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Chen YZ, Zhu XM, Lv P, Hou XK, Pan Y, Li A, Du Z, Xuan JF, Guo X, Xing JX, Liu K, Yao J. Association of histone modification with the development of schizophrenia. Biomed Pharmacother 2024; 175:116747. [PMID: 38744217 DOI: 10.1016/j.biopha.2024.116747] [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: 02/29/2024] [Revised: 05/06/2024] [Accepted: 05/10/2024] [Indexed: 05/16/2024] Open
Abstract
Schizophrenia, influenced by genetic and environmental factors, may involve epigenetic alterations, notably histone modifications, in its pathogenesis. This review summarizes various histone modifications including acetylation, methylation, phosphorylation, ubiquitination, serotonylation, lactylation, palmitoylation, and dopaminylation, and their implications in schizophrenia. Current research predominantly focuses on histone acetylation and methylation, though other modifications also play significant roles. These modifications are crucial in regulating transcription through chromatin remodeling, which is vital for understanding schizophrenia's development. For instance, histone acetylation enhances transcriptional efficiency by loosening chromatin, while increased histone methyltransferase activity on H3K9 and altered histone phosphorylation, which reduces DNA affinity and destabilizes chromatin structure, are significant markers of schizophrenia.
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Affiliation(s)
- Yun-Zhou Chen
- School of Forensic Medicine, China Medical University, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Liaoning Province, PR China; China Medical University Center of Forensic Investigation, PR China
| | - Xiu-Mei Zhu
- School of Forensic Medicine, China Medical University, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Liaoning Province, PR China; China Medical University Center of Forensic Investigation, PR China
| | - Peng Lv
- School of Forensic Medicine, China Medical University, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Liaoning Province, PR China; China Medical University Center of Forensic Investigation, PR China
| | - Xi-Kai Hou
- School of Forensic Medicine, China Medical University, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Liaoning Province, PR China; China Medical University Center of Forensic Investigation, PR China
| | - Ying Pan
- School of Forensic Medicine, China Medical University, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Liaoning Province, PR China; China Medical University Center of Forensic Investigation, PR China
| | - Ang Li
- School of Forensic Medicine, China Medical University, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Liaoning Province, PR China; China Medical University Center of Forensic Investigation, PR China
| | - Zhe Du
- School of Forensic Medicine, China Medical University, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Liaoning Province, PR China; China Medical University Center of Forensic Investigation, PR China
| | - Jin-Feng Xuan
- School of Forensic Medicine, China Medical University, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Liaoning Province, PR China; China Medical University Center of Forensic Investigation, PR China
| | - Xiaochong Guo
- Laboratory Animal Center, China Medical University, PR China
| | - Jia-Xin Xing
- School of Forensic Medicine, China Medical University, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Liaoning Province, PR China; China Medical University Center of Forensic Investigation, PR China.
| | - Kun Liu
- Key Laboratory of Health Ministry in Congenital Malformation, Shengjing Hospital of China Medical University, PR China.
| | - Jun Yao
- School of Forensic Medicine, China Medical University, PR China; Key Laboratory of Forensic Bio-evidence Sciences, Liaoning Province, PR China; China Medical University Center of Forensic Investigation, PR China.
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2
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Emani PS, Liu JJ, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee CY, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken TE, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard JF, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman GE, Huang A, Jiang Y, Jin T, Jorstad NL, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran JR, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan AS, Riesenmy TR, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini KJ, Wamsley B, Wang G, Xia Y, Xiao S, Yang AC, Zheng S, Gandal MJ, Lee D, Lein ES, Roussos P, Sestan N, Weng Z, White KP, Won H, Girgenti MJ, Zhang J, Wang D, Geschwind D, Gerstein M. Single-cell genomics and regulatory networks for 388 human brains. Science 2024; 384:eadi5199. [PMID: 38781369 DOI: 10.1126/science.adi5199] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 04/05/2024] [Indexed: 05/25/2024]
Abstract
Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.
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Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jason J Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Declan Clarke
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Matthew Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Chirag Gupta
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Ran Meng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Che Yu Lee
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Cagatay Dursun
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Shaoke Lou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yuhang Chen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Zhiyuan Chu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Timur Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, CA 92697, USA
- Mathematical, Computational and Systems Biology, University of California, Irvine, CA 92697, USA
| | - Yunyang Li
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
| | - Pengyu Ni
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Xiao Zhou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | | | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Lucy Bicks
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Tanima Chatterjee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | | | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yi Dai
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Ziheng Duan
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | | | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Michael Gancz
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Diego Garrido-Martín
- Department of Genetics, Microbiology and Statistics, Universitat de Barcelona, Barcelona 08028, Spain
| | - Sophia Gaynor-Gillett
- Tempus Labs, Chicago, IL 60654, USA
- Department of Biology, Cornell College, Mount Vernon, IA 52314, USA
| | - Jennifer Grundman
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Natalie Hawken
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Ella Henry
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Ao Huang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Yunzhe Jiang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Ting Jin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | | | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA 90095, USA
| | - Saniya Khullar
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Jianyin Liu
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Junhao Liu
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Shuang Liu
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Samantha Mazariegos
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | | | - Eric Nguyen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Milos Pjanic
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Henry Pratt
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Diana Quintero
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | | | - Tiernon R Riesenmy
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | | | | | - Rosemarie Terwilliger
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06520, USA
| | | | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Gaoyuan Wang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yan Xia
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Shaohua Xiao
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Andrew C Yang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Suchen Zheng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, 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
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Kevin P White
- Yong Loo Lin School of Medicine, National University of Singapore, 117597 Singapore
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06520, USA
- Clinical Neuroscience Division, National Center for Posttraumatic Stress Disorder, Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Daniel Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, 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
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, 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
- Department of Biomedical Informatics & Data Science, Yale University, New Haven, CT 06520, USA
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3
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Gedik H, Peterson R, Chatzinakos C, Dozmorov MG, Vladimirov V, Riley BP, Bacanu SA. A novel multi-omics mendelian randomization method for gene set enrichment and its application to psychiatric disorders. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.14.24305811. [PMID: 38699366 PMCID: PMC11065030 DOI: 10.1101/2024.04.14.24305811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Genome-wide association studies (GWAS) of psychiatric disorders (PD) yield numerous loci with significant signals, but often do not implicate specific genes. Because GWAS risk loci are enriched in expression/protein/methylation quantitative loci (e/p/mQTL, hereafter xQTL), transcriptome/proteome/methylome-wide association studies (T/P/MWAS, hereafter XWAS) that integrate xQTL and GWAS information, can link GWAS signals to effects on specific genes. To further increase detection power, gene signals are aggregated within relevant gene sets (GS) by performing gene set enrichment (GSE) analyses. Often GSE methods test for enrichment of "signal" genes in curated GS while overlooking their linkage disequilibrium (LD) structure, allowing for the possibility of increased false positive rates. Moreover, no GSE tool uses xQTL information to perform mendelian randomization (MR) analysis. To make causal inference on association between PD and GS, we develop a novel MR GSE (MR-GSE) procedure. First, we generate a "synthetic" GWAS for each MSigDB GS by aggregating summary statistics for x-level (mRNA, protein or DNA methylation (DNAm) levels) from the largest xQTL studies available) of genes in a GS. Second, we use synthetic GS GWAS as exposure in a generalized summary-data-based-MR analysis of complex trait outcomes. We applied MR-GSE to GWAS of nine important PD. When applied to the underpowered opioid use disorder GWAS, none of the four analyses yielded any signals, which suggests a good control of false positive rates. For other PD, MR-GSE greatly increased the detection of GO terms signals (2,594) when compared to the commonly used (non-MR) GSE method (286). Some of the findings might be easier to adapt for treatment, e.g., our analyses suggest modest positive effects for supplementation with certain vitamins and/or omega-3 for schizophrenia, bipolar and major depression disorder patients. Similar to other MR methods, when applying MR-GSE researchers should be mindful of the confounding effects of horizontal pleiotropy on statistical inference.
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4
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Emani PS, Liu JJ, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee CY, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken TE, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard JF, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman GE, Huang A, Jiang Y, Jin T, Jorstad NL, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran JR, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan AS, Riesenmy TR, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini KJ, Wamsley B, Wang G, Xia Y, Xiao S, Yang AC, Zheng S, Gandal MJ, Lee D, Lein ES, Roussos P, Sestan N, Weng Z, White KP, Won H, Girgenti MJ, Zhang J, Wang D, Geschwind D, Gerstein M. Single-cell genomics and regulatory networks for 388 human brains. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.18.585576. [PMID: 38562822 PMCID: PMC10983939 DOI: 10.1101/2024.03.18.585576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.
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Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jason J Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Declan Clarke
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Matthew Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Chirag Gupta
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Ran Meng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Che Yu Lee
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Cagatay Dursun
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shaoke Lou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yuhang Chen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Zhiyuan Chu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Timur Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
- Mathematical, Computational and Systems Biology, University of California, Irvine, CA, 92697, USA
| | - Yunyang Li
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA
| | - Pengyu Ni
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Xiao Zhou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | | | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lucy Bicks
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Tanima Chatterjee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | | | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Department of Opthalmology, Perlman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Yi Dai
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Ziheng Duan
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | | | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Michael Gancz
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Diego Garrido-Martín
- Department of Genetics, Microbiology and Statistics, Universitat de Barcelona, Barcelona, 08028, Spain
| | - Sophia Gaynor-Gillett
- Tempus Labs, Inc., Chicago, IL, 60654, USA
- Department of Biology, Cornell College, Mount Vernon, IA, 52314, USA
| | - Jennifer Grundman
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Natalie Hawken
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Ella Henry
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Ao Huang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Yunzhe Jiang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Ting Jin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | | | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA, 90095, USA
| | - Saniya Khullar
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Jianyin Liu
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Junhao Liu
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Shuang Liu
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale University, New Haven, CT, 06510, USA
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Michael Margolis
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Samantha Mazariegos
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | | | - Eric Nguyen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Milos Pjanic
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Henry Pratt
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Diana Quintero
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | | | - Tiernon R Riesenmy
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Manman Shi
- Tempus Labs, Inc., Chicago, IL, 60654, USA
| | | | - Rosemarie Terwilliger
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06520, USA
| | | | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Gaoyuan Wang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yan Xia
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shaohua Xiao
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Andrew C Yang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Suchen Zheng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, 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
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA, 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- 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
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University, New Haven, CT, 06510, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Kevin P White
- Yong Loo Lin School of Medicine, National University of Singapore, 117597, Singapore
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT, 06520, USA
- Clinical Neuroscience Division, National Center for Posttraumatic Stress Disorder, Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Daniel Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, 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
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA
- Department of Biomedical Informatics & Data Science, Yale University, New Haven, CT, 06520, USA
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5
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López-Otín C, Kroemer G. The missing hallmark of health: psychosocial adaptation. Cell Stress 2024; 8:21-50. [PMID: 38476764 PMCID: PMC10928495 DOI: 10.15698/cst2024.03.294] [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: 01/11/2024] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 03/14/2024] Open
Abstract
The eight biological hallmarks of health that we initially postulated (Cell. 2021 Jan 7;184(1):33-63) include features of spatial compartmentalization (integrity of barriers, containment of local perturbations), maintenance of homeostasis over time (recycling & turnover, integration of circuitries, rhythmic oscillations) and an array of adequate responses to stress (homeostatic resilience, hormetic regulation, repair & regeneration). These hallmarks affect all eight somatic strata of the human body (molecules, organelles, cells, supracellular units, organs, organ systems, systemic circuitries and meta-organism). Here we postulate that mental and socioeconomic factors must be added to this 8×8 matrix as an additional hallmark of health ("psychosocial adaptation") and as an additional stratum ("psychosocial interactions"), hence building a 9×9 matrix. Potentially, perturbation of each of the somatic hallmarks and strata affects psychosocial factors and vice versa. Finally, we discuss the (patho)physiological bases of these interactions and their implications for mental health improvement.
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Affiliation(s)
- Carlos López-Otín
- Centre de Recherche des Cordeliers, Equipe labellisée par la Ligue contre le cancer, Université Paris Cité, Sorbonne Université, Inserm U1138, Institut Universitaire de France, Paris, France
- Facultad de Ciencias de la Vida y la Naturaleza, Universidad Nebrija, Madrid, Spain
- Departamento de Bioquímica y Biología Molecular, Instituto Universitario de Oncología (IUOPA), Universidad de Oviedo
| | - Guido Kroemer
- Centre de Recherche des Cordeliers, Equipe labellisée par la Ligue contre le cancer, Université Paris Cité, Sorbonne Université, Inserm U1138, Institut Universitaire de France, Paris, France
- Metabolomics and Cell Biology Platforms, Institut Gustave Roussy, Villejuif, France
- Institut du Cancer Paris CARPEM, Department of Biology, Hôpital Européen Georges Pompidou, AP-HP, Paris, France
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6
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Sánchez-Ramírez E, Ung TPL, Stringari C, Aguilar-Arnal L. Emerging Functional Connections Between Metabolism and Epigenetic Remodeling in Neural Differentiation. Mol Neurobiol 2024:10.1007/s12035-024-04006-w. [PMID: 38340204 DOI: 10.1007/s12035-024-04006-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 01/30/2024] [Indexed: 02/12/2024]
Abstract
Stem cells possess extraordinary capacities for self-renewal and differentiation, making them highly valuable in regenerative medicine. Among these, neural stem cells (NSCs) play a fundamental role in neural development and repair processes. NSC characteristics and fate are intricately regulated by the microenvironment and intracellular signaling. Interestingly, metabolism plays a pivotal role in orchestrating the epigenome dynamics during neural differentiation, facilitating the transition from undifferentiated NSC to specialized neuronal and glial cell types. This intricate interplay between metabolism and the epigenome is essential for precisely regulating gene expression patterns and ensuring proper neural development. This review highlights the mechanisms behind metabolic regulation of NSC fate and their connections with epigenetic regulation to shape transcriptional programs of stemness and neural differentiation. A comprehensive understanding of these molecular gears appears fundamental for translational applications in regenerative medicine and personalized therapies for neurological conditions.
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Affiliation(s)
- Edgar Sánchez-Ramírez
- Departamento de Biología Celular y Fisiología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Thi Phuong Lien Ung
- Laboratory for Optics and Biosciences, Ecole Polytechnique, CNRS, INSERM, Institut Polytechnique de Paris, Palaiseau, France
| | - Chiara Stringari
- Laboratory for Optics and Biosciences, Ecole Polytechnique, CNRS, INSERM, Institut Polytechnique de Paris, Palaiseau, France
| | - Lorena Aguilar-Arnal
- Departamento de Biología Celular y Fisiología, Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City, Mexico.
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7
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Martínez-Peula O, Morentin B, Callado LF, Meana JJ, Rivero G, Ramos-Miguel A. Permissive epigenetic regulatory mechanisms at the histone level are enhanced in postmortem dorsolateral prefrontal cortex of individuals with schizophrenia. J Psychiatry Neurosci 2024; 49:E35-E44. [PMID: 38302137 PMCID: PMC10843339 DOI: 10.1503/jpn.230054] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 09/28/2023] [Accepted: 11/03/2023] [Indexed: 02/03/2024] Open
Abstract
BACKGROUND Susceptibility to schizophrenia is determined by interactions between genes and environment, possibly via epigenetic mechanisms. Schizophrenia has been associated with a restrictive epigenome, and histone deacetylase (HDAC) inhibitors have been postulated as coadjuvant agents to potentiate the efficacy of current antipsychotic drugs. We aimed to evaluate global histone posttranslational modifications (HPTMs) and HDAC expression and activity in the dorsolateral prefrontal cortex (DLPFC) of individuals with schizophrenia. METHODS We used postmortem DLPFC samples of individuals with schizophrenia and controls matched for sex, age, and postmortem interval. Schizophrenia samples were classified into antipsychotic-treated or antipsychotic-free subgroups according to blood toxicology. Expression of HPTMs and HDAC was quantified by Western blot. HDAC activity was measured with a fluorometric assay. RESULTS H3K9ac, H3K27ac, and H3K4me3 were globally enhanced in the DLPFC of individuals with schizophrenia (+24%-42%, p < 0.05). HDAC activity (-17%, p < 0.01) and HDAC4 protein expression (-20%, p < 0.05) were downregulated in individuals with schizophrenia. Analyses of antipsychotic-free and antipsychotic-treated subgroups revealed enhanced H3K4me3 and H3K27ac (+24%-49%, p < 0.05) and reduced HDAC activity in the antipsychotic-treated, but not in the antipsychotic-free subgroup. LIMITATIONS Special care was taken to control the effect of confounding factors: age, sex, postmortem interval, and storage time. However, replication studies in bigger cohorts might strengthen the association between permissive HPTMs and schizophrenia. CONCLUSION We found global HPTM alterations consistent with an aberrantly permissive epigenome in schizophrenia. Further studies to elucidate the significance of enhanced permissive HPTMs in schizophrenia and its association with the mechanism of action of antipsychotic drugs are encouraged.
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Affiliation(s)
- Oihane Martínez-Peula
- From the Department of Pharmacology, University of the Basque Country, UPV/EHU, Leioa, Spain (Martínez-Peula, Callado, Meana, Rivero, Ramos-Miguel); Section of Forensic Pathology, Basque Institute of Legal Medicine, Bilbao, Spain (Morentin); the Biobizkaia Health Research Institute, Barakaldo, Spain ( Morentin, Callado, Meana, Rivero, Ramos-Miguel); and the Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, ISCIII, Spain (Callado, Meana, Rivero, Ramos-Miguel)
| | - Benito Morentin
- From the Department of Pharmacology, University of the Basque Country, UPV/EHU, Leioa, Spain (Martínez-Peula, Callado, Meana, Rivero, Ramos-Miguel); Section of Forensic Pathology, Basque Institute of Legal Medicine, Bilbao, Spain (Morentin); the Biobizkaia Health Research Institute, Barakaldo, Spain ( Morentin, Callado, Meana, Rivero, Ramos-Miguel); and the Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, ISCIII, Spain (Callado, Meana, Rivero, Ramos-Miguel)
| | - Luis F Callado
- From the Department of Pharmacology, University of the Basque Country, UPV/EHU, Leioa, Spain (Martínez-Peula, Callado, Meana, Rivero, Ramos-Miguel); Section of Forensic Pathology, Basque Institute of Legal Medicine, Bilbao, Spain (Morentin); the Biobizkaia Health Research Institute, Barakaldo, Spain ( Morentin, Callado, Meana, Rivero, Ramos-Miguel); and the Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, ISCIII, Spain (Callado, Meana, Rivero, Ramos-Miguel)
| | - J Javier Meana
- From the Department of Pharmacology, University of the Basque Country, UPV/EHU, Leioa, Spain (Martínez-Peula, Callado, Meana, Rivero, Ramos-Miguel); Section of Forensic Pathology, Basque Institute of Legal Medicine, Bilbao, Spain (Morentin); the Biobizkaia Health Research Institute, Barakaldo, Spain ( Morentin, Callado, Meana, Rivero, Ramos-Miguel); and the Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, ISCIII, Spain (Callado, Meana, Rivero, Ramos-Miguel)
| | - Guadalupe Rivero
- From the Department of Pharmacology, University of the Basque Country, UPV/EHU, Leioa, Spain (Martínez-Peula, Callado, Meana, Rivero, Ramos-Miguel); Section of Forensic Pathology, Basque Institute of Legal Medicine, Bilbao, Spain (Morentin); the Biobizkaia Health Research Institute, Barakaldo, Spain ( Morentin, Callado, Meana, Rivero, Ramos-Miguel); and the Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, ISCIII, Spain (Callado, Meana, Rivero, Ramos-Miguel)
| | - Alfredo Ramos-Miguel
- From the Department of Pharmacology, University of the Basque Country, UPV/EHU, Leioa, Spain (Martínez-Peula, Callado, Meana, Rivero, Ramos-Miguel); Section of Forensic Pathology, Basque Institute of Legal Medicine, Bilbao, Spain (Morentin); the Biobizkaia Health Research Institute, Barakaldo, Spain ( Morentin, Callado, Meana, Rivero, Ramos-Miguel); and the Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, ISCIII, Spain (Callado, Meana, Rivero, Ramos-Miguel)
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8
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Michalski C, Wen Z. Leveraging iPSC technology to assess neuro-immune interactions in neurological and psychiatric disorders. Front Psychiatry 2023; 14:1291115. [PMID: 38025464 PMCID: PMC10672983 DOI: 10.3389/fpsyt.2023.1291115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 10/19/2023] [Indexed: 12/01/2023] Open
Abstract
Communication between the immune and the nervous system is essential for human brain development and homeostasis. Disruption of this intricately regulated crosstalk can lead to neurodevelopmental, psychiatric, or neurodegenerative disorders. While animal models have been essential in characterizing the role of neuroimmunity in development and disease, they come with inherent limitations due to species specific differences, particularly with regard to microglia, the major subset of brain resident immune cells. The advent of induced pluripotent stem cell (iPSC) technology now allows the development of clinically relevant models of the central nervous system that adequately reflect human genetic architecture. This article will review recent publications that have leveraged iPSC technology to assess neuro-immune interactions. First, we will discuss the role of environmental stressors such as neurotropic viruses or pro-inflammatory cytokines on neuronal and glial function. Next, we will review how iPSC models can be used to study genetic risk factors in neurological and psychiatric disorders. Lastly, we will evaluate current challenges and future potential for iPSC models in the field of neuroimmunity.
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Affiliation(s)
- Christina Michalski
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - Zhexing Wen
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
- Department of Cell Biology, Emory University School of Medicine, Atlanta, GA, United States
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, United States
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9
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Ursini G, Di Carlo P, Mukherjee S, Chen Q, Han S, Kim J, Deyssenroth M, Marsit CJ, Chen J, Hao K, Punzi G, Weinberger DR. Prioritization of potential causative genes for schizophrenia in placenta. Nat Commun 2023; 14:2613. [PMID: 37188697 PMCID: PMC10185564 DOI: 10.1038/s41467-023-38140-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 04/17/2023] [Indexed: 05/17/2023] Open
Abstract
Our earlier work has shown that genomic risk for schizophrenia converges with early life complications in affecting risk for the disorder and sex-biased neurodevelopmental trajectories. Here, we identify specific genes and potential mechanisms that, in placenta, may mediate such outcomes. We performed TWAS in healthy term placentae (N = 147) to derive candidate placental causal genes that we confirmed with SMR; to search for placenta and schizophrenia-specific associations, we performed an analogous analysis in fetal brain (N = 166) and additional placenta TWAS for other disorders/traits. The analyses in the whole sample and stratifying by sex ultimately highlight 139 placenta and schizophrenia-specific risk genes, many being sex-biased; the candidate molecular mechanisms converge on the nutrient-sensing capabilities of placenta and trophoblast invasiveness. These genes also implicate the Coronavirus-pathogenesis pathway and showed increased expression in placentae from a small sample of SARS-CoV-2-positive pregnancies. Investigating placental risk genes for schizophrenia and candidate mechanisms may lead to opportunities for prevention that would not be suggested by study of the brain alone.
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Affiliation(s)
- Gianluca Ursini
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA.
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Pasquale Di Carlo
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
- Group of Psychiatric Neuroscience, Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari Aldo Moro, Bari, Italy
| | - Sreya Mukherjee
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Qiang Chen
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Shizhong Han
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Jiyoung Kim
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
| | - Maya Deyssenroth
- Departments of Environmental Medicine and Public Health, Icahn School of Public Health at Mount Sinai, New York, NY, USA
| | - Carmen J Marsit
- Departments of Environmental Health and Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Jia Chen
- Departments of Environmental Medicine and Public Health, Icahn School of Public Health at Mount Sinai, New York, NY, USA
| | - Ke Hao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Giovanna Punzi
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Johns Hopkins University Medical Campus, Baltimore, MD, USA.
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA.
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
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10
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Abdolmaleky HM, Martin M, Zhou JR, Thiagalingam S. Epigenetic Alterations of Brain Non-Neuronal Cells in Major Mental Diseases. Genes (Basel) 2023; 14:896. [PMID: 37107654 PMCID: PMC10137903 DOI: 10.3390/genes14040896] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 03/22/2023] [Accepted: 04/06/2023] [Indexed: 04/29/2023] Open
Abstract
The tissue-specific expression and epigenetic dysregulation of many genes in cells derived from the postmortem brains of patients have been reported to provide a fundamental biological framework for major mental diseases such as autism, schizophrenia, bipolar disorder, and major depression. However, until recently, the impact of non-neuronal brain cells, which arises due to cell-type-specific alterations, has not been adequately scrutinized; this is because of the absence of techniques that directly evaluate their functionality. With the emergence of single-cell technologies, such as RNA sequencing (RNA-seq) and other novel techniques, various studies have now started to uncover the cell-type-specific expression and DNA methylation regulation of many genes (e.g., TREM2, MECP2, SLC1A2, TGFB2, NTRK2, S100B, KCNJ10, and HMGB1, and several complement genes such as C1q, C3, C3R, and C4) in the non-neuronal brain cells involved in the pathogenesis of mental diseases. Additionally, several lines of experimental evidence indicate that inflammation and inflammation-induced oxidative stress, as well as many insidious/latent infectious elements including the gut microbiome, alter the expression status and the epigenetic landscapes of brain non-neuronal cells. Here, we present supporting evidence highlighting the importance of the contribution of the brain's non-neuronal cells (in particular, microglia and different types of astrocytes) in the pathogenesis of mental diseases. Furthermore, we also address the potential impacts of the gut microbiome in the dysfunction of enteric and brain glia, as well as astrocytes, which, in turn, may affect neuronal functions in mental disorders. Finally, we present evidence that supports that microbiota transplantations from the affected individuals or mice provoke the corresponding disease-like behavior in the recipient mice, while specific bacterial species may have beneficial effects.
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Affiliation(s)
- Hamid Mostafavi Abdolmaleky
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Surgery, Nutrition/Metabolism Laboratory, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - Marian Martin
- Department of Neurology, Albert Einstein College of Medicine, New York, NY 10461, USA
| | - Jin-Rong Zhou
- Department of Surgery, Nutrition/Metabolism Laboratory, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - Sam Thiagalingam
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Pathology & Laboratory Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
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11
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Arzate-Mejia RG, Mansuy IM. Remembering through the genome: the role of chromatin states in brain functions and diseases. Transl Psychiatry 2023; 13:122. [PMID: 37041131 PMCID: PMC10090084 DOI: 10.1038/s41398-023-02415-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 03/19/2023] [Accepted: 03/24/2023] [Indexed: 04/13/2023] Open
Abstract
Chromatin is the physical substrate of the genome that carries the DNA sequence and ensures its proper functions and regulation in the cell nucleus. While a lot is known about the dynamics of chromatin during programmed cellular processes such as development, the role of chromatin in experience-dependent functions remains not well defined. Accumulating evidence suggests that in brain cells, environmental stimuli can trigger long-lasting changes in chromatin structure and tri-dimensional (3D) organization that can influence future transcriptional programs. This review describes recent findings suggesting that chromatin plays an important role in cellular memory, particularly in the maintenance of traces of prior activity in the brain. Inspired by findings in immune and epithelial cells, we discuss the underlying mechanisms and the implications for experience-dependent transcriptional regulation in health and disease. We conclude by presenting a holistic view of chromatin as potential molecular substrate for the integration and assimilation of environmental information that may constitute a conceptual basis for future research.
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Affiliation(s)
- Rodrigo G Arzate-Mejia
- Laboratory of Neuroepigenetics, Brain Research Institute, Medical Faculty, University of Zurich, Zurich, Switzerland
- Institute for Neuroscience, Department of Health Science and Technology, Swiss Federal Institute of Technology Zürich (ETHZ), Zurich, Switzerland
- Center for Neuroscience Zürich, University Zürich and ETHZ, Zürich, Switzerland
| | - Isabelle M Mansuy
- Laboratory of Neuroepigenetics, Brain Research Institute, Medical Faculty, University of Zurich, Zurich, Switzerland.
- Institute for Neuroscience, Department of Health Science and Technology, Swiss Federal Institute of Technology Zürich (ETHZ), Zurich, Switzerland.
- Center for Neuroscience Zürich, University Zürich and ETHZ, Zürich, Switzerland.
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12
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Wawrzczak-Bargieła A, Bilecki W, Maćkowiak M. Epigenetic Targets in Schizophrenia Development and Therapy. Brain Sci 2023; 13:brainsci13030426. [PMID: 36979236 PMCID: PMC10046502 DOI: 10.3390/brainsci13030426] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 02/24/2023] [Accepted: 02/26/2023] [Indexed: 03/06/2023] Open
Abstract
Schizophrenia is regarded as a neurodevelopmental disorder with its course progressing throughout life. However, the aetiology and development of schizophrenia are still under investigation. Several data suggest that the dysfunction of epigenetic mechanisms is known to be involved in the pathomechanism of this mental disorder. The present article revised the epigenetic background of schizophrenia based on the data available in online databases (PubMed, Scopus). This paper focused on the role of epigenetic regulation, such as DNA methylation, histone modifications, and interference of non-coding RNAs, in schizophrenia development. The article also reviewed the available data related to epigenetic regulation that may modify the severity of the disease as a possible target for schizophrenia pharmacotherapy. Moreover, the effects of antipsychotics on epigenetic malfunction in schizophrenia are discussed based on preclinical and clinical results. The obtainable data suggest alterations of epigenetic regulation in schizophrenia. Moreover, they also showed the important role of epigenetic modifications in antipsychotic action. There is a need for more data to establish the role of epigenetic mechanisms in schizophrenia therapy. It would be of special interest to find and develop new targets for schizophrenia therapy because patients with schizophrenia could show little or no response to current pharmacotherapy and have treatment-resistant schizophrenia.
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13
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Martella N, Pensabene D, Varone M, Colardo M, Petraroia M, Sergio W, La Rosa P, Moreno S, Segatto M. Bromodomain and Extra-Terminal Proteins in Brain Physiology and Pathology: BET-ing on Epigenetic Regulation. Biomedicines 2023; 11:biomedicines11030750. [PMID: 36979729 PMCID: PMC10045827 DOI: 10.3390/biomedicines11030750] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 02/24/2023] [Accepted: 02/25/2023] [Indexed: 03/06/2023] Open
Abstract
BET proteins function as histone code readers of acetylated lysins that determine the positive regulation in transcription of genes involved in cell cycle progression, differentiation, inflammation, and many other pathways. In recent years, thanks to the development of BET inhibitors, interest in this protein family has risen for its relevance in brain development and function. For example, experimental evidence has shown that BET modulation affects neuronal activity and the expression of genes involved in learning and memory. In addition, BET inhibition strongly suppresses molecular pathways related to neuroinflammation. These observations suggest that BET modulation may play a critical role in the onset and during the development of diverse neurodegenerative and neuropsychiatric disorders, such as Alzheimer’s disease, fragile X syndrome, and Rett syndrome. In this review article, we summarize the most recent evidence regarding the involvement of BET proteins in brain physiology and pathology, as well as their pharmacological potential as targets for therapeutic purposes.
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Affiliation(s)
- Noemi Martella
- Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche, Italy
| | - Daniele Pensabene
- Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche, Italy
- Department of Science, University Roma Tre, Viale Marconi 446, 00146 Rome, Italy
- Laboratory of Neurodevelopment, Neurogenetics and Neuromolecular Biology, IRCCS Santa Lucia Foundation, 64 via del Fosso di Fiorano, 00179 Rome, Italy
| | - Michela Varone
- Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche, Italy
| | - Mayra Colardo
- Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche, Italy
| | - Michele Petraroia
- Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche, Italy
| | - William Sergio
- Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche, Italy
| | - Piergiorgio La Rosa
- Division of Neuroscience, Department of Psychology, Sapienza University of Rome, via dei Marsi 78, 00185 Rome, Italy
| | - Sandra Moreno
- Department of Science, University Roma Tre, Viale Marconi 446, 00146 Rome, Italy
- Laboratory of Neurodevelopment, Neurogenetics and Neuromolecular Biology, IRCCS Santa Lucia Foundation, 64 via del Fosso di Fiorano, 00179 Rome, Italy
| | - Marco Segatto
- Department of Biosciences and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche, Italy
- Correspondence:
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Sun Z, Lee-Sarwar K, Kelly RS, Lasky-Su JA, Litonjua AA, Weiss ST, Liu YY. Revealing the importance of prenatal gut microbiome in offspring neurodevelopment in humans. EBioMedicine 2023; 90:104491. [PMID: 36868051 PMCID: PMC9996363 DOI: 10.1016/j.ebiom.2023.104491] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 02/01/2023] [Accepted: 02/09/2023] [Indexed: 03/05/2023] Open
Abstract
BACKGROUND It has been widely recognized that a critical time window for neurodevelopment occurs in early life and the host's gut microbiome plays an important role in neurodevelopment. Following recent demonstrations that the maternal prenatal gut microbiome influences offspring brain development in murine models, we aim to explore whether the critical time window for the association between the gut microbiome and neurodevelopment is prenatal or postnatal for human. METHODS Here we leverage a large-scale human study and compare the associations between the gut microbiota and metabolites from mothers during pregnancy and their children with the children's neurodevelopment. Specifically, using multinomial regression integrated in Songbird, we assessed the discriminating power of the maternal prenatal and child gut microbiome for children's neurodevelopment at early life as measured by the Ages & Stages Questionnaires (ASQ). FINDINGS We show that the maternal prenatal gut microbiome is more relevant than the children's gut microbiome to the children's neurodevelopment in the first year of life (maximum Q2 = 0.212 and 0.096 separately using the taxa at the class level). Moreover, we found that Fusobacteriia is more associated with high fine motor skills in ASQ in the maternal prenatal gut microbiota but become more associated with low fine motor skills in the infant gut microbiota (rank = 0.084 and -0.047 separately), suggesting the roles of the same taxa with respect to neurodevelopment can be opposite at the two stages of fetal neurodevelopment. INTERPRETATION These findings shed light, especially in terms of timing, on potential therapeutic interventions to prevent neurodevelopmental disorders. FUNDING This work was supported by the National Institutes of Health (grant numbers: R01AI141529, R01HD093761, RF1AG067744, UH3OD023268, U19AI095219, U01HL089856, R01HL141826, K08HL148178, K01HL146980), and the Charles A. King Trust Postdoctoral Fellowship.
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Affiliation(s)
- Zheng Sun
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Kathleen Lee-Sarwar
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Rachel S Kelly
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Jessica A Lasky-Su
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Augusto A Litonjua
- Division of Pediatric Pulmonary Medicine, Department of Pediatrics, University of Rochester Medical Center, Rochester, NY, 14642, USA
| | - Scott T Weiss
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA
| | - Yang-Yu Liu
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, 02115, USA; Center for Artificial Intelligence and Modeling, The Carl R. Woese Institute of Genomic Biology, University of Illinois at Urbana-Champaign, Champaign, 61801, USA.
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15
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Gene Expression and Epigenetic Regulation in the Prefrontal Cortex of Schizophrenia. Genes (Basel) 2023; 14:genes14020243. [PMID: 36833173 PMCID: PMC9957055 DOI: 10.3390/genes14020243] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/03/2023] [Accepted: 01/13/2023] [Indexed: 01/19/2023] Open
Abstract
Schizophrenia pathogenesis remains challenging to define; however, there is strong evidence that the interaction of genetic and environmental factors causes the disorder. This paper focuses on transcriptional abnormalities in the prefrontal cortex (PFC), a key anatomical structure that determines functional outcomes in schizophrenia. This review summarises genetic and epigenetic data from human studies to understand the etiological and clinical heterogeneity of schizophrenia. Gene expression studies using microarray and sequencing technologies reported the aberrant transcription of numerous genes in the PFC in patients with schizophrenia. Altered gene expression in schizophrenia is related to several biological pathways and networks (synaptic function, neurotransmission, signalling, myelination, immune/inflammatory mechanisms, energy production and response to oxidative stress). Studies investigating mechanisms driving these transcriptional abnormalities focused on alternations in transcription factors, gene promoter elements, DNA methylation, posttranslational histone modifications or posttranscriptional regulation of gene expression mediated by non-coding RNAs.
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Kundakovic M. BET-ting on histone proteomics in schizophrenia. Trends Neurosci 2022; 45:716-717. [PMID: 35718601 PMCID: PMC9691262 DOI: 10.1016/j.tins.2022.06.001] [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: 06/01/2022] [Accepted: 06/06/2022] [Indexed: 10/18/2022]
Abstract
In a recent study, Farrelly, Zheng, and colleagues used a histone proteomics approach and patient-derived neurons to show increase in histone variant H2A.Z acetylation associated with schizophrenia (SCZ). They identified the bromo- and extraterminal (BET) protein BRD4 as an H2A.Z acetylation 'reader', and showed that a BRD4 inhibitor ameliorated the SCZ-associated transcriptional signature, revealing a new candidate target for treatment.
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Affiliation(s)
- Marija Kundakovic
- Department of Biological Sciences, Fordham University, Bronx, NY, USA.
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17
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Park J, Lee K, Kim K, Yi SJ. The role of histone modifications: from neurodevelopment to neurodiseases. Signal Transduct Target Ther 2022; 7:217. [PMID: 35794091 PMCID: PMC9259618 DOI: 10.1038/s41392-022-01078-9] [Citation(s) in RCA: 76] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2022] [Revised: 06/11/2022] [Accepted: 06/21/2022] [Indexed: 12/24/2022] Open
Abstract
Epigenetic regulatory mechanisms, including DNA methylation, histone modification, chromatin remodeling, and microRNA expression, play critical roles in cell differentiation and organ development through spatial and temporal gene regulation. Neurogenesis is a sophisticated and complex process by which neural stem cells differentiate into specialized brain cell types at specific times and regions of the brain. A growing body of evidence suggests that epigenetic mechanisms, such as histone modifications, allow the fine-tuning and coordination of spatiotemporal gene expressions during neurogenesis. Aberrant histone modifications contribute to the development of neurodegenerative and neuropsychiatric diseases. Herein, recent progress in understanding histone modifications in regulating embryonic and adult neurogenesis is comprehensively reviewed. The histone modifications implicated in neurodegenerative and neuropsychiatric diseases are also covered, and future directions in this area are provided.
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Affiliation(s)
- Jisu Park
- Department of Biological Sciences and Biotechnology, Chungbuk National University, Cheongju, Chungbuk, Republic of Korea
| | - Kyubin Lee
- Department of Biological Sciences and Biotechnology, Chungbuk National University, Cheongju, Chungbuk, Republic of Korea
| | - Kyunghwan Kim
- Department of Biological Sciences and Biotechnology, Chungbuk National University, Cheongju, Chungbuk, Republic of Korea.
| | - Sun-Ju Yi
- Department of Biological Sciences and Biotechnology, Chungbuk National University, Cheongju, Chungbuk, Republic of Korea.
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