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Trastulla L, Dolgalev G, Moser S, Jiménez-Barrón LT, Andlauer TFM, von Scheidt M, Budde M, Heilbronner U, Papiol S, Teumer A, Homuth G, Völzke H, Dörr M, Falkai P, Schulze TG, Gagneur J, Iorio F, Müller-Myhsok B, Schunkert H, Ziller MJ. Distinct genetic liability profiles define clinically relevant patient strata across common diseases. Nat Commun 2024; 15:5534. [PMID: 38951512 PMCID: PMC11217418 DOI: 10.1038/s41467-024-49338-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2024] [Accepted: 05/31/2024] [Indexed: 07/03/2024] Open
Abstract
Stratified medicine holds great promise to tailor treatment to the needs of individual patients. While genetics holds great potential to aid patient stratification, it remains a major challenge to operationalize complex genetic risk factor profiles to deconstruct clinical heterogeneity. Contemporary approaches to this problem rely on polygenic risk scores (PRS), which provide only limited clinical utility and lack a clear biological foundation. To overcome these limitations, we develop the CASTom-iGEx approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue specific gene expression levels. The paradigmatic application of this approach to coronary artery disease or schizophrenia patient cohorts identified diverse strata or biotypes. These biotypes are characterized by distinct endophenotype profiles as well as clinical parameters and are fundamentally distinct from PRS based groupings. In stark contrast to the latter, the CASTom-iGEx strategy discovers biologically meaningful and clinically actionable patient subgroups, where complex genetic liabilities are not randomly distributed across individuals but rather converge onto distinct disease relevant biological processes. These results support the notion of different patient biotypes characterized by partially distinct pathomechanisms. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine paradigms.
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Affiliation(s)
- Lucia Trastulla
- Max Planck Institute of Psychiatry, Munich, Germany
- Technische Universität München Medical Graduate Center Experimental Medicine, Munich, Germany
- Human Technopole, Milan, Italy
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Georgii Dolgalev
- Department of Psychiatry, University of Münster, Münster, Germany
| | - Sylvain Moser
- Max Planck Institute of Psychiatry, Munich, Germany
- Technische Universität München Medical Graduate Center Experimental Medicine, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Laura T Jiménez-Barrón
- Max Planck Institute of Psychiatry, Munich, Germany
- International Max Planck Research School for Translational Psychiatry (IMPRS-TP), Munich, Germany
| | - Till F M Andlauer
- Max Planck Institute of Psychiatry, Munich, Germany
- Department of Neurology, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany
| | - Moritz von Scheidt
- Klinik für Herz-und Kreislauferkrankungen, Deutsches Herzzentrum München, Technical University Munich, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Monika Budde
- Institute of Psychiatric Phenomics and Genomics (IPPG), LMU University Hospital, LMU Munich, Munich, 80336, Germany
| | - Urs Heilbronner
- Institute of Psychiatric Phenomics and Genomics (IPPG), LMU University Hospital, LMU Munich, Munich, 80336, Germany
| | - Sergi Papiol
- Max Planck Institute of Psychiatry, Munich, Germany
- Institute of Psychiatric Phenomics and Genomics (IPPG), LMU University Hospital, LMU Munich, Munich, 80336, Germany
| | - Alexander Teumer
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Henry Völzke
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Institute of Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Marcus Dörr
- German Center for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Peter Falkai
- Max Planck Institute of Psychiatry, Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, 80336, Germany
| | - Thomas G Schulze
- Institute of Psychiatric Phenomics and Genomics (IPPG), LMU University Hospital, LMU Munich, Munich, 80336, Germany
- Department of Psychiatry and Behavioral Sciences, SUNY Upstate Medical University, Syracuse, NY, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Julien Gagneur
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
- Institute of Human Genetics, School of Medicine and Health, Technical University of Munich, Munich, Germany
- Computational Health Center, Helmholtz Center Munich, Neuherberg, Germany
| | | | - Bertram Müller-Myhsok
- Max Planck Institute of Psychiatry, Munich, Germany
- Institute of Translational Medicine, University of Liverpool, Liverpool, UK
| | - Heribert Schunkert
- Klinik für Herz-und Kreislauferkrankungen, Deutsches Herzzentrum München, Technical University Munich, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Michael J Ziller
- Max Planck Institute of Psychiatry, Munich, Germany.
- Department of Psychiatry, University of Münster, Münster, Germany.
- Center for Soft Nanoscience, University of Münster, Münster, Germany.
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2
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Pratt HE, Andrews G, Shedd N, Phalke N, Li T, Pampari A, Jensen M, Wen C, Consortium P, Gandal MJ, Geschwind DH, Gerstein M, Moore J, Kundaje A, Colubri A, Weng Z. Using a comprehensive atlas and predictive models to reveal the complexity and evolution of brain-active regulatory elements. SCIENCE ADVANCES 2024; 10:eadj4452. [PMID: 38781344 PMCID: PMC11114231 DOI: 10.1126/sciadv.adj4452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 04/25/2024] [Indexed: 05/25/2024]
Abstract
Most genetic variants associated with psychiatric disorders are located in noncoding regions of the genome. To investigate their functional implications, we integrate epigenetic data from the PsychENCODE Consortium and other published sources to construct a comprehensive atlas of candidate brain cis-regulatory elements. Using deep learning, we model these elements' sequence syntax and predict how binding sites for lineage-specific transcription factors contribute to cell type-specific gene regulation in various types of glia and neurons. The elements' evolutionary history suggests that new regulatory information in the brain emerges primarily via smaller sequence mutations within conserved mammalian elements rather than entirely new human- or primate-specific sequences. However, primate-specific candidate elements, particularly those active during fetal brain development and in excitatory neurons and astrocytes, are implicated in the heritability of brain-related human traits. Additionally, we introduce PsychSCREEN, a web-based platform offering interactive visualization of PsychENCODE-generated genetic and epigenetic data from diverse brain cell types in individuals with psychiatric disorders and healthy controls.
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Affiliation(s)
- Henry E. Pratt
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Gregory Andrews
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Tongxin Li
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Khoury College of Computer Science, Northeastern University, Boston, MA 02115, USA
| | - Anusri Pampari
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Matthew Jensen
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Cindy Wen
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | | | - Michael J. Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Daniel H. Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Mark Gerstein
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Andrés Colubri
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
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3
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Casey C, Fullard JF, Sleator RD. Unravelling the genetic basis of Schizophrenia. Gene 2024; 902:148198. [PMID: 38266791 DOI: 10.1016/j.gene.2024.148198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 12/07/2023] [Accepted: 01/19/2024] [Indexed: 01/26/2024]
Abstract
Neuronal development is a highly regulated mechanism that is central to organismal function in animals. In humans, disruptions to this process can lead to a range of neurodevelopmental phenotypes, including Schizophrenia (SCZ). SCZ has a significant genetic component, whereby an individual with an SCZ affected family member is eight times more likely to develop the disease than someone with no family history of SCZ. By examining a combination of genomic, transcriptomic and epigenomic datasets, large-scale 'omics' studies aim to delineate the relationship between genetic variation and abnormal cellular activity in the SCZ brain. Herein, we provide a brief overview of some of the key omics methods currently being used in SCZ research, including RNA-seq, the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and high-throughput chromosome conformation capture (3C) approaches (e.g., Hi-C), as well as single-cell/nuclei iterations of these methods. We also discuss how these techniques are being employed to further our understanding of the genetic basis of SCZ, and to identify associated molecular pathways, biomarkers, and candidate drug targets.
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Affiliation(s)
- Clara Casey
- Department of Biological Sciences, Munster Technological University, Bishopstown, Cork, Ireland; Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
| | - Roy D Sleator
- Department of Biological Sciences, Munster Technological University, Bishopstown, Cork, Ireland.
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4
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Fulton SL, Bendl J, Gameiro-Ros I, Fullard JF, Al-Kachak A, Lepack AE, Stewart AF, Singh S, Poller WC, Bastle RM, Hauberg ME, Fakira AK, Chen M, Cuttoli RDD, Cathomas F, Ramakrishnan A, Gleason K, Shen L, Tamminga CA, Milosevic A, Russo SJ, Swirski F, Blitzer RD, Slesinger PA, Roussos P, Maze I. ZBTB7A regulates MDD-specific chromatin signatures and astrocyte-mediated stress vulnerability in orbitofrontal cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.04.539425. [PMID: 37205394 PMCID: PMC10187272 DOI: 10.1101/2023.05.04.539425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Hyperexcitability in the orbitofrontal cortex (OFC) is a key clinical feature of anhedonic domains of Major Depressive Disorder (MDD). However, the cellular and molecular substrates underlying this dysfunction remain unknown. Here, cell-population-specific chromatin accessibility profiling in human OFC unexpectedly mapped genetic risk for MDD exclusively to non-neuronal cells, and transcriptomic analyses revealed significant glial dysregulation in this region. Characterization of MDD-specific cis-regulatory elements identified ZBTB7A - a transcriptional regulator of astrocyte reactivity - as an important mediator of MDD-specific chromatin accessibility and gene expression. Genetic manipulations in mouse OFC demonstrated that astrocytic Zbtb7a is both necessary and sufficient to promote behavioral deficits, cell-type-specific transcriptional and chromatin profiles, and OFC neuronal hyperexcitability induced by chronic stress - a major risk factor for MDD. These data thus highlight a critical role for OFC astrocytes in stress vulnerability and pinpoint ZBTB7A as a key dysregulated factor in MDD that mediates maladaptive astrocytic functions driving OFC hyperexcitability.
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Affiliation(s)
- Sasha L. Fulton
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jaroslav Bendl
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Isabel Gameiro-Ros
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F. Fullard
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Amni Al-Kachak
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ashley E. Lepack
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrew F. Stewart
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sumnima Singh
- Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- The Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Wolfram C. Poller
- Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- The Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Ryan M. Bastle
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mads E. Hauberg
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Amanda K. Fakira
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Min Chen
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Romain Durand-de Cuttoli
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Flurin Cathomas
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Aarthi Ramakrishnan
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kelly Gleason
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Li Shen
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Carol A. Tamminga
- Department of Psychiatry, UT Southwestern Medical Center, Dallas, TX, USA
| | - Ana Milosevic
- Laboratory of Molecular and Cellular Neuroscience, Rockefeller University, New York, New York, USA
| | - Scott J. Russo
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Filip Swirski
- Department of Cardiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- The Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Robert D. Blitzer
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Paul A. Slesinger
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, New York, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, New York, USA
| | - Ian Maze
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
- Howard Hughes Medical Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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5
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Ramamurthy E, Welch G, Cheng J, Yuan Y, Gunsalus L, Bennett DA, Tsai LH, Pfenning AR. Cell type-specific histone acetylation profiling of Alzheimer's disease subjects and integration with genetics. Front Mol Neurosci 2023; 15:948456. [PMID: 36683855 PMCID: PMC9853565 DOI: 10.3389/fnmol.2022.948456] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2022] [Accepted: 08/11/2022] [Indexed: 01/07/2023] Open
Abstract
We profile genome-wide histone 3 lysine 27 acetylation (H3K27ac) of 3 major brain cell types from hippocampus and dorsolateral prefrontal cortex (dlPFC) of subjects with and without Alzheimer's Disease (AD). We confirm that single nucleotide polymorphisms (SNPs) associated with late onset AD (LOAD) show a strong tendency to reside in microglia-specific gene regulatory elements. Despite this significant colocalization, we find that microglia harbor more acetylation changes associated with age than with amyloid-β (Aβ) load. In contrast, we detect that an oligodendrocyte-enriched glial (OEG) population contains the majority of differentially acetylated peaks associated with Aβ load. These differential peaks reside near both early onset risk genes (APP, PSEN1, PSEN2) and late onset AD risk loci (including BIN1, PICALM, CLU, ADAM10, ADAMTS4, SORL1, FERMT2), Aβ processing genes (BACE1), as well as genes involved in myelinating and oligodendrocyte development processes. Interestingly, a number of LOAD risk loci associated with differentially acetylated risk genes contain H3K27ac peaks that are specifically enriched in OEG. These findings implicate oligodendrocyte gene regulation as a potential mechanism by which early onset and late onset risk genes mediate their effects, and highlight the deregulation of myelinating processes in AD. More broadly, our dataset serves as a resource for the study of functional effects of genetic variants and cell type specific gene regulation in AD.
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Affiliation(s)
- Easwaran Ramamurthy
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Gwyneth Welch
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Jemmie Cheng
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States
| | - Yixin Yuan
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, United States
| | - Laura Gunsalus
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, United States
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, United States
| | - Li-Huei Tsai
- Department of Brain and Cognitive Sciences, Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, United States
- Broad Institute of MIT and Harvard, Cambridge, MA, United States
| | - Andreas R. Pfenning
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, United States
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6
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Tan Z, Peng Y, Xiong Y, Xiong F, Zhang Y, Guo N, Tu Z, Zong Z, Wu X, Ye J, Xia C, Zhu T, Liu Y, Lou H, Liu D, Lu S, Yao X, Liu K, Snowdon RJ, Golicz AA, Xie W, Guo L, Zhao H. Comprehensive transcriptional variability analysis reveals gene networks regulating seed oil content of Brassica napus. Genome Biol 2022; 23:233. [PMID: 36345039 PMCID: PMC9639296 DOI: 10.1186/s13059-022-02801-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 10/22/2022] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Regulation of gene expression plays an essential role in controlling the phenotypes of plants. Brassica napus (B. napus) is an important source for the vegetable oil in the world, and the seed oil content is an important trait of B. napus. RESULTS We perform a comprehensive analysis of the transcriptional variability in the seeds of B. napus at two developmental stages, 20 and 40 days after flowering (DAF). We detect 53,759 and 53,550 independent expression quantitative trait loci (eQTLs) for 79,605 and 76,713 expressed genes at 20 and 40 DAF, respectively. Among them, the local eQTLs are mapped to the adjacent genes more frequently. The adjacent gene pairs are regulated by local eQTLs with the same open chromatin state and show a stronger mode of expression piggybacking. Inter-subgenomic analysis indicates that there is a feedback regulation for the homoeologous gene pairs to maintain partial expression dosage. We also identify 141 eQTL hotspots and find that hotspot87-88 co-localizes with a QTL for the seed oil content. To further resolve the regulatory network of this eQTL hotspot, we construct the XGBoost model using 856 RNA-seq datasets and the Basenji model using 59 ATAC-seq datasets. Using these two models, we predict the mechanisms affecting the seed oil content regulated by hotspot87-88 and experimentally validate that the transcription factors, NAC13 and SCL31, positively regulate the seed oil content. CONCLUSIONS We comprehensively characterize the gene regulatory features in the seeds of B. napus and reveal the gene networks regulating the seed oil content of B. napus.
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Affiliation(s)
- Zengdong Tan
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Yan Peng
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Yao Xiong
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Feng Xiong
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Yuting Zhang
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Ning Guo
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Zhuo Tu
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Zhanxiang Zong
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Xiaokun Wu
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Jiang Ye
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Chunjiao Xia
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Tao Zhu
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Yinmeng Liu
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Hongxiang Lou
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Dongxu Liu
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Shaoping Lu
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Xuan Yao
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
| | - Kede Liu
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China
| | - Rod J. Snowdon
- grid.8664.c0000 0001 2165 8627Department of Plant Breeding, Justus Liebig University, Giessen, Germany
| | - Agnieszka A. Golicz
- grid.8664.c0000 0001 2165 8627Department of Plant Breeding, Justus Liebig University, Giessen, Germany
| | - Weibo Xie
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China ,grid.35155.370000 0004 1790 4137Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan, China
| | - Liang Guo
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China ,grid.35155.370000 0004 1790 4137Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Wuhan, China ,grid.488316.00000 0004 4912 1102Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China
| | - Hu Zhao
- grid.35155.370000 0004 1790 4137National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, China ,Hubei Hongshan Laboratory, Wuhan, China
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7
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Pai B, Tome-Garcia J, Cheng WS, Nudelman G, Beaumont KG, Ghatan S, Panov F, Caballero E, Sarpong K, Marcuse L, Yoo J, Jiang Y, Schaefer A, Akbarian S, Sebra R, Pinto D, Zaslavsky E, Tsankova NM. High-resolution transcriptomics informs glial pathology in human temporal lobe epilepsy. Acta Neuropathol Commun 2022; 10:149. [PMID: 36274170 PMCID: PMC9590125 DOI: 10.1186/s40478-022-01453-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 09/30/2022] [Indexed: 11/16/2022] Open
Abstract
The pathophysiology of epilepsy underlies a complex network dysfunction between neurons and glia, the molecular cell type-specific contributions of which remain poorly defined in the human disease. In this study, we validated a method that simultaneously isolates neuronal (NEUN +), astrocyte (PAX6 + NEUN-), and oligodendroglial progenitor (OPC) (OLIG2 + NEUN-) enriched nuclei populations from non-diseased, fresh-frozen human neocortex and then applied it to characterize the distinct transcriptomes of such populations isolated from electrode-mapped temporal lobe epilepsy (TLE) surgical samples. Nuclear RNA-seq confirmed cell type specificity and informed both common and distinct pathways associated with TLE in astrocytes, OPCs, and neurons. Compared to postmortem control, the transcriptome of epilepsy astrocytes showed downregulation of mature astrocyte functions and upregulation of development-related genes. To gain further insight into glial heterogeneity in TLE, we performed single cell transcriptomics (scRNA-seq) on four additional human TLE samples. Analysis of the integrated TLE dataset uncovered a prominent subpopulation of glia that express a hybrid signature of both reactive astrocyte and OPC markers, including many cells with a mixed GFAP + OLIG2 + phenotype. A further integrated analysis of this TLE scRNA-seq dataset and a previously published normal human temporal lobe scRNA-seq dataset confirmed the unique presence of hybrid glia only in TLE. Pseudotime analysis revealed cell transition trajectories stemming from this hybrid population towards both OPCs and reactive astrocytes. Immunofluorescence studies in human TLE samples confirmed the rare presence of GFAP + OLIG2 + glia, including some cells with proliferative activity, and functional analysis of cells isolated directly from these samples disclosed abnormal neurosphere formation in vitro. Overall, cell type-specific isolation of glia from surgical epilepsy samples combined with transcriptomic analyses uncovered abnormal glial subpopulations with de-differentiated phenotype, motivating further studies into the dysfunctional role of reactive glia in temporal lobe epilepsy.
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Affiliation(s)
- Balagopal Pai
- Department of Pathology and Laboratory Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jessica Tome-Garcia
- Department of Pathology and Laboratory Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Wan Sze Cheng
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - German Nudelman
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Kristin G Beaumont
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Icahn Institute for Data Science and Genomic Technology, New York, NY, 10029, USA
| | - Saadi Ghatan
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Fedor Panov
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Elodia Caballero
- Department of Pathology and Laboratory Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Kwadwo Sarpong
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Icahn Institute for Data Science and Genomic Technology, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lara Marcuse
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jiyeoun Yoo
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Yan Jiang
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Anne Schaefer
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Schahram Akbarian
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Robert Sebra
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Icahn Institute for Data Science and Genomic Technology, New York, NY, 10029, USA
| | - Dalila Pinto
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Icahn Institute for Data Science and Genomic Technology, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Elena Zaslavsky
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Nadejda M Tsankova
- Department of Pathology and Laboratory Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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8
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D'Ambrosio E, Pergola G, Pardiñas AF, Dahoun T, Veronese M, Sportelli L, Taurisano P, Griffiths K, Jauhar S, Rogdaki M, Bloomfield MAP, Froudist-Walsh S, Bonoldi I, Walters JTR, Blasi G, Bertolino A, Howes OD. A polygenic score indexing a DRD2-related co-expression network is associated with striatal dopamine function. Sci Rep 2022; 12:12610. [PMID: 35871219 PMCID: PMC9308811 DOI: 10.1038/s41598-022-16442-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Accepted: 07/11/2022] [Indexed: 11/09/2022] Open
Abstract
The D2 dopamine receptor (D2R) is the primary site of the therapeutic action of antipsychotics and is involved in essential brain functions relevant to schizophrenia, such as attention, memory, motivation, and emotion processing. Moreover, the gene coding for D2R (DRD2) has been associated with schizophrenia at a genome-wide level. Recent studies have shown that a polygenic co-expression index (PCI) predicting the brain-specific expression of a network of genes co-expressed with DRD2 was associated with response to antipsychotics, brain function during working memory in patients with schizophrenia, and with the modulation of prefrontal cortex activity after pharmacological stimulation of D2 receptors. We aimed to investigate the relationship between the DRD2 gene network and in vivo striatal dopaminergic function, which is a phenotype robustly associated with psychosis and schizophrenia. To this aim, a sample of 92 healthy subjects underwent 18F-DOPA PET and was genotyped for genetic variations indexing the co-expression of the DRD2-related genetic network in order to calculate the PCI for each subject. The PCI was significantly associated with whole striatal dopamine synthesis capacity (p = 0.038). Exploratory analyses on the striatal subdivisions revealed a numerically larger effect size of the PCI on dopamine function for the associative striatum, although this was not significantly different than effects in other sub-divisions. These results are in line with a possible relationship between the DRD2-related co-expression network and schizophrenia and extend it by identifying a potential mechanism involving the regulation of dopamine synthesis. Future studies are needed to clarify the molecular mechanisms implicated in this relationship.
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Affiliation(s)
- Enrico D'Ambrosio
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Giulio Pergola
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Antonio F Pardiñas
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Tarik Dahoun
- Department of Child and Adolescent Psychiatry, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Mattia Veronese
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Leonardo Sportelli
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Paolo Taurisano
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Kira Griffiths
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Sameer Jauhar
- Centre for Affective Disorders, Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Maria Rogdaki
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - Michael A P Bloomfield
- Division of Psychiatry, University College London, 6th Floor, Maple House, 149 Tottenham Court Road, London, W1T 7NF, UK
| | | | - Ilaria Bonoldi
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK
| | - James T R Walters
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of Medicine, Cardiff University, Cardiff, UK
| | - Giuseppe Blasi
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy.
| | - Oliver D Howes
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, SE5 8AF, UK.
- Institute of Clinical Sciences (ICS), Faculty of Medicine, Imperial College London, Du Cane Road, London, UK.
- H. Lundbeck A/S, Ottiliavej 9, 2500, Valby, Denmark.
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9
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Almodóvar-Payá C, Guardiola-Ripoll M, Giralt-López M, Gallego C, Salgado-Pineda P, Miret S, Salvador R, Muñoz MJ, Lázaro L, Guerrero-Pedraza A, Parellada M, Carrión MI, Cuesta MJ, Maristany T, Sarró S, Fañanás L, Callado LF, Arias B, Pomarol-Clotet E, Fatjó-Vilas M. NRN1 Gene as a Potential Marker of Early-Onset Schizophrenia: Evidence from Genetic and Neuroimaging Approaches. Int J Mol Sci 2022; 23:ijms23137456. [PMID: 35806464 PMCID: PMC9267632 DOI: 10.3390/ijms23137456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/27/2022] [Accepted: 06/28/2022] [Indexed: 12/10/2022] Open
Abstract
Included in the neurotrophins family, the Neuritin 1 gene (NRN1) has emerged as an attractive candidate gene for schizophrenia (SZ) since it has been associated with the risk for the disorder and general cognitive performance. In this work, we aimed to further investigate the association of NRN1 with SZ by exploring its role on age at onset and its brain activity correlates. First, we developed two genetic association analyses using a family-based sample (80 early-onset (EO) trios (offspring onset ≤ 18 years) and 71 adult-onset (AO) trios) and an independent case–control sample (120 healthy subjects (HS), 87 EO and 138 AO patients). Second, we explored the effect of NRN1 on brain activity during a working memory task (N-back task; 39 HS, 39 EO and 39 AO; matched by age, sex and estimated IQ). Different haplotypes encompassing the same three Single Nucleotide Polymorphisms(SNPs, rs3763180–rs10484320–rs4960155) were associated with EO in the two samples (GCT, TCC and GTT). Besides, the GTT haplotype was associated with worse N-back task performance in EO and was linked to an inefficient dorsolateral prefrontal cortex activity in subjects with EO compared to HS. Our results show convergent evidence on the NRN1 association with EO both from genetic and neuroimaging approaches, highlighting the role of neurotrophins in the pathophysiology of SZ.
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Affiliation(s)
- Carmen Almodóvar-Payá
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Maria Guardiola-Ripoll
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Maria Giralt-López
- Departament de Psiquiatria, Hospital Universitari Germans Trias i Pujol (HUGTP), 08916 Badalona, Barcelona, Spain;
- Departament de Psiquiatria i Medicina Legal, Universitat Autònoma de Barcelona (UAB), 08193 Bellaterra, Barcelona, Spain
| | - Carme Gallego
- Department of Cell Biology, Molecular Biology Institute of Barcelona (IBMB-CSIC), 08028 Barcelona, Barcelona, Spain;
| | - Pilar Salgado-Pineda
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Salvador Miret
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Centre de Salut Mental d’Adults de Lleida, Servei de Psiquiatria, Salut Mental i Addiccions, Hospital Universitari Santa Maria de Lleida, 25198 Lleida, Lleida, Spain
- Institut de Recerca Biomèdica (IRB), 25198 Lleida, Lleida, Spain
| | - Raymond Salvador
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - María J. Muñoz
- Complex Assistencial en Salut Mental Benito Menni, 08830 Sant Boi de Llobregat, Barcelona, Spain;
| | - Luisa Lázaro
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Department of Child and Adolescent Psychiatry and Psychology, Institute of Neurosciences, Hospital Clinic de Barcelona, 08036 Barcelona, Barcelona, Spain
- Departament de Medicina, Universitat de Barcelona (UB), 08036 Barcelona, Barcelona, Spain
- Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), 08036 Barcelona, Barcelona, Spain
| | - Amalia Guerrero-Pedraza
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Complex Assistencial en Salut Mental Benito Menni, 08830 Sant Boi de Llobregat, Barcelona, Spain;
| | - Mara Parellada
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Servicio de Psiquiatría del Niño y del Adolescente, Hospital General Universitario Gregorio Marañón, 28007 Madrid, Madrid, Spain
- Instituto de Investigación Sanitaria del Hospital Gregorio Marañón (IiSGM), 28007 Madrid, Madrid, Spain
- Departamento de Psiquiatría, Facultad de Medicina, Universidad Complutense, 28040 Madrid, Madrid, Spain
| | | | - Manuel J. Cuesta
- Servicio de Psiquiatría, Hospital Universitario de Navarra, 31008 Pamplona, Navarra, Spain;
- Instituto de Investigación Sanitaria de Navarra (IdiSNA), 31008 Pamplona, Navarra, Spain
| | - Teresa Maristany
- Departament de Diagnòstic per la Imatge, Hospital Sant Joan de Déu Fundació de Recerca, 08950 Esplugues de Llobregat, Barcelona, Spain;
| | - Salvador Sarró
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
| | - Lourdes Fañanás
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), 08028 Barcelona, Barcelona, Spain
| | - Luis F. Callado
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Department of Pharmacology, University of the Basque Country, UPV/EHU, 48940 Leioa, Bizkaia, Spain
- Biocruces Bizkaia Health Research Institute, 48903 Barakaldo, Bizkaia, Spain
| | - Bárbara Arias
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Institut de Biomedicina de la Universitat de Barcelona (IBUB), 08028 Barcelona, Barcelona, Spain
| | - Edith Pomarol-Clotet
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Correspondence: (E.P.-C.); (M.F.-V.)
| | - Mar Fatjó-Vilas
- FIDMAG Germanes Hospitalàries Research Foundation, 08830 Sant Boi de Llobregat, Barcelona, Spain; (C.A.-P.); (M.G.-R.); (P.S.-P.); (R.S.); (A.G.-P.); (S.S.)
- Instituto de Salud Carlos III, Biomedical Research Network in Mental Health (CIBERSAM), 28029 Madrid, Madrid, Spain; (S.M.); (L.L.); (M.P.); (L.F.); (L.F.C.); (B.A.)
- Departament de Biologia Evolutiva, Ecología i Ciències Ambientals, Universitat de Barcelona (UB), 08028 Barcelona, Barcelona, Spain
- Correspondence: (E.P.-C.); (M.F.-V.)
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10
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Ali MB, Dreger DL, Buckley RM, Mansoor S, Khan QM, Ostrander EA. Genetic Origins of the Two Canis lupus familiaris (Dog) Freight Dog Populations. J Hered 2022; 113:160-170. [PMID: 35575082 PMCID: PMC9113510 DOI: 10.1093/jhered/esac002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 01/24/2022] [Indexed: 01/27/2023] Open
Abstract
Despite periodic drops in popularity, Arctic sled dogs continue to play a vital role in northern societies, providing both freight transit and recreational race activities. In this study, we selected the Mackenzie River Husky, a freight dog of complex history, and the Chinook, an American Kennel Club recognized freight dog breed whose heritage reportedly overlaps that of the MKRH, for detailed population analysis. We tested each to determine their component breeds and used admixture analysis to ascertain their population structure. We utilized haplotype analysis to identify genomic regions shared between each population and their founding breeds. Our data show that the Alaskan Malamutes and modern Greenland sled dog contributed to both populations, but there are also unexpected contributions from the German Shepherd dog and Collie. We used haplotype analysis to identify genomic regions nearing fixation in population type and identify provocative genes in each region. Finally, in response to recent reports regarding the importance of dietary lipid genes in Arctic dogs, we analyzed 8 such genes in a targeted analysis observing signatures of selection in both populations at the MLXIPL gene loci. These data highlight the genetic routes that breeds of similar function have taken toward their occupation as successful sled dogs.
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Affiliation(s)
- Muhammad Basil Ali
- National Institute for Biotechnology and Genetic Engineering College (NIBGE), Faisalabad, Pakistan
- Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
| | - Dayna L Dreger
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 51, Room 5351, Bethesda, MD 20892, USA
| | - Reuben M Buckley
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 51, Room 5351, Bethesda, MD 20892, USA
| | - Shahid Mansoor
- National Institute for Biotechnology and Genetic Engineering College (NIBGE), Faisalabad, Pakistan
- Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
| | - Qaiser M Khan
- National Institute for Biotechnology and Genetic Engineering College (NIBGE), Faisalabad, Pakistan
- Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad, Pakistan
| | - Elaine A Ostrander
- National Human Genome Research Institute, National Institutes of Health, 50 South Drive, Building 51, Room 5351, Bethesda, MD 20892, USA
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11
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Kyzar EJ, Bohnsack JP, Pandey SC. Current and Future Perspectives of Noncoding RNAs in Brain Function and Neuropsychiatric Disease. Biol Psychiatry 2022; 91:183-193. [PMID: 34742545 PMCID: PMC8959010 DOI: 10.1016/j.biopsych.2021.08.013] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Revised: 08/05/2021] [Accepted: 08/12/2021] [Indexed: 02/07/2023]
Abstract
Noncoding RNAs (ncRNAs) represent the majority of the transcriptome and play important roles in regulating neuronal functions. ncRNAs are exceptionally diverse in both structure and function and include enhancer RNAs, long ncRNAs, and microRNAs, all of which demonstrate specific temporal and regional expression in the brain. Here, we review recent studies demonstrating that ncRNAs modulate chromatin structure, act as chaperone molecules, and contribute to synaptic remodeling and behavior. In addition, we discuss ncRNA function within the context of neuropsychiatric diseases, particularly focusing on addiction and schizophrenia, and the recent methodological developments that allow for better understanding of ncRNA function in the brain. Overall, ncRNAs represent an underrecognized molecular contributor to complex neuronal processes underlying neuropsychiatric disorders.
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Affiliation(s)
- Evan J Kyzar
- Center for Alcohol Research in Epigenetics, Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois; Department of Psychiatry, Columbia University Irving Medical Center, New York State Psychiatric Institute, New York, New York
| | - John Peyton Bohnsack
- Center for Alcohol Research in Epigenetics, Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois
| | - Subhash C Pandey
- Center for Alcohol Research in Epigenetics, Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois; Jesse Brown Veterans Affairs Medical Center, University of Illinois at Chicago, Chicago, Illinois; Department of Anatomy and Cell Biology, University of Illinois at Chicago, Chicago, Illinois.
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12
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Troutman TD, Kofman E, Glass CK. Exploiting dynamic enhancer landscapes to decode macrophage and microglia phenotypes in health and disease. Mol Cell 2021; 81:3888-3903. [PMID: 34464593 PMCID: PMC8500948 DOI: 10.1016/j.molcel.2021.08.004] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 07/19/2021] [Accepted: 07/30/2021] [Indexed: 12/24/2022]
Abstract
The development and functional potential of metazoan cells is dependent on combinatorial roles of transcriptional enhancers and promoters. Macrophages provide exceptionally powerful model systems for investigation of mechanisms underlying the activation of cell-specific enhancers that drive transitions in cell fate and cell state. Here, we review recent advances that have expanded appreciation of the diversity of macrophage phenotypes in health and disease, emphasizing studies of liver, adipose tissue, and brain macrophages as paradigms for other tissue macrophages and cell types. Studies of normal tissue-resident macrophages and macrophages associated with cirrhosis, obese adipose tissue, and neurodegenerative disease illustrate the major roles of tissue environment in remodeling enhancer landscapes to specify the development and functions of distinct macrophage phenotypes. We discuss the utility of quantitative analysis of environment-dependent changes in enhancer activity states as an approach to discovery of regulatory transcription factors and upstream signaling pathways.
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Affiliation(s)
- Ty D Troutman
- Department of Medicine, University of California, San Diego, San Diego, CA, USA; Division of Allergy and Immunology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA; Center for Inflammation and Tolerance, Cincinnati Children's Hospital Medical Center, Cincinnati, OH 45229, USA
| | - Eric Kofman
- Department of Cellular and Molecular Medicine, University of California, San Diego, San Diego, CA, USA; Bioinformatics and Systems Biology Graduate Program, University of California, San Diego, San Diego, CA, USA
| | - Christopher K Glass
- Department of Medicine, University of California, San Diego, San Diego, CA, USA; Department of Cellular and Molecular Medicine, University of California, San Diego, San Diego, CA, USA.
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13
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Long J, Long T, Li Y, Yuan P, Liu K, Li J, Cheng L. A Functional Polymorphism in Accessible Chromatin Region Confers Risk of Non-Small Cell Lung Cancer in Chinese Population. Front Oncol 2021; 11:698993. [PMID: 34552866 PMCID: PMC8450516 DOI: 10.3389/fonc.2021.698993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2021] [Accepted: 08/17/2021] [Indexed: 11/21/2022] Open
Abstract
Background The disease-associated non-coding variants identified by genome-wide association studies (GWASs) were enriched in open chromatin regions (OCRs) and implicated in gene regulation. Genetic variants in OCRs thus may exert regulatory functions and contribute to non-small cell lung cancer (NSCLC) susceptibility. Objective To fine map potential functional variants in GWAS loci that contribute to NSCLC predisposition using chromatin accessibility and histone modification data and explore their functions by population study and biochemical experimental analyses. Methods We mapped the chromatin accessible regions of lung tissues using data of assay for transposase-accessible chromatin using sequencing (ATAC-seq) in The Cancer Genome Atlas (TCGA) and prioritized potential regulatory variants within lung cancer GWAS loci by aligning with histone signatures using data of chromatin immunoprecipitation assays followed by sequencing (ChIP-seq) in the Encyclopedia of DNA Elements (ENCODE). A two-stage case–control study with 1,830 cases and 2,001 controls was conducted to explore the associations between candidate variants and NSCLC risk in Chinese population. Bioinformatic annotations and biochemical experiments were performed to further reveal the potential functions of significant variants. Results Sixteen potential functional single-nucleotide polymorphisms (SNPs) were selected as candidates from bioinformatics analyses. Three variants out of the 16 candidate SNPs survived after genotyping in stage 1 case–control study, and only the results of SNP rs13064999 were successfully validated in the analyses of stage 2 case–control study. In combined analyses, rs13064999 was significantly associated with NSCLC risk [additive model; odds ratio (OR) = 1.17; 95%CI, 1.07–1.29; p = 0.001]. Functional annotations indicated its potential enhancer bioactivity, and dual-luciferase reporter assays revealed a significant increase in luciferase activity for the reconstructed plasmid with rs13064999 A allele, when compared to the one with wild-type G allele (pA549 < 0.001, pSK-MES-1 = 0.004). Further electrophoretic mobility shift assays (EMSA) and super-shift assays confirmed a stronger affinity of HP1γ for the binding motif containing SNP rs13064999 A allele. Conclusion These findings suggested that the functional variant rs13064999, identified by the integration of ATAC-seq and ChIP-seq data, contributes to the susceptibility of NSCLC by affecting HP1γ binding, while the exact biological mechanism awaits further exploration.
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Affiliation(s)
- Jieyi Long
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tingting Long
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Li
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Peihong Yuan
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ke Liu
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiaoyuan Li
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Liming Cheng
- Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
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14
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Barrera J, Song L, Gamache JE, Garrett ME, Safi A, Yun Y, Premasinghe I, Sprague D, Chipman D, Li J, Fradin H, Soldano K, Gordân R, Ashley-Koch AE, Crawford GE, Chiba-Falek O. Sex dependent glial-specific changes in the chromatin accessibility landscape in late-onset Alzheimer's disease brains. Mol Neurodegener 2021; 16:58. [PMID: 34429139 PMCID: PMC8383438 DOI: 10.1186/s13024-021-00481-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 08/11/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND In the post-GWAS era, there is an unmet need to decode the underpinning genetic etiologies of late-onset Alzheimer's disease (LOAD) and translate the associations to causation. METHODS We conducted ATAC-seq profiling using NeuN sorted-nuclei from 40 frozen brain tissues to determine LOAD-specific changes in chromatin accessibility landscape in a cell-type specific manner. RESULTS We identified 211 LOAD-specific differential chromatin accessibility sites in neuronal-nuclei, four of which overlapped with LOAD-GWAS regions (±100 kb of SNP). While the non-neuronal nuclei did not show LOAD-specific differences, stratification by sex identified 842 LOAD-specific chromatin accessibility sites in females. Seven of these sex-dependent sites in the non-neuronal samples overlapped LOAD-GWAS regions including APOE. LOAD loci were functionally validated using single-nuclei RNA-seq datasets. CONCLUSIONS Using brain sorted-nuclei enabled the identification of sex-dependent cell type-specific LOAD alterations in chromatin structure. These findings enhance the interpretation of LOAD-GWAS discoveries, provide potential pathomechanisms, and suggest novel LOAD-loci.
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Affiliation(s)
- Julio Barrera
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Lingyun Song
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Julia E. Gamache
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Melanie E. Garrett
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC 27701 USA
| | - Alexias Safi
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Young Yun
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Ivana Premasinghe
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Daniel Sprague
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Danielle Chipman
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Jeffrey Li
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Hélène Fradin
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
| | - Karen Soldano
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC 27701 USA
| | - Raluca Gordân
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC 27705 USA
- Department of Computer Science, Duke University, Durham, NC 27705 USA
| | - Allison E. Ashley-Koch
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC 27701 USA
- Department of Medicine, Duke University Medical Center, DUMC, Box 104775, Durham, NC 27708 USA
| | - Gregory E. Crawford
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
- Department of Pediatrics, Division of Medical Genetics, Duke University Medical Center, DUMC, Box 3382, Durham, NC 27708 USA
- Center for Advanced Genomic Technologies, Duke University Medical Center, Durham, NC 27708 USA
| | - Ornit Chiba-Falek
- Department of Neurology, Division of Translational Brain Sciences, Duke University Medical Center, DUMC, Box 2900, Durham, NC 27710 USA
- Center for Genomic and Computational Biology, Duke University Medical Center, Durham, NC 27708 USA
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15
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Saric A, Freeman SA, Williamson CD, Jarnik M, Guardia CM, Fernandopulle MS, Gershlick DC, Bonifacino JS. SNX19 restricts endolysosome motility through contacts with the endoplasmic reticulum. Nat Commun 2021; 12:4552. [PMID: 34315878 PMCID: PMC8316374 DOI: 10.1038/s41467-021-24709-1] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 06/24/2021] [Indexed: 12/12/2022] Open
Abstract
The ability of endolysosomal organelles to move within the cytoplasm is essential for the performance of their functions. Long-range movement involves coupling of the endolysosomes to motor proteins that carry them along microtubule tracks. This movement is influenced by interactions with other organelles, but the mechanisms involved are incompletely understood. Herein we show that the sorting nexin SNX19 tethers endolysosomes to the endoplasmic reticulum (ER), decreasing their motility and contributing to their concentration in the perinuclear area of the cell. Tethering depends on two N-terminal transmembrane domains that anchor SNX19 to the ER, and a PX domain that binds to phosphatidylinositol 3-phosphate on the endolysosomal membrane. Two other domains named PXA and PXC negatively regulate the interaction of SNX19 with endolysosomes. These studies thus identify a mechanism for controlling the motility and positioning of endolysosomes that involves tethering to the ER by a sorting nexin.
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Affiliation(s)
- Amra Saric
- Neurosciences and Cellular and Structural Biology Division, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Spencer A Freeman
- Program in Cell Biology, Peter Gilgan Centre for Research and Learning, Hospital for Sick Children, Toronto, ON, Canada
- Department of Biochemistry, University of Toronto, Toronto, ON, Canada
| | - Chad D Williamson
- Neurosciences and Cellular and Structural Biology Division, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Michal Jarnik
- Neurosciences and Cellular and Structural Biology Division, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Carlos M Guardia
- Neurosciences and Cellular and Structural Biology Division, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
| | - Michael S Fernandopulle
- Neurogenetics Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
| | - David C Gershlick
- Neurosciences and Cellular and Structural Biology Division, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA
- Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK
| | - Juan S Bonifacino
- Neurosciences and Cellular and Structural Biology Division, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA.
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16
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Limited Association between Schizophrenia Genetic Risk Factors and Transcriptomic Features. Genes (Basel) 2021; 12:genes12071062. [PMID: 34356078 PMCID: PMC8304922 DOI: 10.3390/genes12071062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/29/2021] [Accepted: 07/08/2021] [Indexed: 11/16/2022] Open
Abstract
Schizophrenia is a polygenic disorder with many genomic regions contributing to schizophrenia risk. The majority of genetic variants associated with schizophrenia lie in the non-coding genome and are thought to contribute to transcriptional regulation. Extensive transcriptomic dysregulation has been detected from postmortem brain samples of schizophrenia-affected individuals. However, the relationship between schizophrenia genetic risk factors and transcriptomic features has yet to be explored. Herein, we examined whether varying gene expression features, including differentially expressed genes (DEGs), co-expression networks, and central hubness of genes, contribute to the heritability of schizophrenia. We leveraged quantitative trait loci and chromatin interaction profiles to identify schizophrenia risk variants assigned to the genes that represent different transcriptomic features. We then performed stratified linkage disequilibrium score regression analysis on these variants to estimate schizophrenia heritability enrichment for different gene expression features. Notably, DEGs and co-expression networks showed nominal heritability enrichment. This nominal association can be partly explained by cellular heterogeneity, as DEGs were associated with the genetic risk of schizophrenia in a cell type-specific manner. Moreover, DEGs were enriched for target genes of schizophrenia-associated transcription factors, suggesting that the transcriptomic signatures of schizophrenia are the result of transcriptional regulatory cascades elicited by genetic risk factors.
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17
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Hu B, Won H, Mah W, Park RB, Kassim B, Spiess K, Kozlenkov A, Crowley CA, Pochareddy S, Li Y, Dracheva S, Sestan N, Akbarian S, Geschwind DH. Neuronal and glial 3D chromatin architecture informs the cellular etiology of brain disorders. Nat Commun 2021; 12:3968. [PMID: 34172755 PMCID: PMC8233376 DOI: 10.1038/s41467-021-24243-0] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 05/26/2021] [Indexed: 02/06/2023] Open
Abstract
Cellular heterogeneity in the human brain obscures the identification of robust cellular regulatory networks, which is necessary to understand the function of non-coding elements and the impact of non-coding genetic variation. Here we integrate genome-wide chromosome conformation data from purified neurons and glia with transcriptomic and enhancer profiles, to characterize the gene regulatory landscape of two major cell classes in the human brain. We then leverage cell-type-specific regulatory landscapes to gain insight into the cellular etiology of several brain disorders. We find that Alzheimer's disease (AD)-associated epigenetic dysregulation is linked to neurons and oligodendrocytes, whereas genetic risk factors for AD highlighted microglia, suggesting that different cell types may contribute to disease risk, via different mechanisms. Moreover, integration of glutamatergic and GABAergic regulatory maps with genetic risk factors for schizophrenia (SCZ) and bipolar disorder (BD) identifies shared (parvalbumin-expressing interneurons) and distinct cellular etiologies (upper layer neurons for BD, and deeper layer projection neurons for SCZ). Collectively, these findings shed new light on cell-type-specific gene regulatory networks in brain disorders.
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Affiliation(s)
- Benxia Hu
- grid.410711.20000 0001 1034 1720UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Department of Genetics, University of North Carolina, Chapel Hill, NC USA
| | - Hyejung Won
- grid.410711.20000 0001 1034 1720UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Department of Genetics, University of North Carolina, Chapel Hill, NC USA
| | - Won Mah
- grid.410711.20000 0001 1034 1720UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Department of Genetics, University of North Carolina, Chapel Hill, NC USA
| | - Royce B. Park
- grid.59734.3c0000 0001 0670 2351Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA ,grid.59734.3c0000 0001 0670 2351Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Bibi Kassim
- grid.59734.3c0000 0001 0670 2351Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA ,grid.59734.3c0000 0001 0670 2351Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Keeley Spiess
- grid.410711.20000 0001 1034 1720UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC USA
| | - Alexey Kozlenkov
- grid.59734.3c0000 0001 0670 2351Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA ,grid.59734.3c0000 0001 0670 2351Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY USA ,grid.274295.f0000 0004 0420 1184James J. Peters VA Medical Center, Bronx, NY USA
| | - Cheynna A. Crowley
- grid.410711.20000 0001 1034 1720Department of Genetics, University of North Carolina, Chapel Hill, NC USA
| | - Sirisha Pochareddy
- grid.47100.320000000419368710Department of Neuroscience and Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT USA
| | | | - Yun Li
- grid.410711.20000 0001 1034 1720Department of Genetics, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Biostatistics, University of North Carolina, Chapel Hill, NC USA ,grid.410711.20000 0001 1034 1720Computer Science, University of North Carolina, Chapel Hill, NC USA
| | - Stella Dracheva
- grid.59734.3c0000 0001 0670 2351Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA ,grid.59734.3c0000 0001 0670 2351Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY USA ,grid.274295.f0000 0004 0420 1184James J. Peters VA Medical Center, Bronx, NY USA
| | - Nenad Sestan
- grid.47100.320000000419368710Department of Psychiatry, Yale School of Medicine, New Haven, CT USA ,grid.47100.320000000419368710Department of Genetics, Yale School of Medicine, New Haven, CT USA ,grid.47100.320000000419368710Department of Comparative Medicine, Program in Integrative Cell Signaling and Neurobiology of Metabolism, Yale School of Medicine, New Haven, CT USA ,grid.47100.320000000419368710Program in Cellular Neuroscience, Neurodegeneration, and Repair and Yale Child Study Center, Yale School of Medicine, New Haven, CT USA
| | - Schahram Akbarian
- grid.59734.3c0000 0001 0670 2351Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY USA ,grid.59734.3c0000 0001 0670 2351Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Daniel H. Geschwind
- grid.19006.3e0000 0000 9632 6718Neurogenetics Program, Department of Neurology, David Geffen School of Medicine University of California, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, CA 90095 USA ,grid.19006.3e0000 0000 9632 6718Department of Human Genetics, David Geffen School of Medicine University of California, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Psychiatry and Biobehavioral Sciences, Semel Institute, David Geffen School of Medicine University of California, Los Angeles, CA USA
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18
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Stępniak K, Machnicka MA, Mieczkowski J, Macioszek A, Wojtaś B, Gielniewski B, Poleszak K, Perycz M, Król SK, Guzik R, Dąbrowski MJ, Dramiński M, Jardanowska M, Grabowicz I, Dziedzic A, Kranas H, Sienkiewicz K, Diamanti K, Kotulska K, Grajkowska W, Roszkowski M, Czernicki T, Marchel A, Komorowski J, Kaminska B, Wilczyński B. Mapping chromatin accessibility and active regulatory elements reveals pathological mechanisms in human gliomas. Nat Commun 2021; 12:3621. [PMID: 34131149 PMCID: PMC8206121 DOI: 10.1038/s41467-021-23922-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2020] [Accepted: 05/19/2021] [Indexed: 12/15/2022] Open
Abstract
Chromatin structure and accessibility, and combinatorial binding of transcription factors to regulatory elements in genomic DNA control transcription. Genetic variations in genes encoding histones, epigenetics-related enzymes or modifiers affect chromatin structure/dynamics and result in alterations in gene expression contributing to cancer development or progression. Gliomas are brain tumors frequently associated with epigenetics-related gene deregulation. We perform whole-genome mapping of chromatin accessibility, histone modifications, DNA methylation patterns and transcriptome analysis simultaneously in multiple tumor samples to unravel epigenetic dysfunctions driving gliomagenesis. Based on the results of the integrative analysis of the acquired profiles, we create an atlas of active enhancers and promoters in benign and malignant gliomas. We explore these elements and intersect with Hi-C data to uncover molecular mechanisms instructing gene expression in gliomas.
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Affiliation(s)
- Karolina Stępniak
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Magdalena A Machnicka
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland
| | - Jakub Mieczkowski
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
- Medical University of Gdansk, International Research Agenda 3P Medicine Laboratory, Gdansk, Poland
| | - Anna Macioszek
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland
| | - Bartosz Wojtaś
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Bartłomiej Gielniewski
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Katarzyna Poleszak
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Malgorzata Perycz
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Sylwia K Król
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Rafał Guzik
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland
| | - Michał J Dąbrowski
- Institute of Computer Science of the Polish Academy of Sciences, Warsaw, Poland
| | - Michał Dramiński
- Institute of Computer Science of the Polish Academy of Sciences, Warsaw, Poland
| | - Marta Jardanowska
- Institute of Computer Science of the Polish Academy of Sciences, Warsaw, Poland
| | - Ilona Grabowicz
- Institute of Computer Science of the Polish Academy of Sciences, Warsaw, Poland
| | - Agata Dziedzic
- Institute of Computer Science of the Polish Academy of Sciences, Warsaw, Poland
| | - Hanna Kranas
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland
- Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Karolina Sienkiewicz
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland
| | - Klev Diamanti
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Katarzyna Kotulska
- Departments of Neurology, Neurosurgery, Neuropathology, The Children's Memorial Health Institute, Warsaw, Poland
| | - Wiesława Grajkowska
- Departments of Neurology, Neurosurgery, Neuropathology, The Children's Memorial Health Institute, Warsaw, Poland
| | - Marcin Roszkowski
- Departments of Neurology, Neurosurgery, Neuropathology, The Children's Memorial Health Institute, Warsaw, Poland
| | - Tomasz Czernicki
- Department of Neurosurgery, Medical University of Warsaw, Warsaw, Poland
| | - Andrzej Marchel
- Department of Neurosurgery, Medical University of Warsaw, Warsaw, Poland
| | - Jan Komorowski
- Department of Cell and Molecular Biology, Uppsala University, Uppsala, Sweden
| | - Bozena Kaminska
- Nencki Institute of Experimental Biology of the Polish Academy of Sciences, Warsaw, Poland.
| | - Bartek Wilczyński
- Faculty of Mathematics, Informatics and Mechanics, University of Warsaw, Warsaw, Poland.
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19
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Su C, Argenziano M, Lu S, Pippin JA, Pahl MC, Leonard ME, Cousminer DL, Johnson ME, Lasconi C, Wells AD, Chesi A, Grant SFA. 3D promoter architecture re-organization during iPSC-derived neuronal cell differentiation implicates target genes for neurodevelopmental disorders. Prog Neurobiol 2021; 201:102000. [PMID: 33545232 PMCID: PMC8096691 DOI: 10.1016/j.pneurobio.2021.102000] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 12/07/2020] [Accepted: 01/23/2021] [Indexed: 12/27/2022]
Abstract
Neurodevelopmental disorders are thought to arise from interrupted development of the brain at an early age. Genome-wide association studies (GWAS) have identified hundreds of loci associated with susceptibility to neurodevelopmental disorders; however, which noncoding variants regulate which genes at these loci is often unclear. To implicate neuronal GWAS effector genes, we performed an integrated analysis of transcriptomics, epigenomics and chromatin conformation changes during the development from Induced pluripotent stem cell-derived neuronal progenitor cells (NPCs) into neurons using a combination of high-resolution promoter-focused Capture-C, ATAC-seq and RNA-seq. We observed that gene expression changes during the NPC-to-neuron transition were highly dependent on both promoter accessibility changes and long-range interactions which connect distal cis-regulatory elements (enhancer or silencers) to developmental-stage-specific genes. These genome-scale promoter-cis-regulatory-element atlases implicated 454 neurodevelopmental disorder-associated, putative causal variants mapping to 600 distal targets. These putative effector genes were significantly enriched for pathways involved in the regulation of neuronal development and chromatin organization, with 27 % expressed in a stage-specific manner. The intersection of open chromatin and chromatin conformation revealed development-stage-specific gene regulatory architectures during neuronal differentiation, providing a rich resource to aid characterization of the genetic and developmental basis of neurodevelopmental disorders.
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Affiliation(s)
- Chun Su
- Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States
| | - Mariana Argenziano
- Heart Institute, University of South Florida, 560 Channelside Dr, Tampa FL 33602, United States
| | - Sumei Lu
- Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States
| | - James A Pippin
- Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States
| | - Matthew C Pahl
- Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States
| | - Michelle E Leonard
- Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States
| | - Diana L Cousminer
- Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States
| | - Matthew E Johnson
- Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States
| | - Chiara Lasconi
- Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States
| | - Andrew D Wells
- Department of Pathology, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States; Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, 3615 Civic Center Boulevard, Philadelphia, PA, United States
| | - Alessandra Chesi
- Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States
| | - Struan F A Grant
- Division of Human Genetics, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States; Division of Diabetes and Endocrinology, The Children's Hospital of Philadelphia, 3615 Civic Center Boulevard, Philadelphia, PA, United States; Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, 3615 Civic Center Boulevard, Philadelphia, PA, United States; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, 3615 Civic Center Boulevard, Philadelphia, PA, United States.
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20
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Egervari G. Chromatin accessibility in neuropsychiatric disorders. Neurobiol Learn Mem 2021; 181:107438. [PMID: 33845131 DOI: 10.1016/j.nlm.2021.107438] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 04/02/2021] [Accepted: 04/07/2021] [Indexed: 10/21/2022]
Abstract
Epigenetic mechanisms have recently emerged as critical regulators of brain function in health and disease. By controlling the accessibility and the expression of specific genes, these pathways can mediate transient and long-lasting changes in neuronal function in both physiological and pathological contexts. Due to the extreme complexity of the epigenetic regulatory landscape, emerging methods that directly assay chromatin accessibility are of particular interest. Here, I review recent insights gained on open and closed chromatin states in the brain, with emphasis on neuropsychiatric disorders. These advances generated an invaluable wealth of information that can help us better understand gene regulation in the brain and its impairments that contribute to the development of disease.
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Affiliation(s)
- Gabor Egervari
- Epigenetics Institute, Department of Cell and Developmental Biology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.
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21
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Amatya B, Lee H, Asico LD, Konkalmatt P, Armando I, Felder RA, Jose PA. SNX-PXA-RGS-PXC Subfamily of SNXs in the Regulation of Receptor-Mediated Signaling and Membrane Trafficking. Int J Mol Sci 2021; 22:ijms22052319. [PMID: 33652569 PMCID: PMC7956473 DOI: 10.3390/ijms22052319] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 02/13/2021] [Accepted: 02/22/2021] [Indexed: 12/26/2022] Open
Abstract
The SNX-PXA-RGS-PXC subfamily of sorting nexins (SNXs) belongs to the superfamily of SNX proteins. SNXs are characterized by the presence of a common phox-homology (PX) domain, along with other functional domains that play versatile roles in cellular signaling and membrane trafficking. In addition to the PX domain, the SNX-PXA-RGS-PXC subfamily, except for SNX19, contains a unique RGS (regulators of G protein signaling) domain that serves as GTPase activating proteins (GAPs), which accelerates GTP hydrolysis on the G protein α subunit, resulting in termination of G protein-coupled receptor (GPCR) signaling. Moreover, the PX domain selectively interacts with phosphatidylinositol-3-phosphate and other phosphoinositides found in endosomal membranes, while also associating with various intracellular proteins. Although SNX19 lacks an RGS domain, all members of the SNX-PXA-RGS-PXC subfamily serve as dual regulators of receptor cargo signaling and endosomal trafficking. This review discusses the known and proposed functions of the SNX-PXA-RGS-PXC subfamily and how it participates in receptor signaling (both GPCR and non-GPCR) and endosomal-based membrane trafficking. Furthermore, we discuss the difference of this subfamily of SNXs from other subfamilies, such as SNX-BAR nexins (Bin-Amphiphysin-Rvs) that are associated with retromer or other retrieval complexes for the regulation of receptor signaling and membrane trafficking. Emerging evidence has shown that the dysregulation and malfunction of this subfamily of sorting nexins lead to various pathophysiological processes and disorders, including hypertension.
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Affiliation(s)
- Bibhas Amatya
- The George Washington University, Washington, DC 20052, USA;
| | - Hewang Lee
- Department of Medicine, The George Washington University School of Medicine & Health Sciences, Washington, DC 20052, USA; (H.L.); (L.D.A.); (P.K.); (I.A.)
| | - Laureano D. Asico
- Department of Medicine, The George Washington University School of Medicine & Health Sciences, Washington, DC 20052, USA; (H.L.); (L.D.A.); (P.K.); (I.A.)
| | - Prasad Konkalmatt
- Department of Medicine, The George Washington University School of Medicine & Health Sciences, Washington, DC 20052, USA; (H.L.); (L.D.A.); (P.K.); (I.A.)
| | - Ines Armando
- Department of Medicine, The George Washington University School of Medicine & Health Sciences, Washington, DC 20052, USA; (H.L.); (L.D.A.); (P.K.); (I.A.)
| | - Robin A. Felder
- Department of Pathology, University of Virginia Health Sciences Center, Charlottesville, VA 22908, USA;
| | - Pedro A. Jose
- Department of Medicine, The George Washington University School of Medicine & Health Sciences, Washington, DC 20052, USA; (H.L.); (L.D.A.); (P.K.); (I.A.)
- Department of Pathology, University of Virginia Health Sciences Center, Charlottesville, VA 22908, USA;
- Department of Pharmacology/Physiology, The George Washington University School of Medicine & Health Sciences, Washington, DC 20052, USA
- Correspondence:
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22
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Powell SK, O'Shea C, Brennand KJ, Akbarian S. Parsing the Functional Impact of Noncoding Genetic Variants in the Brain Epigenome. Biol Psychiatry 2021; 89:65-75. [PMID: 33131715 PMCID: PMC7718420 DOI: 10.1016/j.biopsych.2020.06.033] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 05/29/2020] [Accepted: 06/01/2020] [Indexed: 12/31/2022]
Abstract
The heritability of common psychiatric disorders has motivated global efforts to identify risk-associated genetic variants and elucidate molecular pathways connecting DNA sequence to disease-associated brain dysfunction. The overrepresentation of risk variants among gene regulatory loci instead of protein-coding loci, however, poses a unique challenge in discerning which among the many thousands of variants identified contribute functionally to disease etiology. Defined broadly, psychiatric epigenomics seeks to understand the effects of disease-associated genetic variation on functional readouts of chromatin in an effort to prioritize variants in terms of their impact on gene expression in the brain. Here, we provide an overview of epigenomic mapping in the human brain and highlight findings of particular relevance to psychiatric genetics. Computational methods, including convolutional neuronal networks, and other machine learning approaches hold great promise for elucidating the functional impact of both common and rare genetic variants, thereby refining the epigenomic architecture of psychiatric disorders and enabling integrative analyses of regulatory noncoding variants in the context of large population-level genome and phenome databases.
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Affiliation(s)
- Samuel K Powell
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Callan O'Shea
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Kristen J Brennand
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, New York.
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23
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Errichiello E, Giorda R, Gambale A, Iolascon A, Zuffardi O, Giglio S. RB1CC1 duplication and aberrant overexpression in a patient with schizophrenia: further phenotype delineation and proposal of a pathogenetic mechanism. Mol Genet Genomic Med 2020; 9:e1561. [PMID: 33340270 PMCID: PMC7963413 DOI: 10.1002/mgg3.1561] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Revised: 11/20/2020] [Accepted: 11/05/2020] [Indexed: 12/26/2022] Open
Abstract
Background Copy number variants in coding and noncoding genomic regions have been implicated as risk factor for schizophrenia (SCZ). Rare duplications of the RB1CC1 gene were found enriched in SCZ patients. Considering that the effect of such duplications on RB1CC1 expression has never been evaluated and partial gene duplications of RB1CC1 have also been reported in SCZ patients, it is unclear whether the pathogenesis is mediated by haploinsufficiency rather than genuine overexpression of the gene. Methods and Results We studied a patient with schizophrenia, suicidality, and obesity, who carried a de novo RB1CC1 complete duplication, as assessed by high‐resolution array‐CGH. Molecular breakpoint cloning allowed to identify nonhomologous end joining (NHEJ) as driving mechanism in this rearrangement. On the contrary, trio‐based whole‐exome sequencing excluded other potential causative variants related to the phenotype. Functional assays showed significant overexpression of RB1CC1 in the peripheral blood lymphocytes of the proband compared to control subjects, suggesting overdosage as leading mechanism in SCZ pathophysiology. Conclusion We hypothesized a pathogenetic model that might explain the correlation between RB1CC1 overexpression and schizophrenia by altering different cell signaling pathways, including autophagy, a promising therapeutic target for schizophrenic patients.
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Affiliation(s)
- Edoardo Errichiello
- Unit of Medical Genetics, Department of Molecular Medicine, University of Pavia, Pavia, Italy
| | - Roberto Giorda
- Laboratory of Molecular Biology, Scientific Institute IRCCS Eugenio Medea, Bosisio Parini, Italy
| | - Antonella Gambale
- Department of Molecular Medicine and Medical Biotechnologies, University "Federico II" of Naples, Naples, Italy.,CEINGE, Advanced Biotechnologies, Naples, Italy
| | - Achille Iolascon
- Department of Molecular Medicine and Medical Biotechnologies, University "Federico II" of Naples, Naples, Italy.,CEINGE, Advanced Biotechnologies, Naples, Italy
| | - Orsetta Zuffardi
- Unit of Medical Genetics, Department of Molecular Medicine, University of Pavia, Pavia, Italy
| | - Sabrina Giglio
- Unit of Medical Genetics, Department of Medical Sciences and Public Health, University of Cagliari, Cagliari, Italy
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24
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Lawler AJ, Brown AR, Bouchard RS, Toong N, Kim Y, Velraj N, Fox G, Kleyman M, Kang B, Gittis AH, Pfenning AR. Cell Type-Specific Oxidative Stress Genomic Signatures in the Globus Pallidus of Dopamine-Depleted Mice. J Neurosci 2020; 40:9772-9783. [PMID: 33188066 PMCID: PMC7726543 DOI: 10.1523/jneurosci.1634-20.2020] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2020] [Revised: 08/23/2020] [Accepted: 08/27/2020] [Indexed: 12/23/2022] Open
Abstract
Neuron subtype dysfunction is a key contributor to neurologic disease circuits, but identifying associated gene regulatory pathways is complicated by the molecular complexity of the brain. For example, parvalbumin-expressing (PV+) neurons in the external globus pallidus (GPe) are critically involved in the motor deficits of dopamine-depleted mouse models of Parkinson's disease, where cell type-specific optogenetic stimulation of PV+ neurons over other neuron populations rescues locomotion. Despite the distinct roles these cell types play in the neural circuit, the molecular correlates remain unknown because of the difficulty of isolating rare neuron subtypes. To address this issue, we developed a new viral affinity purification strategy, Cre-Specific Nuclear Anchored Independent Labeling, to isolate Cre recombinase-expressing (Cre+) nuclei from the adult mouse brain. Applying this technology, we performed targeted assessments of the cell type-specific transcriptomic and epigenetic effects of dopamine depletion on PV+ and PV- cells within three brain regions of male and female mice: GPe, striatum, and cortex. We found GPe PV+ neuron-specific gene expression changes that suggested increased hypoxia-inducible factor 2α signaling. Consistent with transcriptomic data, regions of open chromatin affected by dopamine depletion within GPe PV+ neurons were enriched for hypoxia-inducible factor family binding motifs. The gene expression and epigenomic experiments performed on PV+ neurons isolated by Cre-Specific Nuclear Anchored Independent Labeling identified a transcriptional regulatory network mediated by the neuroprotective factor Hif2a as underlying neural circuit differences in response to dopamine depletion.SIGNIFICANCE STATEMENT Cre-Specific Nuclear Anchored Independent Labeling is an enhanced, virus-based approach to isolate nuclei of a specific cell type for transcriptome and epigenome interrogation that decreases dependency on transgenic animals. Applying this technology to GPe parvalbumin-expressing neurons in a mouse model of Parkinson's disease, we discovered evidence for an upregulation of the oxygen homeostasis maintaining pathway involving Hypoxia-inducible factor 2α. These results provide new insight into how neuron subtypes outside the substantia nigra pars compacta may be compensating at a molecular level for differences in the motor production neural circuit during the progression of Parkinson's disease. Furthermore, they emphasize the utility of cell type-specific technologies, such as Cre-Specific Nuclear Anchored Independent Labeling, for isolated assessment of specific neuron subtypes in complex systems.
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Affiliation(s)
- Alyssa J Lawler
- Computational Biology
- Biological Sciences
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Ashley R Brown
- Computational Biology
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Rachel S Bouchard
- Biological Sciences
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Noelle Toong
- Computational Biology
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Yeonju Kim
- Computational Biology
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Nitinram Velraj
- Computational Biology
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Grant Fox
- Computational Biology
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Michael Kleyman
- Computational Biology
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Byungsoo Kang
- Computational Biology
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Aryn H Gittis
- Biological Sciences
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
| | - Andreas R Pfenning
- Computational Biology
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213
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25
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Corces MR, Shcherbina A, Kundu S, Gloudemans MJ, Frésard L, Granja JM, Louie BH, Eulalio T, Shams S, Bagdatli ST, Mumbach MR, Liu B, Montine KS, Greenleaf WJ, Kundaje A, Montgomery SB, Chang HY, Montine TJ. Single-cell epigenomic analyses implicate candidate causal variants at inherited risk loci for Alzheimer's and Parkinson's diseases. Nat Genet 2020; 52:1158-1168. [PMID: 33106633 PMCID: PMC7606627 DOI: 10.1038/s41588-020-00721-x] [Citation(s) in RCA: 184] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2019] [Accepted: 09/18/2020] [Indexed: 02/06/2023]
Abstract
Genome-wide association studies of neurological diseases have identified thousands of variants associated with disease phenotypes. However, most of these variants do not alter coding sequences, making it difficult to assign their function. Here, we present a multi-omic epigenetic atlas of the adult human brain through profiling of single-cell chromatin accessibility landscapes and three-dimensional chromatin interactions of diverse adult brain regions across a cohort of cognitively healthy individuals. We developed a machine-learning classifier to integrate this multi-omic framework and predict dozens of functional SNPs for Alzheimer's and Parkinson's diseases, nominating target genes and cell types for previously orphaned loci from genome-wide association studies. Moreover, we dissected the complex inverted haplotype of the MAPT (encoding tau) Parkinson's disease risk locus, identifying putative ectopic regulatory interactions in neurons that may mediate this disease association. This work expands understanding of inherited variation and provides a roadmap for the epigenomic dissection of causal regulatory variation in disease.
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Affiliation(s)
- M Ryan Corces
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Anna Shcherbina
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Soumya Kundu
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Michael J Gloudemans
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Laure Frésard
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Jeffrey M Granja
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Program in Biophysics, Stanford University, Stanford, CA, USA
| | - Bryan H Louie
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Tiffany Eulalio
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA
| | - Shadi Shams
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - S Tansu Bagdatli
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Maxwell R Mumbach
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Boxiang Liu
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
- Baidu Research, Sunnyvale, CA, USA
| | - Kathleen S Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - William J Greenleaf
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Stephen B Montgomery
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
| | - Thomas J Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA.
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26
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Chromatin accessibility mapping of the striatum identifies tyrosine kinase FYN as a therapeutic target for heroin use disorder. Nat Commun 2020; 11:4634. [PMID: 32929078 PMCID: PMC7490718 DOI: 10.1038/s41467-020-18114-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Accepted: 08/04/2020] [Indexed: 12/30/2022] Open
Abstract
The current opioid epidemic necessitates a better understanding of human addiction neurobiology to develop efficacious treatment approaches. Here, we perform genome-wide assessment of chromatin accessibility of the human striatum in heroin users and matched controls. Our study reveals distinct neuronal and non-neuronal epigenetic signatures, and identifies a locus in the proximity of the gene encoding tyrosine kinase FYN as the most affected region in neurons. FYN expression, kinase activity and the phosphorylation of its target Tau are increased by heroin use in the post-mortem human striatum, as well as in rats trained to self-administer heroin and primary striatal neurons treated with chronic morphine in vitro. Pharmacological or genetic manipulation of FYN activity significantly attenuates heroin self-administration and responding for drug-paired cues in rodents. Our findings suggest that striatal FYN is an important driver of heroin-related neurodegenerative-like pathology and drug-taking behavior, making FYN a promising therapeutic target for heroin use disorder. Epigenetic mechanisms have emerged as contributors to the molecular impairments caused by exposure to environmental factors such as abused substances. Here the authors perform epigenetic profiling of the striatum and identify the tyrosine kinase FYN is an important driver of neurodegenerative-like pathology and drug-taking behaviour.
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27
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Powell SK, O'Shea CP, Shannon SR, Akbarian S, Brennand KJ. Investigation of Schizophrenia with Human Induced Pluripotent Stem Cells. ADVANCES IN NEUROBIOLOGY 2020; 25:155-206. [PMID: 32578147 DOI: 10.1007/978-3-030-45493-7_6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Schizophrenia is a chronic and severe neuropsychiatric condition manifested by cognitive, emotional, affective, perceptual, and behavioral abnormalities. Despite decades of research, the biological substrates driving the signs and symptoms of the disorder remain elusive, thus hampering progress in the development of treatments aimed at disease etiologies. The recent emergence of human induced pluripotent stem cell (hiPSC)-based models has provided the field with a highly innovative approach to generate, study, and manipulate living neural tissue derived from patients, making possible the exploration of fundamental roles of genes and early-life stressors in disease-relevant cell types. Here, we begin with a brief overview of the clinical, epidemiological, and genetic aspects of the condition, with a focus on schizophrenia as a neurodevelopmental disorder. We then highlight relevant technical advancements in hiPSC models and assess novel findings attained using hiPSC-based approaches and their implications for disease biology and treatment innovation. We close with a critical appraisal of the developments necessary for both further expanding knowledge of schizophrenia and the translation of new insights into therapeutic innovations.
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Affiliation(s)
- Samuel K Powell
- Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Callan P O'Shea
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sara Rose Shannon
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Schahram Akbarian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kristen J Brennand
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Genetics and Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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28
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Xiang Y, Cakir B, Park IH. Deconstructing and reconstructing the human brain with regionally specified brain organoids. Semin Cell Dev Biol 2020; 111:40-51. [PMID: 32553582 DOI: 10.1016/j.semcdb.2020.05.023] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 04/21/2020] [Accepted: 05/27/2020] [Indexed: 12/31/2022]
Abstract
Brain organoids, three-dimensional neural cultures recapitulating the spatiotemporal organization and function of the brain in a dish, offer unique opportunities for investigating the human brain development and diseases. To model distinct parts of the brain, various region-specific human brain organoids have been developed. In this article, we review current approaches to produce human region-specific brain organoids, developed through the endeavor of many researchers. We highlight the applications of human region-specific brain organoids, especially in reconstructing regional interactions in the brain through organoid fusion. We also outline the existing challenges to drive forward further the brain organoid technology and its applications for future studies.
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Affiliation(s)
- Yangfei Xiang
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA.
| | - Bilal Cakir
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - In-Hyun Park
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA.
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29
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Rajarajan P, Akbarian S. Use of the epigenetic toolbox
to contextualize common variants associated with schizophrenia risk
. DIALOGUES IN CLINICAL NEUROSCIENCE 2020; 21:407-416. [PMID: 31949408 PMCID: PMC6952750 DOI: 10.31887/dcns.2019.21.4/sakbarian] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Schizophrenia is a debilitating psychiatric disorder with a complex genetic architecture and limited understanding of its neuropathology, reflected by the lack of diagnostic measures and effective pharmacological treatments. Geneticists have recently identified more than 145 risk loci comprising hundreds of common variants of small effect sizes, most of which lie in noncoding genomic regions. This review will discuss how the epigenetic toolbox can be applied to contextualize genetic findings in schizophrenia. Progress in next-generation sequencing, along with increasing methodological complexity, has led to the compilation of genome-wide maps of DNA methylation, histone modifications, RNA expression, and more. Integration of chromatin conformation datasets is one of the latest efforts in deciphering schizophrenia risk, allowing the identification of genes in contact with regulatory variants across 100s of kilobases. Large-scale multiomics studies will facilitate the prioritization of putative causal risk variants and gene networks that contribute to schizophrenia etiology, informing clinical diagnostics and treatment downstream.
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Affiliation(s)
- Prashanth Rajarajan
- Graduate School of Biomedical Sciences; Department of Psychiatry; Friedman Brain Institute; Icahn School of Medicine at Mount Sinai, New York, NY, US
| | - Schahram Akbarian
- Department of Psychiatry; Friedman Brain Institute; Icahn School of Medicine at Mount Sinai, New York, NY, US
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30
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Liu W, Li W, Cai X, Yang Z, Li H, Su X, Song M, Zhou DS, Li X, Zhang C, Shao M, Zhang L, Yang Y, Zhang Y, Zhao J, Chang H, Yao YG, Fang Y, Lv L, Li M, Xiao X. Identification of a functional human-unique 351-bp Alu insertion polymorphism associated with major depressive disorder in the 1p31.1 GWAS risk loci. Neuropsychopharmacology 2020; 45:1196-1206. [PMID: 32193514 PMCID: PMC7235090 DOI: 10.1038/s41386-020-0659-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Revised: 02/16/2020] [Accepted: 03/11/2020] [Indexed: 12/28/2022]
Abstract
Genome-wide association studies (GWAS) have reported substantial single-nucleotide polymorphisms (SNPs) associated with major depressive disorder (MDD), but the underlying functional variations in the GWAS risk loci are unclear. Here we show that the European MDD genome-wide risk-associated allele of rs12129573 at 1p31.1 is associated with MDD in Han Chinese, and this SNP is in strong linkage disequilibrium (LD) with a human-unique Alu insertion polymorphism (rs70959274) in the 5' flanking region of a long non-coding RNA (lncRNA) LINC01360 (Long Intergenic Non-Protein Coding RNA 1360), which is preferably expressed in human testis in the currently available expression datasets. The risk allele at rs12129573 is almost completely linked with the absence of this Alu insertion. The Alu insertion polymorphism (rs70959274) is significantly associated with a lower RNA level of LINC01360 and acts as a transcription silencer likely through modulating the methylation of its internal CpG sites. Luciferase assays confirm that the presence of Alu insertion at rs70959274 suppresses transcriptional activities in human cells, and deletion of the Alu insertion through CRISPR/Cas9-directed genome editing increases RNA expression of LINC01360. Deletion of the Alu insertion in human cells also leads to dysregulation of gene expression, biological processes and pathways relevant to MDD, such as the alterations of mRNA levels of DRD2 and FLOT1, transcription of genes involved in synaptic transmission, neurogenesis, learning or memory, and the PI3K-Akt signaling pathway. In summary, we identify a human-unique DNA repetitive polymorphism in robust LD with the MDD risk-associated SNP at the prominent 1p31.1 GWAS loci, and offer insights into the molecular basis of the illness.
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Affiliation(s)
- Weipeng Liu
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China ,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan China
| | - Wenqiang Li
- 0000 0004 1808 322Xgrid.412990.7Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan China
| | - Xin Cai
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China ,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan China
| | - Zhihui Yang
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China ,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan China
| | - Huijuan Li
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China ,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan China
| | - Xi Su
- 0000 0004 1808 322Xgrid.412990.7Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan China
| | - Meng Song
- 0000 0004 1808 322Xgrid.412990.7Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan China
| | - Dong-Sheng Zhou
- 0000 0004 1782 599Xgrid.452715.0Department of Psychiatry, Ningbo Kangning Hospital, Ningbo, Zhejiang, China
| | - Xingxing Li
- 0000 0004 1782 599Xgrid.452715.0Department of Psychiatry, Ningbo Kangning Hospital, Ningbo, Zhejiang, China
| | - Chen Zhang
- 0000 0004 0368 8293grid.16821.3cShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Minglong Shao
- 0000 0004 1808 322Xgrid.412990.7Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan China
| | - Luwen Zhang
- 0000 0004 1808 322Xgrid.412990.7Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan China
| | - Yongfeng Yang
- 0000 0004 1808 322Xgrid.412990.7Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan China
| | - Yan Zhang
- 0000 0004 1808 322Xgrid.412990.7Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan China
| | - Jingyuan Zhao
- 0000 0004 1808 322Xgrid.412990.7Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan China ,0000 0004 1808 322Xgrid.412990.7Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan China
| | - Hong Chang
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China
| | - Yong-Gang Yao
- 0000000119573309grid.9227.eKey Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China ,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan China ,0000000119573309grid.9227.eCAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China ,0000000119573309grid.9227.eKIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan China
| | - Yiru Fang
- 0000 0004 0368 8293grid.16821.3cShanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China ,0000000119573309grid.9227.eCAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
| | - Luxian Lv
- Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China. .,Henan Key Lab of Biological Psychiatry, International Joint Research Laboratory for Psychiatry and Neuroscience of Henan, Xinxiang Medical University, Xinxiang, Henan, China. .,Henan Province People's Hospital, Zhengzhou, Henan, China.
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China. .,CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China. .,KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
| | - Xiao Xiao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China. .,KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
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Ma L, Semick SA, Chen Q, Li C, Tao R, Price AJ, Shin JH, Jia Y, Brandon NJ, Cross AJ, Hyde TM, Kleinman JE, Jaffe AE, Weinberger DR, Straub RE. Schizophrenia risk variants influence multiple classes of transcripts of sorting nexin 19 (SNX19). Mol Psychiatry 2020; 25:831-843. [PMID: 30635639 DOI: 10.1038/s41380-018-0293-0] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2018] [Revised: 09/16/2018] [Accepted: 10/03/2018] [Indexed: 01/15/2023]
Abstract
Genome-wide association studies (GWAS) have identified many genomic loci associated with risk for schizophrenia, but unambiguous identification of the relationship between disease-associated variants and specific genes, and in particular their effect on risk conferring transcripts, has proven difficult. To better understand the specific molecular mechanism(s) at the schizophrenia locus in 11q25, we undertook cis expression quantitative trait loci (cis-eQTL) mapping for this 2 megabase genomic region using postmortem human brain samples. To comprehensively assess the effects of genetic risk upon local expression, we evaluated multiple transcript features: genes, exons, and exon-exon junctions in multiple brain regions-dorsolateral prefrontal cortex (DLPFC), hippocampus, and caudate. Genetic risk variants strongly associated with expression of SNX19 transcript features that tag multiple rare classes of SNX19 transcripts, whereas they only weakly affected expression of an exon-exon junction that tags the majority of abundant transcripts. The most prominent class of SNX19 risk-associated transcripts is predicted to be overexpressed, defined by an exon-exon splice junction between exons 8 and 10 (junc8.10) and that is predicted to encode proteins that lack the characteristic nexin C terminal domain. Risk alleles were also associated with either increased or decreased expression of multiple additional classes of transcripts. With RACE, molecular cloning, and long read sequencing, we found a number of novel SNX19 transcripts that further define the set of potential etiological transcripts. We explored epigenetic regulation of SNX19 expression and found that DNA methylation at CpG sites near the primary transcription start site and within exon 2 partially mediate the effects of risk variants on risk-associated expression. ATAC sequencing revealed that some of the most strongly risk-associated SNPs are located within a region of open chromatin, suggesting a nearby regulatory element is involved. These findings indicate a potentially complex molecular etiology, in which risk alleles for schizophrenia generate epigenetic alterations and dysregulation of multiple classes of SNX19 transcripts.
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Affiliation(s)
- Liang Ma
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA
| | - Stephen A Semick
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA
| | - Qiang Chen
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA
| | - Chao Li
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA
| | - Ran Tao
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA
| | - Amanda J Price
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA.,McKusick-Nathans Institute of Genetic Medicine, Baltimore, MD, 21205, USA
| | - Joo Heon Shin
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA
| | - Yankai Jia
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA
| | | | - Nicholas J Brandon
- AstraZeneca Neuroscience, IMED Biotech Unit, AstraZeneca R&D, Boston, MA, 02451, USA
| | - Alan J Cross
- AstraZeneca Neuroscience, IMED Biotech Unit, AstraZeneca R&D, Boston, MA, 02451, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA.,Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA.,Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Andrew E Jaffe
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA.,Department of Mental Health, Johns Hopkins School of Public Health, Baltimore, MD, 21205, USA.,Department of Biostatistics, Johns Hopkins School of Public Health, Baltimore, MD, 21205, USA
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA.,McKusick-Nathans Institute of Genetic Medicine, Baltimore, MD, 21205, USA.,Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.,Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA.,Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Richard E Straub
- Lieber Institute for Brain Development, Baltimore, MD, 21205, USA.
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Vogel Ciernia A, Laufer BI, Hwang H, Dunaway KW, Mordaunt CE, Coulson RL, Yasui DH, LaSalle JM. Epigenomic Convergence of Neural-Immune Risk Factors in Neurodevelopmental Disorder Cortex. Cereb Cortex 2020; 30:640-655. [PMID: 31240313 PMCID: PMC7306174 DOI: 10.1093/cercor/bhz115] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 05/07/2019] [Accepted: 05/08/2019] [Indexed: 12/11/2022] Open
Abstract
Neurodevelopmental disorders (NDDs) affect 7-14% of all children in developed countries and are one of the leading causes of lifelong disability. Epigenetic modifications are poised at the interface between genes and environment and are predicted to reveal insight into NDD etiology. Whole-genome bisulfite sequencing was used to examine DNA cytosine methylation in 49 human cortex samples from 3 different NDDs (autism spectrum disorder, Rett syndrome, and Dup15q syndrome) and matched controls. Integration of methylation changes across NDDs with relevant genomic and genetic datasets revealed differentially methylated regions (DMRs) unique to each type of NDD but with shared regulatory functions in neurons and microglia. NDD DMRs were enriched within promoter regions and for transcription factor binding sites with identified methylation sensitivity. DMRs from all 3 disorders were enriched for ontologies related to nervous system development and genes with disrupted expression in brain from neurodevelopmental or neuropsychiatric disorders. Genes associated with NDD DMRs showed expression patterns indicating an important role for altered microglial function during brain development. These findings demonstrate an NDD epigenomic signature in human cortex that will aid in defining therapeutic targets and early biomarkers at the interface of genetic and environmental NDD risk factors.
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Affiliation(s)
- A Vogel Ciernia
- Department of Medical Microbiology and Immunology, MIND Institute, Genome Center, University of California, Davis, CA 95616, USA
| | - B I Laufer
- Department of Medical Microbiology and Immunology, MIND Institute, Genome Center, University of California, Davis, CA 95616, USA
| | - H Hwang
- Department of Medical Microbiology and Immunology, MIND Institute, Genome Center, University of California, Davis, CA 95616, USA
| | - K W Dunaway
- Department of Medical Microbiology and Immunology, MIND Institute, Genome Center, University of California, Davis, CA 95616, USA
| | - C E Mordaunt
- Department of Medical Microbiology and Immunology, MIND Institute, Genome Center, University of California, Davis, CA 95616, USA
| | - R L Coulson
- Department of Medical Microbiology and Immunology, MIND Institute, Genome Center, University of California, Davis, CA 95616, USA
| | - D H Yasui
- Department of Medical Microbiology and Immunology, MIND Institute, Genome Center, University of California, Davis, CA 95616, USA
| | - J M LaSalle
- Department of Medical Microbiology and Immunology, MIND Institute, Genome Center, University of California, Davis, CA 95616, USA
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33
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Koshi-Mano K, Mano T, Morishima M, Murayama S, Tamaoka A, Tsuji S, Toda T, Iwata A. Neuron-specific analysis of histone modifications with post-mortem brains. Sci Rep 2020; 10:3767. [PMID: 32111906 PMCID: PMC7048733 DOI: 10.1038/s41598-020-60775-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 02/17/2020] [Indexed: 01/25/2023] Open
Abstract
Histone modifications govern chromatin structures and regulate gene expression to orchestrate cellular functions in the central nervous system, where neuronal cells are postmitotic and developmentally inactive, the functional and age-dependent changes also accumulate in the epigenetic states. Because the brain is composed of several types of cells, such as the neurons, glial cells, and vascular cells, the analysis of histone modifications using bulk brain tissue might obscure alterations specific to neuronal cells. Furthermore, among the various epigenetic traits, analysis of the genome-wide distribution of DNA methylation in the bulk brain is predominantly a reflection of DNA methylation of the non-neuronal cells, which may be a potential caveat of previous studies on neurodegenerative diseases using bulk brains. In this study, we established a method of neuron-specific ChIP-seq assay, which allows for the analysis of genome-wide distribution of histone modifications specifically in the neuronal cells derived from post-mortem brains. We successfully enriched neuronal information with high reproducibility and high signal-to-noise ratio. Our method will further facilitate the understanding of neurodegeneration.
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Affiliation(s)
- Kagari Koshi-Mano
- Department of Neurology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Tatsuo Mano
- Department of Neurology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Maho Morishima
- Department of Neuropathology, Tokyo Metropolitan Geriatric Hospital, 35-2 Sakaecho, Itabashi, Tokyo, 173-0015, Japan
| | - Shigeo Murayama
- Department of Neuropathology, Tokyo Metropolitan Geriatric Hospital, 35-2 Sakaecho, Itabashi, Tokyo, 173-0015, Japan
| | - Akira Tamaoka
- Department of Neurology, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki, 305-8575, Japan
| | - Shoji Tsuji
- Department of Neurology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Tatsushi Toda
- Department of Neurology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Atsushi Iwata
- Department of Neurology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
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Al-Naama N, Mackeh R, Kino T. C 2H 2-Type Zinc Finger Proteins in Brain Development, Neurodevelopmental, and Other Neuropsychiatric Disorders: Systematic Literature-Based Analysis. Front Neurol 2020; 11:32. [PMID: 32117005 PMCID: PMC7034409 DOI: 10.3389/fneur.2020.00032] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 01/10/2020] [Indexed: 12/15/2022] Open
Abstract
Neurodevelopmental disorders (NDDs) are multifaceted pathologic conditions manifested with intellectual disability, autistic features, psychiatric problems, motor dysfunction, and/or genetic/chromosomal abnormalities. They are associated with skewed neurogenesis and brain development, in part through dysfunction of the neural stem cells (NSCs) where abnormal transcriptional regulation on key genes play significant roles. Recent accumulated evidence highlights C2H2-type zinc finger proteins (C2H2-ZNFs), the largest transcription factor family in humans, as important targets for the pathologic processes associated with NDDs. In this review, we identified their significant accumulation (74 C2H2-ZNFs: ~10% of all human member proteins) in brain physiology and pathology. Specifically, we discuss their physiologic contribution to brain development, particularly focusing on their actions in NSCs. We then explain their pathologic implications in various forms of NDDs, such as morphological brain abnormalities, intellectual disabilities, and psychiatric disorders. We found an important tendency that poly-ZNFs and KRAB-ZNFs tend to be involved in the diseases that compromise gross brain structure and human-specific higher-order functions, respectively. This may be consistent with their characteristic appearance in the course of species evolution and corresponding contribution to these brain activities.
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Affiliation(s)
- Njoud Al-Naama
- Laboratory of Molecular and Genomic Endocrinology, Division of Translational Medicine, Sidra Medicine, Doha, Qatar
| | - Rafah Mackeh
- Laboratory of Molecular and Genomic Endocrinology, Division of Translational Medicine, Sidra Medicine, Doha, Qatar
| | - Tomoshige Kino
- Laboratory of Molecular and Genomic Endocrinology, Division of Translational Medicine, Sidra Medicine, Doha, Qatar
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Dahl A, Nguyen K, Cai N, Gandal MJ, Flint J, Zaitlen N. A Robust Method Uncovers Significant Context-Specific Heritability in Diverse Complex Traits. Am J Hum Genet 2020; 106:71-91. [PMID: 31901249 PMCID: PMC7042488 DOI: 10.1016/j.ajhg.2019.11.015] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 11/26/2019] [Indexed: 02/08/2023] Open
Abstract
Gene-environment interactions (GxE) can be fundamental in applications ranging from functional genomics to precision medicine and is a conjectured source of substantial heritability. However, unbiased methods to profile GxE genome-wide are nascent and, as we show, cannot accommodate general environment variables, modest sample sizes, heterogeneous noise, and binary traits. To address this gap, we propose a simple, unifying mixed model for gene-environment interaction (GxEMM). In simulations and theory, we show that GxEMM can dramatically improve estimates and eliminate false positives when the assumptions of existing methods fail. We apply GxEMM to a range of human and model organism datasets and find broad evidence of context-specific genetic effects, including GxSex, GxAdversity, and GxDisease interactions across thousands of clinical and molecular phenotypes. Overall, GxEMM is broadly applicable for testing and quantifying polygenic interactions, which can be useful for explaining heritability and invaluable for determining biologically relevant environments.
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Affiliation(s)
- Andy Dahl
- Department of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Medicine, University of California San Francisco, San Francisco, CA 94158, USA.
| | - Khiem Nguyen
- Department of Medicine, University of California San Francisco, San Francisco, CA 94158, USA
| | - Na Cai
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SA, UK; European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Michael J Gandal
- Department of Psychiatry, Semel Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jonathan Flint
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Noah Zaitlen
- Department of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA; Department of Medicine, University of California San Francisco, San Francisco, CA 94158, USA.
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36
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The genome-wide risk alleles for psychiatric disorders at 3p21.1 show convergent effects on mRNA expression, cognitive function, and mushroom dendritic spine. Mol Psychiatry 2020; 25:48-66. [PMID: 31723243 DOI: 10.1038/s41380-019-0592-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2019] [Revised: 10/30/2019] [Accepted: 10/31/2019] [Indexed: 12/13/2022]
Abstract
Schizophrenia and bipolar disorder (BPD) are believed to share clinical features, etiological factors, and disease pathologies (such as impaired cognitive functions and dendritic spine pathology). Meanwhile, there is growing evidence of shared genetic risk between schizophrenia and BPD, despite that our knowledge of the functional risk variations and biological mechanisms is still limited. Here, we conduct summary data-based Mendelian randomization (SMR) analyses through combining the statistical data from genome-wide association studies (GWAS) of both schizophrenia and BPD and multiple expression quantitative trait loci (eQTL) datasets of the human brain dorsolateral prefrontal cortex (DLPFC) tissues. These integrative investigations identify a lead risk locus at the chromosome 3p21.1 region, which contains numerous single-nucleotide polymorphisms (SNPs) in varied linkage disequilibrium (LD) and encompasses more than 20 genes. Further analyses suggest that many SNPs at 3p21.1 are significantly associated with both schizophrenia and BPD, and even depression, and the psychiatric risk alleles at 3p21.1 are correlated with mRNA expression of multiple genes such as NEK4, GNL3, and PBRM1. We also identify a 335-bp functional Alu polymorphism rs71052682 in significant LD with the psychiatric GWAS risk SNP rs2251219, and confirm the regulatory effects of this Alu polymorphism on transcription activities. We then explore the involvement of the 3p21.1 locus in the common clinical features and etiology of these illnesses. We reveal that psychiatric risk alleles at 3p21.1 in low-to-high LD consistently predict worse cognitive functions in humans, and manipulating the gene expression (NEK4, GNL3, and PBRM1) linked with higher genetic risk could reduce the density of mushroom dendritic spines in rat primary cortical neurons, mirroring the spine pathology in the prefrontal cortex of psychiatric patients. Our results find that, although the risk alleles at 3p21.1 are in low-to-moderate LD spanning a large genomic area, their underlying biological mechanisms in psychiatric disorders likely converge. These results provide essential insights into the neural mechanisms underlying the chromosome 3p21.1 risk locus in the shared pathological and etiological features of both schizophrenia and BPD.
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37
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Hor CN, Yeung J, Jan M, Emmenegger Y, Hubbard J, Xenarios I, Naef F, Franken P. Sleep-wake-driven and circadian contributions to daily rhythms in gene expression and chromatin accessibility in the murine cortex. Proc Natl Acad Sci U S A 2019; 116:25773-25783. [PMID: 31776259 PMCID: PMC6925978 DOI: 10.1073/pnas.1910590116] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The timing and duration of sleep results from the interaction between a homeostatic sleep-wake-driven process and a periodic circadian process, and involves changes in gene regulation and expression. Unraveling the contributions of both processes and their interaction to transcriptional and epigenomic regulatory dynamics requires sampling over time under conditions of unperturbed and perturbed sleep. We profiled mRNA expression and chromatin accessibility in the cerebral cortex of mice over a 3-d period, including a 6-h sleep deprivation (SD) on day 2. We used mathematical modeling to integrate time series of mRNA expression data with sleep-wake history, which established that a large proportion of rhythmic genes are governed by the homeostatic process with varying degrees of interaction with the circadian process, sometimes working in opposition. Remarkably, SD caused long-term effects on gene-expression dynamics, outlasting phenotypic recovery, most strikingly illustrated by a damped oscillation of most core clock genes, including Arntl/Bmal1, suggesting that enforced wakefulness directly impacts the molecular clock machinery. Chromatin accessibility proved highly plastic and dynamically affected by SD. Dynamics in distal regions, rather than promoters, correlated with mRNA expression, implying that changes in expression result from constitutively accessible promoters under the influence of enhancers or repressors. Serum response factor (SRF) was predicted as a transcriptional regulator driving immediate response, suggesting that SRF activity mirrors the build-up and release of sleep pressure. Our results demonstrate that a single, short SD has long-term aftereffects at the genomic regulatory level and highlights the importance of the sleep-wake distribution to diurnal rhythmicity and circadian processes.
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Affiliation(s)
- Charlotte N Hor
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, CH-1015 Lausanne, Switzerland
| | - Jake Yeung
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Maxime Jan
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, CH-1015 Lausanne, Switzerland
- Vital-IT Systems Biology Division, Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Yann Emmenegger
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, CH-1015 Lausanne, Switzerland
| | - Jeffrey Hubbard
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, CH-1015 Lausanne, Switzerland
| | - Ioannis Xenarios
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, CH-1015 Lausanne, Switzerland
| | - Felix Naef
- Institute of Bioengineering, School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Paul Franken
- Center for Integrative Genomics, Faculty of Biology and Medicine, University of Lausanne, CH-1015 Lausanne, Switzerland;
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38
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Duan J, Sanders AR, Gejman PV. From Schizophrenia Genetics to Disease Biology: Harnessing New Concepts and Technologies. JOURNAL OF PSYCHIATRY AND BRAIN SCIENCE 2019; 4:e190014. [PMID: 31555746 PMCID: PMC6760308 DOI: 10.20900/jpbs.20190014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Schizophrenia (SZ) is a severe mental disorder afflicting around 1% of the population. It is highly heritable but with complex genetics. Recent research has unraveled a plethora of risk loci for SZ. Accordingly, our conceptual understanding of SZ genetics has been rapidly evolving, from oligogenic models towards polygenic or even omnigenic models. A pressing challenge to the field, however, is the translation of the many genetic findings of SZ into disease biology insights leading to more effective treatments. Bridging this gap requires the integration of genetic findings and functional genomics using appropriate cellular models. Harnessing new technologies, such as the development of human induced pluripotent stem cells (hiPSC) and the CRISPR/Cas-based genome/epigenome editing approach are expected to change our understanding of SZ disease biology to a fundamentally higher level. Here, we discuss some new developments.
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Affiliation(s)
- Jubao Duan
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neurosciences, The University of Chicago, Chicago, IL 60637, USA
| | - Alan R. Sanders
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neurosciences, The University of Chicago, Chicago, IL 60637, USA
| | - Pablo V. Gejman
- Center for Psychiatric Genetics, NorthShore University HealthSystem, Evanston, IL 60201, USA
- Department of Psychiatry and Behavioral Neurosciences, The University of Chicago, Chicago, IL 60637, USA
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39
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Genetic Variation in Long-Range Enhancers. Curr Top Behav Neurosci 2019; 42:35-50. [PMID: 31396896 DOI: 10.1007/7854_2019_110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/17/2023]
Abstract
Cis-regulatory elements (CREs), including insulators, promoters, and enhancers, play critical roles in the establishment and maintenance of normal cellular function. Within each cell, the 3D structure of chromatin is arranged in specific patterns to expose the CREs required for optimal spatiotemporal regulation of gene expression. CREs can act over large distances along the linear genome, facilitated by looping of the intervening chromatin to allow direct interaction between distal regulatory elements and their target genes. A number of pathologies are associated with dysregulation of CRE function, including developmental disorders, cancers, and neuropsychiatric disease. A majority of known neuropsychiatric disease risk loci are noncoding, and increasing evidence suggests that they contribute to disease through disruption of CREs. As such, rather than directly altering the amino acid content of proteins, these variants are instead thought to affect where, when, and to what extent a given gene is expressed. The distances over which CREs can operate often render their target genes difficult to identify. Furthermore, as many risk loci contain multiple variants in high linkage disequilibrium, identification of the causative single nucleotide polymorphism(s) therein is not straightforward. Thus, deciphering the genetic etiology of complex neuropsychiatric disorders presents a significant challenge.
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40
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Yang K, Sawa A. Open Sesame: Open Chromatin Regions Shed Light onto Non-coding Risk Variants. Cell Stem Cell 2019; 21:285-287. [PMID: 28886358 DOI: 10.1016/j.stem.2017.08.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Human genetics and stem cell biology have advanced neurobiology for neurodevelopmental psychiatric disorders. In this issue of Cell Stem Cell, Forrest et al. (2017) demonstrate that studying the landscape of open chromatin regions in stem cell-derived neurons helps functional interpretation of non-coding genetic variants associated with these diseases.
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Affiliation(s)
- Kun Yang
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Akira Sawa
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
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41
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Tenenbaum JD, Bhuvaneshwar K, Gagliardi JP, Fultz Hollis K, Jia P, Ma L, Nagarajan R, Rakesh G, Subbian V, Visweswaran S, Zhao Z, Rozenblit L. Translational bioinformatics in mental health: open access data sources and computational biomarker discovery. Brief Bioinform 2019; 20:842-856. [PMID: 29186302 PMCID: PMC6585382 DOI: 10.1093/bib/bbx157] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Revised: 10/24/2017] [Indexed: 12/12/2022] Open
Abstract
Mental illness is increasingly recognized as both a significant cost to society and a significant area of opportunity for biological breakthrough. As -omics and imaging technologies enable researchers to probe molecular and physiological underpinnings of multiple diseases, opportunities arise to explore the biological basis for behavioral health and disease. From individual investigators to large international consortia, researchers have generated rich data sets in the area of mental health, including genomic, transcriptomic, metabolomic, proteomic, clinical and imaging resources. General data repositories such as the Gene Expression Omnibus (GEO) and Database of Genotypes and Phenotypes (dbGaP) and mental health (MH)-specific initiatives, such as the Psychiatric Genomics Consortium, MH Research Network and PsychENCODE represent a wealth of information yet to be gleaned. At the same time, novel approaches to integrate and analyze data sets are enabling important discoveries in the area of mental and behavioral health. This review will discuss and catalog into an organizing framework the increasingly diverse set of MH data resources available, using schizophrenia as a focus area, and will describe novel and integrative approaches to molecular biomarker discovery that make use of mental health data.
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Affiliation(s)
- Jessica D Tenenbaum
- Department of Biostatistics and Bioinformatics at the Duke University School of Medicine
| | | | | | - Kate Fultz Hollis
- Department of Biomedical Informatics and Clinical Epidemiology at Oregon Health and Science University
| | - Peilin Jia
- University of Texas Health Science Center at Houston
| | - Liang Ma
- Bioinformatics and Systems Medicine Laboratory (BSML), Center for Precision Health, School of Biomedical Informatics, the University of Texas Health Science Center at Houston
| | | | | | - Vignesh Subbian
- Department of Biomedical Engineering and the Department of Systems and Industrial Engineering at the University of Arizona
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42
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Egervari G, Kozlenkov A, Dracheva S, Hurd YL. Molecular windows into the human brain for psychiatric disorders. Mol Psychiatry 2019; 24:653-673. [PMID: 29955163 PMCID: PMC6310674 DOI: 10.1038/s41380-018-0125-2] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Revised: 05/14/2018] [Accepted: 06/05/2018] [Indexed: 12/20/2022]
Abstract
Delineating the pathophysiology of psychiatric disorders has been extremely challenging but technological advances in recent decades have facilitated a deeper interrogation of molecular processes in the human brain. Initial candidate gene expression studies of the postmortem brain have evolved into genome wide profiling of the transcriptome and the epigenome, a critical regulator of gene expression. Here, we review the potential and challenges of direct molecular characterization of the postmortem human brain, and provide a brief overview of recent transcriptional and epigenetic studies with respect to neuropsychiatric disorders. Such information can now be leveraged and integrated with the growing number of genome-wide association databases to provide a functional context of trait-associated genetic variants linked to psychiatric illnesses and related phenotypes. While it is clear that the field is still developing and challenges remain to be surmounted, these recent advances nevertheless hold tremendous promise for delineating the neurobiological underpinnings of mental diseases and accelerating the development of novel medication strategies.
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Affiliation(s)
- Gabor Egervari
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Addiction Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, School of Medicine at Mount Sinai, New York, NY, USA
- Epigenetics Institute and Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Alexey Kozlenkov
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters VA Medical Center, Bronx, NY, USA
| | - Stella Dracheva
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, School of Medicine at Mount Sinai, New York, NY, USA
- James J. Peters VA Medical Center, Bronx, NY, USA
| | - Yasmin L Hurd
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Addiction Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, School of Medicine at Mount Sinai, New York, NY, USA.
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43
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Fullard JF, Charney AW, Voloudakis G, Uzilov AV, Haroutunian V, Roussos P. Assessment of somatic single-nucleotide variation in brain tissue of cases with schizophrenia. Transl Psychiatry 2019; 9:21. [PMID: 30655504 PMCID: PMC6336839 DOI: 10.1038/s41398-018-0342-0] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2018] [Revised: 09/15/2018] [Accepted: 11/13/2018] [Indexed: 12/20/2022] Open
Abstract
The genetic architecture of schizophrenia (SCZ) includes numerous risk loci across a range of frequencies and sizes, including common and rare single-nucleotide variants and insertions/deletions (indels), as well as rare copy number variants (CNVs). Despite the clear heritability of the disease, monozygotic twins are discordant for SCZ at a significant rate. Somatic variants-genetic changes that arise after fertilization rather than through germline inheritance-are widespread in the human brain and known to contribute to risk for both rare and common neuropsychiatric conditions. The contribution of somatic variants in the brain to risk of SCZ remains to be determined. In this study, we surveyed somatic single-nucleotide variants (sSNVs) in the brains of controls and individuals with SCZ (n = 10 and n = 9, respectively). From each individual, whole-exome sequencing (WES) was performed on DNA from neuronal and non-neuronal nuclei isolated by fluorescence activated nuclear sorting (FANS) from frozen postmortem prefrontal cortex (PFC) samples, as well as DNA extracted from temporal muscle as a reference. We identified an increased burden of sSNVs in cases compared to controls (SCZ rate = 2.78, control rate = 0.70; P = 0.0092, linear mixed effects model), that included a higher rate of non-synonymous and loss-of-function variants (SCZ rate = 1.33, control rate = 0.50; P = 0.047, linear mixed effects model). Our findings suggest sSNVs in the brain may constitute an additional component of the complex genetic architecture of SCZ. This perspective argues for the need to further investigate somatic variation in the brain as an explanation of the discordance in monozygotic twins and a potential guide to the identification of novel therapeutic targets.
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Affiliation(s)
- John F. Fullard
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA ,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, Institute for Genomics and Multiscale Biology, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Alexander W. Charney
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA ,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, Institute for Genomics and Multiscale Biology, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Georgios Voloudakis
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA
| | - Andrew V. Uzilov
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, Institute for Genomics and Multiscale Biology, One Gustave L. Levy Place, New York, NY 10029 USA ,Sema4, 333 Ludlow Street, Stamford, CT 06902 USA
| | - Vahram Haroutunian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029 USA ,0000 0004 0420 1184grid.274295.fMental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY 10468 USA
| | - Panos Roussos
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY, 10029, USA. .,Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, Institute for Genomics and Multiscale Biology, One Gustave L. Levy Place, New York, NY, 10029, USA. .,Mental Illness Research, Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, 10468, USA.
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44
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Rizzardi LF, Hickey PF, Rodriguez DiBlasi V, Tryggvadóttir R, Callahan CM, Idrizi A, Hansen KD, Feinberg AP. Neuronal brain-region-specific DNA methylation and chromatin accessibility are associated with neuropsychiatric trait heritability. Nat Neurosci 2019; 22:307-316. [PMID: 30643296 PMCID: PMC6348048 DOI: 10.1038/s41593-018-0297-8] [Citation(s) in RCA: 89] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2018] [Accepted: 11/13/2018] [Indexed: 12/21/2022]
Abstract
Epigenetic modifications confer stable transcriptional patterns in the brain and both normal and abnormal brain function involve specialized brain regions. We examined DNA methylation by whole genome bisulfite sequencing in neuronal and non-neuronal populations from four brain regions (anterior cingulate gyrus, hippocampus, prefrontal cortex, and nucleus accumbens) as well as chromatin accessibility in the latter two. We find pronounced differences in CpG and non-CpG differentially methylated regions (CG- and CH-DMRs) only in neuronal cells across regions. While neuronal CH-DMRs were highly associated with differential gene expression, CG-DMRs were consistent with chromatin accessibility and enriched for regulatory regions. These CG-DMRs comprise ~12 Mb of the genome that is highly enriched for genomic regions associated with heritability of neuropsychiatric traits including addictive behavior, schizophrenia, and neuroticism, suggesting a mechanistic link between pathology and differential neuron-specific epigenetic regulation in distinct brain regions.
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Affiliation(s)
- Lindsay F Rizzardi
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Peter F Hickey
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Varenka Rodriguez DiBlasi
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD, USA.,Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Rakel Tryggvadóttir
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Colin M Callahan
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Adrian Idrizi
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kasper D Hansen
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA. .,McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Andrew P Feinberg
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA. .,Department of Biomedical Engineering, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA. .,Department of Mental Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
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45
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Gianfrancesco O, Bubb VJ, Quinn JP. Treating the "E" in "G × E": Trauma-Informed Approaches and Psychological Therapy Interventions in Psychosis. Front Psychiatry 2019; 10:9. [PMID: 30761022 PMCID: PMC6363686 DOI: 10.3389/fpsyt.2019.00009] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2018] [Accepted: 01/08/2019] [Indexed: 12/31/2022] Open
Abstract
Despite advances in genetic research, causal variants affecting risk for schizophrenia remain poorly characterized, and the top 108 loci identified through genome-wide association studies (GWAS) explain only 3.4% of variance in risk profiles. Such work is defining the highly complex nature of this condition, with omnigenic models of schizophrenia suggesting that gene regulatory networks are sufficiently interconnected such that altered expression of any "peripheral" gene in a relevant cell type has the capacity to indirectly modulate the expression of "core" schizophrenia-associated genes. This wealth of associated genes with small effect sizes makes identifying new druggable targets difficult, and current pharmacological treatments for schizophrenia can involve serious side effects. However, the fact that the majority of schizophrenia genome-wide associated variants fall within non-coding DNA is suggestive of their potential to modulate gene regulation. This would be consistent with risks that can be mediated in a "gene × environment" (G × E) manner. Stress and trauma can alter the regulation of key brain-related pathways over the lifetime of an individual, including modulation of brain development, and neurochemistry in the adult. Recent studies demonstrate a significant overlap between psychotic symptoms and trauma, ranging from prior trauma contributing to psychosis, as well as trauma in response to the experience of psychosis itself or in response to treatment. Given the known effects of trauma on both CNS gene expression and severity of psychosis symptoms, it may be that pharmacological treatment alone risks leaving individuals with a highly stressful and unresolved environmental component that continues to act in a "G × E" manner, with the likelihood that this would negatively impact recovery and relapse risk. This review aims to cover the recent advances elucidating the complex genetic architecture of schizophrenia, as well as the long-term effects of early life trauma on brain function and future mental health risk. Further, the evidence demonstrating the role of ongoing responses to trauma or heightened stress sensitivity, and their impact on the course of illness and recovery, is presented. Finally, the need for trauma-informed approaches and psychological therapy-based interventions is discussed, and a brief overview of the evidence to determine their utility is presented.
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Affiliation(s)
- Olympia Gianfrancesco
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom.,MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Vivien J Bubb
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom
| | - John P Quinn
- Department of Molecular and Clinical Pharmacology, Institute of Translational Medicine, University of Liverpool, Liverpool, United Kingdom
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46
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McClymont SA, Hook PW, Soto AI, Reed X, Law WD, Kerans SJ, Waite EL, Briceno NJ, Thole JF, Heckman MG, Diehl NN, Wszolek ZK, Moore CD, Zhu H, Akiyama JA, Dickel DE, Visel A, Pennacchio LA, Ross OA, Beer MA, McCallion AS. Parkinson-Associated SNCA Enhancer Variants Revealed by Open Chromatin in Mouse Dopamine Neurons. Am J Hum Genet 2018; 103:874-892. [PMID: 30503521 DOI: 10.1016/j.ajhg.2018.10.018] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 10/17/2018] [Indexed: 12/31/2022] Open
Abstract
The progressive loss of midbrain (MB) dopaminergic (DA) neurons defines the motor features of Parkinson disease (PD), and modulation of risk by common variants in PD has been well established through genome-wide association studies (GWASs). We acquired open chromatin signatures of purified embryonic mouse MB DA neurons because we anticipated that a fraction of PD-associated genetic variation might mediate the variants' effects within this neuronal population. Correlation with >2,300 putative enhancers assayed in mice revealed enrichment for MB cis-regulatory elements (CREs), and these data were reinforced by transgenic analyses of six additional sequences in zebrafish and mice. One CRE, within intron 4 of the familial PD gene SNCA, directed reporter expression in catecholaminergic neurons from transgenic mice and zebrafish. Sequencing of this CRE in 986 individuals with PD and 992 controls revealed two common variants associated with elevated PD risk. To assess potential mechanisms of action, we screened >16,000 proteins for DNA binding capacity and identified a subset whose binding is impacted by these enhancer variants. Additional genotyping across the SNCA locus identified a single PD-associated haplotype, containing the minor alleles of both of the aforementioned PD-risk variants. Our work posits a model for how common variation at SNCA might modulate PD risk and highlights the value of cell-context-dependent guided searches for functional non-coding variation.
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Affiliation(s)
- Sarah A McClymont
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Paul W Hook
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Alexandra I Soto
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Xylena Reed
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - William D Law
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Samuel J Kerans
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Eric L Waite
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Nicole J Briceno
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Joey F Thole
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Michael G Heckman
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Nancy N Diehl
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Jacksonville, FL 32224, USA
| | | | - Cedric D Moore
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Heng Zhu
- Department of Pharmacology and Molecular Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Jennifer A Akiyama
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Diane E Dickel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
| | - Axel Visel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA; US Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA; School of Natural Sciences, University of California, Merced, CA 95343, USA
| | - Len A Pennacchio
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA; US Department of Energy Joint Genome Institute, Walnut Creek, CA 94598, USA; Comparative Biochemistry Program, University of California, Berkeley, CA 94720, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA; Neuroscience Track, Mayo Graduate School, Jacksonville, FL 32224, USA; Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Michael A Beer
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Andrew S McCallion
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Molecular and Comparative Pathobiology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA; Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.
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47
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Chen X, Duan H, Xiao L, Gan J. Genetic and Epigenetic Alterations Underlie Oligodendroglia Susceptibility and White Matter Etiology in Psychiatric Disorders. Front Genet 2018; 9:565. [PMID: 30524471 PMCID: PMC6262033 DOI: 10.3389/fgene.2018.00565] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Accepted: 11/06/2018] [Indexed: 12/19/2022] Open
Abstract
Numerous genetic risk loci are found to associate with major neuropsychiatric disorders represented by schizophrenia. The pathogenic roles of genetic risk loci in psychiatric diseases are further complicated by the association with cell lineage- and/or developmental stage-specific epigenetic alterations. Besides aberrant assembly and malfunction of neuronal circuitry, an increasing volume of discoveries clearly demonstrate impairment of oligodendroglia and disruption of white matter integrity in psychiatric diseases. Nonetheless, whether and how genetic risk factors and epigenetic dysregulations for neuronal susceptibility may affect oligodendroglia is largely unknown. In this mini-review, we will discuss emerging evidence regarding the functional interplay between genetic risk loci and epigenetic factors, which may underlie compromised oligodendroglia and myelin development in neuropsychiatric disorders. Transcriptional and epigenetic factors are the major aspects affected in oligodendroglia. Moreover, multiple disease susceptibility genes are connected by epigenetically modulated transcriptional and post-transcriptional mechanisms. Oligodendroglia specific complex molecular orchestra may explain how distinct risk factors lead to the common clinical expression of white matter pathology of neuropsychiatric disorders.
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Affiliation(s)
- Xianjun Chen
- Department of Psychiatry, Mental Diseases Prevention and Treatment Institute of PLA, PLA 91st Central Hospital, Jiaozuo, China
| | - Huifeng Duan
- Department of Psychiatry, Mental Diseases Prevention and Treatment Institute of PLA, PLA 91st Central Hospital, Jiaozuo, China
| | - Lan Xiao
- Department of Histology and Embryology, Chongqing Key Laboratory of Neurobiology, Army Medical University (Third Military Medical University), Chongqing, China
| | - Jingli Gan
- Department of Psychiatry, Mental Diseases Prevention and Treatment Institute of PLA, PLA 91st Central Hospital, Jiaozuo, China
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Pihlstrøm L, Blauwendraat C, Cappelletti C, Berge-Seidl V, Langmyhr M, Henriksen SP, van de Berg WDJ, Gibbs JR, Cookson MR, Singleton AB, Nalls MA, Toft M. A comprehensive analysis of SNCA-related genetic risk in sporadic parkinson disease. Ann Neurol 2018; 84:117-129. [PMID: 30146727 DOI: 10.1002/ana.25274] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Revised: 04/13/2018] [Accepted: 06/15/2018] [Indexed: 12/15/2022]
Abstract
OBJECTIVE The goal of this study was to refine our understanding of disease risk attributable to common genetic variation in SNCA, a major locus in Parkinson disease, with potential implications for clinical trials targeting α-synuclein. We aimed to dissect the multiple independent association signals, stratify individuals by SNCA-specific risk profiles, and explore expression quantitative trait loci. METHODS We analyzed participant-level data from 12,503 patients and 12,502 controls, optimizing a risk model and assessing SNCA-specific risk scores and haplotypes as predictors of individual risk. We also explored hypotheses about functional mechanisms and correlated risk variants to gene expression in human brain and protein levels in cerebrospinal fluid. RESULTS We report and replicate a novel, third independent association signal at genome-wide significance level downstream of SNCA (rs2870004, p = 3.0*10-8 , odds ratio [OR] = 0.88, 95% confidence interval [CI] = 0.84-0.92). SNCA risk score stratification showed a 2-fold difference in disease susceptibility between top and bottom quintiles (OR = 1.99, 95% CI = 1.78-2.23). Contrary to previous reports, we provide evidence supporting top variant rs356182 as functional in itself and associated with a specific SNCA 5' untranslated region transcript isoform in frontal cortex. INTERPRETATION The SNCA locus harbors a minimum of 3 independent association signals for Parkinson disease. We demonstrate a fine-grained stratification of α-synuclein-related genetic burden in individual patients of potential future clinical relevance. Further efforts to pinpoint the functional mechanisms are warranted, including studies of the likely causal top variant rs356182 and its role in regulating levels of specific SNCA mRNA transcript variants. Ann Neurol 2018;83:117-129.
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Affiliation(s)
- Lasse Pihlstrøm
- Department of Neurology, Oslo University Hospital, Oslo, Norway
| | - Cornelis Blauwendraat
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD.,Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
| | | | | | | | | | - Wilma D J van de Berg
- Department of Anatomy and Neurosciences, Clinical Neuroanatomy Section, Amsterdam Neuroscience, VU Medical Center, Amsterdam, the Netherlands
| | - J Raphael Gibbs
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
| | - Mark R Cookson
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
| | | | | | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD.,Data Tecnica International, Glen Echo, MD
| | - Mathias Toft
- Department of Neurology, Oslo University Hospital, Oslo, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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49
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García-Cabezas MÁ, Barbas H, Zikopoulos B. Parallel Development of Chromatin Patterns, Neuron Morphology, and Connections: Potential for Disruption in Autism. Front Neuroanat 2018; 12:70. [PMID: 30174592 PMCID: PMC6107687 DOI: 10.3389/fnana.2018.00070] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Accepted: 07/30/2018] [Indexed: 12/27/2022] Open
Abstract
The phenotype of neurons and their connections depend on complex genetic and epigenetic processes that regulate the expression of genes in the nucleus during development and throughout life. Here we examined the distribution of nuclear chromatin patters in relation to the epigenetic landscape, phenotype and connections of neurons with a focus on the primate cerebral cortex. We show that nuclear patterns of chromatin in cortical neurons are related to neuron size and cortical connections. Moreover, we point to evidence that reveals an orderly sequence of events during development, linking chromatin and gene expression patterns, neuron morphology, function, and connections across cortical areas and layers. Based on this synthesis, we posit that systematic studies of changes in chromatin patterns and epigenetic marks across cortical areas will provide novel insights on the development and evolution of cortical networks, and their disruption in connectivity disorders of developmental origin, like autism. Achieving this requires embedding and interpreting genetic, transcriptional, and epigenetic studies within a framework that takes into consideration distinct types of neurons, local circuit interactions, and interareal pathways. These features vary systematically across cortical areas in parallel with laminar structure and are differentially affected in disorders. Finally, based on evidence that autism-associated genetic polymorphisms are especially prominent in excitatory neurons and connectivity disruption affects mostly limbic cortices, we employ this systematic approach to propose novel, targeted studies of projection neurons in limbic areas to elucidate the emergence and time-course of developmental disruptions in autism.
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Affiliation(s)
- Miguel Á García-Cabezas
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, MA, United States
| | - Helen Barbas
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, MA, United States.,Graduate Program in Neuroscience, Boston University, Boston, MA, United States
| | - Basilis Zikopoulos
- Graduate Program in Neuroscience, Boston University, Boston, MA, United States.,Human Systems Neuroscience Laboratory, Department of Health Sciences, Boston University, Boston, MA, United States
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50
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Abstract
Chromatin-related phenomena regulate gene expression by altering the compaction and accessibility of DNA to relevant transcription factors, thus allowing every cell in the body to attain distinct identities and to function properly within a given cellular context. These processes occur not only in the developing central nervous system, but continue throughout the lifetime of a neuron to constantly adapt to changes in the environment. Such changes can be positive or negative, thereby altering the chromatin landscape to influence cellular and synaptic plasticity within relevant neural circuits, and ultimately behavior. Given the importance of epigenetic mechanisms in guiding physiological adaptations, perturbations in these processes in brain have been linked to several neuropsychiatric and neurological disorders. In this review, we cover some of the recent advances linking chromatin dynamics to complex brain disorders and discuss new methodologies that may overcome current limitations in the field.
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Affiliation(s)
- Ryan M Bastle
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Ian Maze
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029.,Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029
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