Genomics, Proteomics, and the Nervous System [1 ed.] 1441971963, 9781441971968, 1441971971, 9781441971975

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Advances in Neurobiology

Series Editor Abel Lajtha

For further volumes: www.springer.com/series/8787

James D. Clelland Editor

Genomics, Proteomics, and the Nervous System

Editor James D. Clelland, Ph.D. Nathan S. Kline Institute for Psychiatric Research 140 Old Orangeburg Road Orangeburg, NY 10962 and New York University School of Medicine Langone Medical Center 550 First Avenue New York, NY 10016 USA [email protected]

ISSN 2190-5215 e-ISSN 2190-5223 ISBN 978-1-4419-7196-8 e-ISBN 978-1-4419-7197-5 DOI 10.1007/978-1-4419-7197-5 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2010938371 © Springer Science+Business Media, LLC 2011 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)

Preface

Mammalian central and peripheral nervous systems are highly complex at the structural, genetic and molecular levels, composed of multiple cell types and tissue structures. Thousands of genes, regulated at the genomic level via sequence variation or epigenetic regulation, are expressed at the RNA level and translated into proteins required to develop and maintain these cells and tissues, and along with small regulatory RNA molecules, lipids, and small molecule neurotransmitters, these gene products constitute the physical substrate for learning, memory, emotion, sensory perception, and consciousness itself. The potential for malfunction of this large number of complex biological systems is great, leading to the many behavioral and cognitive deficits observed in human psychiatric and neurological disorders, such as schizophrenia, autism and Alzheimer’s disease. This Volume of Advances of Neurobiology discusses research designed to increase our understanding of the nervous system and its structures and activities, through the utilization of genomic and proteomic technologies, addressing facets including development and epigenetic regulation, functions in learning and memory, and changes associated with neurological and psychiatric disorders. Specifically, the development of high-throughput genomic and proteomic analysis technologies, including microarray and high-throughput DNA sequencing technology, as well as integrated protein separation and mass spectrometry analysis systems, have created the opportunity for researchers to collect datasets that include measurements for all or most of the RNA species or the complement of proteins, within a particular biological sample. These high dimensional datasets are being generated for different nervous system cells and tissues, such as laser-capture microdissected neurons, or samples of postmortem pre-frontal cortical tissue. Different approaches have then been utilized to extract pertinent information, and these range from comparisons of postmortem cells and/or tissues using samples collected from subjects with and without disease states, for example patients with Alzheimer’s disease compared to control subjects, in order to discover differences between the samples that reflect aspects of the disease pathology, and that can then be investigated further to determine their role(s) in disease development. In addition, and in disorders such as autism, genome-wide expression analysis can provide data that allows for more focused investigations to test hypotheses regarding disease etiology, such as immune system dysfunction. Other experimental approaches include the utilization v

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of tissue or animal models to determine the effects of external stimuli on for example, investigation of prenatal viral infection as a model of schizophrenia. Although studies that utilize genomic and proteomic approaches differ widely, they can provide both data to support pre-existing hypotheses, plus they can implicate previously unconsidered biological networks and pathways in mammalian development, in nervous system functioning, and in the etiologies of diseases. A further important aspect in the development of genomic and proteomic approaches to nervous system research is the use of computational interrogation methods, that can be used to extract relevant information from the high dimensional data-sets. These techniques include cluster analysis and group classification algorithms, and the development of software tools allows the bench researcher to perform useful analyses of the multivariate datasets produced in genomics and proteomics experiments. The future ability to collect, store and analyze large-scale datasets will be central to the growing area of personalized medicine, whereby treatment choices and monitoring of individual’s responses to medications will be performed through the utilization of genomic and proteomic methods. Firstly, I would like to thank Dr. Catherine Clelland for her invaluable help in editing this volume. We would like to thank each of the authors who have contributed their outstanding work. We would also like to thank Dr. Abel Lajtha and Ms. Kristine Immediato for their contributions during the completion of this volume. Finally, we would like to dedicate this volume to our wonderful daughter Ayrleigh Clelland. New York, NY 10016

James D. Clelland

Contents

Part I Development 1

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The Genomics of Turner Syndrome and Sex-Biased Neuropsychiatric Disorders ..................................................................... Phoebe M.Y. Lynn, Evangelia Stergiakouli, and William Davies Mental Retardation and Human Chromosome 21 Gene Overdosage: From Functional Genomics and Molecular Mechanisms Towards Prevention and Treatment of the Neuropathogenesis of Down Syndrome ............. Mohammed Rachidi and Carmela Lopes Epigenetic Programming of Stress Responses and Trans-Generational Inheritance Through Natural Variations in Maternal Care: A Role for DNA Methylation in Experience-Dependent (Re)programming of Defensive Responses ............................................................................. Ian C.G. Weaver

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Prenatal Viral Infection in Mouse: An Animal Model of Schizophrenia ........................................................................................ 113 S. Hossein Fatemi and Timothy D. Folsom

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Proteomic Actions of Growth Hormone in the Nervous System .......... 137 Steve Harvey and Marie-Laure Baudet

Part II 6

Learning and Memory

Gene Expression and Signal Transduction Cascades Mediating Estrogen Effects on Memory ................................................. 161 Kristina K. Aenlle and Thomas C. Foster

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Contents

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Diagnostic Genome Profiling in Mental Retardation .......................... 177 David A. Koolen, Joris A. Veltman, and Bert B.A. de Vries

8

Genomic Imprinting and Sexual Experience-Dependent Learning in the Mouse ............................................................................ 195 William T. Swaney and Eric B. Keverne

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Proteomic Analysis of the Postsynaptic Density................................... 227 Ayse Dosemeci

Part III

Behavior

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Functional Genomic Dissection of Speech and Language Disorders ................................................................................ 253 Sonja C. Vernes and Simon E. Fisher

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Studying Human Circadian Behaviour Using Peripheral Cells ....................................................................................... 279 Lucia Pagani, Anne Eckert, and Steven A. Brown

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Genome-Wide Expression Profiles of Amygdala and Hippocampus in Mice After Fear Conditioning ........................... 303 Zheng Zhao and Yinghe Hu

Part IV Psychiatric Disorders 13

Genetic Studies of Schizophrenia .......................................................... 333 Brien Riley

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Proteomics of the Anterior Cingulate Cortex in Schizophrenia. ..................................................................................... 381 Danielle Clark, Irina Dedova, and Izuru Matsumoto

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Proteome Effects of Antidepressant Medications ................................ 399 Lucia Carboni, Chiara Piubelli, and Enrico Domenici

Part V

Neurological Disorders

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MicroRNAs in Neurodegenerative Disorders ....................................... 445 Catherine L. Clelland and James D. Clelland

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Specific and Surrogate Cerebrospinal Fluid Markers in Creutzfeldt–Jakob Disease ................................................................. 455 Gianluigi Zanusso, Michele Fiorini, Pier Giorgio Righetti, and Salvatore Monaco

Contents

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Genome-Wide Expression Studies in Autism-Spectrum Disorders: Moving from Neurodevelopment to Neuroimmunology...................... 469 Roberto Sacco, Antonio M. Persico, Krassimira A. Garbett, and Károly Mirnics

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Protein Expression Profile of Alzheimer’s Disease Mouse Model Generated by Difference Gel Electrophoresis (DIGE) Approach .................................................................................... 489 Daria Sizova

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Proteomic Analysis of CNS Injury and Recovery ................................ 511 Günther K.H. Zupanc and Marianne M. Zupanc

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MALDI Imaging of Formalin-Fixed Paraffin-Embedded Tissues: Application to Model Animals of Parkinson Disease for Biomarker Hunting ............................................................. 537 Isabelle Fournier, Julien Franck, Céline Meriaux, and Michel Salzet

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Comparative Proteomic Analysis as a Method to Investigate Inflammatory and Neuropathic Pain .................................................... 557 Ellen Niederberger

Index ................................................................................................................. 583

Contributors

Kristina K. Aenlle Department of Neuroscience, McKnight Brain Institute, University of Florida, 100244, Gainesville, FL 32610-0244, USA Marie-Laure Baudet Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge CB2 3D4, UK Steven A. Brown Chronobiology and Sleep Research Group, Institut für Pharmakologie und Toxikologie, Medizinische Fakultät, Universität Zürich, Winterthurerstrasse 190, CH-8057 Zürich, Switzerland Lucia Carboni Neurosciences Centre of Excellence for Drug Discovery, GlaxoSmithKline, 37135, Verona, Italy Danielle Clark Discipline of Pathology, The University of Sydney, NSW 2006, Australia James D. Clelland Movement Disorders and Molecular Psychiatry, Nathan S. Kline Institute for Psychiatric Research, 140 Old Orangeburg Road, Orangeburg, NY 10962, USA Department of Psychiatry, New York University School of Medicine, Langone Medical Center, 550 First Avenue, New York, NY 10016, USA Catherine L. Clelland Department of Pathology and Cell Biology and Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032, USA William Davies Behavioural Genetics Group, Department of Psychological Medicine, School of Medicine and School of Psychology, MRC Centre for Neuropsychiatric Genetics and Genomics, University of Cardiff, Cardiff, UK xi

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Contributors

Irina Dedova Schizophrenia Research Institute, 384 Victoria Street, Darlinghurst, NSW 2010, Australia; School of Biomedical and Health Sciences, University of Western Sydney, NSW 1797, Australia Enrico Domenici Neurosciences Centre of Excellence for Drug Discovery, GlaxoSmithKline, 37135 Verona, Italy Ayse Dosemeci Laboratory of Neurobiology, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892, USA Anne Eckert Psychiatric University Clinic, Basel, Switzerland S. Hossein Fatemi Department of Psychiatry, Division of Neuroscience Research, University of Minnesota, Medical School, MMC 392, 420 Delaware Street S.E, Minneapolis, MN 55455, USA; Departments of Pharmacology and Neuroscience, University of Minnesota Medical School, Minneapolis, MN 55455, USA; Department of Neuroscience, University of Minnesota Medical School, Minneapolis, MN 55455, USA Michele Fiorini Department of Neurological and Visual Sciences, Section of Clinical Neurology, University of Verona, P.le L.A. Scuro, 10, 37134 Verona, Italy Simon E. Fisher Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; Language and Genetics Department, Max Planck Institute for Psycholinguistics, 6525 XD, Nijmegen, The Netherlands Timothy D. Folsom Department of Psychiatry, Division of Neuroscience Research, University of Minnesota, Medical School, MMC 392, 420 Delaware Street S.E, Minneapolis, MN 55455, USA Thomas C. Foster Department of Neuroscience, McKnight Brain Institute, University of Florida, 100244, Gainesville, FL 32610-0244, USA Isabelle Fournier Laboratoire de Neuroimmunologie et Neurochimie Evolutives, FRE CNRS 3249, MALDI Imaging Team, Université Lille Nord de France, Université de Lille1, Bâtiment SN3, 1er étage, 59655 Villeneuve d’Ascq Cedex, France

Contributors

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Julien Franck Laboratoire de Neuroimmunologie et Neurochimie Evolutives, FRE CNRS 3249, MALDI Imaging Team, Université Lille Nord de France, Université de Lille1, Bâtiment SN3, 1er étage, 59655 Villeneuve d’Ascq Cedex, France Krassimira A. Garbett Department of Psychiatry, Vanderbilt University, Nashville, TN 37203, USA Steve Harvey Department of Physiology, University of Alberta, 7-41 Medical Sciences Building, Edmonton, Alberta T6G 2H7, Canada Yinghe Hu Key Laboratory of Brain Functional Genomics, MOE & STCSM, Shanghai Institute of Brain Functional Genomics, East China Normal University, 3663 Zhongshan Road (N), Shanghai, 200062, China Eric B. Keverne Sub-Department of Animal Behaviour, University of Cambridge, High Street, Madingley, Cambridge CB23 8AA, UK David A. Koolen Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands Carmela Lopes University of French Polynesia, Tahiti, French Polynesia Phoebe M.Y. Lynn Behavioural Genetics Group, Department of Psychological Medicine, School of Medicine and School of Psychology, University of Cardiff, Cardiff, UK Izuru Matsumoto Discipline of Pathology, The University of Sydney, NSW 2006, Australia Schizophrenia Research Institute, 384 Victoria Street, Darlinghurst, NSW 2010, Australia Céline Meriaux Laboratoire de Neuroimmunologie et Neurochimie Evolutives, FRE CNRS 3249, MALDI Imaging Team, Université Lille Nord de France, Université de Lille1, Bâtiment SN3, 1er étage, 59655 Villeneuve d’Ascq Cedex, France Károly Mirnics Department of Psychiatry, Vanderbilt University, 8130A MRB III, 465 21st Avenue South, Nashville, TN 37203, USA Salvatore Monaco Department of Neurological and Visual Sciences, Section of Clinical Neurology, University of Verona, P.le L.A. Scuro, 10, 37134 Verona, Italy

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Contributors

Ellen Niederberger Pharmazentrum frankfurt/ZAFES, Institut für Klinische Pharmakologie, Klinikum der Johann Wolfgang Goethe-Universität Frankfurt, Theodor Stern Kai 7, 60590 Frankfurt am Main, Germany Lucia Pagani Psychiatric University Clinic, Basel, Switzerland Antonio M. Persico Laboratory of Molecular Psychiatry and Neurogenetics, University “Campus Bio-Medico”, Via Alvaro del Portillo 21, 00128 Rome, Italy Chiara Piubelli Neurosciences Centre of Excellence for Drug Discovery, GlaxoSmithKline, 37135 Verona, Italy Mohammed Rachidi EA 3508, Laboratory of Genetic Dysregulation Models: Trisomy 21 and Hyperhomocysteinemia, University of Paris 7-Denis Diderot, Tour 54, E2-54-53, Case 7104, 2 Place Jussieu, Paris 75251, France Pier Giorgio Righetti Department of Chemistry, Materials and Chemical Engineering, Polytechnic of Milano, Milano 20131, Italy Brien Riley Departments of Psychiatry and Human & Molecular Genetics, and Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA Roberto Sacco Laboratory of Molecular Psychiatry and Neurogenetics, University “Campus Bio-Medico”, Rome, Italy Department of Experimental Neurosciences, I.R.C.C.S. “Fondazione Santa Lucia”, Rome, Italy Michel Salzet Laboratoire de Neuroimmunologie et Neurochimie Evolutives, FRE CNRS 3249, MALDI Imaging Team, Université Lille Nord de France, Université de Lille1, Bâtiment SN3, 1er étage, 59655 Villeneuve d’Ascq Cedex, France Daria Sizova Department of Genetics, University of Pennsylvania School of Medicine, Clinical Research Building, Room 755, 415 Curie Boulevard, Philadelphia, PA 19104-6149, USA Evangelia Stergiakouli Department of Psychological Medicine, School of Medicine, MRC Centre for Neuropsychiatric Genetics and Genomics, University of Cardiff, Cardiff, UK

Contributors

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William T. Swaney Behavioural Biology and Helmholtz Institute, Utrecht University, 3508 TB, Utrecht, The Netherlands Joris A. Veltman Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands Sonja C. Vernes Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK Bert B.A. de Vries Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, P.O. Box 9101, 6500 HB Nijmegen, The Netherlands Ian C.G. Weaver The Krembil Family Epigenetics Laboratory, Centre for Addiction and Mental Health (CAMH), 250 College Street, Toronto, ON, Canada M5T 1R8 Gianluigi Zanusso Department of Neurological and Visual Sciences, Section of Clinical Neurology, University of Verona, P.le L.A. Scuro, 10, 37134 Verona, Italy Zheng Zhao Key Laboratory of Brain Functional Genomics, MOE & STCSM, Shanghai Institute of Brain Functional Genomics, East China Normal University, 3663 Zhongshan Road (N), Shanghai 200062, China Günther K.H. Zupanc Department of Biology, Northeastern University, 134 Mugar Life Sciences, 360 Huntington Avenue, Boston, MA 02115, USA Marianne M. Zupanc School of Engineering and Science, Jacobs University Bremen, Campus Ring 1, 28759 Bremen, Germany

Part I

Development

The Genomics of Turner Syndrome and Sex-Biased Neuropsychiatric Disorders Phoebe M.Y. Lynn, Evangelia Stergiakouli, and William Davies

Abstract Turner Syndrome (TS) is a developmental disorder caused by the absence of all, or part, of an X chromosome. Subjects with TS exhibit a welldefined neurocognitive profile characterised by deficits in aspects of memory, attention and social functioning. In this chapter, we focus on recent work analysing the genomic underpinnings of these cognitive endophenotypes. Through studying TS, we are likely to gain insights into the neural processes impacted upon by X-linked genes. As males and females differ with respect to their complements of X-linked genes, work on TS may provide clues as to the genetic basis of sexspecific vulnerability to certain neuropsychiatric disorders. Keywords ADHD฀•฀Amygdala฀•฀Attention฀•฀Autism฀•฀Behaviour฀•฀Brain฀•฀Emotion฀ recognition฀•฀Genomic฀imprinting฀•฀X฀chromosome฀•฀X-inactivation฀•฀X-monosomy

1

Turner Syndrome

Turner Syndrome (TS) is a chromosomal disorder affecting approximately 1 in 1,800–2,500 live female births (Rovet, 2004). Interestingly, approximately 99% of affected foetuses do not reach term (Sybert & McCauley, 2004), but those that do survive to birth show a comparatively mild phenotype. TS is caused by complete or partial฀X-monosomy฀(Nijhuis-van฀der฀Sanden,฀Eling,฀&฀Otten,฀2003). Approximately 50% of TS individuals exhibit complete loss of one X chromosome (karyotype 45,X), whilst the remainder comprise of females with cryptic mosaicism (in which a proportion of cells, including those in the brain, can have additional sex-linked sequences besides the single X chromosome) or structural sex chromosome abnormalities (Sagi et al., 2006). The single intact X chromosome is inherited W. Davies (*) Behavioural฀Genetics฀Group,฀Department฀of฀Psychological฀Medicine,฀School฀of฀Medicine฀ and฀School฀of฀Psychology,฀MRC฀Centre฀for฀Neuropsychiatric฀Genetics฀and฀Genomics, University of Cardiff, Cardiff, UK e-mail: [email protected]

J.D. Clelland (ed.), Genomics, Proteomics, and the Nervous System, Advances฀in฀Neurobiology฀2,฀DOI฀10.1007/978-1-4419-7197-5_1,฀ ©฀Springer฀Science+Business฀Media,฀LLC฀2011

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P.M.Y.฀Lynn฀et฀al.

maternally฀in฀around฀70%฀of฀TS฀individuals฀(45,Xm), and the remainder possess an X chromosome of paternal origin (45,Xp) (Uematsu et al., 2002). Subjects affected by TS display characteristic physiological, neuropsychological and฀neuroanatomical฀features.฀Physiological฀deficits฀linked฀to฀the฀syndrome฀include฀ short stature, ovarian dysgenesis, webbed neck, oedema, cardiovascular defects, renal malformations and sensorineural hearing loss (Hamelin, Anglin, Quigley, & Deal, 2006). Neuropsychological abnormalities associated with TS include deficits in attentional function (subjects show poor performance on attentionally demanding tasks (Romans, Stefanatos, Roeltgenm, Kushner, & Ross, 1998; Ross et al., 2002; Temple, Carney, & Mullarkey, 1996) and tend to be readily distracted in real life situations (Rovet & Ireland, 1994), in visuospatial skills (Murphy et al., 1997; Ross, Roeltgen, & Zinn, 2006),฀ in฀ some฀ forms฀ of฀ memory฀ (Bishop฀ et฀ al.,฀ 2000; Buchanan,฀Pavlovic,฀&฀Rovet,฀1998; Haberecht et al., 2001), in recognising facial emotions฀(notably฀fear฀and฀anger;฀Lawrence,฀Kuntsi,฀Coleman,฀Campbell,฀&฀Skuse,฀ 2003; Weiss et al., 2007) and in arithmetic skills (Mazzocco, 1998). TS subjects may also demonstrate subtle motor function abnormalities (Nijhuis-van der Sanden et al., 2003; Rovet, 2004)฀ and฀ difficulties฀ in฀ aspects฀ of฀ social฀ cognition฀ (Lagrou฀ et al., 2006; McCauley, Feuillan, Kushner, & Ross, 2001; Schmidt et al., 2006; Skuse et al., 1997). The lack of X-linked material in TS also seems to confer enhanced vulnerability to disorders of social cognition, behavioural flexibility and attention such as autism, ADHD and schizophrenia (Donnelly et al., 2000;฀Prior,฀ Chue, & Tibbo, 2000; Russell et al., 2006). Neuroanatomical abnormalities have been found in parietal lobe, amygdala, orbitofrontal฀cortex฀and฀superior฀temporal฀gyrus฀(Good฀et฀al.,฀2003; Kesler et al., 2003;฀Lawrence฀et฀al.,฀2003), which have been consistently linked to some of the neuropsychological characteristics associated with the TS phenotype. Visuospatial impairments have been linked to abnormalities in the parietal lobe; reduced activation in the parietal-occipital regions during a visuospatially demanding task has been shown in TS subjects (Haberecht et al., 2001). Significantly larger grey matter has been found in the amygdala and orbitofrontal cortex in TS individuals when compared to normal controls, and it has been suggested that the aberrant connections between these two structures contribute to the deficits in affective processing seen฀in฀TS฀subjects฀(Good฀et฀al.,฀2003; Kesler et al., 2004). There is significantly greater right superior temporal gyrus volume in TS individuals compared to controls฀(along฀with฀a฀parent-of-origin฀effect฀(POE);฀see฀below);฀the฀superior฀temporal฀ gyrus is important in language processes, and therefore this difference between TS and control subjects might explain the preserved or superior verbal skills observed in TS females (Kesler et al., 2003; Skuse et al., 1997).฀Lastly,฀aberrant฀frontal฀cortical฀ function has been shown in TS subjects during a visuospatial working memory task; anomalies in the frontal region could feasibly contribute to the impairments in attention, impulsivity and social functions in TS (Haberecht et al., 2001). Whilst TS arises from the lack of an entire X chromosome (or part thereof), its presentation can also depend upon the parental origin of the remaining intact X chromosome, such that the appearance of 45,Xp and 45,Xm฀subjects฀differs.฀POE฀ on physiological parameters (notably neck webbing, cardiovascular defects and

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sensorineural hearing loss) have been described in TS (Chu et al., 1994; Hamelin et al., 2006),฀though฀their฀existence฀is฀somewhat฀controversial฀(Bondy฀et฀al.,฀2007; Mathur et al., 1991).฀POE฀have฀also฀been฀noted฀with฀respect฀to฀the฀neuropsychology฀ and฀ neuroanatomy฀ of฀ TS.฀ Using฀ image฀ and฀ story฀ recall฀ tasks,฀ Bishop฀ et฀ al.฀ (2000) have shown that visuospatial working memory is impaired in 45,Xp subjects relative to 45,Xm (and 46,XX) subjects, while the 45,Xm group exhibited poorer verbal material retention than the other two groups. The parental origin of the X chromosome also appears to influence social cognitive functioning, notably the inhibition of a prepotent response (Skuse et al., 1997). Specifically, 45,Xm subjects perform more poorly than 45,Xp (and 46,XX) subjects on a task taxing behavioural inhibition and demonstrate enhanced vulnerability to autism, the archetypal disorder฀ of฀ social฀ cognition฀ (Baron-Cohen,฀ Knickmeyer,฀ &฀ Belmonte,฀ 2005). Using magnetic resonance imaging (MRI) to examine neuroanatomy in vivo, X-linked POE฀have฀been฀found฀in฀the฀superior฀temporal฀gyrus฀(Kesler฀et฀al.,฀2003), caudate nuclei, thalamus, and the temporal lobe (Cutter et al., 2006); in 45,Xm subjects, bilateral superior temporal gyrus volume is significantly greater than that in 45,Xp and 46,XX subjects, whereas the bilateral caudate nuclei and thalamus grey matter and the temporal lobe white matter have been shown to be larger in 45,Xp than 45,Xm฀individuals.฀Furthermore,฀there฀is฀evidence฀for฀an฀X-linked฀POE฀in฀the฀hippocampus whereby 45,Xm have a larger right hippocampal volume than 45,Xp subjects, which might explain the differential performance on visuospatial memory performance between these two groups (Cutter et al., 2006; Moscovitch, Nadel, Winocur,฀Gilboa,฀&฀Rosenbaum,฀2006).฀The฀existence฀of฀POE฀on฀TS฀neurocognitive฀measures฀and฀neuroanatomy,฀as฀for฀the฀POE฀on฀physiology,฀is฀disputed,฀and฀it฀ is฀ likely฀ that฀ POE,฀ should฀ they฀ exist,฀ will฀ be฀ relatively฀ subtle฀ (Skuse,฀ 2005). However, that is not to say that these effects will be unimportant!

1.1

Genetic Mechanisms Underlying TS Endophenotypes

The characteristic features associated with TS outlined above presumably arise due to haploinsufficiency for the products of one (or more) X-linked genes that normally escape X-inactivation (the epigenetic process by which, in the somatic cells of 46,XX females, one of the two X chromosomes is randomly inactivated). Between฀15฀and฀20%฀of฀human฀X-linked฀genes฀are฀thought฀to฀escape฀X-inactivation฀ and hence are expressed from both X chromosomes in 46,XX females (Carrel & Willard, 2005); these genes will only be expressed from the single X chromosome in TS subjects and thus represent candidates for TS endophenotypes. However, it is important to be aware that data on escape from X-inactivation have generally been obtained from cell culture studies and confirmed in a limited number of tissues. The exact degree of escape from X-inactivation for a gene (and therefore its relevance to the TS phenotype) is likely to vary according to the precise tissue examined, and according฀to฀the฀time฀point฀at฀which฀it฀is฀assayed฀(Bittel฀et฀al.,฀2008; Carrel, Hunt, & Willard, 1996; Carrel & Willard, 2005).

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The฀ X-linked฀ POE฀ could฀ arise฀ due฀ to฀ the฀ differential฀ expansion฀ of฀ repeat฀ sequences in parental germlines, such that 45,Xp and 45,Xm subjects possess different numbers of repeats in certain key genes (e.g. FMR1) , which may in turn influence expression (Weinhäusel & Haas, 2001).฀Alternatively,฀the฀POE฀could฀arise฀due฀ to the action of one or more so-called X-linked imprinted genes (Davies, Isles, Burgoyne,฀&฀Wilkinson,฀2006). Imprinted genes, in contrast to most mammalian genes, are inherited in duplicate, but as a consequence of differential epigenetic marking, are only expressed from one allele. For approximately half of all imprinted genes, it is the paternally inherited allele that is preferentially expressed, whilst for the remainder the maternally inherited allele is preferentially expressed. Recent evidence (mainly from mouse models) has implicated these genes as key players in neurodevelopmental and behavioural processes (Davies, Isles, Humby, & Wilkinson, 2006; Davies et al., 2005; Wilkinson, Davies, & Isles, 2007). As 45,Xp subjects inherit a single X chromosome from their father, their brain and behavioural functioning can only be influenced by paternally expressed X-linked genes. In contrast, the brain and behaviour of 45,Xm subjects can only be modulated by the action of maternally expressed X-linked genes. Skuse et al. (1997) have postulated the existence of a paternally expressed gene that acts to enhance social cognitive function, to explain the superior performance of 45,Xp subjects relative to 45,Xm subjects in this domain.

1.2

Problems with Investigating the Genomics of TS

Recently, there has been substantial interest in identifying and beginning to characterise candidate genes underlying TS endophenotypes. Through finding such genes, we are likely to gain important insights into the molecular and neurobiological basis of cognitive constructs such as visuospatial memory, attention and face recognition within the normal population. However, the genomics of TS have been difficult to investigate for a variety of reasons. Firstly, as the disorder does not markedly reduce life expectancy there is a lack of post-mortem tissues available for analysis. Moreover, gene expression in tissues that are available (both post-mortem and from living subjects) may be influenced by the presence of cryptic mosaicism, i.e. the presence of additional sex-linked gene sequences (both฀X฀and฀Y)฀in฀a฀subset฀of฀cells฀within฀the฀population฀(Henn฀&฀Zang,฀1997), or by skewed X-inactivation (Zinn et al., 2007). Hence, this may obscure the precise relationship between the action of a gene and its phenotypic manifestation. Finally, to alleviate the short stature and ovarian dysfunction endophenotypes, TS subjects are commonly treated with growth hormone and oestrogen supplements,฀respectively.฀Both฀treatments฀could฀potentially฀influence฀brain฀and฀ behavioural฀functioning฀(Falleti,฀Maruff,฀Burman,฀&฀Harris,฀2006; Hamelin et al., 2006; Ross et al., 2003) and are likely to elicit significant effects on gene expression. Again, these treatments may make the downstream effects of a specific gene difficult to ascertain.

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The problems associated with investigating the genomics of TS may be overcome฀to฀some฀extent฀through฀investigations฀in฀mouse฀models.฀The฀39,XO฀mouse,฀ which like TS subjects possesses just one X chromosome, appears to recapitulate some฀of฀the฀key฀behavioural฀features฀of฀the฀TS฀profile฀(Lynn฀&฀Davies,฀2007). This model is amenable to large-scale neurobiological and behavioural analysis, is unconfounded by mosaicism, and the mice can have a well-controlled behavioural and฀treatment฀history.฀Limitations฀of฀the฀model฀include฀difficulties฀associated฀with฀ assaying complex neuropsychological phenotypes, the fact that some phenotypes sensitive to X-monosomy in man may not be in mouse (either due to more extensive X-inactivation in mice, or to orthologues of X-linked human genes being autosomal in mice) and the fact that some murine X-linked genes do not have human orthologues.฀Nevertheless,฀despite฀these฀caveats,฀the฀39,XO฀mouse฀model฀has฀provided฀ some intriguing clues as to possible TS candidate genes (see below).

1.3

Identification of Candidate Genes for TS Endophenotypes

1.3.1

Human Studies

To date, the main strategy for identifying X-linked regions containing TS candidate genes has been deletion mapping. In this approach, subjects possessing an intact X chromosome and a second X chromosome with a deletion (generally of the terminal region of the short arm of the X chromosome) are compared to 46,XX controls. In theory, a TS endophenotype will be present in subjects lacking the underlying gene(s) on their deleted chromosome, but not in subjects whose deletion does not encompass the gene(s). In Skuse et al. (1997), 45,XXp− subjects (possessing an intact maternally inherited X chromosome and a paternally inherited X chromosome with a large terminal deletion of the short arm) resembled 46,XX females in terms of their social cognitive profile. This implied that the paternally expressed gene that they postulated may be influencing social cognitive function must either reside close to the centromere on the short arm of the X or on the long arm. As the deleted chromosome was preferentially inactivated in 46,XXp− subjects, this result further implied that the gene escaped X-inactivation. Using฀ a฀ combination฀ of฀ deletion฀ mapping฀ and฀ structural฀ neuroimaging,฀ Good฀ et al. (2003) attempted to localise candidate genes underlying the impaired fear and anger recognition seen in TS females and to determine their effects on neuroanatomy. In this study, subjects with deletion of a critical region of Xp11.3 (of paternal or maternal origin) were shown to have impaired fear recognition and significantly increased grey matter volumes bilaterally in the amygdala and orbitofrontal cortex relative to 46,XX controls. This small region, less than 5 Mb in size, contains 21 confirmed genes, of which there is evidence that 5 may escape X-inactivation in man. The authors thus hypothesised that haploinsufficiency for one or more of these genes could cause aberrant development (and therefore connectivity) of the orbitofrontal cortex-amygdala axis and subsequent impairments in emotion recognition.

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Initially, the prime suspects for the effects described above were the MAOA and MAOB฀ genes฀ encoding฀ the฀ monoamine฀ oxidases฀ A฀ and฀ B,฀ respectively.฀ These฀ enzymes are highly expressed in the amygdala, modulate a wide variety of fundamental neurochemical processes, and can influence neurodevelopment (Vitalis et al., 2002). Moreover, MAOB seems to escape X-inactivation (as indexed by reduced activity฀in฀TS฀platelets฀relative฀to฀those฀of฀46,XX฀subjects฀(Lawrence฀et฀al.,฀2007) though MAOA฀appears฀to฀be฀normally฀X-inactivated฀(Benjamin,฀Van฀Bakel,฀&฀Craig,฀ 2000;฀Nordquist฀&฀Oreland,฀2006). Despite initial understandable interest in the MAOA and MAOB฀genes,฀SNP฀mapping of the critical region suggested no association between markers close to, and within, these genes and impaired fear recognition in a TS sample. Instead, convincing and reproducible association was found between a second gene within the critical 5 Mb region, EFHC2, and fear recognition (Weiss et al., 2007). EFHC2 is a novel brain-expressed transcript spanning 195 kb, and its predicted protein structure contains฀an฀EF-hand฀domain฀which฀is฀generally฀found฀in฀calcium-binding฀proteins.฀ The protein product of EFHC2฀ has฀ 41.6%฀ amino฀ acid฀ identity฀ to฀ EFHC1฀ (Gu,฀ Sander,฀ Heils,฀ Lenzen,฀ &฀ Steinlein,฀ 2005), a protein involved in neural pruning (Suzuki et al., 2004).฀ Assuming฀ that฀ the฀ function฀ of฀ EFHC2฀ is฀ similar฀ to฀ that฀ of฀ EFHC1,฀one฀may฀speculate฀that฀its฀haploinsufficiency฀could฀underlie฀the฀increased฀ amygdala size observed in TS females. Recently, a second study has failed to find any evidence for association between EFHC2 and fear recognition in a new TS cohort (Zinn, Kushner, & Ross, 2008). This inability to replicate the first study could be due to population stratification considerations. However, given the potential importance of the initial findings to TS, and to behavioural genetics in general, it is clear that further research on the potential function of EFHC2 variants is needed. A second region on the distal short arm of the X chromosome has been implicated by deletion mapping in the overall neurocognitive profile of TS (Ross, Roeltgen, Kushner, Wei, & Zinn, 2000; Zinn et al., 2007). This region of Xp22.3, which encompasses around 8.3 Mb, contains 31 annotated genes, including the short stature gene SHOX. SHOX, which encodes a homeobox protein, has previously been implicated in the TS physical phenotype (Ross et al., 2001), but a lack of correlation between the TS neurocognitive profile and height appears to indicate that its haploinsufficiency is unlikely to play a prominent role in the TS brain and behavioural phenotype. Alternative candidate genes for the characteristic TS cognitive profile include NLGN4X and STS; both of these genes are known to escape X-inactivation in man (Carrel & Willard, 2005;฀Yen฀et฀al.,฀1988). NLGN4X encodes฀a฀member฀of฀the฀synaptic฀membrane-bound฀neuroligin฀family฀(Bolliger,฀ Frei,฀Winterhalter,฀&฀Gloor,฀2001), and has been shown to be mutated in cases of autism and mental retardation (Jamain et al., 2003;฀Laumonnier฀et฀al.,฀2004). STS encodes฀steroid฀sulfatase,฀an฀enzymic฀modulator฀of฀neurosteroid฀activity฀(Yen฀et฀al.,฀ 1988). Male subjects with microdeletions encompassing the STS gene can exhibit mental฀ retardation฀ and฀ ADHD฀ (Boycott฀ et฀ al.,฀ 2003;฀ Lonardo฀ et฀ al.,฀ 2007). The NLGN4X and STS gene products will be haploinsufficient in TS subjects, rather than completely absent as in the aforementioned cases, therefore the resultant phenotypic฀ consequences฀ will฀ presumably฀ be฀ more฀ subtle.฀ On฀ the฀ basis฀ of฀ the฀

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available human data, other genes within the Xp22.3 interval may be considered as contributors towards the TS neurocognitive profile. However, the absence of a syntenic region in rodents has precluded comprehensive functional analysis of these genes. Besides฀ potentially฀ being฀ involved฀ in฀ the฀ TS฀ neurocognitive฀ profile,฀ the฀ short฀ arm region Xp11.2-Xp22.3 has also been implicated in some physical TS phenotypes, namely: short stature, ovarian failure, high arched palate and possibly autoimmune thyroid disease (Ross et al., 2006; Zinn et al., 1998). Haploinsufficiency of the protein encoded by the pseudoautosomal gene SHOX appears to be partially responsible for the short stature phenotype in TS; it has been suggested that SHOX haploinsufficiency can account for about two-thirds of the height deficit displayed in TS females (Ross et al., 2001), while the rest of the variance could be explained by฀other฀putative฀height฀loci฀within฀Xp11.2-22.1฀proximal฀to฀PAR1฀and/or฀genetic฀ background (Zinn et al., 1998).฀Ovarian฀failure฀in฀TS฀might฀arise,฀in฀part฀at฀least,฀ from haploinsufficiency for the candidate gene ZFX at Xp21.2. Mutation of the mouse orthologue of this gene leads to growth retardation and a reduced number of germ฀cells฀(Luoh฀et฀al.,฀1997; Simpson & Rajkovic, 1999). Despite several years passing since the first indications that X-linked imprinted genes could contribute to the physical and cognitive aspects of the TS phenotype, still no candidate genes have been identified. Theoretically, X-linked imprinted genes could be identified by microarray comparison of gene expression in 45,Xp and 45,Xm tissues. The messenger RNA from paternally expressed X-linked genes should be present in the former tissue type but absent (or almost absent) from the latter, whilst the reverse would be true for messenger RNA from maternally expressed X-linked genes. The major problem with this approach is the lack of availability of suitable tissues (notably brain), as referred to previously. It is possible that comparing gene expression in surrogate tissues such as blood or skin may provide clues as to imprinted genes influencing brain฀function.฀Preliminary฀investigations฀in฀our฀laboratory฀comparing฀gene฀expression in 45,Xp and 45,Xm blood have so far failed to identify candidate X-linked imprinted฀ genes.฀ Other฀ strategies฀ for฀ identifying฀ novel฀ X-linked฀ imprinted฀ genes฀ may include ascertainment on the basis of differential epigenetic marking, e.g. methylation (Smith & Kelsey, 2001) or on the basis of bioinformatic signatures characteristic of imprinted genes. However, the fact that the sequence content of the X chromosome differs markedly from that of the autosomes (Davies, Isles, & Burgoyne,฀ et฀ al.,฀ 2006) means that proven bioinformatic methods for detecting autosomal฀imprinting฀in฀humans฀(Luedi฀et฀al.,฀2007) may be of limited utility when investigating this chromosome.

1.3.2

Mouse Studies

In฀mice,฀only฀seven฀genes฀are฀known฀to฀escape฀X-inactivation฀(Brown฀&฀Greally,฀ 2003). Thus, identifying candidate genes (and molecular pathways) underlying X-monosomy effects in mice is a much more straightforward procedure than in man.

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As six of these genes also escape X-inactivation in man, their human orthologues may be examined for effects on analogous functions. Several physical phenotypes have now been shown to be sensitive to X-monosomy in mice, including pre- and postnatal฀growth฀(Burgoyne,฀Evans,฀&฀Holland,฀1983;฀Burgoyne,฀Ojarikre,฀&฀Turner฀ 2002),฀oocyte฀loss฀(Burgoyne฀&฀Baker,฀1985) and inner ear development (Hultcrantz, Stenberg, Fransson, & Canlon, 2000). A number of brain and behavioural measures have฀also฀recently฀been฀shown฀to฀be฀sensitive฀to฀X-monosomy฀in฀the฀mouse.฀39,XO฀ mice, like TS subjects, display heightened anxiety under aversive conditions (Isles, Davies,฀Burrmann,฀Burgoyne,฀&฀Wilkinson,฀2004). In the same study, the authors demonstrated฀reduced฀expression฀of฀the฀GABAA receptor subunit genes Gabra1 and Gabrg2,฀and฀increased฀expression฀of฀the฀GABAA receptor subunit gene Gabra3 in 39,XO฀brain฀relative฀to฀40,XX฀brain.฀However,฀the฀GABAergic฀perturbations฀evident฀ in฀ 39,XO฀ mice฀ did฀ not฀ seem฀ to฀ contribute฀ to฀ the฀ fear฀ reactivity฀ phenotype.฀ Instead, the authors proposed the X-escapee Utx, a gene possessing a human orthologue฀ at฀ Xp11.2฀ (Greenfield฀ et฀ al.,฀ 1998), as a candidate for the observed X-monosomy฀ effects฀ on฀ behaviour.฀ Again฀ like฀ TS฀ subjects,฀ 39,XO฀ mice฀ display฀ impaired response accuracy on a behavioural task taxing attention; this deficit was not฀ apparent฀ in฀ 40,XY*X฀ mice฀ (effectively฀ 39,XO฀ mice฀ with฀ an฀ additional฀ small฀ chromosome,฀ Y*X)฀ implying฀ that฀ a฀ gene฀ on฀ Y*X could affect attention (Davies, Humby,฀Isles,฀Burgoyne,฀&฀Wilkinson,฀2007).฀Of฀the฀nine฀or฀so฀genes฀on฀Y*X, two were known to escape X-inactivation in mice: the pseudoautosomal gene Sts and Mid1,฀and฀could฀therefore฀be฀considered฀candidates฀for฀the฀X-monosomy฀effect.฀On฀ the basis of its expression pattern and previous knowledge of its protein product’s function, Sts was considered the better candidate for the attentional phenotype. Interestingly, Sts is the mouse orthologue of STS, a gene previously mentioned as a positional candidate for the neurocognitive profile of TS. It is therefore tempting to speculate that having just one copy of STS (and therefore being haploinsufficient for the steroid sulfatase enzyme) in TS specifically contributes to the deficits in attentional฀ functioning.฀ Moreover,฀ mouse฀ work฀ has฀ hinted฀ that฀ the฀ GABAergic฀ abnormalities฀ seen฀ in฀ the฀ 39,XO฀ mice฀ may฀ be฀ dependent฀ upon฀ Sts฀ levels฀ (Isles฀ et฀ al.,฀ 2004). Current work in our laboratory aims to determine the extent to which steroid sulfatase฀may฀contribute฀to฀attentional฀phenotypes฀via฀GABAergic฀mechanisms฀in฀ man and mouse. In order to discover candidate genes underpinning the enlarged amygdala phenotype (and ensuing neurobehavioural abnormalities) associated with TS,฀Raefski,฀Carone,฀Kaur,฀Krueger,฀and฀O’Neill฀(2007) compared gene expression in฀the฀amygdalae฀of฀late-stage฀39,XO฀and฀40,XX฀embryos.฀This฀study฀revealed฀significant expression differences in 161 genes between the two groups, of which several฀were฀known฀to฀be฀involved฀in฀Wnt฀signalling฀cascades.฀One฀such฀X-linked฀gene,฀ Gpc3,฀was฀downregulated฀approximately฀twofold฀in฀39,XO฀brain.฀Gpc3 encodes a glypican protein, the downregulation of which was hypothesised to lead to activation of the canonical Wnt pathway and subsequent increased cell proliferation and amygdala size. The human orthologue of Gpc3 is located at Xq26, and is apparently subject to X-inactivation (Huber et al., 1999), hence it appears unlikely to be the causative gene for the X-monosomy effect on amygdala size in TS. It may, however, be a downstream effector. Whatever the precise contributions of individual genes,

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it seems that investigating the expression of genes involved in Wnt signalling may shed light on some of the neuroanatomical findings in TS. By฀ using฀ two฀ separate฀ crosses,฀ 39,XO฀ mice฀ may฀ be฀ generated฀ whose฀ single฀ X฀is฀of฀paternal฀or฀maternal฀origin฀(Burgoyne฀&฀Evans,฀2000;฀Evans฀&฀Phillips,฀ 1975). Davies et al. (2005) compared these two groups of mice on a reversal learning task designed to assay behavioural flexibility, i.e. the psychological construct that had been shown by Skuse et al. (1997) to be dependent upon parental origin of the X chromosome. The mouse work accurately recapitulated the human data, in that the mice inheriting their single X chromosome maternally (39,XmO)฀ displayed฀ impaired฀ behavioural฀ flexibility฀ relative฀ to฀ 39,XpO฀ (and฀ 40,XX) subjects, much like 45,Xm TS subjects did relative to 45,Xp subjects. Follow-up studies comparing gene expression in 39,XpO฀ and฀ 39,XmO฀ brains฀ to฀ find possible X-linked imprinted genes underlying this behavioural finding identified Xlr3b as a novel maternally expressed imprinted gene (Davies et al., 2005; Raefski฀&฀O’Neill,฀2005). The exact role, if any, which this gene and its product may play in murine brain development, brain function and cognition remain to be determined. The closest human orthologue to Xlr3b is FAM9B, located within the critical region for the TS neurocognitive profile on Xp22.3. This gene is known to฀ be฀ highly฀ expressed฀ in฀ testis฀ (Martinez-Garay฀ et฀ al.,฀ 2002), but does not appear to be expressed in embryonic brain or in adult sensorimotor cortex (unpublished results). Hence, despite its promising location, it seems a weak a priori candidate for the TS cognitive phenotype.

2

The Genomics of Sex-Biased Neuropsychiatric Disorders

Even฀taking฀into฀account฀possible฀ascertainment฀biases,฀most฀of฀the฀common฀neuropsychiatric disorders exhibit a sex bias; this may be evident in terms of incidence, aetiology, underlying neural substrates or response to therapeutics (Cahill, 2006). Presumably,฀there฀is฀something฀about฀the฀brains฀of฀males฀that฀predisposes฀them฀to฀ developing autism spectrum disorders and ADHD (between 4 and 10 times more prevalent in males), and something about the brains of females that predisposes them to developing disorders such as anorexia nervosa and unipolar depression (between 2 and 10 times more prevalent in females) (Holden, 2005). In the case of autism, this idea has been formalised in the “extreme male brain theory”, which posits that the core behavioural and neurological features of autism (notably the impaired empathising and enhanced systematising) represent extreme versions of typical฀male฀traits฀(Baron-Cohen฀et฀al.,฀2005). Neural differences between males and females must ultimately arise from the differential expression of sex-linked genes between the sexes. There are two dissociable routes through which sex-linked gene expression may affect sex-specific neurobiology: the first, and best studied, route is through influencing the development of the gonads (ovaries in females, testes in males). Steroid hormones secreted by the gonads (notably oestrogen and testosterone in different ratios according to

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the gonadal type) may then act to shape brain function, either by affecting neurodevelopment (organisational effects) or by affecting ongoing brain processes (activational effects). The second route is via direct effects in brain tissue. Interestingly, there seems to be an over-representation of genes influencing cognitive functioning on the sex chromosomes (the X chromosome in particular), exemplified by the fact that X-linked mutations are commonly found to cause mental retardation (Zechner et al., 2001). Hence, this second route of sexual differentiation of the brain may turn out to be at least as important, if not more so, than the first. There are a number of genetic mechanisms that may bring about sex-specific gene expression, and these have been reviewed elsewhere (Davies & Wilkinson, 2006).฀Genes฀that฀escape฀X-inactivation฀will฀generally฀be฀more฀highly฀expressed฀in฀ female than in male brain, though the fold difference in expression will depend upon the efficiency with which the gene escapes the silencing process. Moreover, some genes฀that฀escape฀X-inactivation฀have฀Y-linked฀homologues;฀these฀may,฀or฀may฀not,฀ encode functionally similar products and may, or may not, be expressed at equivalent levels. Hence, male-limited expression of such homologues is a second way in which sex-specific gene expression may be achieved. Vawter et al. (2004) showed by฀ microarray฀ analysis฀ that฀ five฀ Y-linked฀ homologues฀ of฀ X-inactivation฀ escapees฀ (UTY, USP9Y, SMCY, DBY and RPS4Y) were expressed between 2 and 128 times more highly in male than in female post-mortem brain. The same study revealed that levels of the X-inactivation mediating RNA XIST were approximately 14 times higher in female than male brain. X-linked imprinting may also give rise to sexually dimorphic gene expression as a consequence of the fact that females inherit two X chromosomes (one from their father and a second from their mother), whereas males inherit a single X chromosome,฀ invariably฀ from฀ their฀ mother฀ (Davies,฀ Isles,฀ &฀ Burgoyne,฀ et฀ al.,฀ 2006). Therefore, paternally expressed X-linked genes can only be expressed in female brain, whereas maternally expressed X-linked genes can be expressed more highly in male brain (provided they are subject to X-inactivation). A final mechanism that could potentially underpin sex-specific brain development฀is฀the฀expression฀of฀Y-linked฀genes฀with฀no฀X-linked฀counterparts;฀the฀paradigmatic example of such a gene is SRY. This gene encodes a transcription factor which acts to initiate a complex signalling cascade culminating in the development of the testes and testosterone secretion. Thus, it may influence sexual differentiation of the brain indirectly. SRY฀is฀also฀expressed฀throughout฀the฀brain฀(Mayer,฀Lahr,฀Swaab,฀ Pilgrim,฀&฀Reisert,฀1998), and data in rodents suggests that its protein might regulate tyrosine hydroxylase transcription to effect downstream changes in dopaminergic function (Dewing et al., 2006; Milsted et al., 2004). As dopaminergic dysregulation has been implicated in a number of neuropsychiatric disorders which are more prevalent in males (ranging from ADHD and schizophrenia to compulsive gambling and฀alcoholism;฀Blum฀et฀al.,฀2000; Holden, 2005; Staller & Faraone, 2007; Toda & Abi-Dargham, 2007)฀a฀role฀for฀this฀gene฀may฀be฀suspected.฀Ongoing฀work฀in฀our฀ laboratory is aiming to characterise the role of SRY฀ (and฀ other฀ Y-linked฀ brain฀ expressed฀genes)฀in฀rodent฀and฀human฀brain฀function.฀In฀man,฀Y฀chromosome฀variation is captured by using biallelic markers that can be combined to form stable

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l฀ineages฀ of฀ Y฀ chromosome,฀ the฀ so-called฀ haplogroups฀ (Jobling฀ &฀ Tyler-Smith,฀ 2003). Since SRY is a small gene with only one exon, it has limited variation. Thus, markers฀in฀the฀rest฀of฀the฀non-recombining฀region฀of฀Y฀chromosome฀are฀also฀used.฀ Theoretically,฀these฀Y฀chromosome฀variants฀can฀increase฀susceptibility฀to฀neurodevelopmental disorders through their interactions with brain-expressed genes on other chromosomes (such as TH฀encoding฀tyrosine฀hydroxlase)฀and/or฀with฀environmental฀ factors that are known to increase risk to neurodevelopmental disorders such as smoking exposure during pregnancy (Thapar et al., 2003) and birth complications (Thapar et al., 2005).฀Finally,฀Y฀chromosome฀variants฀could฀have฀an฀effect฀on฀cognitive function in the normal population and thus have a modifying effect on risk for neurodevelopmental disorders such as ADHD and schizophrenia. We hope that studying฀Y-linked฀genes฀will฀provide฀insights฀into฀whether฀Y฀chromosome฀variants฀ play an important role not only in male susceptibility to neurodevelopmental disorders but also in variability of cognitive function within the normal population.

3

Insights into Sex-Biased Neuropsychiatric Disorders from Turner Syndrome

Hemizygosity for X-linked genes (in males), and X-linked imprinting can contribute towards sexually dimorphic gene expression profiles. The effects of X-monosomy (effectively equivalent to hemizygosity) and X-linked imprinting on brain development, brain function and behaviour can both be readily ascertained in the “experiment of nature” that is Turner Syndrome (taking into account the caveats listed previously). Importantly, in TS, these effects are unconfounded by the presence of Y-linked฀ genes.฀ From฀ the฀ TS฀ data,฀ it฀ should฀ therefore฀ be฀ possible฀ to฀ generate฀ hypotheses about the genetic and neural substrates underlying sex differences in behaviour and in vulnerability to mental disorders. In general, on endophenotypes shown to be sensitive to X-monosomy (for example, emotion recognition, attention and amygdala size), we might expect hemizygous males to resemble TS subjects more than they resemble 46,XX females (assuming a lack of mitigating factors such as hormonal influences). The fact that males exhibit greater attentional difficulties relative to females, and are substantially more vulnerable to ADHD (Holden, 2005), suggests that hemizygosity for one or more X-linked genes may be responsible for this sex bias. Similarly, the fact that males exhibit larger amygdalae฀than฀females฀(Good฀et฀al.,฀2003) may be explained by their hemizygosity for one or more X-linked genes. The larger male amygdala may result from reduced neural pruning, and this may explain why males exhibit impaired discrimination of facial emotions (Thayer & Johnsen, 2000), and an enhanced vulnerability to autistic spectrum฀ disorders฀ in฀ which฀ emotion฀ recognition฀ processes฀ go฀ awry฀ (Boraston,฀ Blakemore,฀Chilvers,฀&฀Skuse,฀2007;฀Humphreys,฀Minshew,฀Leonard,฀&฀Behrmann,฀ 2007). As discussed previously, studies in TS (and in a TS mouse model) have proposed STS and EFHC2 as candidate genes for the attentional and emotion recognition phenotypes respectively. As STS฀ escapes฀ X-inactivation฀ in฀ females,฀ and฀ as฀ its฀ Y฀

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homologue฀ is฀ a฀ non-expressed฀ pseudogene฀ (Yen฀ et฀ al.,฀ 1988), we may expect its expression to be higher in female than in male brain. Indeed, this appears to be the case (unpublished results). Hence, we may hypothesise that the effective hemizygosity of STS in males predisposes them to developing ADHD (Davies et al., 2007). Currently, little is known about the EFHC2 gene. In mice, the gene appears to escape X-inactivation (unpublished results), and as it resides in a genomic region rich in X-escapees, the same is likely to be true in man. Moreover, the gene does not seem to฀have฀a฀functionally฀equivalent฀Y-linked฀homologue.฀Therefore,฀it฀is฀possible฀that฀ male hemizygosity for EFHC2 may lead to reduced neural pruning in the amygdala, thereby predisposing this sex to autism. A third gene, NLGN4X has been proposed as an attractive candidate for aspects of the TS neurocognitive profile (Zinn et al., 2007) and for predisposition to autism (Jamain et al., 2003;฀Laumonnier฀et฀al.,฀2004). This gene฀has฀a฀Y฀homologue฀(NLGN4Y)฀located฀ay฀Yq11฀(Ylisaukko-oja฀et฀al.,฀2005). Determining the exact contributions of STS, EFHC2, NLGN4X and NLGN4Y to sexually dimorphic brain development (and therefore to sex-specific vulnerability to neuropsychiatric disorders) represents an exciting avenue for further investigation. Due to the nature of X-linked imprinting, we may expect traits underpinned by X-linked paternally expressed genes to be evident in females but not in males, whilst the expression of traits influenced by X-linked maternally expressed genes may vary between the sexes according to whether the causal genes are X-inactivated or not (Davies,฀ Isles,฀ &฀ Burgoyne,฀ et฀ al.,฀ 2006). Skuse et al. (1997) have postulated that female-limited expression of the paternally expressed X-linked gene conferring social competence referred to previously may explain why females score better than males in a questionnaire assessing social cognitive impairment. The existence of an X-linked maternally฀expressed฀gene฀that฀enhances฀visuospatial฀memory฀skills฀(Bishop฀et฀al.,฀ 2000)฀may฀explain฀male฀superiority฀in฀this฀domain฀(Loring-Meier฀&฀Halpern,฀1999), assuming that it is X-inactivated, and thus would be expressed at lower levels in female than male brain. The TS data further suggest that sex differences in the structure/function฀of฀the฀superior฀temporal฀gyrus฀(Im฀et฀al.,฀2006),฀thalamus฀(Li,฀Huang,฀ Constable, & Sinha, 2006) and caudate nucleus (Munro et al., 2006) may arise due to the downstream neurodevelopmental effects of one or more X-linked imprinted genes. Clearly, the identification of X-linked imprinted genes in man, together with subsequent analysis of how these genes may contribute towards sexually dimorphic neurobiology, represents an important goal. In mice, the maternally expressed Xlr genes appear to be subject to X-inactivation, and thus are expressed more highly in male tissues than in female tissues (Davies et al., 2005;฀Raefski฀&฀O’Neill,฀2005). Likewise,฀their฀closest฀human฀orthologue,฀the฀FAM9B gene, is more highly expressed in฀male฀than฀female฀gonads฀(Martinez-Garay฀et฀al.,฀2002).

4

Conclusion

Understanding sex differences in neurobiology, in vulnerability to mental disorders, and in response to therapy represents one of the biggest challenges in psychiatric genetics today. A number of mechanisms can give rise to sexually dimorphic gene

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expression฀and฀subsequent฀differences฀in฀brain฀development฀and/or฀function.฀Two฀ of these mechanisms (X-linked gene dosage and X-linked imprinting) can be studied in the amenable “experiment of nature” provided by Turner Syndrome. Comprehensive฀phenotyping/genomic฀assays฀in฀TS฀(and฀in฀model฀systems฀such฀as฀ the฀ 39,XO฀ mouse)฀ are฀ likely฀ to฀ provide฀ important฀ insights฀ into฀ brain฀ processes฀ affected by these mechanisms, and to identify underlying genes. Such combined analyses will increase our knowledge about the basis of sexually dimorphic neurobiological processes, and will enable more effective sex-specific therapies to be developed for sex-biased neuropsychiatric disorders. Acknowledgements P.M.Y.L.฀is฀supported฀by฀the฀Biotechnology฀and฀Biological฀Sciences฀Research฀ Council฀(BBSRC,฀UK).฀E.S.฀is฀supported฀by฀the฀Wellcome฀Trust฀and฀the฀Medical฀Research฀Council฀ (MRC,฀UK).฀W.D.฀is฀an฀RCUK฀Fellow฀in฀Translational฀Research฀in฀Experimental฀Medicine.

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Yen,฀P.฀H.,฀Marsh,฀B.,฀Allen,฀E.,฀Tsai,฀S.฀P.,฀Ellison,฀J.,฀Connolly,฀L.,฀et฀al.฀(1988).฀The฀human฀ X-linked฀steroid฀sulfatase฀gene฀and฀a฀Y-encoded฀pseudogene:฀Evidence฀for฀an฀inversion฀of฀the฀ Y฀chromosome฀during฀primate฀evolution.฀Cell, 55, 1123–1135. Ylisaukko-oja,฀T.,฀Rehnström,฀K.,฀Auranen,฀M.,฀Vanhala,฀R.,฀Alen,฀R.,฀Kempas,฀E.,฀et฀al.฀(2005).฀ Analysis of four neuroligin genes as candidates for autism. European Journal of Human Genetics, 13, 1285–1292. Zechner, U., Wilda, M., Kehrer-Sawatzki, H., Vogel, W., Fundele, R., & Hameister, H. (2001). A high density of X-linked genes for general cognitive ability: a run-away process shaping human evolution? Trends in Genetics, 17,฀697–701. Zinn,฀A.,฀Kushner,฀H.,฀&฀Ross,฀J.฀L.฀(2008).฀EFHC2฀SNP฀rs7055196฀is฀not฀associated฀with฀fear฀ recognition in 45, X Turner syndrome. American Journal of Medical Genetics. Part B, 147, 507–509. Zinn,฀A.,฀Roeltgen,฀D.,฀Stefanatos,฀G.,฀Ramos,฀R.,฀Elder,฀F.,฀Kushner,฀H.,฀et฀al.฀(2007).฀A฀Turner฀ syndrome neurocognitive phenotype maps to Xp22.3. Behavioral and Brain Functions, 3, 24. Zinn,฀A.,฀Tonk,฀V.฀S.,฀Chen,฀Z.,฀Flejter,฀W.฀L.,฀Gardner,฀H.฀A.,฀Guerra,฀R.,฀et฀al.฀(1998).฀Evidence฀ for a Turner syndrome locus or loci at Xp11.2-p22.1. American Journal of Human Genetics, 63,฀1757–1766.

Mental Retardation and Human Chromosome 21 Gene Overdosage: From Functional Genomics and Molecular Mechanisms Towards Prevention and Treatment of the Neuropathogenesis of Down Syndrome Mohammed Rachidi and Carmela Lopes Abstract Down syndrome (DS), caused by a genomic imbalance of human chromosome 21 (HSA21), is mainly observed as trisomy 21 and is the major genetic cause of mental retardation (MR). MR and associated neurological and behavioural alterations result from dysregulation in critical HSA21 genes and associated molecular pathways. Gene expression, transcriptome, proteome and functional genomics studies, in human, trisomic and transgenic mouse models have shown similar genotype/phenotype correlation and parallel outcomes suggesting that the same evolutionarily conserved genetic programmes are perturbed by gene-dosage effects. The expression variations caused by this gene-dosage imbalance may firstly induce brain functional variations at cellular level, as primary phenotypes, and finally induce neuromorphological alterations and cognitive deficits as secondary phenotypes. The identification of trisomic genes overexpressed in the brain and their function, their developmental regulated expression and their downstream effects, their interaction with other proteins, and their involvement in regulatory and metabolic pathways is giving a clearer view of the origin of the MR in DS. This led to the identification of potential targets in the altered molecular pathways involved in MR pathogenesis, such as calcineurin, NFATs and MAPK pathways, that may be potentially corrected, in the perspective of new therapeutic approaches. Treatment of DS mouse models with NMDA receptor or GABAA antagonists allowed post-drug rescue of cognitive deficits. Besides these new pharmacotherapies, the regulation of gene expression by microRNAs or small interfering RNAs provide exciting possibilities for exogenous correction of the aberrant gene expression in DS and provide potential directions for clinical therapeutics of MR. Herein, we highlight the genetic networks and molecular mechanisms implicated in the pathogenesis of MR in DS and, thereafter, we outline some of the therapeutic strategies for the treatment of this as yet incurable cognitive disorder with a considerable impact on public health.

M. Rachidi (*) EA 3508, Laboratory of Genetic Dysregulation Models: Trisomy 21 and Hyperhomocysteinemia, University of Paris 7-Denis Diderot, Tour 54, E2-54-53, Case 7104, 2 Place Jussieu, Paris 75251, France e-mail: [email protected]

J.D. Clelland (ed.), Genomics, Proteomics, and the Nervous System, Advances in Neurobiology 2, DOI 10.1007/978-1-4419-7197-5_2, © Springer Science+Business Media, LLC 2011

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Keywords Trisomy฀21฀•฀Mental฀retardation฀•฀Learning฀and฀memory฀•฀Down฀syndrome฀ critical฀ region฀ •฀ Genotype-phenotype฀ correlation฀ •฀ Mouse฀ models฀ •฀ Gene-dosage฀ imbalance฀•฀Transcriptome฀•฀Proteome฀•฀MicroRNAs฀•฀Gene฀expression฀variation฀ •฀ Molecular฀ mechanism฀ model฀ •฀ NFATs/calcineurin฀ pathways฀ •฀ NMDA฀ receptor฀ antagonist฀•฀GABAA฀antagonists฀•฀Pharmacotherapy Abbreviations AChEI AD APP ATP BAC BFCN CA1 CA3 CaMKII CBR1 ChAT CIT-K CREB DS DSCAM DSCR DSCR1 DYN1 DYRK1A EGF EPSCs ERG ES ETS2 GABAA GIRK2 HSA21 IQ ITSN1 KCNJ6 LPS LTD LTP MAPK MCIP1 miRNA

Acetylcholinesterase inhibitor Alzheimer’s disease Amyloid precursor protein Adenosine triphosphate Bacterial artificial chromosome Basal forebrain cholinergic neurons Cornu ammonis 1 Cornu ammonis 3 Calcium/calmodulin-dependent protein kinase Carbonyl reductase 1 Choline acetyl transferase Citron kinase c-AMP response element-binding protein Down syndrome Down syndrome cell adhesion molecule Down syndrome critical region Down syndrome critical region gene 1 Dynamin 1 Dual-specificity tyrosine-(Y)-phosphorylation kinase 1A Epidermal growth factor Excitatory postsynaptic currents Ets related gene Embryonic stem cells v-ets erythroblastosis virus E26 oncogene homolog 2 Gamma-aminobutyric acid type A receptor G-protein coupled inward rectifying potassium channel subunit 2 Human chromosome 21 Intelligence quotient Intersectin gene 1 Potassium inwardly rectifying channel J6 Lipopolysaccharide Long-term depression Long-term potentiation Mitogen activated protein kinase Myocyte-enriched calcineurin-interacting protein 1 MicroRNA

Mental Retardation and Human Chromosome 21 Gene Overdosage

MMU16 MR NFATc NGF NMDA NMDA-R PP1 PTZ qRT-PCR RCAN1 S100B SAGE SHH SIM2 SNP SOD1 SYNJ1 TBS TPRD TTC3 YAC

1

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Mouse chromosome 16 Mental retardation Nuclear factor of activated T cells Nerve growth factor N-methyl-d-aspartate N-methyl-d-aspartate receptor Protein phosphatase 1 Pentylenetetrazol Quantitative reverse transcriptase polymerase chain reaction Regulator of calcineurin 1 protein S100 calcium-binding protein beta Serial analysis of gene expression Sonic hedgehog Single minded 2 Single nucleotide polymorphism Superoxide dismutase 1 Synaptojanin gene 1 Theta-burst stimulation Tetratricopeptide repeat domain Down syndrome Tetratricopeptide repeat domain 3 Yeast artificial chromosome

Mental Retardation in Down Syndrome: An Invalidating Neuropathological Aspect with Hard Impact on Public Health

Trisomy of human chromosome 21 (HSA21) is the most frequent genetic cause of mental retardation (MR) and other phenotypic abnormalities, including heart defects, cranio-facial abnormalities, cognitive impairment and Alzheimer’s disease (AD), collectively known as Down syndrome (DS) and affecting 1 in 700 live births (Roizen & Patterson, 2003). While the clinical phenotypes of each DS individual are variable in trait number and intensity, the MR remains the invariable hallmark disorder of DS and the most invalidating pathological aspect contributing to about 30% of all moderate-to-severe cases of MR (Lejeune, 1990; Pulsifer, 1996; Stoll, Alembik, Dott, & Roth, 1990). Early infants show delayed cognitive development, leading to mild–moderate MR and decrease of the intelligence quotient (IQ) from early in the first year to late childhood (Brown, Greer, Aylward, & Hunt, 1990; Hodapp, Ewans, & Gray, 1999). DS patients have difficulties in both learning and memory. Moreover, the learning can be complicated by avoidance strategies when faced with cognitive challenges (Wishart, 1995). Although all domains of development follow the usual sequence, a deficiency in language production relative to other areas of development often causes substantial impairment (Chapman, Seung, Schwartz, & Kay-Raining Bird, 1998).

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The impairment of prefrontal cortex and cerebellar function (Nadel, 2003), speech and articulation are also particularly affected. The lower performances of DS in linguistic tasks may be partially explained in terms of impairment of the frontocerebellar structures involved in articulation and verbal working memory (Fabbro, Alberti, Gagliardi, & Borgatti, 2002). In adult life, the IQ of DS patients persists at low levels (30–70) and also undergoes a decline in cognitive performance (Chapman & Hesketh, 2000; Vicari, 2004, 2006) that has been interpreted as the consequence of accelerated ageing in DS (Devenny et al., 1996; Lott & Head, 2005). In addition, an early onset of an Alzheimer disease-like neurohistopathology is systematically observed by the fourth decade (Dalton & Crapper-McLachlan, 1986). DS children have more behavioural and psychiatric problems than in other children, but fewer than in other individuals with MR. Adult DS patients can have a similar prevalence of psychiatric problems to other people with intellectual disability. A raised frequency of psychiatric problems is also related to the increased prevalence of depression in people with DS. However, they seem protected from some psychiatric disorders such as personality disorder, schizophrenia and anxiety (Collacot, Cooper, Branford, & McGrother, 1998). On the other hand, DS children show continuous but gradual improvement in mental age throughout childhood; IQs generally decline from early in the first year to late childhood (Hodapp & Zigler, 1990). Improvements in cognitive abilities and in quality of life of individuals with DS have resulted from improvements in medical care, identification and treatment of psychiatric disorders (such as depression, autism, and disruptive behaviour disorders) and early implementation of special educational programmes and interventions with typical educational settings (Connolly, Morgan, Russell, & Fulliton, 1993).

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Mental Retardation in Down Syndrome: A Consequence of Developmental and Functional Brain Alterations

Individuals wih DS have a functionally abnormal brain with developmental alterations in morphogenesis and histogenesis. The brain of DS subjects is characterised by several postmortem macroscopic features that are related to pre- and post-natal abnormalities leading to retardation of brain growth (Schmidt-Sidor, Wisniewski, Shepard, & Sersen, 1990). Infants and children with DS have delayed brain maturation, retardation of growth and delayed and disorganised second phase of cortical development and lamination emergence, cortical dysgenesis, delayed myelination, fewer neurons and lower neuronal density, abnormal synaptic connection (Wisniewski, 1990; Wisniewski & Schmidt-Sidor, 1989), shortened basilar dendrites, decreased number of spines with altered morphology, and defective cortical layering in several cortical areas (Becker, Armstrong, & Chan, 1986; Golden & Hyman, 1994; Marin-Padilla, 1976; Schmidt-Sidor et al., 1990; Takashima, Becker, Armstrong, & Chan, 1981; Takashima, Iida, Mito, & Arima, 1994).

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Overall, brain volume is reduced in DS subjects (Becker, Mito, Takashima, & Onodera, 1991; Coyle, Oster-Granite, & Gearhart, 1986; Wisniewski, 1990), including cerebellar and cerebral grey and white matter (Kesslak, Nagata, Lott, & Nalcioglu, 1994; Pearlson et al., 1998; Pinter, Eliez, Schmitt, Capone, & Reiss, 2001; Raz et al., 1995; Schapiro, Haxby, & Grady, 1992; Schapiro, Luxenberg, Kaye, Haxby, & Friedland, 1989; Weis, Weber, Neuhold, & Rett, 1991). In particular, the reduced cerebellum shows a decreased volume of lobules VI to VIII (Ayraham, Sugarman, Rotshenker, & Groner, 1991; Jernigan, Bellugi, Sowell, Doherty, & Hesselink, 1993; Raz et al., 1995). Hippocampus volume is disproportionally reduced (Aylward et al., 1999; Kesslak et al., 1994; Krasuski, Alexander, Horwitz, Rapoport, & Schapiro, 2002; Pearlson et al., 1998; Pinter, Eliez et al., 2001; Raz et al., 1995), in particular at the level of the corpus callosum (Lai & Williams, 1989; Wang, Doherty, Hesselink, & Bellugi, 1992). The anterior cortex, including frontal and anterior temporal lobes, also appears reduced after adjustment for total cerebral grey matter volume (Jernigan et al., 1993; Lai & Williams, 1989; Teipel et al., 2004), whereas amygdala volume reductions do not exceed the overall reduction of brain size (Aylward et al., 1999; Pinter, Brown et al., 2001; Pinter, Eliez et al., 2001). On the other hand, an increased volume is found in other brain areas, such as ventricles (Ikeda & Arai, 2002; Kesslak et al., 1994; Pearlson et al., 1998; Schimmel, Hammerman, Bromiker, & Berger, 2006), parahippocampal gyrus after adjustment for overall brain volume (Kesslak et al., 1994; Raz et al., 1995; Teipel & Hampel, 2006; Teipel et al., 2003), temporal, parietal and posterior cortex, lenticular nucleus and thalamus and hypothalamus (Jernigan et al., 1993; Pinter, Eliez et al., 2001), while the occipital lobe and superior temporal gyrus do not show volume changes after adjustment for overall brain volume (Frangou et al., 1997; Pinter, Eliez et al., 2001). In addition, DS brains are characterised by several neurological defects in cortex lamination (Golden & Hyman, 1994) and in cerebellar foliation (Raz et al., 1995). Morphological and functional defects have also been found at the cellular level determined by alteration in neurogenesis, neuronal differentiation, myelination, dendritogenesis and synaptogenesis (Becker et al., 1986, 1991; Coyle et al., 1986; Dierssen & Ramakers, 2006; Huttenlocher, 1974; Marin-Padilla, 1972, 1976; Purpura, 1974; Takashima, Ieshima, Nakamura, & Becker, 1989; Takashima et al., 1994; Vuksic, Petanjek, Rasin, & Kostovic, 2002; Wisniewski, 1990; Wisniewski & Schmidt-Sidor, 1989). Biochemical alterations also occur in foetal DS brain, which could serve as substrates for the morphological changes (Engidawork & Lubec, 2003), involving a decrease of the choline acetyltransferase and histidine decarboxylase activities and also a decrease of serotonin, histamine, and glutamate levels (Risser, Lubec, Cairns, & Herrera-Marschitz, 1997; Schneider et al., 1997; Wisniewski & Bobinski, 1991). Taken as a whole, these alterations observed in the brain of DS, in particular those in the key regions involved in learning and memory processes, could be the origin of MR (Black, Nadel, & O’Keefe, 1977; Funahashi, Takeda, & Watanabe, 2004; Milner, Squire, & Kandel, 1998; Nadel & Willner, 1980). In addition, although young children with DS appear to be born with a normal septohippocampal cholinergic system (Kish et al., 1989), an ageing-dependent neurodegeneration of the basal forebrain cholinergic neurons (BFCN) was observed (Casanova, Walker, Whitehouse,

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& Price, 1985; Yates et al., 1983). Because BFCN provide the major cholinergic input to the hippocampus and neocortex, the degeneration of these neurons may have functional consequences at the level of cholinergic receptors. These dysfunctions could produce additional learning and memory deficits in older individuals with DS (Yates et al., 1983) and could be an outgrowth of AD in these patients. In addition, an early onset of an Alzheimer disease-like neurohistopathology is systematically observed by the fourth decade (Dalton & Crapper-McLachlan, 1986). The short- and long-term memory deficits observed in DS patients (Brown et al., 2003; Clark & Wilson, 2003; Hodapp et al., 1999; Hulme & Mackenzie, 1992) provide behavioural evidence of hippocampal dysfunction by adolescence (Carlesimo, Marotta, & Vicari, 1997). The spatial learning, also depending on the hippocampus, is particularly affected and there is also evidence for impairment of prefrontal cortex and cerebellar function (Nadel, 2003). In addition to the known effects of the hippocampal formation in spatial memory, the altered cortical layer and cerebellum also may participate to cognitive and behavioural phenotypes in DS (Funahashi et al., 2004). Overall, the MR, the major neurological disorder of DS, is mainly a consequence of functional and developmental brain alterations in neurogenesis, neuronal differentiation, myelination, dendritogenesis and synaptogenesis.

3

Mental Retardation in Down Syndrome: A Consequence of Chromosome 21 Gene Overdosage

In the most cases, DS results from the trisomy of the HSA21 in all cells of the afflicted individuals (LeJeune, Gautier, & Turpin, 1959) and the generally accepted molecular origin of DS is the chromosomal imbalance associated to the HSA21 triplication and thus the overdosage of HSA21 genes that could be responsible for the phenotype seen in DS patients (Antonarakis, 1998). In some rare cases, no more than 1% of living trisomic patients, DS results from a partial trisomy 21 showing variable phenotypes depending of the extra copy of the triplicated region. Clinical, cytogenetic and molecular analysis of such patients allowed narrowing a region of HSA21, called Down syndrome critical region (DSCR), localised on the distal part of the long arm, around the marker D21S55, and flanked by D21S17 and Ets related gene (ERG) (Delabar et al., 1993; Korenberg et al., 1994; Rahmani et al., 1989). The chromosomal imbalance due to the extra copy of DSCR is associated with the expression of many features of the disease and contributes significantly, but not exclusively, to MR (Delabar et al., 1993; Korenberg et al., 1994; Rahmani et al., 1989).

3.1

Chromosomal Imbalance Effects on Mental Retardation

The DSCR, containing the genes located between the carbonyl reductase 1 (CBR1) and the transcriptional regulator Ets-related gene (ERG) loci (Fig. 1) has been

27

Mental Retardation and Human Chromosome 21 Gene Overdosage ES#21

D2lS5

Tc1

21P Dp(16)1Yu

LIPl CXADR

q21.1

D2lSL922 q21.2

Ms1Ts65

MRPL39

Ts65Dn

Ms1Rhr/ Ts65Dn Ts2Cje

APP q21.3 Ts1Cje

SODl q22.11

SYNJl IFNARl

ITSNl DSCRl

RUNXl CBRl CLDNl4 TTC3

SIM2

q22.12 230E8

DYRKl A GIRK2 ETS2

MX1 ZNF295

Ts1Rhr

152F7

q22.13 141G6 q22.2

285E6

q22.3

Sl00B

Fig. 1 Down syndrome mouse models. The boundary localisations of the HSA21 or its mouse syntenic triplicated regions in the DS mouse models are indicated on the right of the HSA21. Black lines indicate partial trisomic 16 and transchromosomal mice. Grey lines indicate segmental transgenic mice carrying human YACs, containing the DS critical region (DSCR). Monogenic transgenic mice are indicated on the left of the HSA21

designated as the DS critical region that, when duplicated, is associated with multiple neurological features of DS, including MR (Delabar et al., 1993; Korenberg et al., 1994; Toyoda et al., 2002). Consequently, the major phenotypes of DS, particularly MR, may have their origin in the over-dosage of genes located in DSCR. To explain the pathogenesis of DS from the genetic over-dosage, two genetic hypotheses have been considered. 3.1.1

Dosage-Sensitive Gene Hypothesis

This genetic hypothesis holds that the phenotype is a direct result of the cumulative effects of the dosage imbalance of the individual genes located on the triplicated HSA21 or critical region DSCR (Epstein, 1986, 1990; Korenberg et al., 1990). According to this “dosage-sensitive gene” hypothesis, a subset of genes on the triplicated HSA21 is directly responsible for particular pathological traits associated with trisomy 21. Consequently, the DSCR was defined as a minimal interval of the HSA21 that carries the dosage-sensitive genes necessary and sufficient for typical features of DS individuals (Delabar et al., 1993; Korenberg et al., 1994; Rahmani

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et al., 1989). Several phenotypes of DS have also been found in transgenic mice engineered to overexpress HSA21 genes or their mouse orthologs. The observations of cardiac pathology, craniofacial dysmorphology, malformation of cerebellum and overall the deficit of cognitive functions both in DS individuals and in mouse models were in agreement with the “dosage-sensitive gene” hypothesis. 3.1.2

Amplified Developmental Instability Hypothesis

This genetic hypothesis, in contrast to the preceding hypothesis, states that dosage imbalance of the hundreds of genes on HSA21 determines a non-specific disturbance of genomic regulation and expression. This global disruption of the correct balance of gene expression in development pathways alters the normal developmental homeostasis and determines most manifestations of DS (Pritchard & Kola, 1999; Shapiro, 1983; Shapiro & Whither-Azmitia, 1997). In agreement to this hypothesis, the variability of the DS phenotype in the different individuals has also been explained by intervention of stochastic factors during development (Kurnit, Aldridge, Matsuoka, & Matthysse, 1985), which can also be involved in normal development (Kurnit, Layton, & Matthysse, 1987). Moreover, several features observed in DS (for example, AD, cardiac malformations and metabolic diseases) can be observed in other trisomies and in the general population at lower frequency. In addition, the significant increase of the individual variability in DS, as compared to euploid individuals, also supports this hypothesis. Nevertheless, the “amplified developmental instability” hypothesis and the “dosagesensitive genes” hypothesis are not mutually exclusive. It is possible that single genes, or a specific subset of genes, may be involved in specific DS phenotypes, while some other DS phenotypes may be due to a more general disturbance in gene dosage imbalance as a result of the extra chromosomal material (Antonarakis, 2001).

3.2

Gene Dosage Imbalance in Down Syndrome Determine Dysregulation of HSA21 Gene Expression

3.2.1

Primary and Secondary Gene Effects

The genetic origin of DS is the overdosage of HSA21 genes that could be responsible for the genesis of the neurological and cognitive defects seen in DS patients (Antonarakis, 1998). The 1.5-fold increase of HAS21 gene dosage may determine a primary effect on gene transcription consisting in a 1.5-fold increase of expression level of these genes (Kurnit, 1979; Mao et al., 2005; Mao, Zielke, Zielke, & Pevsner, 2003). Genes on the trisomic HSA21 encoding transcription factors and other proteins, that can directly or indirectly influence gene expression, may produce a secondary genome-wide transcriptional downstream misregulation, which may consist of

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gene over-expression different from 1.5-fold, and also in down-regulation of genes on both HSA21 and the other chromosomes. This secondary effect of the chromosomal imbalance could be complex and highly variable in the different cells and during the lifespan (Dauphinot et al., 2005; Epstein, 1986, 1988; Lyle, Gehrig, Neergaard-Henrichsen, Deutsch, & Antonarakis, 2004; Prandini et al., 2007; Saran, Pletcher, Natale, Cheng, & Reeves, 2003; Sultan et al., 2007). An important application of the secondary gene effects on other chromosomes is widely used in antenatal screening programmes for trisomy 21 by detection of abnormal levels of foetal proteins in maternal serum. In particular, the level of the alpha fetoprotein is reduced (Newby et al., 1997) while human chorionic gonadotrophin is increased (Aitken et al., 1993) in trisomy 21, although the encoding genes are located on the chromosomes 4 and 19, respectively. The molecular effects of the 1.5 gene overdosage may be even more complex at the protein level, as additional regulatory points are introduced, such as posttranscriptional, translational and post-translational regulations and post-translational modifications. Modification in the levels of proteins involved in multicomplex protein formation, in protein–protein intections and in metabolic and regulatory networks can determine alterations in these interactions because of the loss of the correct ratio among the proteins and, finally, can alter the function or stability of the proteins. In the brain, it can be considered that the mere presence of the chromosomal imbalance determines misexpression and interaction of crucial genes/proteins involved in neuromorphogenesis and neurogenic cascades. The developmental errors caused by trisomy 21 during neural patterning and signal transduction pathways may lead to defective neuronal circuitry and could be the biological mechanism responsible for the pathogenesis of MR in DS.

3.2.2

Transcriptional Variation as a Consequence of Trisomy 21

DS may be considered as a multifactorial disease with an unusual aetiology characterised by overdosage of HSA21 genes determining gene expression variation that can be responsible for the complex DS phenotype. Thus, expression studies in normal and trisomic tissues contribute to understanding the role of the HSA21 genes and the contribution of their dosage alterations in DS pathogenesis, allowing the selection of HSA21 genes potentially involved in a given DS phenotype. In particular, a gene expressed in developing and/or adult brain may be selected as a candidate gene for MR, particularly when its transcription is restricted to key regions for cognitive functions, such as the hippocampal formation, the cortex and the cerebellum. DNA sequencing of HSA21 (Hattori et al., 2000; International Human Genome Sequencing Consortium, 2004) and gene annotation improve identification of the gene products. These sequencing data and the development of molecular analysis tools allow large-scale application of gene expression analysis. Transcriptome studies are performed by quantitative RT-PCR (qRT-PCR), microarrays and serial

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analysis of gene expression (SAGE), to study gene expression variation in trisomic tissues compared to the euploid ones using human tissues and cell lines (Aït Yahya-Graison et al., 2007; Chou et al., 2008; Deutsch et al., 2005; FitzPatrick et al., 2002; Giannone et al., 2004; Li et al., 2006; Malago et al., 2005; Mao et al., 2003, 2005; Prandini et al., 2007), or mouse trisomic model tissues (Amano et al., 2004; Chrast, Scott, Madani et al., 2000; Dauphinot et al., 2005; Kahlem et al., 2004; Lyle et al., 2004; Potier et al., 2006; Saran et al., 2003; Sultan et al., 2007; Wang et al., 2004). Transcriptome studies of the brain, the cerebellum or neuronal cell lines are particularly abundant, reflecting the major interest in the understanding of the molecular mechanisms involved in MR pathogenesis in DS (Amano et al., 2004; Chrast, Scott, Madani et al., 2000; Dauphinot et al., 2005; Kahlem et al., 2004; Lyle et al., 2004; Mao et al., 2003, 2005; Potier et al., 2006; Saran et al., 2003; Sultan et al., 2007; Wang et al., 2004). Theoretically, the supernumerary copy of HSA21 is expected to result in a 50% increase in the level of transcripts of all genes mapping to HSA21. Most of these works confirm that transcript levels are elevated about 1.5-fold for the majority of trisomic genes in human trisomic tissues and across a broad range of tissues of trisomic mouse models (Aït Yahya-Graison et al., 2007; Amano et al., 2004; Dauphinot et al., 2005; Epstein, 1986; FitzPatrick et al., 2002; Kahlem et al., 2004; Lyle et al., 2004; Mao et al., 2003, 2005; Potier et al., 2006; Prandini et al., 2007; Sultan et al., 2007; Wang et al., 2004). These results indicate that the triplicated genes are overexpressed in a dosage-dependent manner, supporting the hypothesis that a global HSA21 dosage imbalance causes the heterogeneous phenotypes of DS (Shapiro, 1983, 1997). It cannot be excluded that the overexpression of a limited number of genes on HSA21 is responsible for the DS phenotypic features (Korenberg et al., 1990). In addition, in several studies, it was also found that there is not always a direct correlation between genomic imbalance and not all genes are overexpressed ~1.5fold compared to euploid (Aït Yahya-Graison et al., 2007; Dauphinot et al., 2005; Kahlem et al., 2004; Lyle et al., 2004; Potier et al., 2006; Saran et al., 2003), and a decreased expression is also found for some genes, such as GRIK1 (Saran et al., 2003), Ets2 (Engidawork & Lubec, 2003; Greber-Platzer, Schatzmann-Turhani, Cairns, Balcz, & Lubec, 1999; Wang et al., 2004), superoxide dismutase 1 (SOD1) (Engidawork & Lubec, 2003; Wang et al., 2004), DSCR3 (Engidawork & Lubec, 2003), HMGN1 (Engidawork & Lubec, 2003), and CCT8 (Engidawork & Lubec, 2003). For these dysregulated genes, the authors suggested that the initial overexpression of genes from the aneuploid chromosome was amplified by subtle compensatory mechanisms to the gene-dosage effect that may, in turn, result in the extensive variability of the phenotype that characterises DS (Dauphinot et al., 2005; Kahlem et al., 2004; Lyle et al., 2004). The euploid genes, or the euploid region of chromosome 16, in the case of the DS mouse models, were generally found differentially expressed (over or under) (Bahn et al., 2002; Chrast, Scott, Madani et al., 2000; Chrast, Scott, Papasavvas et al., 2000; Dauphinot et al., 2005; FitzPatrick et al., 2002; Mao et al., 2003, 2005; Potier et al., 2006; Saran et al., 2003). These data support a model of a subtle primary upregulation of genes on the trisomic chromosome resulting in a more generalised secondary transcriptional misregulation (FitzPatrick et al., 2002).

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Examination of difference of gene expression in two independent experiments suggests that the global perturbation includes a significant stochastic component. Thus, dosage imbalance of 124 genes in Ts65Dn mice alters the expression of thousands of genes to create a variable trisomic transcriptome (Saran et al., 2003). At the present time, few studies have been performed concerning the HSA21 genes that do not have mouse homologs on the mouse chromosome 16 (MMU16). When gene expression was examined in Ts43H mice, a segmental Ts17 mouse model for DS, 20 brain-specific genes at dosage imbalance gave an average of 1.2fold increased expression of euploid, with expression of only two genes reaching 1.5-fold expression (Vacik et al., 2005). In addition, 12 genes on the nontrisomic portion of chromosome 17 had expression levels that were 90% of euploid level. Brains from Ts2Cje mice exhibited a 1.5-fold expression level of specific trisomic genes comparable to Ts65Dn and different from euploid. Further data and analyses in both humans and mice are needed to reach biologically significant conclusions (Antonarakis & Epstein, 2006; Reeves, 2006). Recently, new aspects of gene expression have acquired more importance in DS studies. The level of the expression variation for a given gene can change in the different tissues, including brain (Dauphinot et al., 2005; Kahlem et al., 2004; Lyle et al., 2004; Mao et al., 2005; Rachidi, Lopes, Charron et al., 2005; Rachidi, Lopes, Delezoide, & Delabar, 2006; Rachidi et al., 2000; Saran et al., 2003; Sultan et al., 2007) and during developmental stages (Dauphinot et al., 2005; Potier et al., 2006; Rachidi, Lopes, Costantine, & Delabar, 2005; Rachidi et al., 2006; Rachidi et al., 2000; Sultan et al., 2007), indicated that there were tissue- and cell-specific changes of gene expression in trisomy 21 during foetal development. Inter-individual gene expression variations can explain at least some phenotypic individual differences, including susceptibility to common disorders. Since the 1970s, quantitative differences in gene expression have been proposed to explain variation in natural populations, participating in evolution and contributing to phenotypic diversity (King & Wilson, 1975). Recent studies indicate that variation in gene expression levels within and among populations is abundant, with significant inter-individual variation (Brem, Yvert, Clinton, & Kruglyak, 2002; Cheung et al., 2003; Oleksiak, Churchill, & Crawford, 2002; Schadt et al., 2003). Most of the differentially expressed genes had significant heritability (Brem et al., 2002; Monks et al., 2004; Morley et al., 2004; Spielman et al., 2007; Storey et al., 2007; Yvert et al., 2003). This inter-individual gene expression variation has also been observed for HSA21 genes in DS (Aït Yahya-Graison et al., 2007; Deutsch et al., 2005; FitzPatrick et al., 2002; Prandini et al., 2007; Stranger et al., 2005; Sultan et al., 2007), and significant eQTLs have been identified (Deutsch et al., 2005). In particular, a cis-eQTL was identified for CCT8 corresponding to a single nucleotide polymorphism (SNP) located within the cis-regulatory region of CCT8 (Deutsch et al., 2005). These results are in agreement with the hypothesis that a molecular mechanism for the variability of phenotypic manifestations of trisomy 21 is a threshold effect of expression of HSA21 genes that show variable levels of expression in the population (Antonarakis, Lyle, Dermitzakis, Reymond, & Deutsch, 2004).

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On the basis of the observed extensive variation in gene expression observed among normal individuals, it has been predicted that for many HSA21 genes there is a considerable overlap in total expression levels between normal and trisomy 21 individuals due to allelic variation (Aït Yahya-Graison et al., 2007; Deutsch et al., 2005; Prandini et al., 2007; Sultan et al., 2007). In this way, two considerations can be proposed. First, the expression variations can explain the differences in the penetrance and variability of the DS phenotypes. It has been proposed that overexpressed genes, showing low levels of expression variation, would be predicted to lead to the more penetrant phenotypes. In contrast, genes with high variation in expression would contribute to incompletely penetrant/variable DS-related phenotypes (Aït Yahya-Graison et al., 2007; Deutsch et al., 2005; Prandini et al., 2007; Sultan et al., 2007). Second, the existence of expression variations suggest caution in the analyses of the gene expression changes, particularly for low variation ratios (less than twofold), because of overlapping of gene expression variation in DS and normal individuals in this variation interval (Aït Yahya-Graison et al., 2007; Deutsch et al., 2005; Prandini et al., 2007; Sultan et al., 2007). In this way, a recent work analysed inter-individual gene expression variations between HSA21 genes in trisomic and normal cell lines. When pooled RNAs were used, a global gene dosage-dependent expression of chromosome 21 genes was observed. In contrast, when inter-individual gene expression variations were analysed, most of the HSA21 genes results compensated for the gene-dosage effect (Aït Yahya-Graison et al., 2007). The authors suggested that overexpressed genes are likely to be involved in DS phenotypes, in contrast to the compensated genes. Moreover, a more recent work analysed the differences in euploid gene expression variation between trisomy 21 and euploid tissues, on the hypothesis that these differences may contribute to the phenotypic variations in DS (Chou et al., 2008). The authors found a group of euploid genes showing greater expression variance in human trisomy 21 tissues than in euploid tissues, and that the number of euploid genes with elevated variance was significantly higher in DS tissues than in the euploid tissues (Chou et al., 2008). Recently, new transcripts, the microRNAs (miRNAs), have been identified that play a role in gene expression regulation. MiRNAs are small, non-protein coding RNAs that link specific mRNA targets and lead to translational repression or mRNA cleavage (Bartel, 2004; Bushati & Cohen, 2007; Wang, Stricker, Gou, & Liu, 2007). Moreover, miRNAs have been shown to play a fundamental role in diverse biological and pathological processes, including cell proliferation, differentiation, apoptosis, carcinogenesis, and cardiovascular disease (Bushati & Cohen, 2007; Wang et al., 2007). It has been demonstrated that each miRNA can potentially regulate a large number of protein-coding genes, and many miRNAs can act in combination to regulate the same target genes (Bushati & Cohen, 2007; Wang et al., 2007). Thus, miRNA target genes are not restricted to a particular functional category or biological pathway, but rather are involved in a wide variety of biological processes. Very recently, bioinformatic analyses have demonstrated that HSA21 harbours five miRNA genes: miR-99a, let-7c, miR-125b-2, miR-155, and miR-802 (Kuhn

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et al., 2008). HSA21 miRNA expression analyses demonstrate that they are overexpressed in foetal brain and heart specimens from individuals with DS when compared with controls (Kuhn et al., 2008; Sethupathy et al., 2007). Moreover, some miRNAs, located on chromosomes other than 21, have been found overexpressed or underexpressed in hippocampus specimens from individuals with DS when compared to controls (Kuhn et al., 2008). The overexpression of the five HSA21 miRNAs in DS individuals may result in the aberrant expression of a large number of proteins in a variety of tissues. Thus, their inhibition or knock-down should normalise the expression level of all miRNA/mRNA targets back to non-trisomic 21 levels. Very interestingly, these potentialities suggest that HSA21 miRNAs may provide novel therapeutic targets in the treatment of individuals with DS. The application of the global genomic approach to in situ expression analysis allowed the establishment of expression atlas of the HSA21 genes for large gene screening and identification of candidate genes for DS phenotypes (Gitton et al., 2002; Reymond et al., 2002). Nevertheless, single gene approaches remain indispensable to determine precise gene expression map in different embryonic, foetal and adult ages in human and mouse. In addition, identification of the brain cell types expressing a given gene supplies fundamental information that helps gene function understanding (Lopes, Chettouh, Delabar, & Rachidi, 2003; Lopes, Rachidi, Gassanova, Sinet, & Delabar, 1999; Rachidi, Lopes, Charron et al., 2005; Rachidi et al., 2000, 2006). These spatio-temporal investigations have been particularly improved with a novel powerful microscopy technology, allowing in situ quantification of mRNA variations in different neuronal cell types in a given key structure of the brain (Rachidi, Lopes, Charron et al., 2005; Rachidi et al., 2000, 2006), and a novel quantitative method (quantitative assessment gene expression, QAGE) for assessment of in situ gene expression (Rachidi et al., unpublished data).

3.2.3

Proteomic Variation as a Consequence of Trisomy 21

It is known that quantity of proteins does always not correspond to the quantity of the corresponding mRNAs, because of several post-translational mechanisms that determine the final protein level in the cells in the given condition. Since the proteins are the final and functional products of the genes, to know how protein levels change in DS cells is a fundamental knowledge for understanding the real genotype/phenotype correlation and, finally, the DS pathogenesis. Initially, western blots have been used to measure the expression level of individual proteins. Several studies, analysing individual or small number of proteins, identified several changes in protein levels. Between the proteins encoded on HSA21, collagen VI A1 chain, COL6A1 (Engidawork, Balic et al., 2001) was found decreased in DS tissues compared to the normal tissues, while HMG14 (Epstein, 2001), S100B (Griffin et al., 1998), carbonyl reductase (Balcz, Kirchner, Cairns, Fountoulakis, & Lubec, 2001), and synaptojanin (Arai, Ijuin, Takenawa, Becker, & Takashima, 2002) were found increased in DS tissues compared to the normal tissues. In addition, some proteins encoded on chromosomes other than

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HSA21 also show level changes. In particular, EF1A1 and EF2 (Freidl, Gulesserian, Lubec, Fountoulakis, & Lubec, 2001), Adenosine triphosphate (ATP)-sensitive potassium channels (Kim & Lubec, 2001), synaptosomal associated protein 25 subunits, drebrin, nucleoside diphosphate kinase B, Rab GDP-dissociation inhibitor beta subunit, histidine triad nucleotide-binding protein (Weitzdoerfer et al., 2001), and stathmin (Cheon, Fountoulakis, Dierssen, Ferreres, & Lubec, 2001) were found decreased in DS tissues compared to the normal tissues, while alcohol dehydrogenase (Balcz et al., 2001) and nicotinic acetylcholine receptor beta 2 subunits (Engidawork, Gulesserian, Balic, Cairns, & Lubec, 2001) were found increased in DS tissues compared to the normal tissues. In a serial study, Lubec et al. analysed expression levels of 31 proteins encoded on HSA21 (Cheon, Bajo, Kim et al., 2003; Cheon, Kim, Ovod et al., 2003; Cheon, Kim, Yaspo et al., 2003; Cheon, Shim, Kim, Hara, & Lubec, 2003; FerrandoMiguel, Cheon, & Lubec, 2004) and only three proteins showed different expression levels in DS compared to controls: Hematopoietic adapter containing Src homology 3 (SH3) domain and sterile a motifs (HACS1) was decreased in DS, compared to controls (Cheon, Bajo, Kim et al., 2003), Synaptojanin-1 was increased in DS, compared to controls (Cheon, Kim, Ovod et al., 2003), and DSCR5 (PIG-P), a component of glycosylphosphatidylinositol-N-acetylglucosaminyltransferase (GPI-GnT) was overexpressed about twofold in DS, compared to controls (Ferrando-Miguel et al., 2004). Genome-wide proteomic approaches are performed using 2D-gel electrophoresis that, more recently, was associated to mass spectrometry, quantifying the protein spots. One of the first works using a global approach, having a limited resolution power, identified 11 proteins, among the 49 proteins analysed, that are deregulated in cerebral cortex of foetal DS, none of which encoded on HSA21 (Engidawork, Gulesserian, Fountoulakis, & Lubec, 2003). Using the same approach, Kadota et al. (2004) have used an in vitro neuronal differentiation system of mouse Embryonic stem (ES) cells containing a single HSA21 (TT2F/hChr21) (Shinohara et al., 2001), using TT2F parental ES cells as a control. The authors have detected only 18 proteins with significantly altered levels, including SOD1 and CCT8, which are encoded on HSA21 (Kadota et al., 2004). Among the other 16 proteins, they found matrix and structural proteins, heat shock/ stress proteins, protein or translational regulators, nuclear transcriptional factors, and enzymes for energy and macromolecular metabolism (Kadota et al., 2004). Among these 16 proteins encoded on other human chromosomes, the authors identified 7 that were overexpressed: protein subunits Atp6v1a1 and Atp6v1b2 of the vacuolar ATPase proton pump, which mediate acidification of intracellular organelles for energy production and convention, actin- (T-plastin and Vil2), filament(Krt2–8) and phospholipid- (Anxa4) related cytoskeleton proteins. In constrast, nine proteins were underexpressed significantly in TT2F/hChr21 cells compared with TT2F cells: AI850305, Eef1D and UchL1, involved in protein catabolism or translation regulation, heat shock proteins Hsp84-1, Hsp70 and Hsp86-1, microtubule- (Mapre2) and calmodulin- (Cnn3) related architectural proteins were underexpressed. Moreover, splicing regulatory elements, HnrnpF and HnrnpC, displayed

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contradictory expression patterns of overexpression and underexpression, respectively (Kadota et al., 2004). Moreover, in a comparison between mRNA and protein level change in TT2F/hChr21 cells compared with TT2F cells, different features were identified. The expression of Anxa4, Atp6v1a1, Atp6v1b2, Krt2–8, Vil2 (overexpressed), and of HnrnpC, Mapre2, UchL1, AI850305 (underexpressed) showed consistent mRNA transcription and protein translation. In contrast, Cnn3, Eef1D, Hsp70, Hsp84, Hsp86, HnrnpF and T-plastin showed disagreement (Kadota et al., 2004), suggesting the existence of post-transcriptional regulation or translational modification. Recently, Shin, Gulesserian, Verger, Delabar, and Lubec (2006) performed a proteomic approach using a non-mosaic polytransgenic mouse model for DS generated by inserting yeast artificial chromosomes (YACs), containing a fragment of the human critical region DSCR, into the murine genome (Smith et al., 1995). These mice carry 141G6 YAC and are polytransgenic for HSA21 genes DSCR3, 5, 6, 9, and tetratricopeptide repeat domain 3 (TTC3). The authors identified 45 proteins showing altered expression levels, among the 422 polypeptides, which were the products of 239 different genes, in mouse transgenic hippocampus compared to control, although none of DSCR3, 5, 6, 9, and TTC3 proteins was detectable using the low resolution Coomassie staining (Shin et al., 2006). These aberrant protein expressions may lead to impairment of cognitive functions. In particular, calcium/calmodulin-dependent protein kinase (CaMKII) protein was decreased in the 141G6 mouse hippocampus (Shin et al., 2006), and it is known that alteration of the CaMKII-pathway leads to a downstream alteration of the c-AMP response element-binding protein (CREB) pathway associated with impairment of fear memory (Bourtchuladze et al., 1994). 141G6 mice showed a lower performance in fear conditioning against sound as acoustic conditional stimulus (Chabert et al., 2004) that could be explained by aberrant protein levels of CaMKII (Shin et al., 2006). In contrast, 141G6 mice showed no cognitive defect by using Morris water maze and the multiple T-maze paradigms (Chabert et al., 2004) that could be explained by threshold levels necessary to alter these functions that was not surpassed, or that these tests are not sensitive enough to detect minor cognitive alterations (Shin et al., 2006). In recent years, it is emerging that protein alterations exist as polymorphisms among wild-type mice of different inbred strains. These polymorphic variations complicate the interpretation of the variation of protein level changes and their correlation to a given disease. Recently, Mao et al. (2007) conceived a simplified approach to analyse the effect of gene-dosage imbalance on proteome in a controlled environment by using mouse ES cells. They investigated four cell lines contained one single overexpressed gene (App, Snca, Dyrk1a, & Dopey2) and two cell lines with a duplication or a deletion, respectively, of a HSA21 segment containing 14 genes. The authors identified globally 255 proteins showing expression variation in the six cell lines. Four features appear in this study: (1) about the same numbers (70–110) of proteins showed expression alterations in each line, with dosage imbalance in only one or 14 genes; (2) dosage alteration of a single gene led to quantitative changes in a large number of proteins; (3) many proteins showed changed expression

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levels in several cell lines (38 proteins have alteration in at least three lines); and (4) 114 proteins were altered only in one cell line (Mao et al., 2007). On the basis of these observations, the authors proposed that the protein level changes may also be explained in part by a global response of the cellular proteome to the gene dosage defect, restoring the balance in the cellular proteome, on the hypothesis that quantitative changes of the proteome by gene dosage effects can be compensated by a rearrangement restoring a new balance. In this way, the cellular proteins were defined as balancer proteins, with altered quantity in several lines, and cell line-specific proteins, when altered only in one cell line. Balancer proteins would function as buffers in the proteome homeostasis without a direct functional correlation with the transgene(s) and among them, in contrast to the cell line-specific proteins, likely including proteins participating to common functional networks of the transgene(s) (Mao et al., 2007). Interestingly, the balancers have more non-synonymous SNPs in coding regions than cell line-specific proteins (Mao et al., 2007), indicating that balancers may have more tolerance towards quantitative changes, whereas cell line-specific proteins need more precise correlation between expression level and function.

4

Modelling Neuronal Alterations and Mental Retardation in Mouse Models of Down Syndrome

The alterations observed in brain of DS patients are likely to take place during embryogenesis and cannot be easily investigated at early stages of human development. Developmental studies in humans are extremely difficult and in vitro molecular biology and cell culture systems do not replicate the complex developmental processes perturbed by trisomy. These investigations became possible with the generation of the mouse models of DS, because of the ability to manipulate their genome genetically and the accessibility to all their tissues at different embryonic, foetal and adult stages. Interestingly, a high degree of conservation of the genomes and molecular mechanisms exists between mouse and human, and human genes on chromosome 21 are syntenic to mouse genes on chromosome 16 (~26.5 Mb), chromosome 10 (~2.3 Mb) and chromosome 17 (~1.1 Mb) (Hattori et al., 2000; Mural et al., 2002; Toyoda et al., 2002). This genetic evidence between the two mammalian species supports the essential use of the mouse in animal models to study the disruption of the developmental process caused by trisomy. More interestingly, the elevated gene expression due to trisomy is very comparable between mice and human and shows similar complexity and a comparable genetic effect with the same outcome on the features of the mouse analogous to DS phenotypes. This make the mouse models powerful tools for dissecting the phenotypic consequences of dosage imbalance that affect single genes or chromosome segments, and they have greatly enhanced our understanding of the cellular and biochemical mechanisms of gene dosage effects involved in DS.

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4.1

Trisomic Mouse Models and Candidate Chromosomal Regions for Mental Retardation in Down Syndrome

These trisomic mouse models with segmental or complete trisomy for MMU16, containing the orthologous region of the most part of HSA21, imitate the genetic complexity seen in trisomy 21 and have clinical phenotypes that correspond well to that observed in DS patients (Table 1).

Table 1 Trisomic and transgenic (Tg) mouse models for Down syndrome, their human syntenic chromosomal regions and genes and their neurological alterations Models Human syntenic region and genes Neurological alterations Ts16 (21q21.1–21q22.3) Trisomic for Decreased brain size; LIP1–ZNF295 region: 158 genes cellular hypoplasia; abnormal neuronal migration. Alterations in cerebellum, Ts65Dn (21q21.2–21q22.3) Trisomic for hippocampus, and cortex; MRPL39–ZNF295 region: synapses, neurotransmitters; 136 genes BFCN, learning and memory deficits Reduced cerebellar volume and Ts1Cje (21q22.11–21q22.3) Trisomic for some brain defects similar SOD1–ZNF295 region: to Ts65Dn; learning deficits 83 genes Spatial learning impairement Ms1Ts65 (21q21.2–21q21.3) Trisomic for even less severe than MRPL39–SOD1 region: Ts65Dn and Ts1Cje 53 genes Ts1Rhr (21q22.13–21q22.3) Trisomic for Altered brain volume and CBR1–MX1 region: 33 genes shape Ts2Cje (21q21.3–21q22.3) Trisomic from Decreased spines density APP- to ZNF295: 132 genes of dendrites; enlarged dendritic spines Dp(16)1Yu (21q21.1–21q22.3) Trisomic for Not identified LIP1–ZNF295 region: 158 genes. Altered cerebellar neuronal Tc1 (HSA21 with two gaps: number, synaptic plasticity, Cxadr-D21S1922; Ifnar1-Runx1) learning and memory Trisomic for 92% of HSA21 genes. ES#21 HSA21 chimaera, Trisomic for HSA21 Impairment in behaviour and genes learning Tg SOD1 SOD1 (21q22.11), superoxide dismutase, Decreased serotonin level; neuronal degeneration in key enzyme in the metabolism of brain; learning defects oxygen-derived free radicals Dystrophic neuritis associated Tg APP APP (21q21.3), b-amyloid precursor with involved congophilic protein in senile plaque formation plaques; learning defects in DS and AD Learning and memory defects Tg Synj1 SYNJ1 (21q22.11), synaptojanin 1 polyphosphoinositide phosphatase in synapses (continued)

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Table 1 (continued) Models

Human syntenic region and genes

Neurological alterations

Tg Ets2

ETS2 (21q22.2), erythroblastosis virus E26 transformation-specific transcription factor

Tg S100b

S100b (21q22.3), calcium-binding protein beta neurotrophic factor released by astrocytes

Tg Dyrk1 TgYac152F7

DYRK1A (21q22.13),Cbr1-Cldn14 (21q22.12-q22.13) containing Dyrk1A dual-specificity tyrosine-(Y)phosphorylation regulated kinase 1A SIM2 (21q22.13), single minded, transcription factor/helix-loop-helix, master regulator in CNS cell fate DSCR1 (21q22-12), Down syndrome critical region 1

Neuonal cell apoptosis; brachycephaly; neurocranial and cervical skeletal defects, Abnormal dendritic development; astrocytosis; learning and memory deficits Abnormal brain structure; increased brain weight and neuronal size; learning deficits Altered behaviour and learning deficits

Tg Sim2

Tg DSCR1

TgYac230E8

TTC3-DYRK1A (21q22.13) containing DOPEY2

Neurological phenotype; impaired working memory in null mice Increased cortical neuronal density; learning deficits

These mouse models represent powerful tools allowing a genetic dissection of the complex DS phenotype, identifying different candidate chromosomal regions, syntenic with HSA21, and candidate genes involved in mouse brain alterations, and permitting a study of the early developmental phenotypes and the molecular and cellular pathogenesis of the brain abnormalities and MR in DS. 4.1.1

Ts16 Mice: Trisomic for Most Part of HSA21 with Three Copies of Complete MMU16

Ts16 mice, the first trisomic model for DS (Epstein, 1986; Lacey-Casem & OsterGranite, 1994), carry three full copies of MMU16, which contain a region orthologous to the larger part of the HSA21 (Cox, Smith, Epstein, & Epstein, 1984; Gearhart, Davisson, & Oster-Granite, 1986). The lethality in utero observed in Ts16 mice, due to the presence of three copies of genomic regions syntenic to other human chromosomes, limited the studies to cell lines and foetal stages. Interestingly, Ts16 foetuses have a number of phenotypes similar to those seen in DS patients, including brain alterations (Behar & Colton, 2003; Cox et al., 1984; Epstein et al., 1985; Gearhart et al., 1986; Lacey-Casem & Oster-Granite, 1994). 4.1.2

Segmental Ts65Dn Mice: Trisomic for Most HSA21 Genes Conserved in Distal End of MMU16

The Ts65Dn is the first segmental trisomy model created and is the most frequently used and the greatest characterised mouse model (Davisson, Schmidt, & Akeson,

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1990). Ts65Dn mice are trisomic for most of the HSA21 orthologous genes conserved in the distal end of MMU16, extending from the gene for mitochondrial ribosomal protein L39 (Mrpl39) to the Znf295 gene, at the distal telomere (Fig. 1). Moreover, Ts65Dn mice are also trisomic for a c. 6 Mb region of chromosome 17 not syntenic to HSA21 (Akeson et al., 2001; Li et al., 2007). Ts65Dn mice display many features that are reminiscent of those seen in people with DS, particularly the neurological phenotypes, including learning and behavioural abnormalities (Sago et al., 1998, 2000). This mouse model shows delayed brain development, decreased cerebellar volume and granular cell density, decreased dentate gyrus, and abnormal synaptic plasticity (Baxter, Moran, Richtsmeier, Troncoso, & Reeves, 2000; Davisson et al., 1990; Kleschevnikov, Belichenko, Villar, Epstein, & Malenka, 2004). Ts65Dn mice also show age-related atrophy, neurodegeneration of BFCN, neurotransmitters alterations and extensive astrocyte hypertrophy, which resembles the neuropathology of AD in DS patients (Casanova et al., 1985; Cooper et al., 2001; Dierssen, Vallna, Baamonde, GarciaCalatayud, & Lumbreras, 1997; Yates et al., 1983). The abnormal learning and behavioural abnormalities, analogous to DS MR, have been demonstrated using different behavioural tests such as T-maze, Y-maze and radial maze. Ts65Dn mice also show important learning defects in the Morris water maze that is the most commonly used test for spatial learning in almost all DS mouse models, and in which the cognitive performances of the different segmental trisomy 16 mouse models can be compared. In the hidden platform test, Ts65Dn mice must learn the spatial relationships between objects in the room and the position of the platform to escape from the water. Ts65Dn mice showed increased search time compared with control and impaired performance that is not improved over successive trials indicating poor learning. In the probe test, in which the platform has been removed, the mice had learned the location of the platform and should search where the platform had been located. In this test, which assesses spatial selectivity, Ts65Dn mice showed a greater preference for the trained quadrant than control mice, providing evidence for learning. However, Ts65Dn mice spent significantly less time in the trained quadrant and crossed the trained site significantly less frequently than did controls. In the reverse platform test, the mice are required to learn a novel position for the hidden platform that has been moved to the quadrant opposite to its original location. Ts65Dn mice showed no decrease in latency, spent more time in the initial trained quadrant and showed increased time to reach the novel position of the platform. In the reverse probe dwell test, Ts65Dn mice continue to show a preference for the initial trained site. In the reverse probe crossing test, Ts65Dn mice failed to show a preference for the trained site. In these different Morris water maze tests, Ts65Dn mice show significant learning and memory deficits with a severe impairment in spatial learning and reversal, but not in visual discrimination learning and reversal (Holtzman et al., 1996; Reeves et al., 1995; Sago et al., 2000). Interestingly, the long-term potentiation (LTP) is reduced in the cornu ammonis (CA1) and dentate gyrus areas of the hippocampus in the Ts65Dn (Kleschevnikov et al., 2004; Siarey et al., 1999; Siarey, Stoll, Rapoport, & Galdzicki, 1997) and the excitatory and inhibitory inputs to pyramidal neurons in cornu ammonis (CA3) of

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the hippocampus are reduced (Hanson, Blank, Valenzuela, Garner, & Madison, 2007). This is particularly interesting since the hippocampal LTP, a form of synaptic plasticity evoked by a train of electrical stimuli, is considered a physiological model of learning and memory.

4.1.3

Segmental Ts1Cje Mice: Trisomic for Three-Quarters of Genes of Ts65Dn, Including DSCR

The Ts(16C-tel)1Cje, or Ts1Cje, present a smaller extra segment of MMU16 than that of the Ts65Dn mice. This mouse model, generated by a fortuitous translocation during the targeting of Sod1 by homologous recombination, carries the translocation from the proximal break-point in Sod1, that is not functional, to Znf295 (Sago et al., 1998) (Fig. 1). The Ts1Cje mouse is trisomic for about three-quarters of the genes that are present in the Ts65Dn mouse. Ts1Cje mice have similar phenotypes to Ts65Dn, often with lower intensity, and fewer similarities to DS than do Ts65Dn mice, but they are important to study the particular effects of trisomy for a subset of genes triplicated in Ts65Dn and not in Ts1Cje. In particular, the neurological phenotypes in Ts1Cje are similar to those observed in Ts65Dn, such as the reduced volume and granule cell of the cerebellum (Olson, Roper et al., 2004) and the reduced LTP in the CA1 and dentate gyrus areas of the hippocampus (Siarey, Villar, Epstein, & Galdzicki, 2005). Ts1Cje mice also show behavioural abnormalities in the Morris water maze tests. These mice displayed moderate to severe impairment in the hidden platform and probe parts of the test. In the reverse platform test, they showed a decrease in latency over the trials of the test, but the rates of decrease were significantly less than the controls and they were not significantly better than Ts65Dn. There was no preference of the trained quadrant in the reverse probe dwell test and Ts1Cje did significantly better than Ts65Dn in reverse crossing and dwell tests (Sago et al., 1998, 2000). Comparison of the behavioural performances of the Ts1Cje and Ts65Dn in the Morris water maze showed that, except in the reverse probe tests, the learning deficits of Ts1Cje mice are similar to those of Ts65Dn. These findings indicate that an important gene or genes involved in these deficits lie in the overlapping region in these mice, from Sod1 to Mx1, and containing the critical region DSCR.

4.1.4

Segmental Ms1Ts65 Mice: Trisomic for Non-DSCR Genes of Ts65Dn and Missing from Ts1Cje

Ts65Dn mice, produced by reciprocal translocation T(17;16)65Dn, and Ts1Cje mice, carrying the reciprocal translocation T(12;16)1Cje, have been mated to produce offspring called Ms1Cje/Ts65Dn, or Ms1Ts65, that are trisomic for the genes present in Ts65Dn and missing from Ts1Cje, corresponding to the segment from MRPL39 to SOD1 (Fig. 1) (Sago et al., 2000).

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These segmental trisomic mice have fewer similarities to DS than do Ts65Dn and Ts1Cje mice. In Ms1Ts65 mice, a neurological alteration has been identified at the cerebellar level, in which the granule cell density is moderately reduced similarly to Ts1Cje compared to Ts65Dn mice, which show significant reduction (Baxter et al., 2000; Olson, Roper et al., 2004). The spatial learning and memory performances of Ms1Ts65 mice, tested by the Morris water maze (Sago et al., 2000), showed reduced latencies in the hidden platform test. In the probe test, the performance of Ms1Ts65 mice was similar to the controls. In the reverse platform test, mice such as Ts1Cje and Ms1Ts65showed a decrease in latency, but the rates of decrease were significantly less than the controls. Although the difference in latency between Ms1Ts65 and Ts1Cje was not statistically significant, Ms1Ts65 was significantly better than Ts65Dn whereas Ts1Cje was not. In the reverse probe dwell test, Ms1Ts65 was also significantly better than Ts65Dn in reverse crossing and dwell tests (Sago et al., 2000). Compared with controls, Ms1Ts65 mice show significant deficits in the latencies of the hidden and reverse hidden platform tests, but not in the probe tests. These results indicate that Ms1Ts65 has little impairment in learning the task in the Morris water maze compared with controls, while their deficits are significantly less severe than those of Ts65Dn. Therefore, whereas triplication of the region from Sod1 to Mx1 plays a major role in the abnormalities of Ts65Dn in the Morris water maze, triplication of the region from App to Sod1 also contributes to the poor performance.

4.1.5

Segmental Ts1Rhr and Ms1Rhr Mice: Trisomic and Monosomic for DSCR

A duplication, Dp(16Cbr1-Mx1)1Rhr, or Ts1Rhr, and a deletion, Ms1Rhr (Fig. 1), of the MMU16 segment between Cbr1 and Mx1 genes have been created using Cre-loxP and ES cell technologies (Olson, Richtsmeier, Leszl, & Reeves, 2004). These mice provide trisomy and monosomy, respectively, for a smaller segment of MMU16 that is orthologous to the critical region DSCR of HSA21 responsible for many of the features of the DS, including craniofacial abnormalities and MR. Ts1Rhr mice have less severe craniofacial dysmorphology than either Ts1Cje or Ts65Dn (Olson, Richtsmeier et al., 2004). Both Ts1Rhr and Ms1Rhr mice show changes in volume and shape of both cerebrum and cerebellum, but different from each other and from Ts65Dn mice (Aldridge, Reeves, Olson, & Richtsmeier, 2007). In contrast, the performances of these two mouse models in the Morris water maze were similar to euploid mice (Olson et al., 2007).

4.1.6

Segmental Ts2Cje Mice: Trisomic from APP to the Telomere

Ts{Rb[12.17(16)]}2Cje mice, or Ts2Cje (Fig. 1), carry a chromosomal rearrangement of the Ts65Dn genome whereby the marker chromosome has been translocated to chromosome 12 forming a Robertsonian chromosome. This stable rearrangement

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confers fertility in males and increases the frequency of transmitted segmental trisomy through the female germline. Like Ts65Dn mice, Ts2Cje mice are about 20% smaller in size postnatally compared with euploid control littermates, and this smaller size persists throughout life (Villar et al., 2005). This trisomic model retains a dosage imbalance of HSA21 homologous genes from App to the telomere and expression levels similar to Ts65Dn within the triplicated region. Similarly to Ts65Dn mice, significant decreases in the density on the dendritic spine of dentate granule cell neurons and enlarged dendritic spines are observed in the Ts2Cje mice (Villar et al., 2005). Ts2Cje mice exhibit neurologica1 features comparable with those of Ts65Dn mice, thereby validating the utility of this segmental trisomy model for the study of the molecular, genetic and developmental mechanisms underlying DS.

4.1.7

Segmental Dp(16)1Yu Mice: Trisomic from LIP1 to ZNF295

To generate a more complete trisomic mouse model of DS, a duplication has been established recently spanning the entire HSA21 syntenic region on MMU16 in mice using Cre/loxP-mediated long-range chromosome engineering. This new DS mouse model carries a chromosomal duplication, Dp(16)1Yu (Fig. 1), spanning 22.9 Mb of the complete HSA21 syntenic region 21q11q22.3 of the MMU16, delimited by the mouse orthologs of LIP1 and ZNF295 genes (Li et al., 2007). The analysis of several genes located within Dp(16)1Yu in the brain and heart tissues showed that the segmental trisomy altered the transcript levels of the genes in the brain and heart of the Dp(16)1Yu/+ model, reflecting the dosage imbalance for the duplicated region. This result supports the conclusion that the duplicated genes are expressed with the exception for transcriptionally inactive genes. About 37% of Dp(16)1Yu/+ embryos exhibit structural heart defects, and about 26 and 22% of Dp(16)1Yu/+ embryos exhibit annular pancreas and malrotation of the intestine, respectively. These phenotypes are also observed in patients with DS at higher frequencies than normal individuals. The cardiovascular and gastrointestinal phenotypes of the mouse model were similar to those of patients with DS. This new mouse model is particularly interesting because of the largest duplication of the HSA21 syntenic region and its stability, and it represents a powerful tool to further understand the molecular and cellular mechanisms of DS.

4.1.8

Transchromosomal ES(#21) Mice: Trisomic for a Large Part of HSA21

To maximally mimic the DS phenotypes, transchromosomal mouse models, carrying a HSA21 or a large part of it, have been generated (Fig. 1). These mouse models, containing an additional entire or partial HSA21, have been developed using a microcell-mediated chromosome transfer approach (MMCT) (Shinohara et al., 2001). The initial transchromosomic mouse model was obtained by transferring a

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HSA21 into mouse ES cells. ES cell lines retaining HSA21 as an independent chromosome were used to produce chimeric mice with a substantial contribution from HSA21-containing cells. Chimeric mice derived from these cells, named ES(#21), in which a high percentage of cells contained a HSA21, demonstrated specific parallels to developmental anomalies seen in DS and a wide range of behavioural abnormalities indicating abnormal brain development and function. Interestingly, these mice present similar phenotypes to those observed in DS, such as thymus and cardiac defects, impairment in learning or emotional behaviour found in open-field, contextual conditioning and forced swim (Shinohara et al., 2001). The high correlation between retention of HSA21 in the brain and behavioural and cognitive alterations found in these transchromosomal mice make them good models to study the complex and critical aspects of DS phenotype, because they provide the complete set of genes that are in dosage imbalance in human with trisomy 21. Further, these genes are introduced in mice into the context of their native cis-acting regulatory elements and chromatin structures; this maximises temporal and tissue-specific gene expression and function under physiologically appropriate conditions.

4.1.9

Transchromosomal TC1 Mice: Trisomic for Almost HSA21 (92% of HSA21 Genes)

Another transchromosomal mouse model, Tc1, has been generated containing an almost complete HSA21 with only two deletions. This mouse model represents the most complete animal model for DS currently available and carrying 92% of human genes (Fig. 1) (O’Doherty et al., 2005). Tc1 mice showed alterations in cerebellar neuronal number, in heart development, and in mandible size. In addition, they have impaired short-term recognition memory and display reduced LTP in the dentate gyrus of the hippocampus, as well as showing a deficit in a novel-object recognition task (O’Doherty et al., 2005). Thus, Tc1 display many aspects of human DS but also recapitulate several of the DS features present in other mouse models (Reeves, 2006). Tc1 mice also have impaired spatial working memory but preserved long-term spatial reference memory in the Morris water maze (Morice et al., 2008). These mice showed a loss of the HSA21 from about 50% of the cells in adult mice, determining a high degree of mosaicism. The effect of this mosaicism may be different in the individuals and contributes to the variability of the phenotype. Therefore, unlike other segmental DS mouse models, Tc1 mice are also trisomic for orthologous genes on mouse chromosomes 10 and 17, consisting of a condition more similar to the trisomy 21 in human (O’Doherty et al., 2005).

4.1.10

Segmental Transgenic Mouse In Vivo Library of Human DSCR

The identification of the critical region DSCR and its association to MR suggests that this major and invariable DS trait arises from triplication of one or few genes

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located in the DSCR. Interestingly, several genes located in the DSCR are involved in brain development and function and the overexpression of these critical genes determine cognitive alterations. In vivo libraries of large insert transgenic mice offer an approach to study the contribution of a genomic region to complex quantitative traits. These mice are frequently transgenic for many genes and, thus, it is possible to investigate the cumulative effects of these genes upon one biological phenotype at a time, allowing multiplex analysis of the relationship between genotype and phenotype. Phenotypic and functional analysis of the in vivo library members could be used to define candidate genes for further analysis in human populations enabling association rather than linkage studies (Risch and Merikangas, 1996) to be employed in the identification of genes contributing to complex traits such as the MR in DS. In this way, transgenic mice containing large fragments of the DSCR have been constructed (Smith et al., 1997; Smith, Zhu, Zhang, Cheng, & Rubin, 1995). The human genome fragments are 4 YACs, 230E8, 152F7 141G6 and 285E6, spanning 2 Mb of the DSCR (Dufresne-Zacharia et al., 1994; Smith et al., 1995). This panel of YAC transgenic mice propagating targeted megabase regions of the genome constitutes an in vivo library allowing genotype/phenotype comparison studies (Fig. 1). The transgenic lines, carrying the YAC 152F7, containing six genes including TTC3 and dual-specificity tyrosine-(Y)-phosphorylation kinase 1A (DYRK1A) genes, show an increase of brain size and neuronal sizes (Branchi et al., 2004; Rachidi et al., 2007), and exhibit severe spatial learning and memory defects (Smith et al., 1997). The transgenic lines, carrying the YAC 230E8, containing seven genes of the DSCR region, including DOPEY2 gene, present increased cortical cell density (Rachidi, Lopes, Costantine et al., 2005; Smith et al., 1997), and increased length of the anterior lobules of the cerebellar vermis (Rachidi et al., 2007), and exhibit spatial learning and memory defects (Smith et al., 1997). The 141G6 mice showed a lower performance in fearconditioning against sound as acoustic conditional stimulus (Chabert et al., 2004), although any evident neuroanatomical and cognitive defects have not yet been demonstrated in the 141G6 mice (Smith et al., 1997). Finally, the performances of transgenic lines carrying YACs 285E6 are not significantly different from the controls, and no detectable neurological defects have been found (Smith et al., 1997). It is of greatest interest to dissect the role of these critical genes of DSCR, by separate analysis and study of their different combinations, to better understand the function of each gene or cooperation of gene groups, in neurological alterations and in learning and memory processes.

5

Genetic Dissection of the Role of the Down Syndrome Critical Region in Mental Retardation

In human, although the concept of the involvement of the critical region DSCR in the principal phenotypes of DS is largely accepted, its delimitation is not completely defined (Delabar et al., 1993; Korenberg et al., 1994; Rahmani et al., 1989), and its existence was rarely controversial (Shapiro & Whither-Azmitia, 1997).

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The genotype/phenotype comparison approach has been applied to the mouse, and different mouse models have been generated allowing the evaluation of the role of the DSCR in DS pathogenesis, particularly in the MR. In a first approach, a transgenic mouse in vivo library has been developed, as described above, by inserting human YACs bearing different fragments of the human DSCR into the murine genome (Smith et al., 1995). The neuroanatomical alterations and defects in learning and memory observed in particular in two transgenic lines (152F7 and 230E8 YAC transgenic mice) indicate that these HSA21 fragments of the DSCR are critical for brain alterations and learning and memory defects, and that the correct dosage of critical genes of these DSCR fragments are crucial for brain function and cognitive impairment (Rachidi et al., 2007; Rachidi, Lopes, Costantine et al., 2005; Smith et al., 1997), in agreement with an important role of the critical region DSCR in neuronal and cognitive alterations observed in DS patients. In an other approach, three other mouse models have been generated: Ts1Rhr mice trisomic for DSCR; Ms1Rhr mice with deleted DSCR; and Ms1Rhr/Ts65Dn mice obtained by breeding Ms1Rhr with Ts65Dn mice, trisomic for genes triplicated in Ts65Dn but not in the DSCR (Olson, Richtsmeier et al., 2004; Olson et al., 2007). Initially, the authors tested the association of craniofacial phenotypes to DSCR and found that three copies of DSCR alone are not sufficient to generate these phenotypes. Moreover, reducing trisomy of the DSCR to disomy in the Ts65Dn mice did not eliminate this phenotype, indicating that the DSCR is also not necessary to generate the cranio-facial phenotypes in mice (Olson, Richtsmeier et al., 2004). Recently, these studies have been extended to test the role of the DSCR in hippocampal function, learning and memory (Olson et al., 2007). Unlike Ts65Dn and Ts1Cje mice, no LTP impairment is detected in the CA1 hippocampal area of Ts1Rhr mice, consistent with the normal spatial learning in the Morris water maze showed by these mice. Thus, trisomy for DSCR is not sufficient to produce deficits in this hippocampal-based task (Olson et al., 2007). Ms1Rhr/Ts65Dn mice, with disomic DSCR, show identical performances to euploid in the Morris water maze. This indicates that the restoration of disomy of DSCR in trisomic mice rescues the spatial learning and memory performance, demonstrating that trisomy of DSCR is necessary for this cognitive phenotype (Olson et al., 2007). Thus, in contrast to the craniofacial phenotype, the combination of the behavioural results of Ts65Dn, Ts1Rhr and Ms1Rhr/Ts65Dn mice show that DSCR is necessary although not sufficient to determine the hippocampal dysfunction seen in Ts65Dn mice (Olson et al., 2007).

6

Transgenic Mouse Models of Down Syndrome

Contrary to segmental trisomic mice imitating the genetic complexity seen in trisomy 21 with eventual interactions between different genes present at three copies, the transgenic mouse models overexpress one or a few genes and allow a direct genotype/ phenotype correlation. The other interesting kinds of mouse models of DS are the transgenic monogenic mouse models that have been generated to study the effect of cell-specific and

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stage-specific overexpression of a unique gene. These mice (Table 1; Fig. 1) include models for overexpression of the Cu-Zn superoxide dismutase1 (SOD1 gene), the neurotrophic factor (S100B gene), the beta amyloid peptide (APP gene), the transcription factor (ETS2 gene), the Drosophila minibrain homolog (DYRK1A gene), and the transcription factor single minded (SIM2 gene), the regulator of calcineurin (RCAN1 or DSCR1 gene), the C21orf5 or (DOPEY2 gene), the tetratricopeptide repeat domain 3 (or tetratricopeptide repeat domain Down syndrome [TPRD] gene), the potassium inwardly rectifying channel (KCJN6 gene), the inersectin (ITSN1 gene), and the synaptoganin (SYNJ1 gene). These transgenic mice showed overexpression of some genes in the key brain regions that play crucial roles in cognitive functions and that were found altered in the brain of DS patients. Moreover, for most of these genes, mouse models overexpressing them have an impaired behaviours and cognitive defects. These transgenic mouse models allow the dissecting of the phenotypic consequences of imbalances that affect single genes and have greatly enhanced our understanding of the cellular and biochemical mechanisms of gene dosage effects involved in the developmental brain alterations and in the MR in DS.

7

Candidate Genes and Genotype/Phenotype Correlation for Mental Retardation in Down Syndrome

The final goal of genetic dissection is the identification of the gene(s) responsible of each phenotypic trait in DS. To date, several HSA21 genes have been identified as candidates for neurological alterations and MR in DS (Table 2), on the basis of different criteria. All these candidate genes show a strong expression in the key brain regions that play crucial roles in cognitive functions and that were found altered in the brain of DS patients. They are overexpressed in the brain of DS patients and/or in DS mouse models. Moreover, for most of these genes, mouse models overexpressing them have impaired behaviours and cognitive defects, similar to those observed in DS patients. Consequently, studies of these candidate genes and of the effects of their overexpression may help the understanding of the developmental brain alterations and the MR in DS.

7.1

Cu-Zn Superoxide Dismutase (SOD1) Gene

SOD1 gene encodes the Cu-Zn superoxide dismutase, a key enzyme in the metabolism of oxygen-derived free radicals. SOD1 product levels, both mRNA and protein, are increased in human and mouse trisomic tissues (Epstein et al., 1987; Kadota et al., 2004; Lyle et al., 2004; Mao et al., 2005; Saran et al., 2003). Mice lacking SOD1 develop subtle motor symptoms by approximately 6 months of age, in which motor unit numbers are reduced early but decline slowly with age, suggesting that axonal sprouting are functionally impaired in the absence of SOD1 (Shefner et al., 1999).

Table 2 HSA21 genes over-expressed in Down syndrome brain and candidates for mental retardation Genes Brain regions References APP (amyloide beta A4) Cortex, midbrain cerebellum Epstein (2001), Saran et al. (2003), Lyle et al. (2004), and Kahlem et al. (2004) SOD1 (superoxide dismutase 1) Cortex, midbrain cerebellum Saran et al. (2003), Lyle et al. (2004), Kadota et al. (2004), and Mao et al. (2005) SYNJ1 (synaptojanin 1) Cortex, midbrain cerebellum Arai et al. (2002) and Lyle et al. (2004) ITSN1 (intersectin 1) Cortex, cerebellum Pucharcos et al. (1999), Amano et al. (2004), and Lyle et al. (2004) DSCR1 (calcipressin 1) Cortex, midbrain cerebellum Fuentes et al. (2000), Amano et al. (2004), Lyle et al. (2004), and Dauphinot et al. (2005) DOPEY2 (DOPEY2/C21orf5) Cortex, cerebrum Lopes et al. (2003), Lyle et al. (2004), and Rachidi, Lopes, Costantine et al. (2005) SIM2 (single-minded 2) Midbrain Vialard et al. (2000) and Lyle et al. (2004) TTC3 (tetratricopeptide repeat domain 3) Cerebrum, cerebellum Saran et al. (2003), Amano et al. (2004), and Lyle et al. (2004) DYRK1A (dual-specificity tyrosine-(Y)Cortex, midbrain cerebellum Saran et al. (2003) and Lyle et al. (2004) phosphorylation kinase) KCNJ6 (potassium inwardly-rectifying Cortex, midbrain Saran et al. (2003), Lyle et al. (2004), and Kahlem et al. channel J6) (2004) Ets2 (v-ets erythroblastosis virus E26) Cortex, cerebrum, cerebellum Saran et al. (2003), Lyle et al. (2004), and Dauphinot et al. (2005) DSCAM (Down syndrome cell adhesion Cortex, midbrain cerebellum Saran et al. (2003), Lyle et al. (2004), and Kahlem et al. molecule) (2004) Cortex Griffin et al. (1998) and Epstein (2001) S100b (S100 calcium-binding protein b)

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The transgenic mice containing human SOD1 had 1.6–6-fold increased enzyme activity as compared to control, associated with decreased plasma serotonin levels and serotonin accumulation rate in transgenic mouse platelets (Epstein et al., 1987), a phenomenon similar to that reported in DS. Human SOD1 transgenic mice show impairment in the ability to adjust their posture in response to a moving surface and show mild deficits in sensori-motor responsiveness (Lalonde, Dumont, Paly, London, & Strazielle, 2004; Lalonde, Le Pecheur, Strazielle, & London, 2005). The overexpression of Sod1 in transgenic mice leads to an impairment in LTP (Gahtan, Auerbach, Groner, & Segal, 1998) and defects in distal motor neuron terminals, indicating that this gene can selectively affect motor neurons (Avraham, Sugarman, Rotshenker, & Groner, 1991; Gurney et al., 1994). Moreover, these transgenic mice showed decreased cell number in several brain areas and decreased LTP in the pyramidal neuron CA1 (Harris-Cerruti et al., 2004; Zang et al., 2004). Premature ageing, one of the characteristics of DS that contributes to decreased cognitive performance in DS adults, may involve oxidative stress and impairment of proteasome activity. Transgenic mice overexpressing the human SOD1 gene show a reduction in proteasome activities in the cortex and an associated increase in the content of oxidised SOD1 protein (Le Pecheur et al., 2005). These results suggest a role of this gene in development of axons and motor neurons.

7.2

Amyloid Precursor Protein (APP) Gene

Amyloide precursor protein (APP) gene encodes the beta-amyloid precursor protein, a protein involved in senile plaque formation in DS and AD (Kang et al., 1987). APP is widely expressed in axons, dendrites, and synapses in both central and peripheral nervous systems. In DS and Ts65Dn, APP is expressed at more than the expected 1.5-fold (Epstein, 2001; Hunter et al., 2003; Kahlem et al., 2004; Lyle et al., 2004), suggesting that other genes on HSA21 directly or indirectly can further up-regulate the APP gene. The transgenic mice TgAPP exhibited overexpression of APP in the neocortex and hippocampus region mimicking features of DS. These amyloid precurseur protein transgenic models with AD-like pathology showed dystrophic neuritis associated with congopholic plaques (Sturchler-Pierrat et al., 1997) and also showed learning defects (Lamb et al., 1993). APP transgenic mice have been tested in the Morris water maze tests and they show impairment in the probe test, measuring the reference memory, and impaired performance in the reverse probe test, measuring the spatial working memory (Janus, 2004). APP-null mice show impairment in the formation of LTP in the CA1 hippocampal region, and paired-pulse depression of GABA-mediated inhibitory post-synaptic currents is also attenuated, indicating that the impaired synaptic plasticity in APP deficient mice is associated with abnormal neuronal morphology and synaptic function within the hippocampus (Seabrook et al., 1999). Hippocampal neurons lacking APP show significantly enhanced amplitudes of evoked AMPA- and N-methyl-d-aspartate

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(NMDA)-receptor-mediated excitatory postsynaptic currents (EPSCs), and increased size of the readily releasable synaptic vesicle pool, indicating that lack of APP increases the number of functional synapses (Priller et al., 2006). These findings suggest a role of APP in the neurophysiology of AD and DS.

7.3

v-ets Erythroblastosis Virus E26 (ETS2) Gene

The HSA21 protooncogene ETS2 encodes a transcription factor ETS2 (Watson et al., 1985), and alteration of its expression has been implicated in the pathophysiological features of DS. ETS2 is expressed in neurons and is crucial for the normal formation of the neuromuscular junction (de Kerchove et al., 2002), and ETS2 is overexpressed in trisomic tissues (Dauphinot et al., 2005; Lyle et al., 2004; Saran et al., 2003). Null mice homozygous for mutation of ETS2 are embryonic lethal and show trophoblast alteration (Yamamoto et al., 1998). Transgenic mice overexpressing ETS2 develop neurocranial and cervical skeletal abnormalities (Sumarsono et al., 1996), similarly to trisomy 16 mice and DS patients. The overexpression of ETS2 induces neuronal apoptosis, suggesting that overexpression of ETS2 may contribute to the increased rate of apoptosis of neurons in DS (Wolvetang, Bradfield, Hatzistavrou et al., 2003). It has been found that ETS2 protein transactivates APP gene and that fibroblasts overexpressing ETS2 show molecular abnormalities seen in DS such as elevated expression of APP gene and increased beta-amyloid proteins (Wolvetang, Bradfield, Tymms et al., 2003). These findings suggest that ETS2 overexpression in DS determines overexpression of APP and may play a role in the pathogenesis of the brain abnormalities in Alzheimer disease and DS.

7.4

S100 Calcium Binding Protein B (S100B) Gene

S100B is a calcium-binding protein synthesised and released by astrocytes in response to serotonin (5-HT)-mediated stimulation of 5-HT1A receptors, and is an important extracellular neurotrophic agent during normal foetal brain development, with effects on neuroblasts and glia, involving the neuronal cytoskeleton (Azmitia, Griffin, Marshak, Van Eldik, & Whitaker-Azmitia, 1992; Morii et al., 1991). It has been found that S100b null mice develop normally, with no evident alterations in the cytoarchitecture of the brain. However, they have enhanced LTP in the hippocampal CA1 region and also enhanced spatial memory in the Morris water maze tests and fear memory in the contextual fear conditioning. These results indicate that S100b is a glial modulator of neuronal synaptic plasticity and of information processing in the brain (Nishiyama, Knopfel, Endo, & Itohara, 2002). The S100B RNA and protein are overexpressed in DS brain and Alzheimer disease (Epstein, 2001; Griffin et al., 1998). Transgenic mice overexpressing mouse

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S100b or human S100B show changes in cytoskeletal markers, such as the dendritic-associated protein, MAP-2, the growth-associated protein-43 and the dendritic spine marker, drebrin, leading to an increased density of dendrites within the hippocampus (Shapiro and Whitaker-Azmitia, 2004). Interestingly, drebrin protein is decreased in DS and AD brain regions (Kojima & Shirao, 2007; Shin & Lubec, 2002). Alterations have also been found in astrocyte morphology and axonal sprouting, especially in the dentate gyrus of the S100B transgenic mice (Bell, Shokrian, Potenzieri, & Whitaker-Azmitia, 2003; Reeves et al., 1994; Shapiro & WhitakerAzmitia, 2004). Mice overexpressing S100B show decreased spatial learning and memory in the Morris water maze, radial-arm maze and Y-maze (Bell et al., 2003; Gerlai & Roder, 1996; Whitaker-Azmitia et al., 1997; Winocur, Roder, & Lobaugh, 2001). These results suggest that S100B overexpression contributes to glial-neuronal interactions, dendritic abnormalities and MR in DS.

7.5

Dual-Specificity Tyrosine Y Kinase 1 Subunit A (DYRK1A) Gene

DYRK1A has been initially identified as the human homolog of the Drosophila minibrain gene, MNB, and is involved in neuroblast proliferation and reduction of the adult Drosophila brain (Tejedor et al., 1995). DYRK1A encodes a serinethreonine kinase (Kentrup et al., 1996). DYRK1A is expressed in the cortex, hippocampus and cerebellum (Guimera, Casas, Estivill, & Pritchard, 1999; Guimera et al., 1996; Rahmani, Lopes, Rachidi, & Delabar, 1998) and is overexpressed in mouse trisomic model Ts65Dn (Guimera et al., 1999), in DS foetal brain and in other trisomic tissues (Lyle et al., 2004; Saran et al., 2003). The Dyrk1A mutant mice are lethal during gestation. The heterozygote mice (Dyrk1A+/−) show a decreased size in several brain regions, a decreased neuronal cell number in the superior colliculus, an increased neuronal density in the cortex and in the thalamus, and exhibit neurobehavioural delays and defects (Fotaki et al., 2002). At cellular level, Dyrk1A+/− mice show smaller size of the pyramidal cell somata, shorter dendritic length, lower spine number, and altered spine distribution, suggesting the implication of Dyrk1A in the capability of the pyramidal cells to integrate information (Benavides-Piccione et al., 2005). Two transgenic mouse models overexpressing DYRK1A have been generated. The first one carried a human YAC 152F7, containing DYRK1A (Smith et al., 1995), while the second carried the full-length DYRK1A cDNA (Altafaj et al., 2001). In the Morris water test, the transgenic lines carrying the YAC 152F7 showed lower performance in the probe test, in which the platform is removed. In the reverse learning paradigm, the transgenic mice showed the most severe deficits with no significant learning of the new platform position, indicating deficits in learning flexibility (Smith et al., 1997). A mouse line carrying a 152F7 YAC fragment (152F7tel) containing only the DYRK1A gene showed the same phenotype to the original YAC lines demonstrating that the overexpression of DYRK1A

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is responsible for the learning and memory defects in these mice (Smith et al., 1997). Moreover, these transgenic mice showed increased brain size and neuronal size (Branchi et al., 2004; Rachidi et al., 2007). The significant impairment in spatial learning and memory observed in the two mouse models overexpressing DYRK1A indicates that the correct dosage of DYRK1A gene is crucial for brain hippocampal and prefrontal cortex functions, particularly concerning a cognitive dysfunction of the reference memory (Altafaj et al., 2001; Smith et al., 1997). Moreover, the transgenic mice overexpressing Dyrk1A exhibit neurodevelopmental defects, delayed craniocaudal maturation and motor dysfunction (Altafaj et al., 2001; Fotaki et al., 2002). Recently, DYRK1A bacterial artificial chromosome (BAC) transgenic mice have also shown learning and memory defects (Ahn et al., 2006). In addition, these mice showed abnormal LTP and long-term depression (LTD), suggesting synaptic plasticity alteration (Ahn et al., 2006). These phenotypes are comparable with those found in murine models of DS with trisomy of chromosome 16, and suggest a causative role of DYRK1A in MR in DS patients. Dyrk1A proteins are transported through the neuron dendrites and regulate their development (Hammerle et al., 2003), as also demonstrated by the overexpression of a kinase-deficient DYRK1A that impedes neurite outgrowth (Yang, Ahn, & Chung, 2001). Moreover, DYRK1A is co-localised in dendrites with Dynamin 1 (DYN1), a GTPase putative substrate of DYRK1A, involved in synaptic vesicle recycling, membrane trafficking and neurite outgrowth (Chen-Hwang, Chen, Elzinga, & Hwang, 2002; Hammerle et al., 2003). Dyrk1A proteins also modulate the activity of the CREB, which participates in signal transduction pathways involved in synaptic plasticity and neuronal differentiation (Hammerle et al., 2003). DYRK1A is involved in several pathways and it has recently been demonstrated that it can influence the NFATc pathways through its kinase activity (Arron et al., 2006; Gwack et al., 2006).

7.6

Single-Minded (SIM2) Gene

SIM2, the first gene identified in the DSCR region (Dahmane et al., 1995), shows a high homology with the Drosophila single minded gene, sim, encoding a transcription factor/helix-loop-helix protein (Crews, Thomas, & Goodman, 1988). The Drosophila sim is a master gene of the midline development in the central nervous system, functioning as transcriptional regulator in cell fate determination (Crews et al., 1988; Nambu, Lewis, Wharton, & Crews, 1991; Thomas, Crews, & Goodman, 1988). The mammalian Sim2 is expressed in the embryonic brain in delimited regions of the neuroepithelium of D1 and D2 neuromeric regions and along the neural tube (Dahmane et al., 1995; Ema et al., 1996; Fan et al., 1996; Rachidi, Lopes, Charron et al., 2005). In later human foetal stages, SIM2 gene expression is found at different levels in discrete human brain regions, including the cortical layers, the hippocampus and the cerebellum (Rachidi, Lopes, Charron et al., 2005), which are key regions

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involved in learning and memory, and are also altered in DS patients (Golden & Hyman, 1994; Ito, 2002; Milner et al., 1998; Miyashita, 2004; Raz et al., 1995). Sim2 is overexpressed about 1.5-fold in Ts1Cje mouse foetuses (Vialard et al., 2000) and in trisomic tissues (Lyle et al., 2004). Transgenic mice overexpressing Sim2 display reduced sensitivity to pain and mild impairment of learning (Chrast, Scott, Papasavvas et al., 2000; Ema et al., 1999). These behavioural anomalies found in the Sim2 transgenic mice recall some phenotypes observed in trisomic mouse models for DS, Ts65Dn and Ts1Cje (Coussons-Read & Crnic, 1996; Martinez-Cue et al., 1999; Sago et al., 1998), and in DS patients (Hennequin, Morin, & Feine, 2000). Sim2 mutant mice are lethal in the early post-natal days and show skeletal alteration due probably to cell proliferation defects (Goshu et al., 2002). Functional studies indicated that SIM2 protein control the Shh expression in the brain (Epstein et al., 2000), involved in cell growth and differentiation in the brain. Moreover, SIM2 can inhibit cell cycle by inhibition of cyclin E expression (Meng, Shi, Peng, Zou, & Zhang, 2006) suggesting a key role of SIM2 in neulogical alterations seen in DS.

7.7

Regulator of the Calcineurin (RCAN1) Gene

Also called Down syndrome critical region 1 gene (DSCR1) or myocyte-enriched calcineurin-interacting protein 1 (MCIP1) or calcipressin 1 (CSP1), the regulator of the calcineurin 1 protein (RCAN1) gene directly modulates the activity of the protein phosphatase, calcineurin. The CSP1, the protein encoded by DSCR1, interacts with calcineurin A (Fuentes et al., 2000) to inhibit calcineurin activity (Rothermel, Vega, & Williams, 2000). DSCR1 is highly expressed in brain and heart (Fuentes et al., 1995). It is overexpressed in the brain of DS foetuses (Fuentes et al., 2000), in brains from DS patients with AD symptoms (Ermak, Morgan, & Davies, 2001), and in the brain of DS mouse models (Amano et al., 2004; Dauphinot et al., 2005; Lyle et al., 2004). It has been observed that the calcineurin activity is decreased in AD (Ladner, Czech, Maurice, Lorens, & Lee, 1996), in DS foetal brain tissue, and in Drosophila mutants that overexpress DSCR1 (Chang, Shi, & Min, 2003). As DSCR1 is an inhibitor of calcineurin activity, it is possible that these changes could be caused by increased levels of DSCR1, as occurs in DS, promoting the development of AD. Indeed, overexpression of DSCR1 in rat primary neurones causes formation of aggresome-like inclusion bodies similar to those observed in DS and AD brains, as well as reducing the expression of the synaptic vesicle protein, synaptophysin, in neural processes (Ma et al., 2004). Interestingly, loss-of-function and overexpression of mutants of nebula, the Drosophila orthologue of DSCR1, both display severe learning defects in several basic learning assays, indicating that DSCR1 may affect regulatory pathways of synaptic transmission (Chang et al., 2003). In agreement with this indication, forebrain-specific knock-out of calcineurin in mice results in impaired hippocampal-dependent memory tasks and synaptic plasticity (Zeng et al., 2001). DSCR1/Mcip1−/− mice have an impaired cardiac hypertrophic response to

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pressure overload, suggesting that this gene may also function as a calcineurin facilitator in vivo (Vega et al., 2003). Mice deficient in Mcip1/2 show more dramatic impairment in cardiac hypertrophy than the DSCR1−/−. Moreover, these DSCR1 knock-out mice displayed a neurological phenotype and showed faster overall movements in an open field test and a significant impairment in working memory, as assessed by novel and familiar object recognition analysis (Sanna et al., 2006). Recently, DSCR1 has also been demonstrated to play a role in memory and synaptic plasticity by examining the behavioural and electrophysiological properties of DSCR1 knock-out mice (Hoeffer et al., 2007). These mice exhibit deficits in spatial learning and memory, reduced associative cued memory, and impaired latephase long-term potentiation (L-LTP), phenotypes similar to those of transgenic mice with increased calcineurin activity. Consistent with this, the DSCR1 knock-out mice display increased enzymatic calcineurin activity, increased abundance of a cleaved calcineurin fragment, and decreased phosphorylation of the calcineurin substrate dopamine and cAMP-regulated phosphoprotein-32. These findings suggest that DSCR1 regulates LTP and memory via inhibition of phosphatase signalling (Hoeffer et al., 2007).

7.8

DOPEY2 Gene

C21orf5 gene, that we recently renamed DOPEY2 following HUGO nomenclature, is a member of the Dopey family containing leucine zipper-like domains involved in multiple protein–protein interactions (Rachidi, Lopes, Costantine et al., 2005). DOPEY2 is more highly expressed in the differentiating zones than in the proliferating zones in embryonic human and mouse brain (Lopes et al., 2003; Rachidi et al., 2006), suggesting a role of DOPEY2 in cell differentiation and developmental patterning. This potential role is also supported by the high homology of DOPEY2 with the Caenorhabditis elegans Pad-1, required for embryonic patterning during gastrulation (Guipponi et al., 2000), the yeast Dop1 and DopA, required for normal growth patterning, and cell differentiation and organogenesis in fungi (Dujon, 1996; Pascon & Miller, 2000). DOPEY2 expression becomes restricted to cerebellum, cortex and medial temporal-lobe system during foetal development and in adult brain (Lopes et al., 2003; Rachidi et al., 2006), in which this gene shows different transcriptional intensities, as demonstrated by an improved new optic technology allowing comparison of the cell density and the expression intensity (Rachidi et al., 2006). These findings are of the most interest because the medial temporal-lobe system, including the hippocampal formation and perirhinal cortex, works as a control centre of the memory circuits and storage (Krasuski, 2002; Milner et al., 1998) and also, the cortex and the cerebellum participate in elaboration of memory (Ito, 2002; Miyashita, 2004). DOPEY2 is expressed in brain regions that play key roles in learning and memory and present neuronal alterations in DS patients (Golden & Hyman, 1994; Raz et al., 1995), suggesting a role of this gene in the learning and memory.

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DOPEY2 is overexpressed in DS lymphoblasts 1.5–2-fold compared to normal lymphoblasts (Lopes et al., 2003) and in trisomic tissues (Lyle et al., 2004), suggesting that DOPEY2 is a dosage-sensitive gene. Transgenic mice carrying the human YAC 230E8 (Smith et al., 1995) contain the entire DOPEY2 gene (Lopes et al., 2003; Rachidi, Lopes, Costantine et al., 2005), and overexpress it at less than twofold (Lopes et al., 2003; Rachidi, Lopes, Costantine et al., 2005). These transgenic mice show increased cortical cell density (Rachidi, Lopes, Costantine et al., 2005; Smith et al., 1997) that overexpresses DOPEY2 (Rachidi, Lopes, Costantine et al., 2005). This phenotype corresponds well to the abnormal lamination pattern found in the cortex of DS patients (Golden & Hyman, 1994). Recently, a new cerebellar phenotype has been discovered in two independent mouse lines carrying the YAC 230E8 characterised by elongation of the anteroposterior axis, increased length of rostral folia of the vermis, and abnormal culmen and declivus lobules (Rachidi et al., 2007). These phenotypes in the cortex and cerebellum may also explain the learning and memory deficits of these mouse models (Rachidi, Lopes, Costantine et al., 2005; Rachidi et al., 2007; Smith et al., 1997) suggesting a role of the DOPEY2 gene in neuropathological defects and MR in DS.

7.9

Potassium Inwardly Rectifying Channel (KCNJ6) Gene

Potassium inwardly rectifying channel J6 (KCNJ6) or G-protein coupled inward rectifying potassium channel subunit 2 (GIRK2) (Lesage et al., 1994; Ohira et al., 1997) encodes the GIRK2, a member of the ATP-sensitive potassium channels, involved in increase of the intracellular ATP concentration, linking cellular metabolism to the electrical excitability of the plasma membrane. GIRK2 is highly expressed in the brain, particularly in the cerebellar granule cell, suggesting a role of Girk2 in granule cell differentiation (Goldowitw & Smeyne, 1995). Girk2 mutation is responsible of the weaver phenotype in mouse, characterised by a drastically reduced cerebellum due to the depletion of granular cell neurons (Patil et al., 1995). GIRK2 is overexpressed in trisomic tissues (Kahlem et al., 2004; Lyle et al., 2004; Saran et al., 2003) and in the brain of DS mouse model Ts65Dn, particularly in the hippocampus (Harashima, Jacobowitz, Witta et al., 2006), and determines an increase of GIRK channel density in Ts65Dn neurons and a twofold increase of GABAB-mediated GIRK current (Best, Siarey, & Galdzicki, 2006). In addition, the GIRK2 overexpression seems to alter the GIRK1/GIRK2 ratio, which likely affects the balance between excitatory and inhibitory neuronal transmission in Ts65Dn, and thus overexpression of GIRK2 could contribute to DS neurophysiological phenotypes (Best et al., 2006; Harashima, Jacobowitz, Stoffel et al., 2006; Harashima, Jacobowitz, Witta et al., 2006). Girk2 heterozygous animals show behavioural changes intermediate between wild-type and null mutants only in the elevated plus-maze test after social isolation (Harashima, Jacobowitz, Stoffel et al., 2006), in agreement with gene-dosage

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dependence of RNA and protein expression (Blednow, Stoffel, Chang, & Harris, 2001). Girk2 homozygous mice show a higher level of locomotion and a higher number of rearing in the light area in the light/dark box. In the elevated plus-maze test, these mice spent a higher percentage of time in the open arms and showed a higher number of total entries. These results suggest hyperactivity and reduced anxiety in Girk2 null mice (Harashima, Jacobowitz, Stoffel et al., 2006).

7.10

Tetratricopeptide Down Syndrome (TPRD) Gene

TPRD, also called TTC3, gene (Ohira et al., 1996; Tsukahara, Hattori, Muraki, & Sakaki, 1996), is localised in the DSCR region. TPRD protein contains 2–3 units of a 34-amino acid repeat similar to the tetratricopeptide (TPR) motif, in the different splicing forms (Dahmane et al., 1998), that are involved in protein–protein interactions (Das, Cohen PW, & Barford, 1998; Groves & Barford, 1999). TPRD shows regional and cellular specificity during mouse and human brain development, and its expression is higher in the differentiating areas than in the proliferating ones, suggesting a role of TPRD in neuronal cell differentiation (Lopes et al., 1999; Rachidi et al., 2000). The strong TPRD expression in the human foetal cortex corresponds to the crucial developmental stage when the size of the cortical mantle doubles in thickness and the cortical lamination begins, suggesting a role of TPRD in cortical lamination. Interestingly, TPRD shows a differential expression in the human foetal hippocampus and cerebellum with variable intensities in specific neuronal cell types as estimated by a novel microscopy technology allowing gene transcription quantification (Rachidi et al., 2000). This specific expression pattern corresponds well to abnormal brain regions seen in DS patients (Golden & Hyman, 1994; Raz et al., 1995). TPRD is overexpressed at more than 1.5-fold in trisomic tissues including brain (Amano et al., 2004; Lyle et al., 2004; Saran et al., 2003). To date, two transgenic mice have been produced carrying human YACs, 141G6 and 152F7, each containing TPRD gene (Fig. 1) (Smith et al., 1997). The neurological and behavioural phenotypes observed in the 152F7 mice are determined by the DYRK1A gene overexpression. The 141G6 mice showed a lower performance in fear-conditioning against sound as acoustic conditional stimulus (Chabert et al., 2004), although any evident neuroanatomical and cognitive defects have not yet been demonstrated in the 141G6 mice (Smith et al., 1997). In addition, the 141G6 mice showed aberrant protein expression compared to control mice. Interestingly, these expression protein alterations may potentially lead to impairment of cognitive functions. In particular, these mice showed decreased CaMKII protein in hippocampus (Shin et al., 2006), and it is known that alteration of the CaMKII-pathway lead to a downstream alteration of the CREB pathway associated with impairment of fear memory (Bourtchuladze et al., 1994). Recently, it has been demonstrated that TPRD/TTC3 protein interacts with citron kinase (CIT-K) and citron N (CIT-N), two effectors of the RhoA small

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GTPase, involved in neuronal proliferation and differentiation (Berto et al., 2007). Interestingly, these authors demonstrated that TPRD/TTC3 overexpression strongly inhibits neurite extension, while its knock-down stimulates the neurite extension. In agreement with the previous results (Lopes et al., 1999; Rachidi et al., 2000), these dose-dependent effects are Rho-dependent, suggesting an important role of the TPRD-RhoA-CIT-K in neuronal differentiation (Berto et al., 2007). Overall, the expression pattern, the high overexpression of TPRD in the brain, and its role in neuronal differentiation suggest that this gene could be involved in fine neurological alterations in DS patients, and could participate to MR pathogenesis.

7.11

Down Syndrome Cell Adhesion Molecule (DSCAM) Gene

Down syndrome cell adhesion molecule (DSCAM), an axon guidance molecule mapping to HSA21 (Schmucker et al., 2000; Yamakawa et al., 1998), is expressed in the developing spinal cord and cortex. This gene may be involved in definition of the dorsal–ventral axis in the developing spinal cord at the time of neurite extension and may participate in the determination of regional neuronal fates in the developing cortex (Barlow, Micales, Chen, Lyons, & Korenberg, 2002). DSCAM proteins are expressed in the cerebral and cerebellar white matter, in accordance with the temporal and spatial sequence of myelination. In DS brains, DSCAM protein level is increased in the Purkinje cells at all ages, and in the cortical neurons during adulthood, compared to that for controls. In demented DS patients, DSCAM protein appeared in the core and periphery of senile plaques. This DSCAM expression pattern suggests that this gene may play a role as an adhesion molecule regulating myelination. In addition, the overexpression of DSCAM may also play a role in the MR and the precocious dementia of DS patients (Saito et al., 2000). The DSCAM Drosophila melanogaster homolog, dDscam, has been well characterised, and an important role has been demonstrated in neuronal wiring specificity (Chen et al., 2006; Hattori et al., 2007). During nervous system development, commissural axons project towards and across the ventral midline, a process mediated by netrin-1 and the netrin-1 receptor. It has been demonstrated recently that DSCAM is also required for commissural axon guidance. DSCAM is expressed on spinal commissural axons, binds netrin-1, and is necessary for commissural axons to grow towards and across the midline. Thus, overexpression of DSCAM, by causing enhanced netrin-DSCAM interactions, could contribute to the axonal wiring defects seen in DS (Ly et al., 2008).

7.12

Synaptoganin 1 (SYNJ1) Gene

Synaptojanin 1 (SYNJ1) is a polyphosphoinositide phosphatase that dephosphorylates the phosphatidylinositol-4,5-bisphosphate, a lipid that regulates membrane

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transduction and membrane trafficking in the endocytic pathway at synapses. The phosphatidylinositol is a signalling phospholipid implicated in a wide variety of cellular functions. At synapses, where normal phosphatidylinositol balance is required for proper neurotransmission, the phosphoinositide phosphatase synaptojanin 1 is a key regulator of its metabolism. Synaptojanin is highly enriched in the brain and is located at nerve terminals, and is associated with synaptic vesicles and coated endocytic intermediates (Haffner et al., 1997; McPherson, Takei, Schmid, & De Camilli, 1994). Moreover, the distribution of synaptojanin is coincident with that of other endocytic proteins, such as amphiphysin and dynamin (McPherson, Garcia, Slepnev, David, & Zhang, 1996; McPherson et al., 1994). For these reasons, synaptojanin may play a role in the endocytosis and could be involved in the recycling of synaptic vesicles. Synaptojanin 1 mutant mice die early after birth and exhibit accumulation of clathrin-coated vesicles at nerve terminals and increased synaptic depression in hippocampus, supporting a role for synaptojanin in the uncoating step of the recycling pathway (Cremona et al., 1999). The role that synaptojanin 1 plays in specific steps of the synaptic vesicle cycle has been studied by combined quantitative imaging with electron microscopy on cultured cortical neurons from synaptojanin 1 knock-out mice (Kim et al., 2002). The findings indicate that the rapid degradation of phosphatidylinositol by synaptojanin 1 is of critical importance for efficient synaptic vesicle regeneration and for the recovery of normal presynaptic function after an exocytic burst. In the absence of synaptojanin 1, sustained activity leads to a kinetic delay in synaptic vesicle reformation and to an increased, transient backup of synaptic membrane. This study provides direct evidence for the hypothesis that synaptojanin 1 plays a key physiologic role in the transition from early endocytic compartments to newly reformed synaptic vesicles fully incorporated into the functional pool. These results provide new evidence for a critical role of phosphoinositides in synaptic physiology and for their importance in regulating membrane traffic in the presynaptic terminal (Kim et al., 2002). It has been found that phosphoinositide metabolism is altered in the brain of Ts65Dn mice and in transgenic mice overexpressing Synj1 from BAC constructs. This defect is rescued by restoring Synj1 to disomy in Ts65Dn mice. The Synj1 transgenic mice also exhibit deficits in performance of the Morris water maze task, suggesting that phosphoinositide dyshomeostasis caused by gene dosage imbalance for Synj1 may contribute to brain dysfunction and cognitive disabilities in DS (Vonorov et al., 2008).

7.13

Intersectin 1 (ITSN1) Gene

The human ITSN1 gene spans 250 kb of genomic DNA and maps to HSA21 (Pucharcos et al., 1999). ITSN1 protein has five consecutive SH3 domains (SH3A-E), commonly found in signal transduction and cytoskeletal proteins (Pawson, 1995),

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and which interact with proline-rich domain-containing proteins involved in clathrin-mediated synaptic vesicle endocytosis (McPherson, 1999). ITSN1 encodes two isoforms, a long and a short, and both are expressed in the brain, but the long form is neuronal-specific and the short form is expressed in glial cells (Hussain et al., 1999; Ma et al., 2003). In addition, the long isoform is expressed in zones of proliferating and differentiating neurones, in both adult and foetal mouse brain, and this long ITSN1 transcript is overexpressed in the brains of individuals with DS (Pucharcos et al., 1999). ITSN1 seems to function as a scaffolding protein, providing a link between the components of endocytosis and the actin cytoskeleton, and has a role in signal transduction (Hussain et al., 1999; Jenna et al., 2002; Martina, Bonangelino, Aguilar, & Bonifacino, 2001; Roos & Kelly, 1998; Yamabhai et al., 1998). Interestingly, ITSN1 overexpression blocks clathrin-mediated endocytosis (Sengar, Wang, Bishay, Cohen, & Egan, 1999), presumably through disruption of higher order protein complexes between ITSN1 and its binding partners. Also, ITSN1 overexpression was found to block epidermal growth factor (EGF)-mediated MAPK activation by inhibiting Ras activation directly, most probably by preventing the Ras/mSos interaction, suggesting a role for ITSN1 in Ras activation (Tong et al., 2000). Mice with a null mutation in Intersectin 1 (Itsn1) showed alterations in endocyic and vesicle trafficking, including reduced number of exocytosis events in chromaffin cells, slowing of endocytosis in neurons, increased endosome size in neurons and reduced nerve growth factor (NGF) levels and decreased levels of choline acetyl transferase (ChAT) positive cells in the septal region of the brain (Yu, Chu, Bowser, Keating, & Dubach, 2008). Interestingly, the presence of enlarged endosomes in the neurons of DS is an early sign of AD, suggesting that ITSN1 could contribute to the disturbance in endocytosis in early AD pathogenesis in DS (Yu et al., 2008).

7.14

Contribution of MicroRNAs in Down Syndrome Mental Retardation

MicroRNAs (miRNAs) are small, non-protein coding RNAs that base pair with specific mRNA targets leading to translational repression or mRNA cleavage (Bartel, 2004; Bushati & Cohen, 2007; Wang et al., 2007). MiRNAs are expressed as long primary transcripts that are subsequently processed into mature miRNAs (about 22 nucleotides) by several nuclear and cytoplasmic enzymatic steps (Bushati & Cohen, 2007; Wang et al., 2007). MiRNAs have been shown to play a fundamental role in diverse biological and pathological processes (Bushati & Cohen, 2007; Wang et al., 2007). Recently, five miRNA genes harboured on HSA21, including miR-99a, let-7c, miR-125b-2, miR-155, and miR-802, have been identified (Kuhn et al., 2008). Among these miRNAs, the bic/miR-155 gene is well characterised and its expression is regulated by lipopolysaccharide (LPS) and cytokines (O’Connell, Taganov, Boldin, Cheng, & Baltimore, 2007; Taganov, Boldin, Chang, & Baltimore, 2006).

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As described above, alteration of the expression of the five HSA21-derived miRNAs in DS has been studied, demonstrating that they are overexpressed in DS tissues when compared with normal tissues (Kuhn et al., 2008; Sethupathy et al., 2007). Moreover, other miRNAs have also been identified showing expression alteration (over- or downexpression) in DS tissues when compared with normal tissues (Kuhn et al., 2008). These data suggest that trisomic 21 gene dosage overexpression of HSA21-derived miRNAs results in the decreased expression of specific target proteins and contributes, in part, to features of the neuronal and cardiac DS phenotype. Importantly, HSA21derived miRNAs may provide novel therapeutic targets in the treatment of individuals with DS.

8

Potential Molecular Pathways and Mechanisms Involved in Mental Retardation of Down Syndrome

The important update of the genomic sequence and the identification of HSA21 genes, determination of candidate genes and their mouse orthologs for DS phenotypes, particularly those involved in brain alterations, learning and memory deficits, and also the development and improvement of public databases, datamining and algorithms to perform genome wide analyses (Gardiner, Fortna, Bechtel, & Davisson, 2003; Hattori et al., 2000; International Human Genome Sequencing Consortium, 2004; Kapranov et al., 2002; Nikolaienko, Nguyen, Crinc, Cios, & Gardiner, 2005), has produced important knowledge and tools to study the molecular effects of the expression variation of gene products from the triplicated genes and their functional variations predisposing to specific cognitive deficits in the goal to better understand the molecular pathophysiology of MR in the DS.

8.1

Molecular and Cellular Mechanisms Leading to Mental Retardation in Down Syndrome

Recently, we have proposed a global mechanism model explaining the molecular and cellular origin of MR in DS (Rachidi & Lopes, 2007). In this model, we considered the complexity of gene interactions allowing the gene expression variations caused by the gene overdosage. These expression variations may firstly induce functional alterations at cellular level in the brain, that we called the primary phenotypes, and the final combination of these neuronal alterations could determine brain morphological defects, behavioural alterations and the MR in DS, that we called the secondary phenotypes (Fig. 2). We proposed that three principal genetic mechanisms could participate in concert to determine the final transcriptome and proteome alteration in DS. First, some

3 copies of HSA21 genes Dosage sensitive genes 1.5-fold expression level

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MENTAL RETARDATION

Fig. 2 Molecular and cellular mechanism leading to neurological phenotypes and mental retardation in Down syndrome. In this model, the overdosage of the HSA21 genes induces global alterations of gene expression via different genetic mechanisms. On the one hand, a primary effect of the gene overdosage determines a 1.5-fold gene overexpression. On the other hand, the overexpressed genes on the HSA21 could variably modify the expression level of other trisomic genes on HSA21 and of disomic genes on other chromosomes, by a secondary gene effect or by a more general alteration of the transcriptional homeostasis (amplified developemental instability). These gene expression variations may firstly induce functional alterations at cellular level in the brain, that we called the primary phenotypes. These neuronal alterations could determine the neuromorphological, neurological, and behavioural alterations, which we called the secondary phenotypes. The final combination of these neurological alterations leads to the mental retardation in DS

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HSA21 genes, the dosage-dependent genes, are expressed on average 1.5-fold the normal level as a direct consequence of the 1.5 gene overdosage. In some cases, their overexpression could directly determine a primary phenotype in DS brain. Second, in addition, some of these dosage-dependent genes could modulate directly or directly the expression of target genes on both the HSA21 and the other chromosomes. In these cases, the modulation of the target gene expression could be different of 1.5-fold up-regulation and could also be down-regulated, depending on the nature of the dosage-dependent gene products, and thus determine a secondary gene dosage effect. And three, all or some HSA21 genes with altered expression could participate in the amplified developmental instability of the genome in trisomy 21, determining a more general gene expression alteration and disequilibrium (Fig. 2). These gene expression changes in the brain determine alterations at cellular level, which we globally call primary phenotypes (Fig. 2), include metabolic pathways, regulatory cascades and cellular processes, such as proliferation, differentiation and apoptosis. Recently, alterations in synaptogenesis and dendritogenesis haver received increasing interest for their implication in MR. Abnormal ultrastructure and number of synapses and dendrites are observed both in DS patients and mouse models (Becker et al., 1986, 1991; Belichenko et al., 2004; Benavides-Piccione et al., 2004; Dierssen & Ramakers, 2006; Hanson et al., 2007; Kurt, Davies, Kidd, Dierssen, & Florez, 2000; Kurt, Kafa, Dierssen, & Davies, 2004; Takashima et al., 1994). Moreover, the synapses of trisomic brains also show functional alterations, such as LTP and LTD in the hippocampus and dentate gyrus (Kleschevnikov et al., 2004; Siarey et al., 1997, 1999, 2005), reduced noradrenergic function in the hippocampus (Dierssen et al., 1996, 1997), and reduced excitatory and inhibitory inputs to pyramidal neurons in CA3 of Ts65Dn hippocampus (Hanson et al., 2007). These primary phenotypes and their combinations may determine the more complex secondary phenotypes, in particular functional alterations of the cognitive network and brain plasticity that participate in the MR in DS (Fig. 2). As an elucidated example, during cerebellar development in Ts65Dn mice, a primary cellular phenotype has been identified to be the molecular origin of a DS secondary neurological phenotype (Roper et al., 2006). In Ts65Dn mice, a cerebellar hypoplasia is observed, due to decreased cerebellar granular cells and their precursors. It has been demonstrated that reduced mitosis is determined by a deficit in response to the Sonic hedgehog (Shh) mitogenic signals (Roper et al., 2006). This suggests that a dosage-sensitive gene or genes make cells less sensitive to Shh when overexpressed, corresponding to the primary phenotype, and that determines the cerebellar hypoplasia corresponding to the secondary phenotype.

8.2

Molecular Pathways Contributing to Mental Retardation in Down Syndrome

The genetic disruption caused by trisomy 21 in neural patterning and signal transduction pathways during development leads to alteration of the neuronal circuitry

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and could be the biological mechanism responsible for the pathogenesis of MR in DS. Thus, it is of the most interest to elucidate the molecular pathways involving the HSA21 genes function and to discover which of them are perturbed in trisomy 21 and are relevant to neurological disorders, cognition, learning and memory in DS. Importantly, the first altered genetic pathway involved in some DS phenotypes has been identified (Arron et al., 2006) in which two HSA21 dosage-sensitive genes are involved, DYRK1A and RCAN1/DSCR1, both located in the critical DSCR region, and impact nuclear factor of activated T cells (NFATc) activity. Transgenic mice harbouring different mutations in the NFATc transcription factors exhibit phenotypes similar to features seen in DS (Arron et al., 2006). Moreover, it has been demonstrated that DYRK1A and DSCR1 regulate NFATc and their overexpression dysregulates the NFATc pathways (Arron et al., 2006). The NFATc pathways play critical roles in vertebrate development and organogenesis of several organs (Crabtree & Olson, 2002; Graef, Che, & Crabtree, 2001), in particular the central nervous system. The signalling pathways (Fig. 3) are activated by the entry of calcium into the cell and results in activation of calcineurin, the catalytic subunit of the Ca2+/calmodulindependent protein phosphatase PP2B. In the cytoplasm, activated calcineurin removes phosphate groups from NFATc factors. Dephosphorylated NFATc proteins enter the Ca2+ Cell membrane

P

DSCR1 NFATc

Calcineurin

P P DYRK1A NFATc

Nucleus

Target gene

Fig. 3 Cooperation of gene-dosage imbalance of DYRK1A and DSCR1 dysregulate NFATc signalling pathway. The phosphatase calcineurin is activated by the calcium and removes phosphate groups (P) from NFATc transcription factors in the cytoplasm that allows the dephosphorylated NFATc proteins to enter into the nucleus and activate their target genes. DSCR1 is a cytoplasmic inhibitor of calcineurin and, thus, decreases NFATc dephosphorylation. In the nucleus, NFATc may be phospharylated by DYRK1A kinase and the phosphorylated NFATc returns into the cytoplasm, decreasing gene transcription activity. In DS, overexpression of DSCR1 leads to a decrease in NFATc dephosphorylation and, consequently, to a reduction in nuclear NFATc and target gene transcription. Similarly, in the nucleus, overexpression of DYRK1A leads to increase of the phosphorylated NFATc proteins and their cytoplasmic translocation, and thus to additional decrease of target gene transcription. Thus, DYRK1A and DSCR1 proteins regulate the levels of NFATc phosphorylation and, in DS, their overexpression determines the dysregulation of NFATc-dependent gene expression and their associated phenotypic features

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nucleus and activate their target genes. DSCR1 encodes an inhibitor of calcineurin (Fuentes et al., 2000; Rothermel et al., 2000) and decreases NFATc dephosphorylation in the cytoplasm. Once in the nucleus, NFATc may be phosphorylated by DYRK1A serine-threonine protein kinase, and the phosphorylated forms of NFATc return into the cytoplasm, decreasing gene transcription activity. In normal conditions, DYRK1A and DSCR1 act synergistically to control phosphorylation levels of the NFATc and NFATc-regulated gene transcription (Fig. 3). In transgenic mice overexpressing Dyrk1A or DSCR1 alone, or both Dyrk1A and DSCR1, NFATc is mostly phosphorylated and found in the cytoplasm, suggesting that overexpression of Dyrk1A and DSCR1 reduces NFATc transcriptional activity by increase of the phosphorylated forms of NFATc proteins, which leads to their cytoplasmic localisation. Interestingly, the mice lacking NFATc2 and NFATc4, such as transgenic mice overexpressing DYRK1A and/or DSCR1, have similar phenotypes to those seen in trisomic mouse models, Ts65Dn and Ts1Cje, and DS patients, including neuronal and behavioural phenotypes (Arron et al., 2006). In agreement with this molecular pathway, significant reduced calcineurin activity is detected in DS foetal brain tissue as well as in Drosophila mutants that overexpress DSCR1 (Chang et al., 2003). As described above, both DYRK1A and DSCR1 are involved in synaptic development, maturation and plasticity. Moreover, DYRKIA also appears involved in splicing control. In the nuclei, DYRK1A is localised to the nuclear speckles that represent the splicing compartment (Alvarez, Estivill, & de la Luna, 2003), and several splicing factors and proteins involved in splicing regulation are DYRK1A substrates (de Graaf et al., 2004). The splicing is a fundamental step of mRNA maturation and correct protein production, and almost all genes show alternative splicing forms. Overexpression of DYRK1A in DS may dysregulate the splicing control and may determine several developmental and functional alterations, particularly in the brain. Interestingly, several DYRK1A substrates, including the transcription factors GLI1, ARIP4, GR, FKHR and CREB (Mao et al., 2002; Sitz, Tigges, Baumgartel, Khaspekov, Lutz, 2004; Woods et al., 2001; Yang et al., 2001), are involved in the MAPK pathway. In addition, DSCR1 inhibites calcineurin and, indirectly, affects its substrates, which include dynamin and SYNJ1 (Cousin, Tan, & Robinson, 2001), and is a critical point of connection between the calcineurin and the MAPK pathways (Rothermel et al., 2003). Other genes of the chromosome 21 are involved in the MAPK pathway, such as SUMO3, involved in sumoylation, a post-translational process regulating protein function and activity level, and NRIP1 (also known as RIP140), a steroid hormone co-repressor. The MAPK pathway is involved in regulation of synaptic plasticity and memory (Sweatt, 2001; Sweatt & Weeber, 2003; Thomas & Huganir, 2004). Dysregulation of MAPK affects LTP, spatial learning, and context discrimination, which correspond to some defects observed in Ts65Dn mice (Hyde, Frisone, & Crnic, 2001; Kleschevnikov et al., 2004; Stasko & Costa, 2004) and in children with DS (Pennington, Moon, Edgin, Stedron, & Nadel, 2003). Dysregulation of calcineurin activity is associated with cognitive and behavioural deficits, including spatial learning and context discrimination (Lee & Ahnn, 2004;

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Mansuy, 2003) that are related to DS. Calcineurin interacts with dynamin in a Ca2+dependent fashion during depolarisation-induced vesicle recycling (Liu, Sim, & Robinson, 1994) and, in Drosophila, disruption of this interaction blocks endocytosis and impairs neurotransmission (Kuromi, Yoshihara, & Kidokoro, 1997). Inhibition of calcineurin reduces the level of synaptic vesicle recycling as well as the total vesicle pool size in synaptic terminals (Kumashiro et al., 2005), indicating a potential role for endogenous calcineurin inhibitors in regulating synaptic transmission. It is plausible, given its role in the regulation of calcineurin activity, that overexpression of DSCR1, as observed in DS and AD, may adversely affect at least two calcineurin-dependent pathways by blocking calcineurin activity. Firstly, elevated levels of DSCR1 may disrupt endocytosis and vesicle recycling due to the inhibition of calcineurin-dependent dephosphin dephosphorylation, and secondly, may contribute to the hyperphosphorylation of Tau by reducing calcineurin phosphatase activity. Indeed, while short-term induction of the DSCR1 protein can provide stress protection in neurons, it has been proposed that long-term induction causes gradual accumulation of hyperphosphorylated tau protein, leading to AD (Ermak et al., 2001). DSCR1 knock-out mice showed increased enzymatic activity of both calcineurin and protein phosphatase 1 (PP1) and decreased phosphorylation of the calcineurin substrate DARPP-32, consistent with an elevation in calcineurin activity in the hippocampus of DSCR1 knock-out mice (Hoeffer et al., 2007), demonstrating a critical role for DSCR1 in the proper manifestation of memory and in MR in DS.

9

Potential Directions for Mental Retardation Therapeutics in Down Syndrome

The functional genomic advances for generating gene–phenotype correlations are of the most interest towards the identification of potential targets in the molecular pathways involved in DS phenotype. The efforts are focused particularly on the pathways involved in learning and memory processes in mouse models of DS towards identification of targets for therapeutics that will correct the MR features in DS patients. It is known that individuals with DS present neuropathology indistinguishable from those with AD (Mann & Eisiri, 1989), including loss of acetylcholine and related enzymes in the hippocampus and throughout the neocortex. The cholinergic degeneration found in AD and DS led to the suggestion that pharmacological treatments directed at cholinergic systems might attenuate the degree of dementia in AD (Smith & Swash, 1978). Today, the most widely used treatment for dementia in AD is the administration of acetylcholinesterase inhibitors (AChEI), which enhance cholinergic transmission. Donepezil is a selective AChEI, which produces clinical improvement in patients with dementia in AD (Kaduszkiewicz, Zimmermann, Beck-Bornholdt, & van den Bussche, 2005). Donepezil administration improved cognition in several animal models of impaired learning including aged rodents, in animals with experimentally induced cholinergic deficits and in mouse models of AD (Yoo, Valdovinos, & Williams, 2007). Several studies (Prasher, 2004) have

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addressed the treatment of cognitive decline related to dementia in DS. These studies have reported limited improvements after donepezil treatment in global functioning, cognitive skills and adaptive behaviour in people with DS. Donepezil administration also produces some improvement in language skills in adults (Heller et al., 2003) and children (Heller et al., 2004) with DS. Therapeutic interventions have been tried out to improve learning in Ts65Dn mice. Oestrogen administration improved learning performance in the T-maze and reversed cholinergic impairment in 11–15-month Ts65Dn females (Granholm et al., 2002). Several studies have also suggested that the deficits in learning and memory seen in the Ts65Dn mouse might be partially due to increased inhibition at the synaptic level. Ts65Dn mice show a decrease of excitatory synapses (Kurt et al., 2000, 2004) and in synapse connectivity (Belichenko et al., 2004; Hanson et al., 2007). Furthermore, two studies provided evidence of increases in GABAAreceptor-mediated inhibition in Ts65Dn mice. In Ts65Dn mice, it has been shown that evoked LTP in granule cells of the dentate gyrus is reduced due to an increased GABA-dependent inhibition of these neurons (Kleschevnikov et al., 2004). Moreover, it has been found that there is a significant reduction of the amount of theta-burst stimulation (TBS)-induced LTP in Ts65Dn mice that could be rescued via picrotoxin application. Therefore, an increase in GABAA-mediated inhibition or in plasticity of the inhibitory circuitry in Ts65Dn mice may underlie the cognitive deficits found in these mice (Costa & Grybko, 2005). Recently, it has been demonstrated that administering the GABAA antagonists, picrotoxin, bilobalide or pentylenetetrazol (PTZ), restored cognition and LTP in the Ts65Dn mouse, and suggested that this positive effect could me mediated by reducing inhibition in this mouse (Fernandez et al., 2007). The chronic systemic administration of noncompetitive GABAA antagonists leads to a persistent, post-drug recovery of cognition in Ts65Dn mice, as well as recovery of deficits in LTP. Only 10 days of drug treatment resulted in improved performance in the novel object recognition and spontaneous alternation in the T-maze tasks, an improvement that persisted for several months after drug treatment ended (Fernandez et al., 2007). More recently, these studies were confirmed using the non-competitive GABAA antagonist PTZ which rescued Ts65Dn performance in the Morris water maze (Rueda, Florez, & Martinez-Cué, 2008). These findings suggest that excessive GABAergic inhibition of specific brain circuits is a potential cause of MR in DS, and that GABAA antagonists may be useful therapeutic tools to facilitate functional changes that can ameliorate cognitive impairment in children and young adults with the disorder. More recently, it has been demonstrated that acute injections of the NMDA receptor antagonist memantine rescue performance deficits in the Ts65Dn mouse model of DS on a conditioning fear test (Costa, Scott-McKean, & Stasko, 2008). One target of memantine is the NMDA receptor, whose function is predicted to be perturbed by the integrated effects of increased expression of several HSA21 genes, including RCAN1, APP, ITSN1 and DYRK1A, all of which are being intensively studied for relevance to DS. It is known that NMDA receptors are among the targets of calcineurin. It has been demonstrated that the pharmacological inhibition of calcineurin activity leads

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to increased NMDA receptors mean open time and opening probability (Lieberman & Mody, 1994). Theoretically, such modulation of kinetic parameters should lead to an increase in inhibition of NMDA receptors-mediated currents by open channel blockers, including the noncompetitive NMDA receptors antagonist MK-801. Accordingly, conditional calcineurin null-mutant mice display increased responses to the locomotor-stimulating effects of MK-801 (Miyakawa et al., 2003). DSCR1 knock-out mice have pronounced spatial learning and memory deficits (Hoeffer et al., 2007). These deficits were similar to those found in mice with inducible, hippocampal-restricted overexpression of constitutively active calcineurin (Mansuy, Mayford et al., 1998; Mansuy, Winder et al., 1998) and the direct opposite of learning behaviours of animals in which calcineurin was inhibited by either transgenic expression of a calcineurin inhibitory domain or application of antisense oligonucleotides (Ikegami & Inokuchi, 2000; Malleret et al., 2001). This suggests that DSCR1 provides a constraint on calcineurin activity during learning and memory and that this constraint is absent in the DSCR1 knock-out mice. Moreover, recent findings indicate that acute blockade of calcineurin activity improves memory and cognitive function in AD model mice (Dineley, Hogan, Zhang, & Taglialatela, 2007). These findings strongly suggest that DSCR1 facilitates synaptic plasticity and memory by constraining phosphatase signalling via inhibition of calcineurin and its downstream target PP1. Thus, DSCR1 represents an important potential therapeutic target for the treatment of numerous neurological disorders whose pathologies involve the dysregulation of calcineurin (Hoeffer et al., 2007). In addition, efforts could also be concentrated on the microRNAs of the HSA21 to elucidate their biological role in DS, because it has been demonstrated recently that microRNAs show an increasing importance in the gene expression control and seem to play a fundamental role in diverse biological and pathological processes, including cell proliferation, differentiation, apoptosis, carcinogenesis, and cardiovascular disease (Bushati & Cohen, 2007; Wang et al., 2007). Considering the hypothesis that trisomic 21 gene-dosage overexpression of HSA21-derived miRNAs results in the decreased expression of specific target proteins and contributes, in part, to features of the neuronal and cardiac DS phenotype, HSA21-derived miRNAs may provide novel therapeutic targets in the treatment of individuals with DS (Kuhn et al., 2008). This indicates that studies of variation of gene expression and its genomic regulation, and functional studies of these genes and other conserved DNA elements, are two fundamental research priorities that may also provide potential future directions for MR therapeutics in DS.

10

Conclusion and Perspectives

Partial trisomies of HSA21 or MMU16 allowed genetic dissection of DS phenotypes, particularly the neurological ones, the goal of which is the identification of candidate genes contributing to neurological and behavioural phenotypes, and to MR in DS.

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The gene expression studies in mouse models and human have shown similar genotype/phenotype correlations. The highly parallel outcomes that result when the same evolutionarily conserved genetic programmes are perturbed in mice and human validate the recent studies that focus on DS phenotypes, particularly neurological alterations. Thus, these studies indicate that brain dysfunctions and MR may be due to over-dosage of genes involved, directly or indirectly, in brain developmental processes throughout neurogenesis, neuronal growth and neuronal differentiation. All these studies identified some genes which are overexpressed in the brain and involved in brain development, learning and memory as candidate genes for MR in DS. The increased information about function of the proteins encoded by these genes, their interaction with other proteins and their involvement in regulatory and metabolic pathways is giving a clearer view of the origin of the MR in DS. This leads to the identification of potential targets in the molecular altered pathways involved in MR pathogenesis that may be potentially corrected, in the perspective of new therapeutic approaches. Furthermore, the regulation of gene expression by microRNAs or small interfering RNAs provide exciting possibilities for exogenous correction of the aberrant gene expression in DS and also provide potential directions for clinical therapeutics of MR. Given the new pharmacotherapies for cognitive impairment in a mouse model of DS and the relevance of these findings to the treatment of cognitive deficits in the human DS population, substantial interest emerges in clinical settings and trials in DS and has created substantial interest of the scientific and medical community towards a novel biomedical era for therapeutics of MR in DS. Acknowledgments We are grateful to J. M. Delabar (University Paris 7) for his continuous support. We thank our colleagues of the Department of Molecular Biology-Jacques Monod at the Pateur Insitute (Paris) for their advice and support. We also thank L. Peltzer (University of French Polynesia) and C. Tetaria (Hospital Centre of French Polynesia) for their continuous support.

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Epigenetic Programming of Stress Responses and Trans-Generational Inheritance Through Natural Variations in Maternal Care A Role for DNA Methylation in Experience-Dependent (Re)programming of Defensive Responses Ian C.G. Weaver Abstract Human epidemiological and animal studies show that many chronic adult conditions have their antecedents in compromised fetal and early postnatal development. Mother–infant interactions are the primary source of social stimulation and influence physiological and cellular defense mechanisms resulting in persistent changes in offspring phenotype. These effects appear to be mediated, in part, by neonatal programming of the hypothalamic–pituitary–adrenal (HPA) axis and glucocorticoid function in the neuroendocrine system. Rodent models provide evidence that epigenetic mechanisms are involved: natural variations in maternal care influence HPA stress reactivity in offspring via long-term changes in tissue-specific gene expression. Both in vivo and in vitro studies show that maternal licking and grooming increases glucocorticoid receptor expression in the offspring through increased hippocampal serotonergic tone accompanied by increased histone acetyltransferase activity, histone acetylation and DNA demethylation mediated by the transcription factor NGFI-A. These effects are reversed by early postnatal cross-fostering and by pharmacological manipulations in adulthood, including Trichostatin A (TSA) and l-methionine administration. Maternal care influences the maternal behavior of female offspring, an effect that appears to be related to epigenetic regulation of estrogen receptor-a expression in the medial preoptic area, providing a mechanism for trans-generational inheritance of maternal behavior from mother to offspring. Experience-induced changes in the epigenotype provide a potential mechanism to explain how physiological adaptations to changes in the early environment result in permanent programming and affect risk to disease later in life. Keywords Maternal฀ Behavior฀ ฀ •฀ Medial฀ Preoptic฀ Area฀ •฀ Oxytocin฀ •฀ Estrogen฀ Receptor฀•฀Stress฀•฀Hippocampus฀•฀Glucocorticoid฀Receptor฀•฀Chromatin฀Plasticity฀ •฀DNA฀Methylation I.C.G.฀Weaver฀(*) The฀Krembil฀Family฀Epigenetics฀Laboratory,฀Centre฀for฀Addiction฀and฀Mental฀Health฀(CAMH),฀ 250฀College฀Street,฀Toronto,฀ON,฀Canada฀M5T฀1R8 e-mail: [email protected] J.D.฀Clelland฀(ed.),฀Genomics, Proteomics, and the Nervous System, Advances฀in฀Neurobiology฀2,฀DOI฀10.1007/978-1-4419-7197-5_3,฀ ©฀Springer฀Science+Business฀Media,฀LLC฀2011

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Introduction: Environmental Influences and the Origins of Adult Health and Disease

When฀ asked฀ what฀ worried฀ him฀ most,฀ the฀ British฀ Prime฀ Minister฀ (1957–1963)฀ Harold Macmillan famously replied: “Events, my dear boy, events” (Sandbrook, 2005).฀Our฀ability฀to฀endure฀the฀prevailing฀demands฀of฀life,฀however,฀appears฀to฀be฀ associated with early-life events that influence health in adolescence and adulthood. The importance of early environmental influences on lifelong health has emerged from฀ observations฀ including฀ those฀ by฀ Geoffrey฀ Rose฀ in฀ the฀ 1960s,฀ describing฀ a฀ familial฀ pattern฀ of฀ coronary฀ heart฀ disease฀ (CHD),฀ still฀ birth฀ and฀ infant฀ mortality฀ (Rose, 1964). Infant mortality has since been geographically correlated with cardiovascular disease (Forsdahl, 1977). Retrospective studies found an inverse association between฀birth฀weight฀and฀adult฀CHD฀mortality,฀and฀concluded฀that฀these฀effects฀are฀ mediated฀in฀part฀by฀intrauterine฀deprivation฀(Barker฀&฀Osmond,฀1986).฀Consistent฀ with this hypothesis, low birth weight is associated with an increased incidence of heart disease (Rich-Edwards et al., 1997), hypertension (Law & Shiell, 1996), and type 2 diabetes (Hales et al., 1991), as well as markers of abnormal glucose-insulin metabolism (Hales et al., 1991) and serum cholesterol concentrations (Barker, Martyn,฀ Osmond,฀ Hales,฀ &฀ Fall,฀ 1993).฀ On฀ the฀ other฀ hand,฀ high฀ birth฀ weight฀ is฀ associated with childhood leukemia, testicular cancer and an increased risk in breast cancer (Hjalgrim et al., 2003; Michels et al., 1996; Michels & Xue, 2006). Consequently,฀reduced฀or฀heightened฀overall฀fetal฀body฀growth฀is฀seen฀as฀constitutive marker of a coordinated fetal response to the intrauterine environment, resulting in changes in tissue and organ development that condition the risk of disease later in life (Gluckman & Hanson, 2004). The persistent effects of early-life environmental cues and events (including maternal nutrition) on cellular function and physiology gave rise to the term “programming” (Hales & Barker, 2001; Lucas, 1991). It is now widely appreciated that both prenatal and early postnatal conditions are key in developmental programming and the emergence of certain metabolicdisorder฀ phenotypes฀ in฀ the฀ later฀ stages฀ of฀ life฀ (Gluckman,฀ Hanson,฀ Cooper,฀ &฀ Thornburg, 2008). The generation of different phenotypes from a single genome based on the conditions during early development forms the basis for “phenotypic plasticity.” Plasticity provides an organism with an evolutionary advantageous ability to hone specific biological defensive systems for survival in the prevailing environmental demand (stressors). However, such adaptations can be pathological if there is a mismatch between perinatal adaptation and later-life environmental conditions (Felitti et al., 1998; Lissau & Sorensen, 1994;฀McCauley฀et฀al.,฀1997). Therefore, the ability to cope (stress resilience) plays a vital role in mediating the effects of adverse conditions on health outcome. Stress-diathesis models suggest that maternal influences on the development of neuroendocrine systems that underlie the hypothalamic–pituitary–adrenal (HPA) axis and behavioral responses to stress mediate the relation between early-life environment and health in the adult offspring (Francis & Meaney, 1999; Heim et al., 2000; Nemeroff, 1996; Repetti, Taylor, & Seeman, 2002; Seckl & Meaney, 1993;

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Sroufe, 1997). Importantly, the nature of the mother–offspring interaction influences the expression of genes that regulate the neuronal circuitry of behavioral responses in฀the฀offspring฀throughout฀life.฀This฀raises฀several฀key฀questions:฀(1)฀the฀identity฀ of the relevant genomic targets; (2) the mechanisms that sustain gene expression; (3)฀whether฀the฀programmed฀state฀is฀reversible฀later฀in฀life;฀and฀(4)฀the฀mechanism฀ for trans-generational inheritance. In this review, we discuss the results from studies using rodent models that suggest that maternal care in the first week of postnatal life establishes diverse and stable phenotypes in the offspring through the epigenetic modification of genes expressed in the brain that regulate neuroendocrine and behavioral responses throughout life. In particular, we focus on maternal programming of the rat hippocampal glucocorticoid฀receptor฀(GR)฀and฀HPA฀stress฀responses฀in฀the฀offspring.฀We฀also฀suggest฀a฀ possible mechanism for transmission of maternal care across generations and conclude by considering the implications of our findings within the context of recently published studies in humans.

2

Maternal Care in the Rat and HPA and Behavioral Responses to Stress in Adulthood

Small mammals such as the rat produce altricial, relatively helpless, offspring – they are born blind, deaf, naked (except for small vibrissae on the snout), are unable to urinate and defecate properly, have poor motor coordination and cannot maintain their own body temperature (Krinke, 2000). Neonate survival is dependent on their ability to process sensory information continuously and adapt to changing ambient conditions. Since the mother comprises the prime source of environmental input (nutrition, warmth, stimulation, protection, companionship, etc.), she essentially provides the nurturing environment crucial for survival of the pups. The results of observational studies of mother-pup interactions provide evidence for natural variations in maternal care including stable individual differences in licking/grooming฀(LG)฀and฀arched-back฀nursing฀(ABN)฀posture,฀over฀the฀first฀week฀ of฀lactation฀(Caldji฀et฀al.,฀1998; Francis, Diorio, Liu, & Meaney, 1999; Liu et al., 1997;฀ Myers,฀ Brunelli,฀ Shair,฀ Squire,฀ &฀ Hofer,฀ 1989; Stern, 1997). Exposure to different levels of maternal LG-ABN during the postnatal period is associated with HPA blunting and changes in forebrain GR expression levels that persist into adulthood (Francis et al., 1999; Liu et al., 1997) (Fig. 1). The adult offspring of mothers that฀exhibit฀increased฀levels฀of฀pup฀licking/grooming฀and฀ABN฀(i.e.,฀High฀LG-ABN฀ mothers) over the first week of life show increased hippocampal GR expression and enhanced glucocorticoid feedback sensitivity, decreased hypothalamic corticotropinreleasing฀ factor฀ (CRF)฀ expression,฀ and฀ more฀ modest฀ HPA฀ responses฀ to฀ stress฀ by฀ comparison to adult animals reared by Low LG-ABN mothers (Francis et al., 1999; Liu et al., 1997). In support of this idea that early “nurturing touch” regulates the development of stress reactivity of the neonate, artificially reared offspring that receive฀tactile฀stimulation฀with฀a฀warm,฀wet฀paintbrush฀for฀15฀min฀per฀day฀during฀

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Fig. 1 Hypothalamic–pituitary–adrenal (HPA) axis. In response to a physical or psychological stressor, parvocellular cells in the paraventricular nucleus of the hypothalamus produce corticotrophinreleasing฀factor฀(CRF)฀and฀arginine-vasopressin฀(AVP),฀which฀are฀then฀released฀into฀the฀hypophysial฀ portal฀ circulation.฀ CRF฀ and฀ AVP฀ stimulate฀ the฀ release฀ and฀ synthesis฀ of฀ adrenocorticotroph฀ hormone฀ (ACTH)฀ from฀ pro-opiomelanocortin฀ (POMC)฀ in฀ the฀ anterior฀ pituitary฀ gland.฀ ACTH฀ potently฀induces฀the฀adrenal฀cortex฀to฀secrete฀glucocorticoids฀(GC),฀cortisol฀in฀humans฀and฀corticosterone฀in฀rodents.฀GCs฀feed฀back฀by฀binding฀and฀activating฀hippocampal฀glucocorticoid฀receptors฀ (GR) to inhibit further HPA activity, which prevents tissue damage from extended exposure to GCs,฀facilitating฀stress฀resistance฀and฀behavioral฀adaptation

the first week of postnatal life show increased hippocampal GR expression and decreased฀serum฀glucocorticoid฀release฀(Jutapakdeegul,฀Casalotti,฀Govitrapong,฀&฀ Kotchabhakdi, 2003). Eliminating the difference in hippocampal GR levels eliminates the effects of early experience on HPA responses to stress in adulthood (Meaney, Aitken, Viau, Sharma, & Sarrieau, 1989), suggesting that the difference in hippocampal GR expression serves as a mechanism for the effects of early experience on the development of individual differences in HPA responses to stress (Meaney, 2001). Consistent฀with฀this,฀mice฀with฀forebrain-specific฀disruption฀of฀the฀GR฀gene฀and฀ loss of hippocampal GR expression show impairments to HPA axis regulation and an฀increase฀in฀anxiety-related฀behavior฀(Boyle,฀Kolber,฀Vogt,฀Wozniak,฀&฀Muglia,฀ 2006). Interestingly, the adult offspring of High LG-ABN mothers are behaviorally less fearful under conditions of stress than are animals reared by Low LG-ABN dams฀(Caldji฀et฀al.,฀1998),฀and฀subsequent฀gene฀expression฀profile฀analysis฀of฀these฀ animals suggests that effects of early-life experience have a stable and broad effect on the hippocampal transcriptome, which may play a role in the development

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of฀ anxiety-mediated฀ behaviors฀ through฀ life฀ (Weaver,฀ Meaney,฀ &฀ Szyf,฀ 2006). Importantly, cross-fostering paradigms have provided evidence for direct effects of maternal behavior on the behavioral and neuroendocrine responses to stress (Francis et al., 1999;฀Weaver฀et฀al.,฀2004). These฀findings฀suggest฀that฀the฀developing฀rodent฀forebrain฀is฀exquisitely฀sensitive฀ to tactile stimulation provided by the mother during the first week of life and that different฀frequencies฀of฀LG-ABN฀provided฀during฀this฀period฀program฀neurodevelopment฀ with฀ long-lasting฀ consequences฀ on฀ hippocampal฀ GR฀ function฀ and฀ HPA฀ responses to stress. However, since the rearing mother and not the biological mother defines the behavioral and neuroendocrine responses to stress, these studies support฀an฀epigenetic฀mechanism฀for฀long-term฀programming฀(Fleming,฀O’Day,฀&฀ Kraemer, 1999; Francis et al., 1999; Liu et al., 1997; Meaney, 2001).

3

Epigenetic Gene Regulation: Heritable Changes in Gene Expression Potential

Conrad฀H.฀Waddington฀originally฀defined฀“epigenetics”฀in฀the฀early฀1940s฀as฀the฀ study of “the interactions between genes and their products which bring phenotype into฀ being”฀ (Waddington,฀ 1968). Epigenetics is now understood as the study of heritable changes in gene expression that are not caused by changes in the DNA sequence฀(Jaenisch฀&฀Bird,฀2003).฀While฀the฀DNA฀sequence฀defines฀the฀primary฀ structure฀of฀the฀proteins,฀epigenetic฀mechanisms฀control฀the฀quantity,฀location฀and฀ timing of gene expression and are stably and mitotically heritable, providing a possible mechanism for the maintenance of cell type-specific gene expression in the developing brain (Mill & Petronis, 2007). Epigenetic regulation in mammalian cells is mediated principally through changes฀in฀DNA฀methylation฀(Razin,฀1998), chromatin structure (Kadonaga, 1998), and non-coding RNAs (microRNA) (Bergmann & Lane, 2003;฀Chuang฀&฀Jones,฀ 2007; Saito & Jones, 2006). The “epigenome” refers to the epigenetically modified genome, and the “epigenotype” refers to mitotically heritable patterns of DNA methylation and modifications to chromatin proteins that package DNA.

3.1

Chromatin Structure

In the nucleus of eukaryotic cells, chromosomal DNA is packaged into chromatin fibers in repeating protein–DNA complexes called nucleosomes, comprised of approximately฀146฀bp฀of฀DNA฀wound฀1.8฀times฀around฀an฀octomer฀consisting฀of฀ two฀copies฀each฀of฀histone฀proteins฀H2A,฀H2B,฀H3฀and฀H4฀(Kornberg,฀1974). The attraction between the positively-charged histones and negatively-charged DNA maintains the histone–DNA interaction (Grunstein, 1997).

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The amino-terminal tails of the nucleosomal core histones are subjected to post-translational฀modifications฀such฀as฀acetylation฀(Wade,฀Pruss,฀&฀Wolffe,฀1997), poly-ADP-ribosylation,฀carbonylation฀(Wondrak,฀Cervantes-Laurean,฀Jacobson,฀&฀ Jacobson, 2000), glycosylation, methylation (Jenuwein, 2001), phosphorylation, SUMOylation฀ (Shiio฀ &฀ Eisenman,฀ 2003)฀ and฀ ubiquitination฀ (Shilatifard,฀ 2006). Typically, acetylation occurs at lysine residues and all acetylation modifications are associated with transcriptional activation, as are phosphorylation and arginine methylation modifications (Bernstein et al., 2005).฀ On฀ the฀ other฀ hand,฀ lysine฀ methylation can be associated with either transcriptional activation or repression depending฀on฀the฀lysine฀residue.฀The฀effect฀of฀ubiquitination฀on฀transcription฀likewise฀ is฀ dependent฀ on฀ location,฀ with฀ ubiquitination฀ on฀ H2A฀ and฀ H2B฀ associated฀ with transcriptional repression and activation, respectively. Sumoylation has thus far฀ been฀ associated฀ solely฀ with฀ transcriptional฀ repression.฀ Other฀ chromatin฀ remodeling systems that have been implicated in epigenetic changes include nucleosome sliding (mediated by ATP-dependent chromatin remodeling proteins) and histone substitution (exchange of histones from nucleosome with external histones) (Tsankova, Renthal, Kumar, & Nestler, 2007). Importantly, the relationship between regional patterns of histone modifications and locus-specific transcriptional activity provides evidence for the existence of a “histone code” for dictating cell-specific gene expression programs (Jenuwein & Allis, 2001). For the฀purpose฀of฀this฀review,฀we฀will฀focus฀on฀H3฀acetylation฀of฀lysine฀9฀residues฀ (H3K9Ac)฀at฀the฀5¢ regions and how it pertains to regulating gene activation. The฀amount฀of฀acetylation฀on฀histone฀tails฀is฀controlled฀by฀the฀opposing฀enzymatic activities of histone acetyltransferases (HATs) and histone deacetylases (HDACs)฀(Kuo฀&฀Allis,฀1998).฀Histone฀acetylation฀neutralizes฀the฀positive฀charge฀ of the histone tail and decreases its affinity to negatively charged DNA generating a more open DNA conformation (euchromatin) (Hong, SchrothMatthews, Yau, & Bradbury, 1993;฀Sealy฀&฀Chalkley,฀1978). Transcription factors, regulatory complexes and RNA polymerase transcription factors then have access to the DNA, and expression฀of฀the฀corresponding฀genes฀is฀facilitated.฀Thus,฀H3K9Ac฀is฀a฀marker฀of฀ active฀gene฀transcription.฀On฀the฀other฀hand,฀removal฀of฀the฀acetyl฀group฀by฀HDAC฀ enzymes฀restores฀the฀positive฀charge฀to฀the฀lysine฀residue,฀fostering฀stronger฀interactions between histones and DNA, reducing the accessibility of transcription factors and the transcription apparatus to their cognate binding sites, resulting in gene silencing฀ (heterochromatin)฀ (Davie฀ &฀ Chadee,฀ 1998). Permissive and repressed intermediate chromatin states also provide an additional level of epigenetic regulation (Tsankova et al., 2007). This suggests that the active targeting of histonemodifying฀ enzymes฀ and฀ chromodomain฀ proteins฀ determines฀ the฀ state฀ of฀ histone฀ modification and level of expression of the underlying genes.

3.2

DNA Methylation

Euchromatin is generally associated with hypomethylated DNA, whereas heterochromatin is associated with hypermethylated DNA (Holliday & Pugh, 1975).

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In mammalian genomes, methylation mostly occurs at the carbon-5 position of cytosine residues of 5¢-cytosine-phosphodiester-guanine฀ (CpG)-3¢ dinucleotide motifs, converting฀ cytosine฀ to฀ 5-methylcytosine฀ (5-mC)฀ (Razin฀ &฀ Szyf,฀ 1984). In human cells฀60–80%฀of฀CpG฀dinucleotide฀sequences฀are฀methylated฀(Razin฀&฀Szyf,฀1984). Many฀ studies฀ of฀ epigenetic฀ regulation฀ have฀ focused฀ on฀ CpG-rich฀ regions฀ (CpG฀ islands)฀often฀found฀at฀gene฀promoters฀(Antequera฀&฀Bird,฀1993; Bird, 1996; GardinerGarden & Frommer, 1987). Recent studies, however, illustrate the importance of 5-mC฀markings฀within฀intragenic฀and฀intergenic฀regions฀in฀mediating฀tissue-specific฀ gene฀expression฀(Ching฀et฀al.,฀2005;฀Fazzari฀&฀Greally,฀2004; Khulan et al., 2006). In฀ vertebrates,฀ there฀ is฀ a฀ cell-specific฀ pattern฀ of฀ methylation฀ on฀ CpG฀ dinucleotides฀(Razin฀&฀Szyf,฀1984). These methylation patterns are actively maintained by a฀ family฀ of฀ enzymes฀ called฀ DNA฀ methyltransferases฀ (DNMTs)฀ that฀ catalyze฀ the฀ transfer฀of฀a฀methyl-group฀(CH3฀or฀C1 group) from the methyl donor S-adenosylmethionine฀(SAM)฀to฀cytosine฀residues฀to฀form฀5-mC฀(Adams,฀McKay,฀Craig,฀&฀ Burdon, 1979).฀The฀DNMT-1฀maintenance฀methyltransferase฀has฀a฀preference฀for฀ hemi-methylated DNA (Bestor & Verdine, 1994; Leonhardt & Bestor, 1993; Smith, 1994)฀and฀restores฀methylation฀to฀the฀CpG฀dinucleotides฀of฀the฀nascent฀DNA฀strand฀ following DNA replication, providing a mechanism for the safeguarding of epigenetic programs in proliferating cells (Bestor, 1988, 1992).฀DNMT-3a฀and฀DNMT-3b,฀ on the other hand, are responsible for the wave of de novo methylation during early embryogenesis฀ and฀ actively฀ methylate฀ CpG฀ dinucleotides฀ within฀ non-dividing฀ somatic฀cells,฀such฀as฀neurons฀(Okano,฀Bell,฀Haber,฀&฀Li,฀1999). DNA methylation directly and indirectly regulates gene silencing through sequential฀ effects฀ on฀ chromatin฀ structure฀ (Bird,฀ 2001;฀ Bird฀ &฀ Wolffe,฀ 1999; Hashimshony,฀Zhang,฀Keshet,฀Bustin,฀&฀Cedar,฀ 2003; Kadonaga, 1998; Li, 2002; Nan et al., 1998). In the direct mechanism, DNA methylation within transcription factor binding sites interferes with the binding of methylation sensitive transcription factors to their cognate binding sites (Tate & Bird, 1993;฀ Watt฀ &฀ Molloy,฀ 1988). Herein, DNA methylation serves as an epi-mutation of the transcription factor binding site฀and฀repels฀the฀transcription฀factor.฀Indirectly,฀methylated฀DNA฀attracts฀methyl-CpG฀ binding฀ domain฀ (MBD)-containing฀ protein฀ family฀ members฀ such฀ as฀ methyl-CpG฀ binding฀protein฀(MeCP)-2,฀which฀bind฀to฀methylated฀DNA฀to฀suppress฀gene฀expression (Bird, 2001;฀Bird฀&฀Wolffe,฀1999; Hashimshony et al., 2003; Kadonaga, 1998; Li, 2002; Nan et al., 1998). These MBD proteins are themselves transcriptional repressors, and are further coupled to other co-repressor proteins and histone modification฀ enzymes,฀ leading฀ to฀ repressive฀ chromatin฀ remodeling฀ and฀ gene฀ silencing฀ (Jones et al., 1998; Ng et al., 1999;฀Wade฀et฀al.,฀1999; Zhang et al., 1999).

3.3

DNA Demethylation

Although DNA methylation patterns are removed passively during DNA replication in primordial germ cells (Morgan, Santos, Green, Dean, & Reik, 2005), the precise mechanisms by which active demethylation occurs in mammals remains a subject of debate฀(Ooi฀&฀Bestor,฀2008).฀One฀proposal฀is฀that฀the฀cell฀is฀able฀to฀remove฀and฀replace฀

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mutations฀in฀the฀DNA฀by฀nucleotide฀excision฀repair฀(Weiss,฀Keshet,฀Razin,฀&฀Cedar,฀ 1996). In contrast, base excision repair involves the removal of a mutated or chemically altered฀ base฀ and฀ its฀ replacement฀ with฀ the฀ correct฀ base฀ (David฀ &฀ Williams,฀ 1998). However, the removal of nucleotides would seriously compromise the integrity of the genome when undergoing complete demethylation, as observed in the paternal genome following฀fertilization฀of฀the฀embryo฀(Oswald฀et฀al.,฀2000). In addition, demethylation events are very rapid and it appears unlikely that an excision-repair system would be able to complete genome-wide demethylation and nucleotide replacement within this time period. MBD2b (a shorter isoform of MBD2) has been reported to trigger active DNA demethylation by removal of methyl groups directly from the cytosine base and to induce gene฀ expression฀ in฀ mammalian฀ cells฀ (Bhattacharya,฀ Ramchandani,฀ Cervoni,฀ &฀ Szyf,฀ 1999;฀Cervoni,฀Bhattacharya,฀&฀Szyf,฀1999;฀Cervoni฀&฀Szyf,฀2001;฀Detich,฀Bovenzi,฀&฀ Szyf,฀2003; Detich, Hamm et al. 2003;฀Detich,฀Theberge,฀&฀Szyf,฀2002; Hamm et al., 2008;฀Ramchandani,฀Bhattacharya,฀Cervoni,฀&฀Szyf,฀1999;฀Szyf฀&฀Bhattacharya,฀2002a, 2002b).฀The฀reaction฀requires฀a฀water฀molecule฀and฀transfers฀the฀methyl฀group฀off฀the฀ cytosine to form methanol (Bhattacharya et al., 1999;฀Cervoni฀et฀al.,฀1999; Ramchandani et al., 1999). Although the assignment of demethylase activity to MBD2b was contested (Boeke,฀Ammerpohl,฀Kegel,฀Moehren,฀&฀Renkawitz,฀2000; Ng et al., 1999;฀Wade฀et฀al.,฀ 1999), MBD2b levels are inversely correlated to the levels of DNA methylation of certain genes in hepatocytes (Goel, Mathupala, & Pedersen, 2003) and lymphocytes from lupus patients฀(Balada,฀Ordi-Ros,฀Serrano-Acedo,฀Martinez-Lostao,฀&฀Vilardell-Tarres,฀2007), and depletion of MBD2b results in hypermethylation of unmethylated genes in metastatic cancer (Pakneshan, Tetu, & Rabbani, 2004;฀Shukeir,฀Pakneshan,฀Chen,฀Szyf,฀&฀ Rabbani, 2006). It has been suggested that MBD2b might carry the potential for bidirectional enzymatic฀ activity฀ (Detich฀ et฀ al.,฀ 2002). Likewise, a recent publication provides evidence฀for฀DNA฀demethylation฀induced฀by฀MBD3฀(Brown,฀Suderman,฀Hallett,฀&฀ Szyf,฀2008),฀while฀two฀other฀reports฀propose฀that฀DNMT-3a฀and฀DNMT-3b฀possess฀ deaminase activity and are involved in a dynamic demethylation-methylation pathway that operates during gene transcription (Kangaspeska et al., 2008; Metivier et al., 2008). Herein, MBD2 knockout female mice are significantly slower at retrieving pups to their nests in comparison to the wild-type dams (Hendrich, Guy, Ramsahoye, Wilson,฀&฀Bird,฀2001), signifying the potential involvement of DNA (de)methylation mechanisms in long-term programming by maternal behavior.

4

DNA Methylation and the Maternal Programming of Stress Responses

The 5¢฀non-coding฀variable฀exon฀1฀region฀of฀the฀rat฀hippocampal฀GR฀gene฀contains฀ multiple฀alternate฀sequences,฀including฀the฀exon฀17฀sequence,฀which฀appears฀to฀be฀a฀ brain-specific฀ promoter฀ (McCormick฀ et฀ al.,฀ 2000). In adult rats, hippocampal expression฀of฀GR฀mRNA฀splice฀variants฀containing฀exon฀17 is increased by maternal

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LG-ABN฀behavior.฀High฀and฀Low฀LG-ABN฀mothers฀differ฀in฀the฀frequency฀of฀pup฀ LG-ABN฀only฀during฀the฀first฀postnatal฀week.฀We฀found฀group฀differences฀in฀the฀ methylation฀status฀of฀individual฀CpG฀dinucleotides฀in฀the฀exon฀17฀promoter฀sequence฀ emerged฀during฀the฀same฀time฀period,฀involving฀a฀process฀of฀demethylation฀(Weaver฀ et al., 2004).฀The฀exon฀17 promoter contains a binding site for the transcription factor nerve฀growth฀factor-inducible฀protein฀A฀(NGFI-A,฀also฀known฀as฀Egr-1,฀Zif268฀or฀ Krox-24)฀ (Habener,฀ Meyer,฀ Yun,฀ Waeber,฀ &฀ Hoeffler,฀ 1990; Hyman et al., 1988; Milbrandt, 1987, 1988; Mitchell, Rowe, Boksa, & Meaney, 1990; Montminy, Sevarino,฀ Wagner,฀ Mandel,฀ &฀ Goodman,฀ 1986; Self & Nestler, 1995; Sheng & Greenberg, 1990; Smythe, Rowe, & Meaney, 1994; Tsukada, Fink, Mandel, & Goodman, 1987). By the end of the first postnatal week, the 5¢฀CpG฀dinucleotide฀of฀ the NGFI-A binding site is demethylated in the High LG-ABN but not in the Low LG-ABN฀ group,฀ and฀ the฀ maternal฀ effect฀ persists฀ through฀ to฀ adulthood.฀ Crossfostering reverses the differences in methylation of the 5¢฀CpG฀dinucleotide,฀proposing a direct relationship between maternal behavior and changes in DNA methylation of฀the฀GR฀exon฀17฀promoter฀(Weaver฀et฀al.,฀2004). The methylation differences described above suggest an alteration of NGFI-A binding.฀ In฀ support฀ of฀ this,฀ chromatin฀ immunoprecipitation฀ (ChIP)฀ assays฀ (CraneRobinson,฀Myers,฀Hebbes,฀Clayton,฀&฀Thorne,฀1999) indicate that binding of NGFI-A protein฀to฀the฀hippocampal฀GR฀exon฀17 promoter in adult pups is three-fold higher in offspring฀of฀High฀LG-ABN฀mothers฀than฀in฀offspring฀of฀Low฀LG-ABN฀dams฀(Weaver฀ et al., 2004). Also, transient transfection studies show that DNA methylation reduces the฀ability฀of฀NGFI-A฀to฀activate฀the฀GR฀exon฀17฀promoter฀(Weaver฀et฀al.,฀2007). NGFI-A activates the genes by recruiting a transcriptional coactivator and HAT called cyclic฀ adenosine฀ 3¢, 5¢ monophosphate (cAMP) response element binding proteinbinding฀protein฀(CBP)฀to฀the฀promoter฀region.฀ChIP฀assays฀on฀the฀same฀tissue฀samples฀ used฀in฀the฀NGFI-A฀studies,฀with฀an฀antibody฀against฀the฀acetylated฀form฀of฀H3,฀show฀ increased฀association฀of฀acetylated฀H3K9฀with฀the฀GR฀exon฀17 promoter in offspring of the฀High฀LG-ABN฀mothers฀(Weaver฀et฀al.,฀2007). These findings are consistent with the฀hypothesis฀that฀increased฀NGFI-A฀binding฀to฀the฀GR฀exon฀17 promoter and recruitment of HATs results in increased transcriptional activation. Taken together, these findings suggest that an epi-mutation at a single cytosine residue within the NGFI-A response element alters NGFI-A binding and might explain the sustained effect of maternal care on hippocampal GR expression and HPA responses to stress.

4.1

Epigenetic Programming by Maternal Care Is Reversible in the Adult Animal

Given the bidirectional relationship between DNA methylation and chromatin structure (Razin฀&฀Cedar,฀1977), chromatin remodeling is potentially reversible and therefore amenable฀to฀therapeutic฀intervention฀(Szyf,฀2001). Evidence for this is provided by tissue฀ culture฀ studies.฀ The฀ HDAC฀ inhibitor฀ (HDACi)฀ Trichostatin฀ A฀ (TSA)฀can฀

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induce histone acetylation (Yoshida, Kijima, Akita, & Beppu, 1990) and trigger active,฀replication-independent฀DNA฀demethylation฀(Cervoni฀&฀Szyf,฀2001).฀We฀have฀ proposed that increased acetylation results in increased accessibility of a gene to the demethylation฀machinery฀(Cervoni฀&฀Szyf,฀2001)฀and฀that฀transcription฀is฀required฀ for฀ active฀ DNA฀ demethylation฀ in฀ genes฀ silenced฀ through฀ methylation฀ (D’Alessio,฀ Weaver,฀&฀Szyf,฀2007).฀While฀small฀changes฀in฀DNA฀methylation฀could฀be฀attributable฀in฀part฀to฀the฀small฀number฀of฀new฀neurons฀that฀arise฀from฀the฀subgranulare฀zone฀ of฀the฀dentate฀gyrus฀and฀subventricular฀zone฀of฀the฀lateral฀ventricles฀throughout฀life฀ (Cameron฀&฀Gould,฀1994), widespread changes in the epigenetic state of GR in the mammalian brain could only occur if the DNA demethylation and methylation machinery฀remain฀present฀in฀the฀cell.฀We฀therefore฀addressed฀the฀question฀of฀whether฀ epigenetic programming early in life could be modulated during adulthood. Central฀infusion฀of฀TSA฀in฀the฀adult฀offspring฀of฀Low฀LG-ABN฀mothers฀increased฀ H3K9Ac,฀cytosine฀demethylation,฀NGFI-A฀binding฀and฀GR฀exon฀17 promoter activation and reduced HPA responses and anxiety-related behavior to levels comparable with those฀observed฀in฀the฀offspring฀of฀High฀LG-ABN฀dams฀(Weaver฀et฀al.,฀2004, 2006). Subsequent฀expression฀profiling฀of฀TSA-treated฀rats฀reveal฀specific฀effects฀of฀TSA฀on฀ the฀hippocampal฀transcriptome฀(Weaver฀et฀al.,฀2006). These results suggest causal relationships฀between฀maternal฀care,฀histone฀acetylation,฀DNA฀methylation฀of฀the฀exon฀17 promoter, GR expression and HPA responses to stress. Accordingly,฀we฀reasoned฀that,฀if฀DNA฀methylating฀and฀demethylating฀enzymes฀ dynamically maintain the DNA methylation pattern in adult neurons, then it should also฀be฀possible฀to฀reverse฀the฀demethylated฀state฀of฀the฀GR฀exon฀17 promoter. Dietary l-methionine is converted by methionine adenosyltransferase into SAM, which serves฀ as฀ a฀ methyl฀ donor฀ for฀ DNA฀ methylation฀ (described฀ above)฀ (Cantoni,฀ 1975; Mudd฀ &฀ Cantoni,฀ 1958). In addition, SAM inhibits DNA demethylation either by stimulating฀ DNA฀ methylation฀ enzymes฀ (Pascale฀ et฀ al.,฀ 1991) or by inhibiting demethylases฀(Szyf,฀2001), and systemic injection of the methyl-donor l-methionine has been previously shown to increase the levels of SAM and DNA methylation (Tremolizzo฀et฀al.,฀2002).฀Chronic฀central฀infusion฀of฀adult฀offspring฀of฀High฀or฀Low฀ LG-ABN mothers with l-methionine increased DNA methylation within the NGFI-A binding฀site฀and฀reduced฀NGFI-A฀binding฀to฀the฀exon฀17 promoter selectively in the offspring of High LG-ABN dams, abolishing group differences in both hippocampal GR฀expression฀and฀HPA฀responses฀to฀stress฀(Weaver฀et฀al.,฀2005). These studies illustrate that maternal epigenetic programming early in life can be reversed later in life, suggesting that DNA methylation patterns are dynamic and potentially reversible even in adult neurons, which presumably contain the machinery฀required฀for฀de฀novo฀DNA฀demethylation฀or฀methylation฀that฀mediate฀ CpG฀methylation฀rheostasis฀in฀the฀mature฀mammalian฀brain. Fig. 2 (continued) which mediates HPA and behavioral responses. Asterisk: In the adult rat, the epigenetic฀state฀of฀the฀hippocampal฀GR฀exon฀17 promoter is reversible. Injection of the histone deacetylase inhibitor Trichostatin A (TSA) into the hippocampus of offspring from Low LG-ABN mothers increases฀histone฀acetylation,฀facilitating฀demethylation฀and฀increased฀activation฀of฀the฀GR฀exon฀17 promoter.฀On฀the฀other฀hand,฀l-methionine (MET) inhibits DNA demethylation and increases DNA methylation,฀which฀inhibits฀NGFI-A฀binding฀and฀reduces฀GR฀exon฀17 promoter activity in the offspring of High LG-ABN dams (see text for details)

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Mechanisms Leading from Maternal Care to Chromatin Plasticity

We฀ propose฀ that฀ maternal฀ behavior฀ stimulates฀ a฀ signaling฀ pathway,฀ which฀ activates฀ certain transcription factors directing the epigenetic machinery (chromatin and DNA modifying฀ enzymes)฀ to฀ specific฀ targets฀ within฀ the฀ genome.฀ Our฀ in฀ vivo฀ and฀ in฀ vitro฀ studies suggest that maternal LG in early life elicits a thyroid hormone-dependent increase in serotonin (5-HT) activity at 5-HT7฀receptors,฀and฀the฀subsequent฀activation฀of฀ cAMP and cAMP-dependent protein kinase A (PKA) accompanied by increased hippocampal฀ expression฀ of฀ the฀ transcription฀ factor฀ NGFI-A฀ and฀ CBP฀ (Chawla,฀ Hardingham, Quinn, & Bading, 1998) (Meaney, Aitken, Sapolsky, 1987; Meaney et al., 2000) (Fig. 2a).฀In฀synergy,฀NGFI-A฀also฀directly฀regulates฀transcription฀of฀CBP,฀which฀ has HAT activity (Yu et al., 2004).฀NGFI-A฀and฀CBP฀are฀recruited฀to฀the฀GR฀exon฀17

Fig. 2 Our฀model฀of฀epigenetic฀(re)programming฀of฀hippocampal฀glucocorticoid฀receptor฀(GR)฀gene฀ expression and stress responses by maternal behavior. (a)฀Maternal฀licking/grooming฀and฀arched-back฀ nursing (LG-ABN) of the offspring increases hippocampal serotonin (5-HT) turnover and activation of a 5-HT7฀receptor,฀which฀is฀positively฀coupled฀to฀cyclic฀adenosine฀3¢, 5¢ monophosphate (cAMP). Increased cAMP activity results in activation of protein kinase-A (PKA) and cAMP response elementbinding฀protein฀(CREB).฀Subsequent฀phosphorylated-CREB฀(pCREB)฀activity฀drives฀expression฀of฀ the฀transcription฀factor฀NGFI-A,฀which฀targets฀its฀cognate฀binding฀site฀on฀the฀GR฀exon฀17 promoter. (b)฀NGFI-A฀recruits฀a฀histone฀acetyltransferase฀called฀CREB฀binding฀protein฀(CBP)฀that฀increases฀ acetylation and accessibility to the DNA demethylase MBD2b and stable GR promoter activation. (c) Increased stress levels stimulate GR activation in the hippocampus (described in Fig. 1),

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promoter฀in฀response฀to฀maternal฀care฀(Weaver฀et฀al.,฀2007).฀The฀GR฀exon฀17 promoter region฀ contains฀ a฀ binding฀ site฀ for฀ NGFI-A฀ (McCormick฀ et฀ al.,฀ 2000). Interestingly, NGFI-A can actively target methylated-DNA binding proteins to genomic targets (Carvin,฀ Parr,฀ &฀ Kladde,฀ 2003), and we previously showed that a pharmacological increase in acetylation in vivo using TSA resulted in demethylation of the GR promoter in฀the฀hippocampus฀(Weaver฀et฀al.,฀2004).฀Equally,฀tissue฀culture฀experiments฀demonstrate฀ that฀ recruitment฀ of฀ NGFI-A฀ to฀ the฀ GR฀ exon฀ 17 promoter results in replicationindependent฀demethylation฀(Cervoni฀&฀Szyf,฀2001). We฀have฀recently฀found฀that฀both฀NGFI-A฀and฀MBD2b฀proteins฀simultaneously฀ bind฀the฀same฀GR฀exon฀17 promoter molecule and that binding of NGFI-A to its cognate฀ binding฀ site฀ was฀ required฀ for฀ MBD2b฀ to฀ function฀ as฀ a฀ demethylating฀ enzyme฀(Weaver฀et฀al.,฀unpublished฀data).฀While฀the฀exact฀mechanisms฀by฀which฀ NGFI-A฀recruits฀MBD2b฀to฀the฀GR฀exon฀17 promoter remain unknown, these findings are consistent with the idea that NGFI-A facilitates the accessibility of the DNA sequence฀to฀MBD2b฀leading฀to฀targeted฀active฀demethylation฀(Fig.฀2b). Accordingly, we propose that NGFI-A plays a bimodal role in the regulation of GR expression. During early development, high physiological levels of NGFI-A induced฀by฀maternal฀behavior฀interact฀with฀the฀methylated฀GR฀exon฀17 promoter and฀trigger฀demethylation฀of฀the฀sequence,฀whereas฀later฀in฀life฀physiological฀levels฀ of฀ NGFI-A฀ discriminate฀ between฀ the฀ methylated฀ and฀ unmethylated฀ GR฀ exon฀ 17 promoters฀and฀selectively฀activate฀the฀unmethylated฀sequences.฀Therefore,฀the฀different฀methylation฀states฀of฀the฀GR฀exon฀17 promoter from the offspring of High and Low LG-ABN results in different levels of hippocampal GR expression (Fig. 2c). This suggests that the neonatal brain of altricial species such as the rat is not฀ an฀ immature฀ version฀ of฀ the฀ adult฀ brain฀ but฀ is฀ uniquely฀ designed฀ to฀ optimize฀ epigenetic programming by the mother.

5

Trans-Generational Inheritance of Epigenetic Programming by Maternal Behavior

Another important aspect of epigenetic traits is their potential heritability. Transgenerational epigenetic inheritance has been demonstrated in plants (Richards, 2006)฀and฀mammals฀(Morgan,฀Sutherland,฀Martin,฀&฀Whitelaw,฀1999).฀The฀question฀ here is how these maternal effects remain stably transmitted across generations. Evidence from both human and non-human primates suggest that individual differences in infant-directed behaviors are transmitted from mother to daughter (Fairbanks, 1989;฀Miller,฀Kramer,฀Warner,฀Wickramaratne,฀&฀Weissman,฀1997). In the rat, the adult female offspring of High LG-ABN dams are themselves high in maternal LG-ABN behavior towards their pups and, likewise, the offspring of Low LG-ABN mothers are low in maternal LG-ABN behavior towards their pups (Francis et al., 1999).฀ Consistent฀ with฀ this,฀ cross-fostering฀ paradigms฀ provide฀ evidence for direct effects of maternal behavior on the transmission of maternal

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LG-ABN behavior (Francis et al., 1999), supporting an epigenetic mechanism for transmission of individual differences in maternal behavior. The central neuroanatomical circuitry in the female rat brain thought to mediate maternal-responsive behaviors is termed the maternal circuit (for review, see Fleming, 1986; Numan & Numan, 1994). Mechanisms regulating estrogen receptor (ER)-a฀ function฀ in฀ the฀ medial฀ preoptic฀ area฀ (MPOA)฀ and฀ the฀ connections฀ to฀ the฀ maternal circuit and the mesolimbic dopamine system appear to be crucial in regulating฀ maternal฀ LG-ABN฀ behavior฀ towards฀ the฀ offspring฀ (Champagne,฀ Diorio,฀ Sharma, & Meaney, 2001, 2003;฀ Champagne฀ et฀ al.,฀ 2004;฀ Numan฀ &฀ Callahan,฀ 1980; Stack, Balakrishnan, Numan, & Numan, 2002). In infancy, the female offspring฀of฀High฀LG-ABN฀mothers฀show฀increased฀MPOA฀ER-a expression compared฀to฀Low฀LG-ABN฀mothers,฀which฀is฀maintained฀into฀adulthood฀(Champagne฀ et al., 2003).฀Consistent฀with฀this,฀cross-fostering฀paradigms฀provided฀evidence฀for฀ direct effects of maternal behavior on ER-a฀expression฀in฀the฀MPOA฀(Champagne,฀ Weaver,฀Diorio,฀Dymov,฀Szyf,฀&฀Meaney,฀2006).฀The฀question฀then฀concerns฀the฀ mechanism whereby variations in maternal behavior result in long-term changes of MPOA฀ER-a expression in the offspring.

5.1

Evidence for Epigenetic Mechanisms Linking Maternal Care of the Mother with Maternal Behavior in the Female Offspring

Differential promoter usage is an important mechanism for tissue-specific and developmentally regulated ER-a gene expression (Schibler & Sierra, 1987). The 5¢ non-coding฀variable฀exon฀1฀region฀of฀the฀rat฀ER-a gene contains multiple alternate sequences,฀including฀the฀exon฀1b฀sequence,฀which฀appears฀to฀be฀a฀neuronal฀tissuespecific promoter (Schibler & Sierra, 1987).฀We฀argued฀that฀the฀maternal฀programming of ER-a expression was associated with differences in cytosine methylation of฀the฀exon฀1b฀promoter.฀We฀found฀group฀differences฀in฀the฀methylation฀status฀of฀ individual฀ CpG฀ dinucleotides฀ in฀ the฀ exon฀ 1b฀ promoter฀ sequence;฀ levels฀ of฀ DNA฀ methylation were decreased in the adult offspring of High compared to Low LG-ABN฀mothers฀(Champagne฀et฀al.,฀2006). Activation of the Janus kinase (JAK) and signal transducers and activators of transcription (STAT) pathway increases ER-a expression (Frasor & Gibori, 2003). Exon฀ 1b฀ contains฀ a฀ binding฀ site฀ for฀ the฀ growth฀ hormone-฀ and฀prolactin-activated฀ STAT-5b฀ protein.฀ The฀ difference฀ in฀ methylation฀ of฀ the฀ CpG฀ dinucleotides฀ in฀ the฀ STAT-5b binding site suggests an alteration of STAT-5b binding. In support of this, ChIP฀assays฀indicate฀that฀STAT-5b฀binding฀to฀the฀MPOA฀ER-a฀exon฀1b฀promoter฀ in adult females is increased in offspring of High LG-ABN mothers compared to Low LG-ABN mothers. Finally, we found increased expression of the transcription factor฀ STAT-5b฀ in฀ the฀ MPOA฀ of฀ neonates฀ reared฀ by฀ High฀ compared฀ with฀ Low฀ LG-ABN mothers, with no differences in STAT-5b expression in the adult offspring

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(Champagne฀ et฀ al.,฀ 2006). The role of STAT-5b in epigenetic regulation of the MPOA฀ER-a฀exon฀1b฀promoter฀may฀therefore฀be฀bimodal,฀similar฀to฀the฀proposed฀ role NGFI-A plays in regulation of hippocampal GR expression (described above). From these studies, our working hypothesis is that increased maternal LG-ABN behavior activates STAT-5b expression and targets demethylation of the STAT-5b binding site on the ER-a฀ exon฀ 1b฀ promoter,฀ which฀ increases฀ exon฀ 1b฀ promoter฀ activation and expression of ER-a฀ in฀ the฀ MPOA฀ (Fig.฀ 3a–c). Increased ER-a expression฀in฀the฀MPOA฀might฀serve฀to฀increase฀estrogen฀sensitivity฀in฀response฀to฀ the rising hormone levels experienced in late gestation. ER-a is essential for estradiol-mediated฀ induction฀ of฀ oxytocin฀ receptor฀ (OTR)฀ gene฀ expression฀ and฀ receptor binding (Bale & Dorsa, 1995; de Kloet, Voorhuis, Boschma, & Elands, 1986; Johnson et al., 1989;฀ Young,฀ Wang,฀ Donaldson,฀ &฀ Rissman,฀ 1998). The nonapeptide฀OT฀binds฀its฀cognate฀receptor฀to฀modulate฀gene฀transcription฀and฀is฀a฀ key mediator of complex emotional and social behaviors, including maternal responsivity (Fahrbach, Morrell, & Pfaff, 1984; Pedersen & Prange, 1979) and levels of licking and grooming of the offspring (Fahrbach et al., 1984). Furthermore, increases฀ in฀ hypothalamic฀ OTR฀ binding฀ may฀ potentially฀ activate฀ mesolimbic฀ dopaminergic฀neurons,฀which฀serve฀to฀increase฀the฀duration฀and฀frequency฀of฀LG฀ provided towards the pups (Fig. 3d). Although future studies will obviously be critical in providing evidence of causality in this general cascade of events, we believe these studies form the basis for a mechanism for the programming of individual differences in ER-a expression and the transmission of maternal behavior in the female offspring.

5.2

Environmental Influences and the Mother–Offspring Dyad

Exposure of the mother to environmental adversity alters the nature of the mother– offspring interaction, which in turn influences the development of defensive responses to threat as well as reproductive strategies in the offspring (Agrawal, 2001; Rossiter, 1999) (Fig. 3 asterisk). For example, gestational stress during the third฀trimester฀reduces฀OTR฀levels฀and฀LG฀behavior฀in฀High฀LG-ABN฀mothers,฀an฀ effect฀which฀is฀sustained฀through฀the฀second฀and฀third฀litter฀(Champagne฀&฀Meaney,฀ 2006). The adult offspring of the gestationally stressed High LG-ABN mothers resemble those of Low LG-ABN mothers on behavioral measures of anxiety and maternal฀ behavior฀ (Champagne฀ &฀ Meaney,฀ 2006). Furthermore, the prenatallystressed High LG-ABN offspring also have reduced hippocampal GR protein expression฀ comparable฀ to฀ non-stressed฀ Low฀ LG-ABN฀ offspring฀ (Weaver,฀ Champagne,฀&฀Meaney,฀unpublished฀data).฀Consistent฀with฀this,฀Mueller฀&฀Bale฀ (2008) recently showed using mice that early gestational stress results in increased hypothalamic฀ CRF฀ and฀ GR฀ exon฀ 17 promoter methylation and decreased central CRF฀and฀GR฀expression,฀which฀in฀turn฀increases฀HPA฀responsivity฀in฀the฀offspring฀ (Mueller & Bale, 2008). This is the first illustration of epigenetic reprogramming

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Fig. 3 Our฀model฀of฀epigenetic฀(re)programming฀of฀estrogen฀receptor-alpha฀(ER-a) gene expression in฀ the฀ medial฀ preoptic฀ area฀ (MPOA)฀ and฀ the฀ transmission฀ of฀ maternal฀ behavior฀ in฀ the฀ female฀ offspring. (a) Maternal licking and grooming (LG) toward the offspring might activate the Janus kinase (JAK) and signal transducers and activators of transcription (STAT) pathway that drives expression of the transcription factor STAT-5b, which targets its cognate binding site on the ER-a฀exon฀1b฀promoter.฀ (b) STATs recruit histone acetyltransferases that increase acetylation and accessibility to DNA demethylase฀enzyme(s)฀and฀stable฀ER-a promoter activation. (c) Increased ER-a expression leads to increased estrogen (E) sensitivity in response to the rising hormone levels experienced in late gestation. The hormone-bound form of ER-a is a transcription factor that drives oxytocin receptor (OTR)฀gene฀expression.฀Oxytocin฀(OT)฀binds฀to฀its฀cognate฀receptor฀and฀regulates฀gene฀expression฀in฀ neural systems mediating maternal LG behavior. (d)฀Connections฀between฀the฀mesolimbic฀dopamine฀ (DA)฀neurons฀and฀hypothalamic฀OT฀neurons฀mediate฀these฀effects.฀Before฀the฀onset฀of฀maternal฀LG,฀ the magnitude of DA release is greater amongst High LG mothers, which in turn LG their offspring for longer bouts by comparison to Low LG dams. Asterisk: Points of inflection: gestationally-stress High฀ LG-ABN฀ mothers฀ show฀ reduced฀ MPOA฀ OTR฀ expression฀ and฀ LG฀ behavior;฀ whereas฀ postweaning environmental enrichment and impoverishment reverse the maternal effects of low and high LG฀behavior฀on฀MPOA฀OTR฀expression฀and฀LG฀behavior฀in฀female฀offspring,฀respectively.฀These฀ effects are also transmitted to the next generation of offspring (see text for details)

by stress-mediated modulation of the epigenome during early gestation and suggests฀that฀the฀enzyme(s)฀required฀for฀DNA฀methylation฀are฀involved฀and฀might฀ also contribute to the timing and vulnerability of the developing fetus to maternal perturbations during pregnancy (Mueller & Bale, 2008). Interestingly, post-weaning environmental enrichment and impoverishment can reverse behavioral differences between฀female฀High฀and฀Low฀LG-ABN฀offspring฀on฀measures฀of฀OTR฀expression,฀ maternal฀ behavior฀ and฀ anxiety฀ (Champagne฀ &฀ Meaney,฀ 2007), implying that the

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social environment both within and beyond the postnatal period can (re)program the neural pathways that regulate maternal LG-ABN behavior. Together, these findings suggest that mother–offspring interactions early in life enhance the capacity for defensive responses in the progeny by programming emotional, cognitive and endocrine systems toward increased sensitivity to adversity, and that these programs can be transmitted across generations via an epigenetic mode of inheritance involving maternal behavior, which in turn is influenced by the ambient conditions.

6

Epigenetic Programming Early in Life and Inter-Individual Differences in Human Behavior and Health

Studies in humans suggest that the forebrain GR function is complicit in the regulation฀of฀the฀HPA฀axis฀and฀the฀development฀of฀affective฀disorders฀and฀other฀sequelae฀ (DeRijk & Sternberg, 1997; Holsboer, 2000;฀Invitti,฀Redaelli,฀Baldi,฀&฀Cavagnini,฀ 1999).฀This฀raises฀the฀question฀of฀whether฀epigenetic฀modification฀in฀response฀to฀ early environmental conditions can explain the effects of early infant adversity on adult฀health฀in฀humans฀[for฀detailed฀review,฀see฀Weaver฀(2009)]. Due to the important ethical, social and legal implications arising from any attempt to harvest living cells฀from฀the฀CNS,฀the฀epigenetic฀alterations฀in฀the฀peripheral฀blood฀mononuclear฀ cells฀ (PBMCs)฀ are฀ commonly฀ compared฀ in฀ human฀ studies.฀ Interestingly,฀ during฀ their฀lifetime,฀monozygotic฀twins฀increasingly฀differ฀in฀their฀epigenotype฀(life-long฀ drift) (Fraga et al., 2005),฀which฀might฀explain฀the฀frequent฀discordance฀of฀neuropsychiatric฀ disorders฀ such฀ as฀ schizophrenia฀ and฀ bipolar฀ disorder฀ (Kato,฀ Iwamoto,฀ Kakiuchi,฀Kuratomi,฀&฀Okazaki,฀2005). These studies raise the possibility that suboptimal epigenetic modifications arise over time resulting in late onset mental pathologies. In support of this, ribosomal RNA (rRNA) promoter methylation (Brown฀&฀Szyf,฀2007, 2008) was shown to be increased in suicide victims compared to controls (McGowan et al., 2008), suggesting a reduced capacity for protein synthesis฀in฀suicide฀brains฀(Brown฀&฀Szyf,฀2007, 2008). Protein synthesis has long been฀ known฀ to฀ be฀ required฀ for฀ associative฀ learning฀ to฀ consolidate฀ into฀ long-term฀ memory฀(Agranoff,฀Davis,฀Casola,฀&฀Lim,฀1967), which involves epigenetic regulation฀(Korzus,฀Rosenfeld,฀&฀Mayford,฀2004), and a decline in cognitive plasticity is commonly observed with age (Kadar, Silbermann, Brandeis, & Levy, 1990). More฀recently,฀however,฀we฀found฀altered฀expression฀levels฀of฀DNMT฀enzymes฀and฀ aberrant gene silencing by DNA methylation in suicide brains (Poulter et al., 2008), suggesting that a shift in the steady-state balance between DNA methylating and demethylating machinery might influence specific neural pathways and account for inter-individual differences in emotional reactivity and mental health in humans. The effects of tactile stimulation through mother–infant interactions on interindividual differences in cognitive development and stress responses in rodents is consistent฀with฀work฀in฀humans฀(Feldman,฀Eidelman,฀Sirota,฀&฀Weller,฀2002) and non-human primates (Harlow & Zimmermann, 1959).฀This฀raises฀the฀question฀of฀

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whether฀comparable฀epigenetic฀labile฀regions฀to฀the฀GR฀exon฀17 promoter exist in the human genome. Alignment of splice sites reveals that the distally located exon 1F฀ promoter฀ of฀ human฀ type฀ II฀ GR฀ (hGR,฀ OMIM฀ +138040;฀ NR3C1)฀ shows฀ high฀ homology฀to฀the฀GR฀exon฀17 promoter in the rat, and contains an NGFI-A binding site (Turner & Muller, 2005). Interestingly, studies in healthy human subjects show that฀CpG฀methylation฀patterns฀of฀conserved฀transcription฀factor฀binding฀sites฀on฀the฀ NR3C1฀exon฀1F฀promoter฀are฀both฀stochastic฀and฀unique฀to฀the฀individual฀(Turner,฀ Pelascini, Macedo, & Muller, 2008). Furthermore, neonatal methylation at the 5¢ CpG฀dinucleotide฀within฀the฀NGFI-A฀binding฀site฀on฀the฀NR3C1฀exon฀1F฀promoter฀ has been suggested as an early epigenetic marker of maternal mood and risk of altered฀HPA฀function฀in฀the฀developing฀infant฀(Oberlander฀et฀al.,฀2008). Although future฀studies฀are฀required฀to฀examine฀the฀functional฀consequence฀of฀the฀methylated฀ 5¢฀CpG฀dinucleotide,฀these฀findings฀are฀consistent฀with฀our฀studies฀in฀the฀neonate฀ and adult offspring of Low LG-ABN mothers that show hypermethylation of the 5¢ CpG฀ dinucleotide฀ within฀ the฀ NGFI-A฀ binding฀ site฀ on฀ the฀ exon฀ 17 promoter, decreased฀GR฀expression฀and฀increased฀HPA฀responsivity฀(Weaver฀et฀al.,฀2004). In support of this paradigm, a recent study shows that the NGFI-A binding sites on the NR3C1฀ exon฀ 1F฀ promoter฀ are฀ hypermethylated฀ in฀ the฀ hippocampus฀ of฀ suicide฀ victims with a history of childhood abuse, and that mRNA transcript expression from฀ the฀ exon฀ 1F฀ promoter฀ is฀ decreased฀ in฀ comparison฀ to฀ controls฀ (victims฀ of฀ sudden, accidental death with no history of abuse) (McGowan et al., 2009), suggesting that the transmission of vulnerability for depression from parent to offspring could occur through the epigenetic modification of genomic regions that are implicated in the regulation of stress responses.

7

Concluding Remarks

Epigenetic mechanisms are likely to play an underlying role in the developmental origins of health and disease, whereby transient environmental cues and events during early development can persistently alter gene regulation resulting in metabolic imprinting affecting disease susceptibility. The studies presented in this review provide support for the effect of maternal behavior on endocrine and behavioral responses to stress in the offspring, and that these effects are biologically embedded throughout life by epigenetic programming. However, reprogramming can take place at several points throughout the life-span in response to changes in environmental conditions. Notably, maternal care influences the maternal behavior of female offspring, an effect that also appears to be related to epigenetic regulation of endocrine function, providing a mechanism for trans-generational inheritance of maternal behavior from mother to offspring. Because environmental stressors influence the nature of maternal behavior, maternal care remains a key mediator of epigenetic programming of neurodevelopment, and in turn the expression of biological defense systems that respond to environmental adversity.

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Acknowledgments I would like to thank Dr. Shelley E. Brown for her helpful comments and numerous constructive suggestions throughout the preparation of this manuscript. Competing฀ Interests฀ Statement.฀ The฀ author฀ declares฀ that฀ he฀ has฀ no฀ competing฀ financial฀ interests.

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Proceedings of the National Academy of Sciences of the United States of America, 103, 3480–3485. Weaver,฀I.฀C.฀G.฀(2009).฀Life฀at฀the฀interface฀between฀a฀dynamic฀environment฀and฀a฀fixed฀genome:฀ epigenetic programming of stress responses by maternal behavior. In D. Janigro (Ed) Mammalian brain development, contemporary neuroscience฀(pp.฀17–39).฀Totowa,฀NJ:฀Humana฀ Press. Weiss,฀A.,฀Keshet,฀I.,฀Razin,฀A.,฀&฀Cedar,฀H.฀(1996).฀DNA฀demethylation฀in฀vitro:฀Involvement฀of฀ RNA. Cell, 86,฀709–718. Wondrak,฀G.฀T.,฀Cervantes-Laurean,฀D.,฀Jacobson,฀E.฀L.,฀&฀Jacobson,฀M.฀K.฀(2000).฀Histone฀carbonylation in vivo and in vitro. Biochemical Journal, 351 Pt 3,฀769–777. Yoshida,฀M.,฀Kijima,฀M.,฀Akita,฀M.,฀&฀Beppu,฀T.฀(1990).฀Potent฀and฀specific฀inhibition฀of฀mammalian฀ histone deacetylase both in vivo and in vitro by trichostatin A. The Journal of Biological Chemistry, 265,฀17174–17179. Young,฀L.฀J.,฀Wang,฀Z.,฀Donaldson,฀R.,฀&฀Rissman,฀E.฀F.฀(1998).฀Estrogen฀receptor฀alpha฀is฀essential฀ for induction of oxytocin receptor by estrogen. NeuroReport, 9,฀933–936. Yu,฀J.,฀de฀Belle,฀I.,฀Liang,฀H.,฀&฀Adamson,฀E.฀D.฀(2004).฀Coactivating฀factors฀p300฀and฀CBP฀are฀ transcriptionally฀ crossregulated฀ by฀ Egr1฀ in฀ prostate฀ cells,฀ leading฀ to฀ divergent฀ responses.฀ Molecular Cell, 15,฀83–94. Zhang,฀ Y.,฀ Ng,฀ H.฀ H.,฀ Erdjument-Bromage,฀ H.,฀ Tempst,฀ P.,฀ Bird,฀ A.,฀ &฀ Reinberg,฀ D.฀ (1999).฀ Analysis of the NuRD subunits reveals a histone deacetylase core complex and a connection with DNA methylation. Genes & Development, 13,฀1924–1935.

Prenatal Viral Infection in Mouse: An Animal Model of Schizophrenia S. Hossein Fatemi and Timothy D. Folsom

Abstract Schizophrenia is a major debilitating disease with a lifetime prevalence of 1% throughout the world. There is robust epidemiologic evidence indicating that environmental contributions, such as prenatal infections, may lead to the genesis of schizophrenia. Our laboratory has developed an animal model using human influenza virus to infect pregnant Balb/c and C57BL/6 mice intranasally at selected time points during pregnancy to investigate the role of prenatal viral infection on brain development. In this chapter, we review our research using this model and the changes in brain structure, gene expression, neurochemistry, and behavior that are observed in the offspring of infected dams. Our observations are consistent with findings observed in subjects with schizophrenia, providing additional evidence for the role of prenatal viral infection in the etiology of this disease. Keywords Schizophrenia฀•฀Prenatal฀viral฀infection฀•฀Brain฀•฀Mouse฀•฀Microarray

1

An Introduction to Prenatal Viral Infection and Schizophrenia

The potential role of prenatal viral infection as a cause of schizophrenia dates back to฀Menninger฀(1928), who described 67 cases of schizophrenia in a large cohort of patients฀who฀contracted฀influenza฀during฀the฀pandemic฀of฀1919฀(caused฀by฀the฀same฀ S.H.฀Fatemi฀(*) Department฀of฀Psychiatry,฀Division฀of฀Neuroscience฀Research,฀University฀of฀Minnesota, Medical฀School,฀MMC฀392,฀420฀Delaware฀Street฀S.E,฀Minneapolis,฀MN฀55455,฀USA and Department฀of฀Pharmacology,฀University฀of฀Minnesota฀Medical฀School,฀Minneapolis, MN฀55455,฀USA and Department฀of฀Neuroscience,฀University฀of฀Minnesota฀Medical฀School,฀Minneapolis, MN฀55455,฀USA e-mail:฀[email protected] J.D.฀Clelland฀(ed.),฀Genomics, Proteomics, and the Nervous System, Advances฀in฀Neurobiology฀2,฀DOI฀10.1007/978-1-4419-7197-5_4,฀ ©฀Springer฀Science+Business฀Media,฀LLC฀2011

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strain of virus used in our animal model). Later, an excess of schizophrenic patients were found to be born during late winter and spring, suggesting that influenza infections฀may฀be฀responsible฀for฀these฀cases฀(Hare,฀Price,฀&฀Slater,฀1972;฀Machon,฀ Mednick,฀&฀Schulsinger,฀1983).฀Moreover,฀there฀is฀a฀5–15%฀of฀the฀excess฀schizophrenic฀ births฀ in฀ the฀ Northern฀ Hemisphere฀ which฀ occur฀ during฀ the฀ months฀ of฀ January฀ and฀ March฀ (Boyd,฀ Pulver,฀ &฀ Stewart,฀ 1986;฀ Pallast,฀ Jongbloet,฀ &฀ Straatman, 1994;฀Susser,฀Brown,฀&฀Gorman,฀1999). This excess winter birth is not a฀methodological฀artifact,฀nor฀is฀it฀due฀to฀unusual฀patterns฀of฀conception฀(Pulver,฀ Liang,฀ &฀ Wolyniec,฀ 1992; Susser et al., 1999).฀ Additional฀ studies฀ have฀ shown฀ increased risk of schizophrenia in individuals whose mothers were exposed to influenza฀during฀pregnancy฀(positive฀studies:฀Adams,฀Kendell,฀&฀Hare,฀1993; Barr, Mednick,฀&฀Munk-Jorgensen,฀1990;฀Fahy,฀Jones,฀&฀Sham,฀1993;฀Kunugi,฀Nanko,฀ &฀Takei,฀1995;฀McGrath,฀Pemberton,฀&฀Welham,฀1994;฀O’Callaghan,฀Gibson,฀&฀ Colohan, 1991;฀ Sham,฀ O’Callaghan,฀ &฀ Takei,฀ 1992; Takei et al., 1994; Takei, Sham,฀&฀O’Callaghan,฀1994). Other studies, however, have found equivocal or no effect฀ (Adams฀ et฀ al.,฀ 1993;฀ Erlenmeyer-Kimling฀ et฀ al.,฀ 1994;฀ Kendell฀ &฀ Kemp,฀ 1989;฀ Selten฀ &฀ Sleats,฀ 1994;฀ Susser,฀ Lin,฀ &฀ Brown,฀ 1994;฀ Takei,฀ Van฀ Os,฀ &฀ Murray,฀ 1995;฀ Torrey,฀ Bowler,฀ Taylor,฀ &฀ Gottesman,฀ 1994). The fourth through seventh months of gestation has been identified to be a period during which the risk of฀developing฀schizophrenia฀is฀especially฀high฀(Brown฀et฀al.,฀2004; Susser et al., 1997).฀Additional฀cohort฀studies฀have฀shown฀increased฀risk฀for฀schizophrenia฀following฀ prenatal฀ exposure฀ to฀ influenza฀ (Mednick,฀ Huttunen,฀ &฀ Macon,฀ 1994; Stober,฀Franzek,฀&฀Beckmann,฀1992;฀Wright,฀Rakei,฀Rifkin,฀&฀Murray,฀1995).฀A฀ review฀by฀Brown฀(2006)฀summarized฀that฀there฀was฀a฀10-฀to฀20-fold฀risk฀of฀developing schizophrenia following prenatal exposure to rubella; a sevenfold risk of developing schizophrenia following prenatal exposure to influenza in the first trimester and a threefold increased risk following infection in early to mid-gestation; presence of maternal antibodies against Toxoplasma gondii lead to a 2.5-fold increased฀risk฀(Brown,฀2006). Nucleotide฀ sequences฀ homologous฀ to฀ retroviral฀ polymerase฀ genes฀ have฀ been฀ identified฀in฀the฀cerebrospinal฀fluid฀(CSF)฀of฀subjects฀with฀schizophrenia฀while฀no฀ such sequences were found in individuals with noninflammatory neurological illnesses฀or฀in฀normal฀subjects฀(Karlsson฀et฀al.฀2001;฀Lewis,฀2001). These studies suggest that the development of schizophrenia involves the interaction of genetic and฀environmental฀risks฀on฀brain฀development฀(Lewis).฀Moreover,฀identification฀of฀ potential environmental risk factors, such as influenza virus or retroviruses such as endogenous฀ retroviral-9฀ family฀ and฀ the฀ human฀ endogenous฀ retrovirus-W฀ family฀ (HERV-W,฀ grouped฀ on฀ the฀ basis฀ of฀ a฀ tryptophan฀ (W)฀ tRNA฀ motif฀ identified฀ in฀ HERV-W฀sequences;฀Blond฀et฀al.,฀1999)฀observed฀by฀Karlsson฀et฀al.฀(2001), will help in targeting early interventions at repressing the expression of these transcripts.฀ An฀ alternate฀ approach฀ would฀ be฀ to฀ vaccinate฀ against฀ influenza,฀ thus฀ influencing the course and outcome of schizophrenia in the susceptible individuals (Lewis,฀2001). Several groups, including our laboratory, have shown evidence for viral infections and/or immune challenges being responsible for production of abnormal

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brain structure and function in rodents where mothers were exposed to viral insults throughout฀ pregnancy฀ (Fatemi,฀ Pearce,฀ Brooks,฀ &฀ Sidwell,฀ 2005;฀ Meyer฀ et฀ al.,฀ 2006).฀Application฀of฀the฀viral฀mimic฀polyribocytidilic฀acid฀(PolyI:C)฀at฀embryonic฀day฀9฀(E9)฀(which฀corresponds฀to฀late฀first฀trimester฀of฀pregnancy฀in฀humans)฀ and฀ E17฀ (which฀ corresponds฀ to฀ late฀ second฀ trimester฀ of฀ pregnancy฀ in฀ humans),฀ resulted in distinct behavioral deficits, neuropathological differences and acute cytokine฀ responses฀ (Meyer฀ et฀ al.).฀ Date฀ of฀ exposure฀ resulted฀ in฀ differences฀ of฀ behavioral฀deficits฀with฀those฀exposed฀on฀E9฀showing฀impaired฀exploratory฀behavior฀while฀those฀exposed฀on฀E17฀displayed฀perseverative฀behavior฀(Meyer฀et฀al.).฀ Moreover,฀ time฀ of฀ exposure฀ had฀ differing฀ effects฀ on฀ Reelin฀ expression฀ with฀ a฀ greater฀reduction฀following฀exposure฀on฀E9฀(Meyer฀et฀al.).฀In฀contrast,฀following฀ PolyI:C฀ exposure฀ at฀ E17,฀ there฀ was฀ an฀ upregulation฀ of฀ caspase-3฀ in฀ the฀ dorsal฀ dentate฀ gyrus฀ (Meyer฀ et฀ al.,฀ 2006)฀ signifying฀ increased฀ apoptosis฀ (Rami฀ et฀ al.,฀ 2003).฀ Finally,฀ exposure฀ at฀ E17฀ resulted฀ in฀ increased฀ IL-10฀ and฀ TNF-a in fetal brain฀(Meyer฀et฀al.).฀Taken฀together,฀these฀results฀provide฀evidence฀that฀the฀time฀of฀ prenatal insult results in important differences that are persistent through adulthood.

2

Mouse Brain Development

Mouse฀ brain฀ development฀ progresses฀ through฀ four฀ prenatal฀ stages฀ that฀ exhibit฀ various฀ susceptibilities฀ to฀ prenatal฀ insults.฀ These฀ stages฀ consist฀ of:฀ (1)฀ cleavage฀ and฀blastulation,฀equal฀to฀E0–E5;฀(2)฀implantation,฀gastrulation,฀and฀early฀organogenesis,฀ equal฀ to฀ E5–E10;฀ (3)฀ organogenesis,฀ equal฀ to฀ E10–E14;฀ and฀ (4)฀ fetal฀ growth฀and฀development,฀equal฀to฀E14–E19฀or฀20฀(Hogan,฀Beddington,฀Constantini,฀ &฀ Lacy,฀ 1994). These stages in mouse brain development can be roughly compared฀ to฀ human฀ brain฀ development฀ at฀ the฀ first฀ (E0–E10)฀ and฀ second฀ trimesters (E10–E19/20),฀respectively.฀Mouse฀postnatal฀brain฀development฀(P1–P10)฀corresponds฀roughly฀to฀the฀third฀trimester฀of฀brain฀growth฀in฀man฀(Susser฀et฀al.,฀1999). Recent฀evidence฀points฀to฀several฀prenatal฀sensitive฀periods฀in฀each฀brain฀area฀of฀ the mouse, when neurogenesis, gliogenesis, or neuronal migration is at its peak (Morgane,฀ Austin-LaFrance,฀ Bronzino,฀ Tonkiss,฀ &฀ Galler,฀ 1992). Thus, brain areas, such as the cerebral cortex, hippocampus, and cerebellum, each follow specific฀timetables฀for฀brain฀growth฀(Acuff-Smith฀&฀Vorhees,฀1999;฀Avishai-Eliner,฀ Brunson,฀ Sandman,฀ &฀Baram,฀2002;฀ Boksa฀&฀ Luheshi,฀2003;฀ Kaufmann,฀2000; Morgane฀ et฀ al.,฀ 1992;฀ Romijn,฀ Hofman,฀ &฀ Gramsbergen,฀ 1991; Susser et al., 1999). For example, critical periods of neurogenesis for various brain areas in mouse฀consist฀of฀E9฀(cerebellar฀Purkinje฀cells),฀E11–15.5฀(hippocampal฀pyramidal฀ cells),฀ E11.5–16฀ (cerebral฀ cortex),฀ and฀ P2–13฀ (cerebellar฀ granule฀ cells)฀ (Rodier,฀ 1980). There are additional critical periods for neurogenesis that affect specific brain cell populations. For example, neural crest-derived cells migrating to craniofacial฀structures฀are฀most฀susceptible฀to฀various฀insults฀during฀E8.5–10.5฀in฀the฀ mouse฀(Yamagishi,฀Garg,฀Matsuoka,฀Thomas,฀&฀Srivastava,฀1999).฀Accordingly,฀

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retinoic acid causes deleterious effects on development of brain and craniofacial structures฀during฀the฀E8–10฀period฀(Holson,฀Adams,฀&฀Ferguson,฀1999).฀Previous฀ studies show an increased risk of growth retardation and other morbidity/mortality in฀ mice฀ that฀ were฀ prenatally฀ exposed฀ an฀ H1N1฀ strain฀ of฀ influenza฀ virus฀ in฀ the฀ E8–10฀period฀(Molanova฀&฀Blaskovic,฀1975).฀We฀have฀also฀shown฀that฀administration฀of฀the฀same฀strain฀of฀virus฀on฀E7,฀E9,฀E16,฀and฀E18฀of฀pregnancy฀results฀in฀ multiple฀ brain฀ abnormalities฀ in฀ postnatal฀ mice฀ (Fatemi฀ et฀ al.,฀ 1999; Fatemi, Folsom,฀ Reutiman,฀ &฀ Sidwell,฀ 2008;฀ Fatemi,฀ Pearce,฀ et฀ al.,฀ 2005; Fatemi, Reutiman,฀ Folsom,฀ Huang,฀ et฀ al.,฀ 2008;฀ Fatemi,฀ Reutiman,฀ Folsom,฀ &฀ Sidwell,฀ 2008;฀Fatemi,฀Sidwell,฀Akhter,฀et฀al.,฀1998;฀Fatemi,฀Sidwell,฀Kist,฀et฀al.,฀1998; Su et al., 2008;฀ Winter฀ et฀ al.,฀ 2008). Indeed, the onset of teratogenic susceptibility begins฀at฀relatively฀similar฀temporal฀windows฀in฀mouse฀and฀man฀(E5฀and฀E11–12,฀ respectively)฀(Wilson,฀1964). However, exact extrapolation from mouse to human is not possible based on specific days of pregnancy, but can be construed qualitatively from prenatal and postnatal peaks of neurogenesis, gliogenesis, and/or neuron฀migration/differentiation฀(Morgane฀et฀al.,฀1992). The accumulation of various immunologic, epidemiologic and case study data indicate that prenatal maternal exposure to human influenza infection around late first to mid-second trimester can฀ increase฀ the฀ risk฀ of฀ births฀ that฀ lead฀ to฀ schizophrenia฀ (Brown฀ et฀ al.,฀ 2004; Susser et al., 1999).

3 3.1

Impact of Prenatal Viral Infection on Brain Development Brain Structural Abnormalities Following Prenatal Viral Infection

Numerous฀reports฀have฀documented฀the฀presence฀of฀various฀neuropathologic฀findings฀ in฀ postmortem฀ brains฀ of฀ patients฀ with฀ schizophrenia฀ (Boyer,฀ Phillips,฀ Rousseau,฀ &฀ Ilivitsky,฀ 2007;฀ Crespo-Facorro,฀ Barbadillo,฀ Pelayo-Terán,฀ &฀ Rodríguez-Sánchez,฀ 2007). These findings include: cortical atrophy; ventricular enlargement; reduced volumes of hippocampus, amygdala and parahippocampal gyrus; disturbed cytoarchitecture in hippocampus; and reduced cell size in Purkinje฀cells฀of฀the฀cerebellum฀(Andreasen,฀1999;฀Arnold฀&฀Trojanowski,฀1996). Prenatal฀ viral฀ infection฀ of฀ Balb/c฀ and฀ C57BL/6฀ mice฀ at฀ E9฀ (late฀ first฀ trimester),฀ E16฀(middle฀second฀trimester)฀and฀E18฀(late฀second฀trimester)฀lead฀to฀deleterious฀ effects on brain morphology including changes in volume, fractional anisotropy, and pyramidal cell density consistent with these observed changes in subjects with schizophrenia฀(Fatemi,฀Earle,฀et฀al.,฀2002; Fatemi et al., 1999;฀Fatemi,฀Reutiman,฀ Folsom, Huang, et al., 2008). Following฀infection฀of฀Balb/c฀mice฀at฀E9฀with฀influenza,฀brains฀from฀infected฀ P0฀ offspring฀ displayed฀ decreases฀ in฀ neocortical฀ [39%฀ reduction฀ in฀ layer฀ I฀ (p฀