizumab treatment with concurrent reduction in Th1/Th17 cytokines mRNA

• miR-145 upregulation in PBMCs, plasma and serum was tested as predictor of MS with an area under curves of >0.785

Findings

(continued)

Selmaj et al. (2017)

Vistbakka et al. (2017)

Regev et al. (2016)

Fenoglio et al. (2013)

Meira et al. (2014a)

Meira et al. (2014b)

Mameli et al. (2016)

Sondergaard et al. (2013)

References

12 Epigenetics in Multiple Sclerosis 353

cfcDNA

cfcDNA

cfcDNA

cfcDNA

Methylation pattern of 15 gene promoters

Unmethylated MBP3 and WM1

Demethylated MOG

Methylated LINE-1

24

40

49

59

No. of patients studied

• CpG sites hypermethylated in LINE-1 in RRMS patients

• Demethylated MOG in patients • Higher demethylation index in relapsing patients

• Higher level differentiate relapsing patients from stable patients and HCs

• Methylation pattern of 14 genes differentiated RRMS patients from HC with >75% sensitivity and >91% specificity • Methylation pattern of 5 genes discriminated RRMS(e) from remitting RRMS with >70% sensitivity and 71% specificity

Findings

Dunaeva et al. (2018)

Olsen et al. (2016)

Lehmann-Werman et al. (2016)

Liggett et al. (2010)

References

Abbreviations cfcDNA, cell free circulating DNA; CIS, clinically isolated syndrome; CSF, cerebrospinal fluid; EDSS, Expanded Disability Status Scale; HC, healthy control; PBMC, peripheral blood mononuclear cell; MBP3, myelin basic protein 3; MOG, myelinated oligodendrocyte glycoprotein; MS, multiple sclerosis; PPMS, primary progressive MS; ROC, Receiver Operating Characteristic curve; RRMS, relapsing-remitting MS; SPMS, secondary progressive MS; SIRT, sirtuin

Tissue type

Biomarker candidate

Table 12.4 (continued)

354 V. S.-F. Chan

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parameters (Keller et al. 2009). Another report also found miR-145 in PBMCs, plasma and serum can act as a potential biomarker for the diagnosis of MS (Sondergaard et al. 2013). Apart from that, most of the other studies identified different miRNA candidates, including miR-18a, miR-20b, miR-29a and miR-103 in whole blood (Ingwersen et al. 2015), miR-17 in CD4+ T cells (Meira et al. 2014b), miR15b, miR-23, miR-223, miR-24-3p, miR-191-5p and miR-320a in serum (Fenoglio et al. 2013; Regev et al. 2016; Vistbakka et al. 2017), as well as miR-122-5p, miR196b-5p, miR-301a-3p and miR-532-5p in serum exosomes (Selmaj et al. 2017). Many of these miRNAs candidates were also found to change upon drug treatment, linked with disease progression, and correlated with clinical parameters such as MRI characteristics and EDSS (Table 12.4). Interestingly, miR-181c and miR-633 in CSF were found to have the potential to differentiate RRMS patients from SPMS patients (Haghikia et al. 2012), whereas miR-150 was significantly elevated in CIS patients who subsequently converted to RRMS when compared with non-converters. The level of miR-150 in RRMS patients was also reduced after natalizumab treatment, indicating that miR-150 is likely to be involved in MS pathogenesis (Bergman et al. 2016). Furthermore, the elevated expression of miR-17 and miR-126 in CD4+ T cells in untreated MS patients would be reduced after natalizumab treatment (Meira et al. 2014a, b). Apart from miRNA, lower levels of SIRT1 mRNA and H3K9me2 methylation in peripheral blood also differentiated relapsing MS patients from stable patients, and SIRT1 levels increased with glatiramer acetate treatment responsiveness (Hewes et al. 2017). This two-year longitudinal follow-up study demonstrated a predictive value for SIRT1 and H3K9me2 methylation of around 70% for treatment responsiveness toward glatiramer acetate in RRMS patients. A number of studies have explored the potential of detecting methylation pattern in cell-free circulating DNA (cfcDNA) as biomarkers for MS. Using a panel of 14 gene promoter targets, Liggett et al. showed that differential methylation profiles can differentiate RRMS patients from HCs with over 75% sensitivity and 91% specificity (Liggett et al. 2010). Furthermore, the composite methylation pattern of five of the tested gene promoters could discriminate relapsing patients from those in remission with over 70% sensitivity and specificity. Possibly, the differentially methylated cfcDNA may reflect specific cellular processes in association with disease exacerbation, for instance, tissue-specific cell death (Lehmann-Werman et al. 2016). Indeed, the levels of demethylated oligodendrocyte-specific DNA fragments from MOG, MBP3 and unannotated WM1 locus were found to be significantly higher in relapsing MS patients when compared with inactive patients and HCs (Lehmann-Werman et al. 2016; Olsen et al. 2016). Among all the studies described above, there is no single epigenetic modifier that has been systematically validated as a biomarker for MS diagnosis and prognosis. It is not too surprising that various biomarker studies identified different candidates. Not only because the study cohort sizes were all very small (Table 12.4), there were also many confounding factors, including patient selection criteria, treatment drugs used, duration of disease as well as biomarker assay methods, that all could introduce variability in the outcome. Nevertheless, the preliminary evidence provides a proof

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of concept that warrants further exploration of epigenetic modifiers as biomarkers to monitor MS development and treatment responses. Large-scale multicenter studies with unified patient recruitment criteria, clinical sample collection and isolation protocol and standardized method of biomarker assays are necessary for validating some of these potential candidates.

12.4.2 Epigenetic Modifiers as Therapeutics for MS The development of epigenetic drugs has proven to be fruitful in anticancer therapy and several HDACi and DNMT inhibitors have been approved to treat hematological as well as solid organ malignancies (Heerboth et al. 2014; Raynal et al. 2017). Although still in infancy stage, pre-clinical investigations on exploring therapeutic potential of epigenetic modifiers for MS treatment show promising results (Table 12.5). 5 -Aza-2-deoxycytidine, a DNMT inhibitor, was tested in three independent studies with two different EAE models. While administering at low doses for prophylactic treatment could only ameliorate disease transiently with a corresponding increase in Treg (Chan et al. 2014), a higher dose was effective for both preventive and therapeutic treatments in reducing EAE score and improving brain pathology (Mangano et al. 2014; Wang et al. 2017). 5 -Aza-2-deoxycytidine treatment resulted in an increase in Treg frequency in association with demethylation in FOXP3, and a concomitant reduction in Th17 cells and proinflammatory cytokines production, including IL-6, IL-12, TNFα and IL-1β (Mangano et al. 2014; Wang et al. 2017). Additionally, it also suppressed innate responses from microglia and monocyte-derived macrophages to mitigate disease (Wang et al. 2017). Histone modifiers, mainly HDAC inhibitors, were also tested in various EAE models with different efficacy (Table 12.5). Collectively, various HDACi alleviated EAE severity and CNS inflammation through downregulation of molecules associated with Th17 differentiation and function (e.g. IL-6, IL-21, IL-17, TGFβ, RORγt, STAT3), T cell proliferation and activation (e.g. CD83, CD86, HLA-DR, CD28, IL-2Rα), inflammatory responses (e.g. iNOS, IFNγ, TNFα) and chemotactic events (IL-8R, MIP2) (Camelo et al. 2005; Xie et al. 2009; Zhang et al. 2012; CasteloBranco et al. 2014; Donas et al. 2016). The suppression of Th17/Th1 effector cells function could be through a direct effect on T cells and/or through DCs (Ge et al. 2013; Donas et al. 2016). Distinctively, resveratrol, a SIRT1 activator, was shown to have neuroprotective effect rather than immunosuppressive effect, and promoted a more rapid recovery phase through attenuating axonal loss (Shindler et al. 2010). Although these pre-clinical findings are encouraging, systemic administration of DNA methylation and pan-HDAC inhibitors can have adverse off-target outcome mainly because of the broad spectrum of targets in multiple tissues being affected by these families of enzymes. In particular, various HDAC knockout mice exhibit neuronal deficit phenotypes, and different HDACs may interact cooperatively or antagonistically to mediate neuroprotective or neurotoxic effects (Didonna and Opal 2015). As discussed earlier, low histone acetylation is crucial for remyelination and

DMNT inhibition

miR-326 inhibition

Lentivirus of miRNA sponges

DMNT inhibition

DMNT inhibition

Molecular targets

5 -Aza-2-deoxycytidine (Decitabine)

5 -Aza-2-deoxycytidine

5 -Aza-2-deoxycytidine

Epigenetics modifier tested

• • • • •

• • • • • • • MOG-induced EAE in C57BL/6 mouse model Reduced EAE score Reduced neuroinflammation and infiltrate Downregulation of Il17a/f, Il22, Il23r and Rorc, lowered Th17 MiR-326 targeting of Ets-1, a Th17 negative regulator, was lifted

MOG-induced EAE in C57BL/6 mouse model Effective as both preventive and treatment modalities in reducing EAE score Lower immune infiltrates and inhibition of inflammatory molecules such as IL-1β, TNFα, iNOS Inhibit T cell proliferation in vitro and in vivo Inhibit Th1 and Th17 differentiation in vitro and in vivo Treg differentiation promoted only in vitro Molecular targets involved: cell cycle inhibitors and TET2

• MOG-induced EAE in C57BL/6 and PLP-induced EAE in SJL mouse models • Ameliorated clinical disease in two EAE mouse models under both prophylactic or therapeutic regimen • Higher peripheral Treg frequency in association with demethylation of a CpG island in Foxp3, elevated Foxp3 mRNA • Lower Th17 frequency with lower Rorc mRNA

• MOG-induced EAE in C57BL/6 mouse model • Low dose prophylactic treatment only transiently reduced EAE severity • Reduced CNS lymphocyte infiltration in association with increased Treg frequency in periphery without affecting per-cell suppressive function

Efficacy and mechanisms of action

(continued)

Du et al. (2009)

Wang et al. (2017)

Mangano et al. (2014)

Chan et al. (2014)

References

Table 12.5 Preclinical studies testing therapeutic potential of epigenetics modifiers in murine models of experimental autoimmune encephalomyelitis

12 Epigenetics in Multiple Sclerosis 357

Molecular targets

miR-155 inhibition

miR-26a overexpression

Pan class I and II HDACs inhibition

HATs inhibition

SIRT1 activation

Epigenetics modifier tested

Locked Nucleic acid (LNA)—antisense miRNA

Lentivirus of miRNA

Trochostatin

Curcumin

Resveratrol (SRT501)

Table 12.5 (continued)

• • • •

• • • •

• • • • •

• • • • •

• • • •

PLP-induced EAE in SJL mouse model Oral administration reduced neuronal damages and optic neuritis No impact on spinal inflammation and demyelination but attenuated axonal loss No difference in clinical score at relapsing phase but with improved recovery at remitting phase

MBP-induced EAE in Lewis rat model Oral administration reduced EAE clinical score with reduced inflammatory cell infiltration Downregulation of IL-17, TGFβ, IL-6, IL-21, STAT3 and RORγt expression in vitro Reduced STAT-3 phosphorylation in vitro

MOG-induced EAE in C57BL/6 mouse model Reduced mean EAE score No impact of disease onset time Downregulated expression of CD28, IL-2Rα, IL-8R, IL-12p35 and MIP2 Downregulated chemotactic, pro-Th1 and pro-proliferative mRNAs via E2F transcription factor pathways

MOG-induced EAE in C57BL/6 mouse model Reduced EAE score Reduced demyelination and spinal infiltrate Reduced IL-17, IL-6 and Rorγt but increased Foxp3, regulated Th17/Treg balance Direct targeting of IL-6 mRNA

MOG-induced EAE in C57BL/6 mouse model Reduced EAE clinical score with lower Th1 and Th17 response Reduced Th1 and Th17 polarizing enzymes expressed by DCs Treatment after EAE onset still inhibited disease development

Efficacy and mechanisms of action

(continued)

Shindler et al. (2010)

Xie et al. (2009)

Camelo et al. (2005)

Zhang et al. (2015b)

Murugaiyan et al. (2011)

References

358 V. S.-F. Chan

HDACs inhibition

HDACs inhibition

HDACs inhibition

JMJD3 (HDAC) inhibition

Valproic acid

Vorinostat

Valproic acid

GSK-J4

MOG-induced EAE in DA rat model Acute treatment with thyroid hormone after clinical onset reduced EAE score Reduced CD4+ T cells, particularly Th1 cells infiltrated in brains Enhanced expression in myelin gene in brain Reduced capacity of peripheral non-Treg cells to proliferate

• MOG-induced EAE in C57BL/6 mouse model • Systemic administration reduced EAE clinical score • Reduced costimulatory molecules CD80 and CD86 expression and lowered production of IL-6, IFNγ and TNF in DCs • Elevated Treg generation with enhanced suppressive capacity • No effect on Th1/Th17 frequency • Increased H3K27me3 methylation and lowered H3K4me3 at IL-6 promoter region in DCs

• • • • •

MOG-induced EAE in C57BL/6 mouse model Reduced EAE incidence and severity Reduced CNS inflammation and demyelination Suppressed CD83, CD86 and HLA-DR expression in DCs, and lower Th1 and Th17 frequency in mice • Suppressed LPS-induced activation in DCs and DC-mediated Th1 and Th17 polarizing cytokines production in vitro

• • • •

• MBP-induced EAE in Lewis rat model • Preventive and therapeutic oral administration reduced EAE severity and duration, and CNS pathology • Reduced spinal cord macrophages and lymphocytes • Suppressed TNFα, IL-1β, IL-17, MMP9, iNOS, T-bet and increased IL-4 mRNA in spinal cord • Shifting Th1/Th17 profiles to Th2/Treg in lymph nodes

Efficacy and mechanisms of action

Donas et al. (2016)

Castelo-Branco et al. (2014)

Ge et al. (2013)

Zhang et al. (2012)

References

Abbreviations CNS, central nervous system; DC, dendritic cell; DNMT, DNA methyltransferase; EAE, experimental autoimmune encephalomyelitis; HDAC, histone deacetylase; iNOS, inducible nitric oxide synthase; IFN, interferon; MBP, myelin basic protein; MMP9, matrix metalloproteinase 9; MOG, myelin oligodendrocyte glycoprotein; PLP, proteolipid protein; RORγt, RAR-related orphan receptor gamma; STAT3, signal transducer and activator of transcription 3; TET2, Tet Methylcytosine Dioxygenase 2; TNF, tumor necrosis factor

Molecular targets

Epigenetics modifier tested

Table 12.5 (continued)

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oligodendrocytes differentiation from the progenitors (Shen et al. 2005, 2008), thus long-term pan-HDACi usage may result in neuronal deficit and cognitive impairment that may take a long time to be recognized (Didonna and Opal 2015). As such, the future direction should be focused on isoform-selective HDACi development in order to enhance target specificity and to limit the off-target adverse events in the CNS while preserving their immunosuppressive functions. Compared with HDACi and DNA methylation inhibitors therapy, miRNA therapy shows better target specificity. However, it has a different set of hurdles to overcome. Unmodified miRNA mimics, anti-sense miRNAs (anti-miRs) or miRNA sponges are subjected to degradation by the naturally occurring nuclease in plasma and thus have short half-lives. Without carriers, systemically delivered miRNAs mostly get trapped in the liver and kidney, and the effective concentration in plasma drops rapidly (Chen et al. 2015). Thus, higher doses may be required but this also increases the chance of off-target effects and the potential to induce immunotoxicity. Strategies such as using viral vector, nanoparticles-conjugation, liposome-conjugation and locked nucleic acid (LNA) modification have been tested effective in improving the efficacy of miRNA therapeutics for cancer (Rupaimoole and Slack 2017). With these modifications, the therapeutic potential of three specific miRNAs was tested in MOG-induced EAE in C56BL/6 mice, the most commonly used MS murine model. miR-326 expression in CD4+ T cells was found highly upregulated during acute disease and decreased at remission in EAE mice (Du et al. 2009). Using lentiviral delivery of miRNA sponges to mop up endogenous miR-326, the disease was rendered less severe and accompanied by reduced neuroinflammation and CNS immune cell infiltrates. Similar disease amelioration effects were observed when mice were given anti-miR-155 oligonucleotides before or after the onset of clinical symptoms (Murugaiyan et al. 2011); or in mice given with lentivirus overexpressing miR-26a prior to disease induction (Zhang et al. 2015b). In all these cases, miRNAmediated disease improvement was caused by rebalancing the Th17/Treg ratios through lowering pathogenic Th17 frequency and/or promoting Treg differentiation. The relevance of these miRNAs and their cellular and molecular targets in MS patients have been demonstrated in a number of studies (Du et al. 2009; Junker et al. 2009; Murugaiyan et al. 2011; Honardoost et al. 2014; Lopez-Ramirez et al. 2014; Zhang et al. 2015b). To date, there is no approved miRNA-based therapeutics for any disease yet. Several phase I trials have demonstrated early signs of therapeutic efficacy and acceptable safety profile for miRNA-based drugs in HCV-infected patients (van der Ree et al. 2017), patients with malignant pleural mesothelioma (van Zandwijk et al. 2017) and patients with advanced solid tumors (Beg et al. 2017). Many more miRNA-based therapeutics are in the pipeline for clinical testing (Chakraborty et al. 2017), indicating that miRNA therapeutics may become a clinical reality in the near future. Although using chemical or small molecule inhibitors/activators to modify the epigenome is still the mainstay for developing epigenetic drugs, the recent advancement in CRISPR/dCas9 technology has made targeted therapy against the epigenome feasible. The CRISPR/dCas9 systems enable locus-specific chromatin modification including, transcriptional regulation, DNA methylation, histone modification

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as well as noncoding RNA relocation (Pulecio et al. 2017). Its efficacy in editing the epigenome has been demonstrated clearly (Hilton et al. 2015; Thakore et al. 2015), and its effect is longlasting. Recent advancement in the field also demonstrates the feasibility of targeting multiple genes in vivo (Liao et al. 2017; Zhou et al. 2018). This technology certainly paves the way for the use of next generation translational epigenetics in targeted therapy for MS patients.

12.5 Concluding Remarks Multiple sclerosis is an agonizing disease that slowly cripples patients of a young age, with not only physical disability but also with sensory, visual and cognitive deficits. Current treatment modalities for MS consist of a range of agents, including conventional immunosuppressant such as corticosteroids and a range of disease-modifying agents such as interferon-β, glatiramer acetate, fingolimod as well as monoclonal biologics like the ocrelizumab (targeting B cell marker CD20), natalizumab (targeting adhesion molecule α-4 integrin) and alemtuzumab (targeting mature lymphocyte antigen CD52). These drugs cannot cure the disease but only slow down the worsening of disability in patients, and at the expense of significant health risk associated with the side-effects when taken in long term. With our increasing knowledge of the human genome and epigenome, the advancement in gene sequencing and editing technology, and the escalating computational capacity to perform big data analyses, the future of medicine is foraging into personalized care and treatment for patients. To date, it is well recognized that MS disease development and progression is subject to epigenetic dysregulation, which is highly dynamic and subjected to modulation by environmental factors. As such, it may serve as a good entry point to explore and exploit the translational use of epigenetics for developing diagnostic and therapeutic tools that facilitate the evolution of precision medicine for MS patients. Disclosure No conflicts of interest, financial, or otherwise, are declared by the author.

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Chapter 13

The Epigenetic Regulation of Scleroderma and Its Clinical Application Yangyang Luo and Rong Xiao

Abstract Scleroderma (systemic sclerosis; SSc) is a complex and highly heterogeneous multisystem rheumatic disease characterized by vascular abnormality, immunologic derangement, and excessive deposition of extracellular matrix (ECM) proteins. To date, the etiology of this life-threatening disorder remains not fully clear. More and more studies show epigenetic modifications play a vital role. The aberrant epigenetic status of certain molecules such as Fli-1, BMPRII, NRP1, CD70, CD40L, CD11A, FOXP3, KLF5, DKK1, SFRP1, and so on contributes to the pathogenesis of progressive vasculopathy, autoimmune dysfunction, and tissue fibrosis in SSc. Meanwhile, numerous miRNAs including miR-21, miR-29a, miR-196a, miR-2023p, miR-150, miR-let-7a, and others are involved in the process. In addition, the abnormal epigenetic biomarker levels of CD11a, Foxp3, HDAC2, miR-30b, miR142-3p, miR-150, miR-5196 in SSc are closely correlated with disease severity. In this chapter, we not only review new advancements on the epigenetic mechanisms involved in the pathogenesis of SSc and potential epigenetic biomarkers, but also discuss the therapeutic potential of epigenetic targeting therapeutics such as DNA methylation inhibitors, histone acetylase inhibitors, and miRNA replacement. Keywords Systemic sclerosis · Epigenetics · DNA methylation · Histone modifications · microRNAs · Fibrosis · Biomarker · Wnt signaling List of Abbreviations ADAM12 C3AR1 COL1A1 COL1A2

A disintegrin A metalloprotease 12 C3a receptor 1 Collagen type I alpha 1 Collagen type I alpha 2

Y. Luo Department of Dermatology, Hunan Children’s Hospital, Changsha, China R. Xiao (B) Department of Dermatology, The Second Xiangya Hospital, Central South University, Changsha, China e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2020 C. Chang and Q. Lu (eds.), Epigenetics in Allergy and Autoimmunity, Advances in Experimental Medicine and Biology 1253, https://doi.org/10.1007/978-981-15-3449-2_13

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COL23A1 COL4A2 CSTA CTLA-4 CTSG CTSZ CXCR6 CYC DKK1 DKK2 DNMT1 DNMT3B ELANE ERAs F2R Fzd2 HDAC2 HRCT ICAM-1 IFN ITGA9 LTBR MBD3 MBD4 MMF MTX MYO1E NFE2 ODF3B PAG1 PDE-5 PFT PLAUR PRF1 PRKCH RASSF5 RUNX2 RUNX3 SAMD4A SFRP1 Sirt1 SPI1 STAT1 STAT2 STAT6

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Collagen type XXIII α1 chain Collagen type IV alpha 2 Cystatin A CTL-associated antigen 4 Cathepsin G Cathepsin Z CXC chemokine receptor 6 Cyclophosphamide Dickkopf associated protein 1 Dickkopf associated protein 2 DNA methyltransferase 1 DNA methyltransferase 3B Neutrophil elastase Endothelin Receptor Antagonists Coagulation factor II receptor Frizzled 2 Histone deacetylase 2 High resolution computerized tomography Intercellular adhesion molecule-1 Interferon Integrin α9 Lateral temporal bone resection Methyl-CpG-binding domain 3 Methyl-CpG-binding domain 4 Mycophenolate mofetil Methotrexate Myosin-1e Nuclear factor erythroid 2 Outer dense fiber protein 3B Persistency-associated gene 1 Phosphodiesterase-5 Positron emission tomography Plasminogen activator urokinase receptor Perforin 1 Protein kinase C eta Ras association domain-containing protein 5 Runt-related transcription factor 2 Runt-related transcription factor 3 Sterile alpha motif domain-containing 4A Secreted Frizzled Related Protein 1 Sirtuin 1 Salmonella pathogenicity island 1 Signal transducer and activator of transcription 1 Signal transducer and activator of transcription 2 Signal transducer and activator of transcription 6

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SUV39H2 TET1 TSA WIF-1 Wnt1 Wnt10b ZYX

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Suppressor of variegation 3–9 homologue 2 Ten-eleven translocation 1 Trichostatin A Wnt inhibitory factor–1 Wnt family member 1 Wnt family member 10b Zyxin

13.1 Introduction Scleroderma (systemic sclerosis; SSc) is a highly heterogeneous autoimmune disease characterized by a vascular abnormality that leads to tissue hypoxia and fibroblast dysfunction, resulting in excessive deposition of extracellular matrix (ECM) proteins. In addition, an immune response manifests as altered T lymphocyte and B lymphocyte function and production of autoantibodies (Pattanaik et al. 2011; Wollheim 2005). The disease is also characterized by a striking female predominance, with over 80% of patients being female (Nikpour et al. 2010). The first widely accepted classification criteria for SSc were published in 1980 by the American Rheumatology Association (ARA), but these criteria usually excluded patients with early SSc and 20% of patients with limited cutaneous disease (van den Hoogen et al. 2013). Recently, a new set of SSc classification criteria was formulated by a joint committee of the American College of Rheumatology (ACR) and the European League Against Rheumatology (EULAR), which has improved the specificity of SSc diagnosis compared with the 1980 criteria (Table 13.1) (Xu et al. 2016; van den Hoogen et al. 2013). In this new SSc classification, the maximum weight in each category is added to calculate the total score. Patients with a total score of 9 or more are definitively classified as having systemic sclerosis. The criteria are not applicable to patients with SSc-like disorders such as nephrogenic sclerosing fibrosis, lichen sclerosis, or graft-versus-host disease. The disease consists of multiple overlapping and poorly defined clinical subsets. SSc is traditionally divided into two major subsets based on the overall extent of affected skin: limited cutaneous SSc (lcSSc) and diffuse cutaneous SSc (dcSSc). However, recent retrospective studies suggest that the lcSSc/dcSSc classification should be replaced with the Barnett-Giordano type-3 subset classification: limited (fingers only or no skin involvement), intermediate (extremities but not the trunk), and diffuse (truncal) (Wollheim 2005; Scussel-Lonzetti et al. 2002). The clinical manifestation and the prognosis of each subset are variable. The majority of patients have skin thickening and various degrees of internal organ involvement, including the lungs, heart, kidneys, esophagus, or musculoskeletal system (Kowal-Bielecka 2010). The prognosis largely depends on the incidence of life-limiting complications, including scleroderma renal crisis (SRC), pulmonary arterial hypertension (PAH), interstitial lung disease (ILD), heart failure, and gastrointestinal failure (Muangchan

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Table 13.1 The ACR-EULAR criteria for classification of systemic sclerosis Items

Sub-items

Skin thickening of the fingers of both hands extending proximal to the metacarpophalangeal joints

Weight/Score 9

Skin thickening of the fingers

Puffy fingers Sclerodactyly of the fingers

2 4

Fingertip lesions

Digital tip ulcers Fingertip Pitting Scars

2 3

Telangiectasia

2

Abnormal nailfold capillaries

2

PAH and/or ILD

2

Raynaud’s phenomenon

3

Scleroderma related antibodies

Anti-centromere Anti-topisomerase l Anti-Scl 70 Anti-RNA polymerase III

3

Total score Add the maximum weight in each category to calculate the total score. Patients having a total score of 9 or more are being definitively classified as having systemic sclerosis. The criteria are not applicable to patients with SSc-like disorders (e.g. nephrogenic sclerosing fibrosis, lichen sclerosis, graft-versus-host disease)

et al. 2013). Because of severe organ involvement, SSc patients have a standardized mortality ratio of 3.24 (95% confidence interval) compared with the general population (Kuo et al. 2011). At present, the precise pathogenesis of this complicated and life-threatening disease remains unknown, but the consensus is that it is triggered in genetically susceptible individuals by exposure to specific environmental agents such as silica, viruses, bacteria, drugs, and silicones. These agents can induce changes at the epigenetic level, which in turn causes a series of molecular events that ultimately lead to autoimmune abnormalities and fibrosis (Luo et al. 2013, 2015). In this chapter, we mainly focus on new achievements of epigenetics with respect to pathogenesis and prognostic biomarkers, as well as its potential therapeutic effect in SSc.

13.2 Role of Epigenetics in the Pathogenesis of SSc Epigenetics is defined as stable and inheritable gene expression without any alteration in DNA sequences. Epigenetic mechanisms include DNA methylation, histone modification, and non-coding RNA transcripts (Lu 2013). DNA methylation refers to DNA methyltransferases (DNMTs) transferring a methyl group onto the C5 position of cytosines to form 5-methylcytosine (5mC). S-adenosyl-methionine (SAM)

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is the methyl donor in the process. DNA methylation can be located in CpG islands shores, gene bodies, repetitive sequences, and mainly CpG islands of gene promoter regions. The methylated state of DNA sequences represses gene transcription by a corepressor complex which increases binding of methyl-CpG-binding domain (MBD) proteins, decreases binding of transcription factors, and alters chromatin structure. Conversely, the unmethylated state of DNA sequences activates gene transcription (Fan and Zhang 2009). As another epigenetic mechanism, histone modification refers to a series of post-translational modifications occurring in histone proteins including acetylation, methylation, phosphorylation, deimination, ubiquitylation. β-N-acetylglucosamine, and sumoylation. This epigenetic phenomenon can change the charge of histones and affect the structure of chromatin (the interaction between histone and DNA strand) to promote or repress gene expression (Yun et al. 2011). MicroRNAs (miRNAs) are a group of endogenous, single-stranded non-coding RNAs with approximately 18–25 nucleotides in length. They are very significant post-translational regulators of gene expression (Bartel 2004). miRNAs regulate gene expression in two ways including modulating the DNA methylation and histone modifications of promoter sites and inducing transcript degradation or preventing translation based on the degree of complementarity between the miRNA strand and the 3 untranslated region (UTR) of the target gene. When the complementarity is complete, miRNAs induce degradation; in contrast, miRNAs repress translation (Luo et al. 2013). Genetic research shows that the incidence of SSc is 1.5–1.7% in families with a history of the disease, compared with 0.026% in the general population (Arnett et al. 2001). However, studies between monozygotic and dizygotic twins show that the incidence of SSc is similar in both groups, and the total concordance for SSc is low in twins (4.7%) (Feghali-Bostwick et al. 2013). This suggests that genetics alone cannot fully explain the development of SSc. Recently, accumulating evidence has indicated that epigenetics plays a pivotal role in the pathogenesis of SSc. Systemic sclerosis is a complicated and heterogeneous disease that involves three main processes: progressive fibroproliferative vasculopathy, autoimmune dysfunction, and tissue fibrosis. Four cell types involved in the pathogenic procedure include microvascular endothelial cells (MVECs), T lymphocytes, B lymphocytes, and fibroblasts (FBs) (Manetti 2016). Though the complete mechanisms of these complex processes remain unknown for the most part, new advances in the epigenetics of SSc partially elucidate the pathogenesis.

13.2.1 Epigenetics is Involved in Progressive Vasculopathy Vascular injury is a critical early event in SSc and involves perivascular inflammation, MVECs perturbations, and pathogenic angiogenesis. Endothelial cell structural and functional abnormalities lead to mononuclear cell infiltration via junctional adhesion molecules (JAMs). These cells secrete a large number of cytokines,

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autoantibodies, and growth factors, such as connective tissue growth factor (CTGF), ultimately leading to fibrosis (Altorok et al. 2014; Manetti et al. 2013). Serrati et al. showed that endothelial cells recruit and activate fibroblasts by inducing a connective tissue growth factor (CCN2)/transforming growth factor beta (TGF-β)-dependent mesenchymal-to-mesenchymal transition (Serrati et al. 2013). This implies that endothelial injury plays a critically important role in SSc, and an increasing number of studies show that epigenetic mechanisms contribute to vascular injury (Fig. 13.1). For example, HDAC5 is significantly increased in SSc endothelial cells, and silencing HDAC5 can restore normal angiogenesis by regulating the expression of CYR61, PVRL2, and FSTL1 (Tsou et al. 2016).

Fig. 13.1 Epigenetics is involved in vascular injury in SSc. a Fli-1 is distinctly reduced in endothelial cells in SSc due to the hypermethylation of its promoter and its chromatin deacetylation. The Fli-1 deficiency caused the downregulation of PECAM-1, PDGF-B, S1P1 receptors and the upregulation of MMP9 which produces the histopathologic features of SSc vasculopathy. b BMPRII is significantly reduced in SSc-MVECs due to the hypermethylation of its promoter. Its deficiency increased the expression and availability of TGF-β and ET-1 which are implicated in the pathogenesis of the disease. Meanwhile, it also increases the susceptibility of cells to oxidation injury leading to endothelial injury

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Epigenetic Abnormalities of Fli-1 Contribute to Endothelial Injury

Transcription factor Fli-1 (Friend leukemia integration 1), a member of the E26 transformation-specific (ETs) transcription factor (TF) family, is expressed in endothelial cells, fibroblasts, and immune cells. It participates in the development, differentiation, and activation of these cells. In SSc patients, Fli-1 is distinctly downregulated in endothelial and peri-endothelial cells. Fli-1 deficiency causes the reduction of platelet-derived growth factor (PDGF)-B, vascular endothelial (VE) cadherin, sphingosine 1 phosphate (S1P)1 receptors, platelet/endothelial cell adhesion molecule (PECAM)-1 and the upregulation of matrix metalloproteinase-9 (MMP-9), which together produce the histopathologic features of SSc vasculopathy (Asano et al. 2010). However, it is only the epigenetic regulation (hypermethylation of its promoter and its chromatin deacetylation) of Fli-1 that causes its downregulation (Wang et al. 2006). The downregulation of Fli-1 expression plays a pivotal role in activating endothelial cells, leading to the activation of fibroblasts. Recent studies have shown that the reduction of CCN family member 1 (CCN1) and C-X-C motif chemokine ligand 5 (CXCL5) is also due to Fli-1 deficiency (Ichimura et al. 2014). Fli-1 deficiency can induce the overproduction of progranulin. The overproduction contributes to the constitutive activation of SSc dermal FBs by antagonizing the antifibrotic effect of tumor necrosis factor (TNF) and Galectin-9, which promotes skin fibrosis development by suppressing the production of interferon-γ in skin-infiltrating CD4+ T cells (Ichimura et al. 2015; Saigusa et al. 2017). This further demonstrates that the epigenetic regulation of Fli-1 is deeply involved in aberrant angiogenesis in SSc.

13.2.1.2

Epigenetic Repression of BMPRII Contributes to Vascular Dysfunction

Bone morphogenetic proteins (BMPs) are members of the TGF-β superfamily of proteins regulating cell proliferation, differentiation, and survival (Wang et al. 2014a). Bone morphogenetic protein type II receptor (BMPRII), as BMPs co-receptor, has been proven to be involved in vascular cell proliferation, apoptosis, and the development of vasculopathy. Studies have shown that BMPRII is significantly reduced in SSc-MVECs. Its deficiency increases the expression and availability of TGF-β and the cytokine endothelin-1 (ET-1), which are implicated in the pathogenesis of the disease. The process can be triggered by oxidative stress and high levels of reactive oxygen species. The deficiency of BMPRII increases the susceptibility of cells to oxidation injury. Studies have shown that extensive CpG site methylation in the BMPRII promoter region occurs in SSc-MVECs, which explains the downregulation of BMPRII for the most part (Wang and Kahaleh 2013).

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Potential Epigenetic Regulation of NRP1 Contributes to Endothelial Injury

Neuropilin-1 (NRP1) is a specific co-receptor of vascular endothelial growth factorA (VEGF-A), which is an important angiogenic marker upregulated in both the circulation and skin of SSc patients (Aslani et al. 2018). Romano et al. found that NRP1 is decreased in SSc-MVECs and serum. Circulating levels of sNRP1 can serve as a biomarker reflecting the severity and progression of SSc microvasculopathy. NRP1 deficiency due to the Fli-1 deficiency contributes to the impaired angiogenesis of SSc-MVECs (Romano et al. 2016). Tserel et al. elucidated that the CpG sites of NRP1 are hypomethylated in human monocytes in elderly individuals compared with young individuals (Tserel et al. 2014). However, the methylation status of NRP1 in SSc-MVECs has yet to be investigated and would be worth studying in the future.

13.2.1.4

MiRNAs Abnormality Contributes to Vascular Injury

miR-193b has been shown to be reduced in SSc tissues. The suppression of miR-193b upregulates the expression of urokinase-type plasminogen activator (uPA), which is increased in SSc in a TGF-β-dependent manner. uPA is substantially expressed in vascular smooth muscle cells in SSc skin sections, inducing cell proliferation and inhibiting the apoptosis of smooth muscle cells. Taken together, this data shows that the downregulation of miR-193b contributes to the proliferative vasculopathy in SSc (Iwamoto et al. 2016).

13.2.2 Epigenetics is Involved in Immune Abnormalities Systemic sclerosis is an autoimmune disease characterized by immune cell activation and the production of autoantibodies. Perivascular infiltration of lymphocytes (mainly CD4+ T cells and B cells) occurs in the early stage of SSc. Meanwhile, the number of lymphocytes in peripheral blood is aberrant in SSc. Data shows that autoimmune T and B cell dysfunction plays an important role in SSc (Stummvoll et al. 2004). Mounting evidence indicates that epigenetic dysfunction occurs in immune cells, and the regulation of certain genes influences their activation and proliferation (Fig. 13.2).

13.2.2.1

Epigenetic Abnormalities in Immune Cells at the Global Methylation Level

It was first reported by Lei et al. that the global DNA of CD4+ T cells in SSc is significantly hypomethylated relative to controls. The degree of global DNA hypomethylation positively correlates with the level of MBD4. They also found that

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Fig. 13.2 Epigenetics is involved in immune abnormalities in SSc. a The activation of T cells and B cells is observed in SSc. The co-signaling molecules between T cells and B cells are essential for their activation. Studies show that DNA hypomethylation of the genes’ regulatory sequences contributes to the overexpression of CD40L, CD70, CD11a. The elevation of these co-signaling molecules increases the activation of T cells and B cells to induce the production of autoantibodies and profibrotic cytokines. b The hypermethylation of the regulatory sequence of Foxp3 contributes to its downregulation leading to the imbalance of Treg cell which induces T-cell activation. c The deficiency of transcription of Fli-1 and KLF5 due to epigenetic modifications contributes to the increase of CD19 and activates B cells to produce more antibodies

the methylation-related genes DNMT1, MBD3, and MBD4 are significantly downregulated in SSc (Lei et al. 2009). In addition to global methylation of DNA in SSc, the modification pattern of histone is also abnormal. In a recent study, Wang et al. found that the global H4 acetylation is hyperacetylated, negatively correlating to the expression of HDAC2, and the global histone H3K9 methylation is hypomethylated, positively correlating to the expression of SUV39H2 protein (Wang et al. 2013a).

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Epigenetic Regulation of PBMCs in SSc

Zhu et al. performed integration of global DNA methylation and genome-wide mRNA transcription analysis and observed 925 differentially methylated positions located on 618 genes in peripheral blood mononuclear cells (PBMCs) from SSc patients, with 20 differentially expressed genes inversely correlating with differentially methylated positions. Among them, 12 genes (ELANE, CTSG, LTBR, C3AR1, CSTA, SPI1, ODF3B, SAMD4A, PLAUR, NFE2, ZYX, and CTSZ) are upregulated, and eight genes (RUNX3, PRF1, PRKCH, PAG1, RASSF5, FYN, CXCR6, and F2R) are downregulated (Zhu et al. 2018). Interferon regulatory factor (IRF) molecules play an important role in the regulation of the interferon (IFN) cytokine family and IFN signature genes. Several studies have shown the role of type I IFNs in the pathogenesis of SSc (Wu and Assassi 2013). Rezaei et al. found that interferon regulatory factor 7 (IRF7) is significantly upregulated in the peripheral blood mononuclear cells (PBMCs) of lcSSc patients. CpG2 hypomethylation of IRF7 is distinctly associated with SSc risk, while overall promoter methylation is significantly correlated with the mRNA level of IRF7. These results imply that hypomethylation of the IRF7 promoter may play a vital role in SSc pathogenesis (Rezaei et al. 2017). Recently, Van et al. found aberrant H3K4me3 and H3K27ac marks in monocytes from SSc patients. Related genes with altered histone marks are enriched for immune, IFN, and antiviral pathways. Blocking acetylation readers can suppress the expression of STAT1 and STAT2, which may be developed as a potential therapy to restore monocyte homeostasis (van der Kroef et al. 2019).

13.2.2.3

Epigenetic Regulation of T-Cell Signaling in SSc

The proliferation of CD4(+) T cells, lymphocyte apoptosis, and CD4(+) regulatory T (Treg) cell frequency are significantly elevated in SSc patients and remarkably correlated with clinical phenotypes and clinical progression (Giovannetti et al. 2010). The activation of T cells primarily requires the cooperation of two signaling pathways. In one pathway, T-cell antigen receptors (TCR) recognize antigens to produce a message transferred to the intracellular part by CD3. The other pathway is realized by co-signaling molecules such as LFA-1/ICAM-1, CD40L/CD40, and CD28/CTLA-4. The abnormal expression induced by the epigenetic modification of these co-signaling molecules plays a role in the pathogenesis of SSc. Lian et al. found that CD40L is significantly elevated in CD4+ T cells from female patients with SSc, negatively correlating with the decreased methylation level in DNA regulatory sequences. This suggests that the hypomethylation of CD40L regulatory elements on the inactive X chromosome contributes to its overexpression in female patients. CD40, as its ligand, is expressed in B cells and fibroblasts. The CD40-CD40L interaction stimulates the activation of these two cells to produce antibodies and to undergo tissue fibrosis (Lian et al. 2012).

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Lymphocyte function-associated antigen-1 (LFA-1) (also called CD11a), interacts with ICAM-1, producing an essential co-stimulatory signal between T cells and other cells. In a recent study, Wang et al. found that LFA-1 is elevated in CD4+ T cells from SSc patients positively correlating with disease activity due to the demethylation of its regulatory sequences. After treatment with 5-azaC (a nucleoside analog of cytidine that specifically inhibits DNA methylation by trapping DNMTs), the proliferative response, amount of IgG production by co-cultured B cells, and COL1A2 mRNA expression by co-cultured fibroblasts are significantly upregulated in treated CD4+ T cells. This indicates that the overexpression of CD11a caused by epigenetic regulation contributes to its activation and proliferation, IgG overproduction by B cells, and excessive collagen synthesis by fibroblasts (Wang et al. 2014b). Regulatory T cells (Tregs) are a group of T cells that negatively regulate the immune system by secreting inhibitory cytokines and influence the interaction between itself and other cells. The impairment of Tregs plays a potential role in the pathogenesis of SSc. Kataoka et al. found the proportion of Tregs is decreased in both early-stage and late-stage SSc patients with the downregulation of its TF Runtrelated transcription factor 1 (Runx1), which indicates that a deficiency of Tregs may contribute to the disease (Kataoka et al. 2015). Wang et al. found that the number of Tregs is significantly reduced in SSc, and its iconic molecule, the forkhead box protein 3 gene (FOXP3), is also decreased in CD4+ T cells from SSc patients, inversely correlated with the methylation level of FOXP3 regulatory sequences. The promoter methylation level and expression level of FOXP3 are highly associated with disease activity. This indicates that the hypermethylation of FOXP3 contributes to the abnormalities of Tregs, leading to the immune dysfunction in SSc (Wang et al. 2014c). In addition, Wang et al. found that the methylation level of H3K27me3 in CD4+ T cells is downregulated due to the overexpression of jumonji domain-containing protein 3 (JMJD3) (Wang et al. 2015). Recently, Ding et al. observed an abnormal degree of methylation of IFNassociated genes by performing genome-wide DNA methylation analysis of CD4+ and CD8+ T cells from 24 SSc patients and 24 controls. They found that the global hypomethylation of the type I IFN signaling pathway-associated genes, including eukaryotic translation initiation factor 2 alpha kinase 2 (EIF2AK2), interferon induced transmembrane protein 1 (IFITM1), interferon induced protein 44 like (IFI44L), MX dynamin like GTPase 1 (MX1), and poly (ADP-ribose) polymerase 9 (PARP9), is found in both CD4+ and CD8+ T cells of SSc patients. These genes and type I IFN-α/β are significantly upregulated in the serum of SSc patients, and the levels are distinctly correlated with the methylation status of these genes. These results indicate that the type I IFN pathway is dysfunctional at the epigenetic level in SSc patients, suggesting that the mechanism of DNA methylation might be critical in SSc pathogenesis (Ding et al. 2017).

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Epigenetic Regulation of B-Cell Signaling in SSc

As mentioned above, the active interaction between LFA-1 (co-stimulatory molecule in T cells) and ICAM-1 (its ligand in B cells) promotes T-cell-dependent B-cell activation, leading to higher IgG secretion (Wang et al. 2014b). CD70, another B-cell co-stimulatory molecule, is overexpressed in the CD4+ T cells of SSc patients due to the demethylation of its regulatory sequence (Jiang et al. 2012). The interaction of CD70 and CD27 promotes the B-T cell contact, leading to immune abnormalities. CD19, as the primary signaling component on the surface of B cells, is overexpressed in the peripheral blood of SSc patients. Noda et al. found that the deficiency of transcription of Fli-1 and Krüppel-like factor 5 (KLF5) due to epigenetic modifications contributes to the increase of CD19 and activates B cells to produce more antibodies and excessive IL-6, which induces the production of type I collagen and CTGF (Noda et al. 2014).

13.3 Epigenetics is Involved in Fibrosis SSc is an autoimmune disease characterized by fibrosis in skin and/or internal organs due to the deposition of ECM proteins. Fibrosis, as the hallmark feature of SSc, is complex, involving the cooperation of several cells, growth factors, and other cytokines (Desbois and Cacoub 2016). The mechanism is not entirely clear. The consensus is that it is triggered by endothelial injury due to the induction of inflammation and oxidative stress. The dysfunction of endothelial cells promotes the production of cytokines, recruiting and activating immune cells to release profibrotic molecules (TGF-β, CTGF, and platelet-derived growth factor [PDGF]) in FBs (Babalola et al. 2013). Accumulating evidence shows that epigenetic dysfunction occurs in FBs, and the regulation of certain genes influences their activation and proliferation.

13.3.1 The Role of DNA Methylation in Fibrosis in SSc Altorok et al. identified a total of 3528 differentially methylated CpG sites in FBs from SSc patients, with 2,710 CpG sites in dcSSc patients and 1,021 CpG sites in lcSSc patients. Only 203 CpG sites are differentially methylated in both dcSSc and lcSSc FBs. There are 118 hypomethylated and six hypermethylated genes. Common hypomethylated genes include ITGA9, ADAM12, COL23A1, COL4A2, MYO1E, RUNX1, RUNX2, and RUNX3. This implies that abnormal DNA methylation of certain genes is observed in SSc (Altorok et al. 2015). Hattori et al. observed that global methylation is decreased in SSc FBs with an elevation of TET1, DNMT1, and DNMT3B. Meanwhile, they found that hypoxia upregulates TET1 via HIF-1αindependent mechanisms in SSc FBs, suggesting the involvement of aberrant DNA methylation in the pathogenesis of SSc (Hattori et al. 2015). Moreover, additional data shows that epigenetic regulation of certain genes contributes to the fibrotic process in SSc.

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Role of DNA Methylation in Profibrotic Signaling Cascades in SSc

Regulation of Fli-1 by DNA Methylation in SSc Fli-1 is downregulated in FBs, as mentioned above, and plays an important role not only in the endothelial injury but also in the fibrotic process. It regulates the expression of type I collagen genes and also influences the expression of genes related to ECM remolding. Type I collagen is the most abundant component of the ECM, comprising two pro-α1 (I) chains encoded by the COL1A1 and COL1A2 genes. Fli-1 binds to the promoter of these two genes and suppresses their transcriptional activity (Asano 2015). Wang et al. found that Fli-1 expression levels are significantly reduced in SSc FBs. The levels of Fli-1 deficiency are distinctly inversely correlated with collagen expression levels. More importantly, the epigenetic suppression of Fli-1 in bulk skin and cultivated dermal fibroblasts from SSc patients suggest that Fli-1 deficiency serves as a predisposing factor, reflecting the influence of environmental factors in the disease. They examined the methylation status in the promoter region of the Fli1 gene by methylation-specific PCR. Increased methylation of Fli-1 promoter was noted in SSc FBs, which contributes to its downregulation to a certain degree (Wang et al. 2006; Taniguchi et al. 2017).

Regulation of KLF-5 by DNA Methylation in SSc KLF5, a member of the SP/KLF transcription factor family, is a basic transcription factor that binds to GC boxes at several gene promoters and regulates their transcription. It mediates the signaling functions in cell proliferation, migration, differentiation, and apoptosis, as well as the cell cycle (Dong and Chen 2009). KLF-5 gene expression is significantly downregulated in SSc skin (Whitfield et al. 2003). Noda et al. found that certain CpG islands in the KLF5 promoter are significantly hypermethylated in SSc FBs compared with normal FBs by bisulfate sequencing. After treatment with 5-aza-2 -deoxycytidine, an 86% increase in KLF5 expression occurred in FBs from SSc patients, which indicates that DNA methylation is impacted by KLF-5 expression (Noda et al. 2014).

13.3.1.2

Role of DNA Methylation in Canonical Wnt Signaling in SSc

The Wnt signaling pathway plays a crucial role in many biological processes, including cellular proliferation, embryonic development, and tissue regeneration (Gillespie et al. 2018). Recent studies have demonstrated that canonical Wnt signaling is one of the central profibrotic signaling pathways in SSc. Canonical Wnt signaling is activated by overexpression of Wnt proteins and downregulation of endogenous Wnt antagonists, and subsequently stimulates resident FBs to differentiate into myofibroblasts to release excessive collagen. DKK1 and SFRP1, endogenous Wnt antagonists,

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are decreased in SSc patients. The promoter of DKK1 and SFRP1 are hypermethylated in FBs and peripheral blood mononuclear cells in SSc. Treatment of SSc FBs or bleomycin-challenged mice with 5-aza can inhibit canonical Wnt signaling in vitro and in vivo and effectively ameliorate experimental fibrosis. Studies show that DNA hypermethylation of DKK1 and SFRP1 leads to their low expression in SSc (Dees et al. 2014). Henderson et al. observed TGF-β1 can induce the expression of methyl cap binding protein-2 (MeCP2), which positively regulates the formation of the ECM through enhancing Wnt signaling by epigenetically repressing the Wnt antagonist sFRP-1. This suggests that targeting MeCP2 may be a promising therapeutic approach for treating SSc (van der Kroef et al. 2019).

13.3.2 Role of Histone Modification in Fibrosis in SSc 13.3.2.1

Role of Histone Modification in Profibrotic Signaling Cascades in SSc

Not only does DNA methylation play an important role in profibrotic components, including Fli-1 and KLF-5, but histone modification also contributes to the pathogenesis of SSc. Wang et al. examined the deacetylation of histones H3 and H4 in the promoter region of Fli-1 in SSc FBs and found deacetylation of the Fli-1 gene promoter, suggesting that histone deacetylation is involved in epigenetic repression of Fli-1 expression (Wang et al. 2006). Moreover, phosphorylation at threonine 312 of Fli-1 increases its affinity for p300/CREB-binding protein associated factor (PCAF) leading to the acetylation of Fli-1 at lysine 380. After acetylation, Fli-1 can be released from COL1A2 promotor and rapidly degraded through a proteasomal pathway, thereby losing the function of suppression to the promoter activity of profibrotic gene COL1A2 (Asano et al. 2010). Histones H3 and H4 on the KLF-5 promoter are also distinctly less acetylated in SSc FBs than in normal FBs. The epigenetic downregulation contributes to the low expression of KLF-5 in SSc (Noda et al. 2014). The deficiency of these two factors in mice spontaneously recapitulates all three features of SSc, namely vascular changes, immune abnormalities, and fibrosis. A study by Kramer et al. showed that inhibition of H3K27me3 stimulates the release of collagen in FBs in a time- and dose-dependent manner by inducing the expression of the profibrotic transcription factor Fra-2 in vitro and in vivo. This data demonstrates a negative role of H3 Lys27 histone methylation in fibroblast activation by repressing the expression of Fra-2 in contrast to DNA methylation and histone acetylation (Kramer et al. 2013).

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Role of Histone Modification in Canonical Wnt Signaling in SSc

An increasing number of studies have suggested an important role of Wnt signaling in the pathogenesis of SSc. Studies have shown elevated Wnt signaling activity in SSc patients with increased expression of Wnt signaling molecules Wnt1, Wnt10b, Fzd2, nuclear β-catenin, and LEF-1 and decreased expression of DKK2 and WIF-1 in SSc skin fibroblasts, which are positively correlated with skin fibrosis (Shi et al. 2016). Among these, WIF-1 deficiency in FBs of SSc patients or knocking down WIF-1 in normal FBs is correlated with the expression of Wnt effector β-catenin and the production of collagen. WIF-1 loss and DNA damage can be induced by ultraviolet light, hydrogen peroxide, or bleomycin. DNA damage mediates WIF-1 silencing through the phosphorylation of the transcription factor c-Jun, which in turn activates the expression of activating transcription factor 3 (ATF3). c-Jun and ATF3 together recruit histone deacetylase 3 (HDAC3) to the WIF-1 promoter and inhibit WIF-1 expression. Studies have also indicated that trichostatin A, an HDAC inhibitor, prevents WIF-1 loss, β-catenin induction, and collagen accumulation in an experimental fibrosis model (Svegliati et al. 2014).

13.3.2.3

Role of Histone Modification in TGF-β Signaling in SSc

TGF-β, which can be secreted by T cells and FBs, plays an essential role in cell proliferation, cell differentiation, angiogenesis, tissue repair, and immune regulation. It functions as a potential fibrogenic molecule by increasing collagen synthesis, proliferation, migration, adhesion, and transdifferentiation into myofibroblasts. In a recent study, TGF-β was shown to coordinately regulate the DNA binding activity of the transcriptional activator Smad3 and the repressor Fli-1, leading to increased ECM production. After the stimulation of TGF-β, Fli-1 loses the transcriptional inhibitory effect on the COL1A2 promoter through a phosphorylation-acetylation cascade, while the TGF-β type I receptor phosphorylates Smad3, leading to its acetylation through the p300/CREB-binding protein, thereby increasing the DNA binding ability of the COL1A2 promoter (Asano et al. 2010). p300, a histone acetyltransferase, is significantly elevated by TGF-β in SSc skin. The process involves the early-immediate transcription factor early growth response 1 (Egr-1), a primary regulator of profibrotic TGF-β signaling independent of Smads (Ghosh et al. 2013). Meanwhile, Sirt1, a member of class III histone deacetylase, is decreased in SSc. It can enhance Smad reporter activity, increase the transcription of TGF-β target genes, and elevate the release of collagen. Though Sirt1 is decreased in SSc, it cannot counterbalance the excessive activation of TGF-β signaling. In contrast, knockdown of Sirt1 inhibits TGF-β/SMAD signaling and reduces the release of collagen in FBs (Zerr et al. 2016).

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13.3.3 Role of microRNAs in Fibrosis in SSc To date, 1,426 miRNA sequences have been identified within the human genome. In one study, a gene chip including 924 miRNA sequences was used to screen for and analyze miRNAs involved in the development of SSc. Twenty-four miRNAs are differentially expressed in SSc skin samples, including nine that are upregulated and 15 that are downregulated. Among the 24, hsa-miR-206, has-let-7g, hsa-miR-133a, hsa-miR-125b, hsa-miR-40-5p, and hsa-miR-23b are highly and specifically associated with SSc pathogenesis. Interestingly, the expression of hsa-miR-206, which regulates at least 15 target genes, is closely correlated with the pathogenesis of SSc (Li et al. 2012). Another study, however, identified miR-21, miR-31, miR-146, miR-503, miR145, and miR-29b as being closely associated with SSc fibrosis. miR-21 expression is upregulated, whereas miR-145 is downregulated, in SSc skin samples and FBs. Both of these miRNAs are known to regulate genes that are involved in fibrosis in SSc (SMAD7, SAMD3, and COL1A1) (Zhu et al. 2012). While miR-29a is significantly downregulated in SSc FBs, its overexpression is known to significantly decrease collagen types I and III mRNA and protein levels, suggesting a unique role for miR-29a in SSc-related fibrogenesis and its potential as a putative therapeutic target (Maurer et al. 2010).

13.3.3.1

Role of microRNAs in TGF-β Signaling in SSc

A study by Honda et al. demonstrated that miR-196a is decreased in SSc. The serum level of miR-196a is negatively correlated with the ratio of diffuse cutaneous SSc, the score of modified Rodnan total skin thickness score, and the prevalence of pitting scars. However, TGF-β small interfering RNAs can normalize the expression of miR196a, leading to the downregulation of type I collagen in SSc fibroblasts (Honda et al. 2012). Meanwhile, TGF-β can downregulate discoidin domain receptor 2 (DDR2), which is significantly decreased in SSc dermal FBs. The low expression of DDR2 expression induces the expression of miR-196a, leading to type I collagen downregulation. This probably acts as a negative feedback mechanism against fibrosis, as decreased DDR2 expression stimulates miR-196a expression and further changes collagen expression (Makino et al. 2013a). miR-29a is strongly downregulated in SSc fibroblasts, and its upregulation significantly decreases the levels of type I and type III collagen. This suggests that miR-29a is an antifibrotic molecule in SSc. The inhibition of TGF-β pathways can increase the levels of miR-29a in vitro and in vivo (Maurer et al. 2010). A study by Ciechomska et al. showed that miR-29a targeting TGF-β-activated kinase 1 binding protein 1 (TAB1) regulates the downstream production of tissue inhibitor of metalloproteinase 2 (TIMP). TAB1 can trigger TIMP-1 production involved in TGF-β transduction. Data has shown that miR-29a plays an antifibrotic role in SSc by repressing TAB1mediated TIMP-1 production (Fig. 13.3a) (Ciechomska et al. 2014), while miR-21

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Fig. 13.3 The role of microRNAs in TGF-β signaling in SSc. a MiR-29a is strongly downregulated in SSc fibroblasts, which target TGF-β activated kinase 1 binding protein 1 (TAB1) and regulate downstream production of TIMP. TAB1 triggers TIMP-1 production and inhibits the expression of matrix metalloproteinase (MMP)-1 leading to collagen production. The inhibition of TGF-β pathways increases the levels of miR-29a in vitro and in vivo. b MiR-21 is significantly upregulated in SSc FBs by TGF-β. The overexpression of miR-21 can decrease levels of Smad7 which is a repressor of SMAD signaling leading to collagen production

is significantly upregulated in SSc FBs regulated by TGF-β. The overexpression of miR-21 can decrease the levels of Smad7, suggesting it has a therapeutic role in SSc (Fig. 13.3b) (Zhu et al. 2013). miR-92a is remarkably increased in SSc and is also stimulated by TGF-β. It may target matrix metalloproteinase-1 (MMP-1) to play a role in excessive collagen accumulation (Kuwatsuka et al. 2009). miR-135b is reduced in SSc FBs and serum. Using prediction software analysis, the target of miR135-b was found to be STAT6. STAT6 is important for the polarization of naïve T cells to Th2 effector cells, and the activation of STAT6 leads to the expression of Th2 cytokines such as IL-4 and IL-13.

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miR-135b repression by methylation regulates IL-13-mediated collagen expression (O’Reilly et al. 2016). miR-202-3p, a member of the miR-202 family located at chromosomal fragile site 10q26.3, is increased in SSc lesion skin. Overexpression of miR-202-3p markedly increases collagen disposition. The expression of MMP1 is inversely correlated with the expression of miR-202-3p. By using a luciferase reporter assay, researchers demonstrated that MMP1 is a target of miR-202-3p. These findings suggest that miR-202-3 may function as a novel profibrotic miRNA by inhibiting the expression of MMP1 (Zhou et al. 2017).

13.3.3.2

Role of Other microRNAs in SSc

In addition to miR-196a and miR-29a, several other miRNAs play a role in the pathogenesis of SSc. Alsaleh et al. demonstrated that miR-30a-3p is a basic repressor of B-cell-activating factor (BAFF) expression in SSc FBs, while BAFF is an important factor for B-cell activation and is overexpressed in SSc. This implies that miR-30a-3p has a potential antifibrotic effect (Alsaleh et al. 2014). miR-150 is downregulated in SSc FBs by DNA methylation and is negatively correlated with the severity of clinical manifestations. Low expression of miR-150 induces the expression of integrin beta3, phosphorylated Smad3, and type I collagen, which suggests that it has an antifibrotic role in SSc (Honda et al. 2013). Meanwhile, miR-let-7a is also downregulated in SSc biopsies, the inhibition of which affects the expression of type I collagen and luciferase activity of the collagen 3 UTR. This implies that miR-let-7a mediates the regulation of collagen, leading to fibrosis (Makino et al. 2013b). miR-129-5p is downregulated in SSc. FBs can also be upregulated by IL-17A expression, which reduces the expression of α1 (I) collagen and CTGF, suggesting that miR-129-5p is a mediator of the therapeutic effect of IL-17A (Nakashima et al. 2012). miR-7 is upregulated in SSc dermal FBs, which has an inhibitory effect on collagen synthesis due to decreased expression of thrombospondin-2 (TSP-2), which is involved in ECM synthesis, cell behavior, and inhibiting the proliferation of MVECs. However, the expression of TSP-2 is upregulated in extracellular sites of SSc dermal FBs. It is possible that the interaction of miR-7 and TSP-2 serves as a negative feedback mechanism for tissue fibrosis. Amplifying this feedback pathway may provide a target for therapy (Kajihara et al. 2012). Moreover, miRNA-155 is overexpressed in SSc dermal and lung FBs, suggesting that the increased miR-155 expression in FBs contributes to fibrosis. This research further demonstrates that miR-155 modulates the fibrosis required for NLRP3 inflammasome-mediated collagen synthesis via an IL-1 signaling mechanism (Artlett et al. 2017).

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13.4 Epigenetic Biomarkers in SSc Biomarkers are indicators of the biologic process, disease severity, disease activity, and therapeutic effect. They play a role in diagnosis and classification, identifying the disease stage, predicting prognosis, and monitoring regression and progression (Castelino and Varga 2013). Systemic sclerosis is a heterogeneous autoimmune disease involving organs including the skin, gastrointestinal tract, lungs, heart, and kidneys. According to the extent of skin involvement, SSc is classified into two subsets: diffuse systemic sclerosis (dSSc) and limited systemic sclerosis (lSSc) (Bergmann and Distler 2015). Because of the heterogeneity of the disorder, the identification and validation of SSc biomarkers is troublesome and challenging. Typically, the modified Rodnan total skin score (MRTSS) and Valentini scleroderma disease activity index (SDAI) are used to evaluate the activity and severity of SSc (Vadasz and Rimar 2014). However, there are limitations for these two evaluation tools. A review by Flavia et al. summarized the biomarkers in SSc, which included circulating antibodies, osteopontin, matrix metalloproteinases, adiponectin, optical coherence tomography, PFTs, and HRCT imaging (Castelino and Varga 2013). However, the authors did not discuss epigenetic biomarkers in SSc in detail; therefore, we summarized the new advancements in this profile in a supplementary table (Table 13.2).

13.4.1 DNA Methylation-Related Biomarkers in SSc In a study by Wang et al., CD11a was found to be upregulated in CD4+ T cells from SSc patients due to the demethylation of its regulatory sequences. The expression of CD11a is positively correlated with disease severity (Wang et al. 2014b). While FOXP3 is decreased in CD4+ T cells from SSc patients due to the hypermethylation of Table 13.2 Potential epigenetic biomarkers in SSc

Mechanism

Type

Expression

DNA methylation

CD11a (demethylation)

Increased

Foxp3 (hypermethylation)

Decreased

Histone methylation

HDAC2

Decreased

Global H4 acetylation of B cells

Hyperacetylation

MicroRNAs

miR-30b

Decreased

miR-142-3p

Decreased

miR-150

Decreased

miR-5196

Increased

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its regulatory sequences. The level of Foxp3 expression is negatively correlated with disease severity (Wang et al. 2014c). Recently, Chen et al. observed that significant differentially hypomethylated sites (DMS) were distinctly enriched in type I interferon (IFN) pathway genes in SSc patients. The methylation levels of the 21 DMS in IFN-related genes in CD4+ T cells showed a remarkable diagnostic value with a high AUC value of 0.90, sensitivity and specificity of 0.82, while IFI44L, another IFN-related gene, showed a high prediction ability in CD4+ and CD8+ T cells. All these imply promising biomarkers for the diagnosis of SSc (Chen et al. 2019).

13.4.2 Histone Modification-Related Biomarkers in SSc As mentioned above, global histone H4 hyperacetylation of B cells in SSc patients is negatively correlated with the expression of HDAC2, which is downregulated. Moreover, the level of global histone H4 acetylation is positively correlated with disease severity, while the expression of HDAC2 is negatively correlated with skin thickness (Wang et al. 2013a).

13.4.3 MicroRNAs-Related Biomarkers in SSc In a study by Tanaka et al., 95 miRNAs were observed to target SSc-related genes, including IL-4, TGF-beta, CTGF, PDGF-B, PDGF receptor (PDGFR) alpha/beta, and COL1A2. Among these miRNAs, 90 are downregulated. miR-30b is the most decreased, repressing the expression of PDGFR-beta and negatively correlating with disease severity (Tanaka et al. 2013). Koba et al. found that the combination of serum levels of miR-206 and miR-21 is a useful way of distinguishing patients with SSc from normal subjects (Koba et al. 2013). Steen et al. found that a circulating miRNA profile can differentiate SSc patients from healthy controls (HC) and systemic lupus erythematosus (SLE) patients. They found that miR-16, -223, and -638 are strongly differentially expressed in SSc and HC, with miR-638 having little correlation with anti-Scl-70. Meanwhile, miR-142-3p, -150, -223, and -638 are significantly differentially expressed in SSc and SLE. This may be a tool for the differentiation of SSc in the future (Steen et al. 2015). Makino et al. found that miR-142-3p is significantly overexpressed in SSc, and this is correlated with disease severity. It may be a useful biomarker for SSc and for the differentiation of SSc from scleroderma spectrum disorder (SSD) (Makino et al. 2012). As mentioned above, miR-150, an antifibrotic molecule, is differentially expressed in SSc. Its decreased expression is negatively correlated with disease severity (Honda et al. 2013). In addition to miRNAs in serum or FBs that can be biomarkers in SSc, miRNAs in the hair root and especially in the hair shaft are differentially expressed in SSc. Wang et al. found the expression of miR-196a in hair shafts is significantly decreased in SSc patients (Wang et al. 2013b). A study by Ciechomska et al. found

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that circulating miR-5196 is significantly elevated in SSc sera and monocytes, and this is positively correlated with the C reactive protein (CRP) level in SSc patients. These findings indicate that miR-5196 can be a biomarker of inflammation, providing useful information regarding SSc activity and severity (Ciechomska et al. 2017).

13.5 Potential Therapeutic Effects of Epigenetics in SSc Systemic sclerosis is a chronic, progressive, and life-threatening autoimmune disease of different clinical patterns characterized by the extent of skin fibrosis, presence of circulating antibodies, and involvement of internal organs. As the pathogenesis of SSc is not completely understood, there is no specific and consistent treatment for this condition (Desbois and Cacoub 2016). Until now, therapy has been based on the extent of skin fibrosis and organ involvement. For example, the use of MTX, CYC, MMF, and D-Pen in skin fibrosis, especially in dSSc patients, is common. Additional examples include the use of CYC, MMF, glucocorticoids, and stem cell transplantation in lung involvement, calcium channel blockers, prostaglandins, ERAs, PDE-5 in vascular complications, and ACE inhibitors in scleroderma renal crisis (Nagaraja et al. 2015). There are also a few new therapies targeting TGF-β signaling and other pathways. However, there are still many questions regarding these therapies, and the treatment is still difficult and intractable. Since epigenetic modifications play an essential role in the process of SSc, we conclude this review with a discussion on potential epigenetic therapies.

13.5.1 Inhibition of DNA Methylation As pointed out above, the transcription factors Fli-1 and BMPRII play an essential role in SSc. Treatment with DNA methyltransferase inhibitor (5-Aza-2 deoxycytidine, decitabine) increases the level of Fli-1 and decreases the expression of BMPRII to inhibit collagen synthesis (Wang et al. 2006; Wang and Kahaleh 2013). Moreover, DKK1 and SFRP1 are endogenous inhibitors of Wnt signaling that are activated and contribute to the pathogenesis of SSc. Dees et al. found that these two inhibitors are downregulated in peripheral blood mononuclear cells from SSc patients due to the hypermethylation of these two genes. However, 5-azaC can inhibit Wnt signaling in vitro and in vivo and effectively ameliorate experimental fibrosis. This further proves the therapeutic effect of 5-azaC (Dees et al. 2014). Nitric oxide (NO) plays an important role in vascular smooth muscle cell proliferation, catalyzed by nitric oxide synthases (NOSs). There are three NOS isoforms: neuronal NOS (NOS1), inducible NOS (INOS or NOS2), and endothelial NOS (eNOS or NOS3). eNOS is downregulated in SSc patients, leading to the increased expression of proinflammatory and vasospastic genes. However, 5-azaC can demethylate the eNOS promoter in endothelial cells and upregulate the expression of eNOS mRNA

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Table 13.3 The effects of inhibition of DNA methylation Target genes

Expression (before)

Methylation status (before)

Treatment

Expression (after)

Effects

Fli-1

↓

DM

5-azaC

↑

Collagen expression↓

BMPRII

↑

DM

5-azaC

↓

Antifibrosis

Foxp3

↓

HM

5-azaC

↑

Regulating immunity

Foxp3

↓

HM

RA

↑

Regulating immunity

DKK1

↓

HM

5-azaC

↑

Antifibrosis

SFRP1

↓

HM

5-azaC

↑

Antifibrosis

eNOS

↓

Not sure

5-azaC

↑

Ant-inflammatory

to achieve antifibrosis (Romero et al. 2000; Matouk and Marsden 2008). In addition, Sun et al. found that retinoic acid (RA), an active metabolite of vitamin A, can increase the expression of FOXP3 by downregulating FOXP3 promoter methylation levels in SSc CD4+ T cells to induce a Treg response. In summary, the inhibition of DNA methylation can produce antifibrosis and regulate immunity effects in many ways (Table 13.3), which implies it has therapeutic potential, although the use of specific inhibitors in clinical trials may be a long way off.

13.5.2 Inhibitors of Histone Modification The inhibitors of histone modification include histone acetylase inhibitors, histone methyltransferase inhibitors, and so on. Histone acetylase inhibitors can alter the balance of acetylation and affect cell growth, cell differentiation, and cell-matrix interactions. They emerged first as a class of agents for anticancer therapy (de Ruijter et al. 2003). TSA, the most potent inhibitor, inhibits the proliferation of fibroblasts and prevents dermal accumulation of extracellular matrix by inhibiting profibrotic Smad transcription factors and upregulating the cell cycle inhibitor p21 (Huber et al. 2007). DZNep, a histone methyltransferase enhancer of zeste homolog 2 (EZH2) inhibitor was also observed to halt fibrosis in vitro and vivo by dose-dependently inhibiting the expression of profibrotic genes and migratory activity of SSc FBs. While EZH2 was upregulated in both SSc dermal FBs and endothelial cells, inhibition of EZH2 not only can restrain fibrosis, but also can restore normal angiogenesis via activating the Notch ligand DLL4 (Tsou et al. 2019). It implies the potential therapeutic role of TSA and DZNep in SSc.

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13.5.3 MicroRNA Replacements In a study by Artlett et al., bleomycin could not induce collagen synthesis in miR155KO fibroblasts. When miR-155KO fibroblasts are transduced into a miR-155 retroviral expression vector, there is a significant induction of total collagen. These findings indicate a role of miR-155 in fibrosis, suggesting a potential therapeutic role of blocking miR-155 in SSc (Artlett et al. 2017).

13.6 Conclusion Systemic sclerosis is a complex, highly heterogeneous, and life-threatening autoimmune disease. Because of its severe complications and high mortality, the disease has received mounting and widespread attention. While classical hereditary factors cannot fully explain the pathogenesis of SSc, epigenetic mechanisms have been shown to play a pivotal role in SSc. However, the detailed mechanisms of the disorder remain poorly understood. Studies show that the epigenetic molecules p300, sirt1, HDAC2, HDAC5, DNMT1, MBD3, MBD4, EZH2, and MeCP2 and numerous miRNAs are differentially expressed in SSc, and the abnormal expression of the genes Fli-1, BMPRII, NRP1, CD40L, CD70, CD11a, FOXP3, KLF-5, DKK1, and SFRP1 due to epigenetic mechanisms contributes to the pathogenesis of SSc. All these factors constitute an intricate network worthy of further exploration and research. Epigenetic abnormalities are correlated with the activity and severity of the disease, which suggests their potential function as biomarkers for diagnosis and prognosis. This has yet to be verified in clinical trials. There is still no specific therapy for this disease; currently, the main drugs that are used include glucocorticoids and immunosuppressors, which have many disadvantages due to their low specificity and side effects. Therefore, finding specific therapeutic ways to treat SSc is a task of top priority. The advancements in the epigenetics in SSc that have been discussed in this review provide a new vision for the treatment of this intractable disorder.

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