1
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Bicks LK, Geschwind DH. Functional neurogenomics in autism spectrum disorders: A decade of progress. Curr Opin Neurobiol 2024; 86:102858. [PMID: 38547564 DOI: 10.1016/j.conb.2024.102858] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 02/29/2024] [Accepted: 02/29/2024] [Indexed: 06/11/2024]
Abstract
Advances in autism spectrum disorder (ASD) genetics have identified many genetic causes, reflecting remarkable progress while at the same time identifying challenges such as heterogeneity and pleiotropy, which complicate attempts to connect genetic risk to mechanisms. High-throughput functional genomic approaches have yielded progress by defining a molecular pathology in the brain of individuals with ASD and in identifying convergent biological pathways through which risk genes are predicted to act. These studies indicate that ASD genetic risk converges in early brain development, primarily during the period of cortical neurogenesis. Over development, genetic perturbations in turn lead to broad neuronal signaling dysregulation, most prominent in glutamatergic cortical-cortical projecting neurons and somatostatin positive interneurons, which is accompanied by glial dyshomeostasis throughout the cerebral cortex. Connecting these developmental perturbations to disrupted neuronal and glial function in the postnatal brain is an important direction in current research. Coupling functional genomic approaches with advances in induced pluripotent stem cell-derived neural organoid development provides a promising avenue for connecting brain pathology to developmental mechanisms.
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Affiliation(s)
- Lucy K Bicks
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, 695 Charles E. Young Drive South, Los Angeles, CA 90095, USA. https://twitter.com/Bickslucy
| | - D H Geschwind
- Program in Neurobehavioral Genetics, Center for Autism Research and Treatment, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, 695 Charles E. Young Drive South, Los Angeles, CA 90095, USA; Department of Psychiatry, Semel Institute, David Geffen School of Medicine, University of California, Los Angeles, 695 Charles E. Young Drive South, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA.
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2
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Pedicone C, Weitzman SA, Renton AE, Goate AM. Unraveling the complex role of MAPT-containing H1 and H2 haplotypes in neurodegenerative diseases. Mol Neurodegener 2024; 19:43. [PMID: 38812061 PMCID: PMC11138017 DOI: 10.1186/s13024-024-00731-x] [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: 09/30/2023] [Accepted: 05/11/2024] [Indexed: 05/31/2024] Open
Abstract
A ~ 1 Mb inversion polymorphism exists within the 17q21.31 locus of the human genome as direct (H1) and inverted (H2) haplotype clades. This inversion region demonstrates high linkage disequilibrium, but the frequency of each haplotype differs across ancestries. While the H1 haplotype exists in all populations and shows a normal pattern of genetic variability and recombination, the H2 haplotype is enriched in European ancestry populations, is less frequent in African ancestry populations, and nearly absent in East Asian ancestry populations. H1 is a known risk factor for several neurodegenerative diseases, and has been associated with many other traits, suggesting its importance in cellular phenotypes of the brain and entire body. Conversely, H2 is protective for these diseases, but is associated with predisposition to recurrent microdeletion syndromes and neurodevelopmental disorders such as autism. Many single nucleotide variants and copy number variants define H1/H2 haplotypes and sub-haplotypes, but identifying the causal variant(s) for specific diseases and phenotypes is complex due to the extended linkage equilibrium. In this review, we assess the current knowledge of this inversion region regarding genomic structure, gene expression, cellular phenotypes, and disease association. We discuss recent discoveries and challenges, evaluate gaps in knowledge, and highlight the importance of understanding the effect of the 17q21.31 haplotypes to promote advances in precision medicine and drug discovery for several diseases.
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Affiliation(s)
- Chiara Pedicone
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sarah A Weitzman
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alan E Renton
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alison M Goate
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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3
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Deng C, Whalen S, Steyert M, Ziffra R, Przytycki PF, Inoue F, Pereira DA, Capauto D, Norton S, Vaccarino FM, Pollen AA, Nowakowski TJ, Ahituv N, Pollard KS. Massively parallel characterization of regulatory elements in the developing human cortex. Science 2024; 384:eadh0559. [PMID: 38781390 DOI: 10.1126/science.adh0559] [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: 02/15/2023] [Accepted: 03/13/2024] [Indexed: 05/25/2024]
Abstract
Nucleotide changes in gene regulatory elements are important determinants of neuronal development and diseases. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 open chromatin regions, including thousands of sequences with cell type-specific accessibility and variants associated with brain gene regulation. In primary cells, we identified 46,802 active enhancer sequences and 164 variants that alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.
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Affiliation(s)
- Chengyu Deng
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Sean Whalen
- Gladstone Institutes, San Francisco, CA 94158, USA
| | - Marilyn Steyert
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94143, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA 94143, USA
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
- Chan Zuckerberg Biohub, San Francisco, San Francisco, CA 94158, USA
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
| | - Ryan Ziffra
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94143, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA 94143, USA
| | | | - Fumitaka Inoue
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto 606-8501, Japan
| | - Daniela A Pereira
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94158, USA
- Graduate Program of Genetics, Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Minas Gerais 31270-901, Brazil
| | - Davide Capauto
- Child Study Center, Yale University, New Haven, CT 06520, USA
| | - Scott Norton
- Child Study Center, Yale University, New Haven, CT 06520, USA
| | - Flora M Vaccarino
- Child Study Center, Yale University, New Haven, CT 06520, USA
- Department of Neuroscience, Yale University, New Haven, CT 06520, USA
| | - Alex A Pollen
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA 94143, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Tomasz J Nowakowski
- Department of Anatomy, University of California, San Francisco, San Francisco, CA 94143, USA
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA 94143, USA
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA 94143, USA
- Kavli Institute for Fundamental Neuroscience, University of California, San Francisco, CA 94143, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA 94158, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Katherine S Pollard
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94158, USA
- Gladstone Institutes, San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub, San Francisco, San Francisco, CA 94158, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA 94158, USA
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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. 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] [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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5
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Zeng B, Bendl J, Deng C, Lee D, Misir R, Reach SM, Kleopoulos SP, Auluck P, Marenco S, Lewis DA, Haroutunian V, Ahituv N, Fullard JF, Hoffman GE, Roussos P. Genetic regulation of cell type-specific chromatin accessibility shapes brain disease etiology. Science 2024; 384:eadh4265. [PMID: 38781378 DOI: 10.1126/science.adh4265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 12/20/2023] [Indexed: 05/25/2024]
Abstract
Nucleotide variants in cell type-specific gene regulatory elements in the human brain are risk factors for human disease. We measured chromatin accessibility in 1932 aliquots of sorted neurons and non-neurons from 616 human postmortem brains and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTLs). Only 10.4% of caQTLs are shared between neurons and non-neurons, which supports cell type-specific genetic regulation of the brain regulome. Incorporating allele-specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms that underlie disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs and identified the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides insights into disease etiology.
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Affiliation(s)
- Biao Zeng
- Center for Disease Neurogenomics, 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 Sciences, 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
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, 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 Sciences, 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
| | - Chengyu Deng
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, 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 Sciences, 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
| | - Ruth Misir
- Center for Disease Neurogenomics, 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 Sciences, 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
| | - Sarah M Reach
- Center for Disease Neurogenomics, 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 Sciences, 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
| | - Steven P Kleopoulos
- Center for Disease Neurogenomics, 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 Sciences, 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
| | - Pavan Auluck
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD 20892, USA
| | - Stefano Marenco
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD 20892, USA
| | - David A Lewis
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Vahram Haroutunian
- Department of Psychiatry, 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 Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - John F Fullard
- Center for Disease Neurogenomics, 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 Sciences, 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
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, 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 Sciences, 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
| | - Panos Roussos
- Center for Disease Neurogenomics, 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 Sciences, 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
- Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, Bronx, NY 10468, USA
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6
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Gouveia Roque C, Phatnani H, Hengst U. The broken Alzheimer's disease genome. CELL GENOMICS 2024; 4:100555. [PMID: 38697121 PMCID: PMC11099344 DOI: 10.1016/j.xgen.2024.100555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 02/25/2024] [Accepted: 04/07/2024] [Indexed: 05/04/2024]
Abstract
The complex pathobiology of late-onset Alzheimer's disease (AD) poses significant challenges to therapeutic and preventative interventions. Despite these difficulties, genomics and related disciplines are allowing fundamental mechanistic insights to emerge with clarity, particularly with the introduction of high-resolution sequencing technologies. After all, the disrupted processes at the interface between DNA and gene expression, which we call the broken AD genome, offer detailed quantitative evidence unrestrained by preconceived notions about the disease. In addition to highlighting biological pathways beyond the classical pathology hallmarks, these advances have revitalized drug discovery efforts and are driving improvements in clinical tools. We review genetic, epigenomic, and gene expression findings related to AD pathogenesis and explore how their integration enables a better understanding of the multicellular imbalances contributing to this heterogeneous condition. The frontiers opening on the back of these research milestones promise a future of AD care that is both more personalized and predictive.
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Affiliation(s)
- Cláudio Gouveia Roque
- Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY 10013, USA; The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA.
| | - Hemali Phatnani
- Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY 10013, USA; Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY 10032, USA
| | - Ulrich Hengst
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA; Department of Pathology & Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA.
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7
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He Z, Chu B, Yang J, Gu J, Chen Z, Liu L, Morrison T, Belloy ME, Qi X, Hejazi N, Mathur M, Le Guen Y, Tang H, Hastie T, Ionita-laza I, Sabatti C, Candès E. Beyond guilty by association at scale: searching for causal variants on the basis of genome-wide summary statistics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.28.582621. [PMID: 38464202 PMCID: PMC10925326 DOI: 10.1101/2024.02.28.582621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Understanding the causal genetic architecture of complex phenotypes is essential for future research into disease mechanisms and potential therapies. Here, we present a novel framework for genome-wide detection of sets of variants that carry non-redundant information on the phenotypes and are therefore more likely to be causal in a biological sense. Crucially, our framework requires only summary statistics obtained from standard genome-wide marginal association testing. The described approach, implemented in open-source software, is also computationally efficient, requiring less than 15 minutes on a single CPU to perform genome-wide analysis. Through extensive genome-wide simulation studies, we show that the method can substantially outperform usual two-stage marginal association testing and fine-mapping procedures in precision and recall. In applications to a meta-analysis of ten large-scale genetic studies of Alzheimer's disease (AD), we identified 82 loci associated with AD, including 37 additional loci missed by conventional GWAS pipeline. The identified putative causal variants achieve state-of-the-art agreement with massively parallel reporter assays and CRISPR-Cas9 experiments. Additionally, we applied the method to a retrospective analysis of 67 large-scale GWAS summary statistics since 2013 for a variety of phenotypes. Results reveal the method's capacity to robustly discover additional loci for polygenic traits and pinpoint potential causal variants underpinning each locus beyond conventional GWAS pipeline, contributing to a deeper understanding of complex genetic architectures in post-GWAS analyses.
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Affiliation(s)
- Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, 94305, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Benjamin Chu
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - James Yang
- Department of Statistics, Stanford University, Stanford, CA 94305, USA
| | - Jiaqi Gu
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Zhaomeng Chen
- Department of Statistics, Stanford University, Stanford, CA 94305, USA
| | - Linxi Liu
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Tim Morrison
- Department of Statistics, Stanford University, Stanford, CA 94305, USA
| | - Michael E. Belloy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
| | - Xinran Qi
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Nima Hejazi
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Maya Mathur
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, 94305, USA
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA
| | - Yann Le Guen
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Hua Tang
- Department of Pediatrics, Stanford University, Stanford, CA 94305, USA
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Trevor Hastie
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
- Department of Statistics, Stanford University, Stanford, CA 94305, USA
| | - Iuliana Ionita-laza
- Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - Chiara Sabatti
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
- Department of Statistics, Stanford University, Stanford, CA 94305, USA
| | - Emmanuel Candès
- Department of Statistics, Stanford University, Stanford, CA 94305, USA
- Department of Mathematics, Stanford University, Stanford, CA 94305, USA
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8
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Asanomi Y, Kimura T, Shimoda N, Shigemizu D, Niida S, Ozaki K. CRISPR/Cas9-mediated knock-in cells of the late-onset Alzheimer's disease-risk variant, SHARPIN G186R, reveal reduced NF-κB pathway and accelerated Aβ secretion. J Hum Genet 2024; 69:171-176. [PMID: 38351238 PMCID: PMC11043039 DOI: 10.1038/s10038-024-01224-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 12/27/2023] [Accepted: 01/25/2024] [Indexed: 04/26/2024]
Affiliation(s)
- Yuya Asanomi
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
| | - Tetsuaki Kimura
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
| | - Nobuyoshi Shimoda
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
| | - Daichi Shigemizu
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Shumpei Niida
- Center for Core Facility Administration, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu, Aichi, Japan.
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
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9
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Fu T, Amoah K, Chan TW, Bahn JH, Lee JH, Terrazas S, Chong R, Kosuri S, Xiao X. Massively parallel screen uncovers many rare 3' UTR variants regulating mRNA abundance of cancer driver genes. Nat Commun 2024; 15:3335. [PMID: 38637555 PMCID: PMC11026479 DOI: 10.1038/s41467-024-46795-7] [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: 05/01/2023] [Accepted: 03/06/2024] [Indexed: 04/20/2024] Open
Abstract
Understanding the function of rare non-coding variants represents a significant challenge. Using MapUTR, a screening method, we studied the function of rare 3' UTR variants affecting mRNA abundance post-transcriptionally. Among 17,301 rare gnomAD variants, an average of 24.5% were functional, with 70% in cancer-related genes, many in critical cancer pathways. This observation motivated an interrogation of 11,929 somatic mutations, uncovering 3928 (33%) functional mutations in 155 cancer driver genes. Functional MapUTR variants were enriched in microRNA- or protein-binding sites and may underlie outlier gene expression in tumors. Further, we introduce untranslated tumor mutational burden (uTMB), a metric reflecting the amount of somatic functional MapUTR variants of a tumor and show its potential in predicting patient survival. Through prime editing, we characterized three variants in cancer-relevant genes (MFN2, FOSL2, and IRAK1), demonstrating their cancer-driving potential. Our study elucidates the function of tens of thousands of non-coding variants, nominates non-coding cancer driver mutations, and demonstrates their potential contributions to cancer.
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Affiliation(s)
- Ting Fu
- Molecular, Cellular and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Kofi Amoah
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Tracey W Chan
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Jae Hoon Bahn
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Jae-Hyung Lee
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Life and Nanopharmaceutical Sciences & Oral Microbiology, School of Dentistry, Kyung Hee University, Seoul, South Korea
| | - Sari Terrazas
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Molecular Biology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Rockie Chong
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Sriram Kosuri
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Xinshu Xiao
- Molecular, Cellular and Integrative Physiology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Molecular Biology Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
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10
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Wang C, Chen C, Lei B, Qin S, Zhang Y, Li K, Zhang S, Liu Y. Constructing eRNA-mediated gene regulatory networks to explore the genetic basis of muscle and fat-relevant traits in pigs. Genet Sel Evol 2024; 56:28. [PMID: 38594607 PMCID: PMC11003151 DOI: 10.1186/s12711-024-00897-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 04/03/2024] [Indexed: 04/11/2024] Open
Abstract
BACKGROUND Enhancer RNAs (eRNAs) play a crucial role in transcriptional regulation. While significant progress has been made in understanding epigenetic regulation mediated by eRNAs, research on the construction of eRNA-mediated gene regulatory networks (eGRN) and the identification of critical network components that influence complex traits is lacking. RESULTS Here, employing the pig as a model, we conducted a comprehensive study using H3K27ac histone ChIP-seq and RNA-seq data to construct eRNA expression profiles from multiple tissues of two distinct pig breeds, namely Enshi Black (ES) and Duroc. In addition to revealing the regulatory landscape of eRNAs at the tissue level, we developed an innovative network construction and refinement method by integrating RNA-seq, ChIP-seq, genome-wide association study (GWAS) signals and enhancer-modulating effects of single nucleotide polymorphisms (SNPs) measured by self-transcribing active regulatory region sequencing (STARR-seq) experiments. Using this approach, we unraveled eGRN that significantly influence the growth and development of muscle and fat tissues, and identified several novel genes that affect adipocyte differentiation in a cell line model. CONCLUSIONS Our work not only provides novel insights into the genetic basis of economic pig traits, but also offers a generalizable approach to elucidate the eRNA-mediated transcriptional regulation underlying a wide spectrum of complex traits for diverse organisms.
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Affiliation(s)
- Chao Wang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China
| | - Choulin Chen
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China
| | - Bowen Lei
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China
| | - Shenghua Qin
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
| | - Yuanyuan Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- School of Life Sciences, Henan University, Kaifeng, 475004, People's Republic of China
- Shenzhen Research Institute of Henan University, Shenzhen, 518000, People's Republic of China
| | - Kui Li
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China
| | - Song Zhang
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
| | - Yuwen Liu
- Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Key Laboratory of Livestock and Poultry Multi-Omics of MARA, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
- Innovation Group of Pig Genome Design and Breeding, Research Centre for Animal Genome, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, 518124, People's Republic of China.
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & Key Lab of Swine Genetics and Breeding of Ministry of Agriculture and Rural Affairs, Huazhong Agricultural University, Wuhan, 430070, People's Republic of China.
- Kunpeng Institute of Modern Agriculture at Foshan, Chinese Academy of Agricultural Sciences, Foshan, 528226, People's Republic of China.
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11
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Nizomov J, Jin W, Xia Y, Liu Y, Li Z, Chen L. MPRAVarDB: an online database and web server for exploring regulatory effects of genetic variants. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.02.587790. [PMID: 38617248 PMCID: PMC11014600 DOI: 10.1101/2024.04.02.587790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Massively parallel reporter assay (MPRA) is an important technology to evaluate the impact of genetic variants on gene regulation. Here, we present MPRAVarDB, an online database and web server, for exploring regulatory effects of genetic variants. MPRAVarDB harbors 18 MPRA experiments designed to assess the regulatory effects of genetic variants associated with GWAS loci, eQTLs and various genomic features, resulting in a total of 242,818 variants tested across more than 30 cell lines and 30 human diseases or traits. MPRAVarDB empowers the query of MPRA variants by genomic region, disease and cell line or by any combination of these query terms. Notably, MPRAVarDB offers a suite of pretrained machine learning models tailored to the specific disease and cell line, facilitating the genome-wide prediction of regulatory variants. MPRAVarDB is friendly to use, and users only need a few clicks to receive query and prediction results.
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Affiliation(s)
- Javlon Nizomov
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603
| | - Weijia Jin
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603
| | - Yi Xia
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603
| | - Yunlong Liu
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202
| | - Zhigang Li
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603
| | - Li Chen
- Department of Biostatistics, University of Florida, Gainesville, FL, 32603
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12
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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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13
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Gaynor-Gillett SC, Cheng L, Shi M, Liu J, Wang G, Spector M, Flaherty M, Wall M, Hwang A, Gu M, Chen Z, Chen Y, Consortium P, Moran JR, Zhang J, Lee D, Gerstein M, Geschwind D, White KP. Validation of Enhancer Regions in Primary Human Neural Progenitor Cells using Capture STARR-seq. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.14.585066. [PMID: 38562832 PMCID: PMC10983874 DOI: 10.1101/2024.03.14.585066] [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
Genome-wide association studies (GWAS) and expression analyses implicate noncoding regulatory regions as harboring risk factors for psychiatric disease, but functional characterization of these regions remains limited. We performed capture STARR-sequencing of over 78,000 candidate regions to identify active enhancers in primary human neural progenitor cells (phNPCs). We selected candidate regions by integrating data from NPCs, prefrontal cortex, developmental timepoints, and GWAS. Over 8,000 regions demonstrated enhancer activity in the phNPCs, and we linked these regions to over 2,200 predicted target genes. These genes are involved in neuronal and psychiatric disease-associated pathways, including dopaminergic synapse, axon guidance, and schizophrenia. We functionally validated a subset of these enhancers using mutation STARR-sequencing and CRISPR deletions, demonstrating the effects of genetic variation on enhancer activity and enhancer deletion on gene expression. Overall, we identified thousands of highly active enhancers and functionally validated a subset of these enhancers, improving our understanding of regulatory networks underlying brain function and disease.
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Affiliation(s)
- Sophia C. Gaynor-Gillett
- Tempus Labs, Inc.; Chicago, IL, 60654, USA
- Department of Biology, Cornell College; Mount Vernon, IA, 52314, USA
| | | | - Manman Shi
- Tempus Labs, Inc.; Chicago, IL, 60654, USA
| | - Jason Liu
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
| | - Gaoyuan Wang
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
| | | | | | | | - Ahyeon Hwang
- Department of Computer Science, University of California Irvine; Irvine, CA, 92697, USA
| | - Mengting Gu
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
| | - Zhanlin Chen
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
| | - Yuhang Chen
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
| | | | | | - Jing Zhang
- Department of Computer Science, University of California Irvine; Irvine, CA, 92697, USA
| | - Donghoon Lee
- Department of Genetics and Genomic Sciences, 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
| | - Mark Gerstein
- Computational Biology and Bioinformatics Program, Yale University; New Haven, CT, 06511, USA
- Department of Statistics and Data Science, Yale University; New Haven, CT, 06511, USA
- Department of Molecular Biophysics and Biochemistry, Yale University; New Haven, CT, 06511, USA
- Department of Computer Science, Yale University; New Haven, CT, 06511, USA
| | - Daniel Geschwind
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles; Los Angeles, CA, 90095, USA
- Department of Psychiatry and Semel Institute, 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
| | - Kevin P. White
- Yong Loo Lin School of Medicine, National University of Singapore; Singapore, 117597
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14
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Farrow SL, Gokuladhas S, Schierding W, Pudjihartono M, Perry JK, Cooper AA, O'Sullivan JM. Identification of 27 allele-specific regulatory variants in Parkinson's disease using a massively parallel reporter assay. NPJ Parkinsons Dis 2024; 10:44. [PMID: 38413607 PMCID: PMC10899198 DOI: 10.1038/s41531-024-00659-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 02/12/2024] [Indexed: 02/29/2024] Open
Abstract
Genome wide association studies (GWAS) have identified a number of genomic loci that are associated with Parkinson's disease (PD) risk. However, the majority of these variants lie in non-coding regions, and thus the mechanisms by which they influence disease development, and/or potential subtypes, remain largely elusive. To address this, we used a massively parallel reporter assay (MPRA) to screen the regulatory function of 5254 variants that have a known or putative connection to PD. We identified 138 loci with enhancer activity, of which 27 exhibited allele-specific regulatory activity in HEK293 cells. The identified regulatory variant(s) typically did not match the original tag variant within the PD associated locus, supporting the need for deeper exploration of these loci. The existence of allele specific transcriptional impacts within HEK293 cells, confirms that at least a subset of the PD associated regions mark functional gene regulatory elements. Future functional studies that confirm the putative targets of the empirically verified regulatory variants will be crucial for gaining a greater understanding of how gene regulatory network(s) modulate PD risk.
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Affiliation(s)
- Sophie L Farrow
- Liggins Institute, The University of Auckland, Auckland, New Zealand.
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand.
| | | | - William Schierding
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
- Department of Ophthalmology, The University of Auckland, Auckland, New Zealand
| | | | - Jo K Perry
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
| | - Antony A Cooper
- Australian Parkinsons Mission, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent's Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Justin M O'Sullivan
- Liggins Institute, The University of Auckland, Auckland, New Zealand.
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand.
- Australian Parkinsons Mission, Garvan Institute of Medical Research, Sydney, NSW, Australia.
- Singapore Institute for Clinical Sciences, Agency for Science Technology and Research, Singapore, Singapore.
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom.
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15
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Rogers BB, Anderson AG, Lauzon SN, Davis MN, Hauser RM, Roberts SC, Rodriguez-Nunez I, Trausch-Lowther K, Barinaga EA, Hall PI, Knuesel MT, Taylor JW, Mackiewicz M, Roberts BS, Cooper SJ, Rizzardi LF, Myers RM, Cochran JN. Neuronal MAPT expression is mediated by long-range interactions with cis-regulatory elements. Am J Hum Genet 2024; 111:259-279. [PMID: 38232730 PMCID: PMC10870142 DOI: 10.1016/j.ajhg.2023.12.015] [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: 11/28/2023] [Revised: 12/12/2023] [Accepted: 12/12/2023] [Indexed: 01/19/2024] Open
Abstract
Tauopathies are a group of neurodegenerative diseases defined by abnormal aggregates of tau, a microtubule-associated protein encoded by MAPT. MAPT expression is near absent in neural progenitor cells (NPCs) and increases during differentiation. This temporally dynamic expression pattern suggests that MAPT expression could be controlled by transcription factors and cis-regulatory elements specific to differentiated cell types. Given the relevance of MAPT expression to neurodegeneration pathogenesis, identification of such elements is relevant to understanding disease risk and pathogenesis. Here, we performed chromatin conformation assays (HiC & Capture-C), single-nucleus multiomics (RNA-seq+ATAC-seq), bulk ATAC-seq, and ChIP-seq for H3K27ac and CTCF in NPCs and differentiated neurons to nominate candidate cis-regulatory elements (cCREs). We assayed these cCREs using luciferase assays and CRISPR interference (CRISPRi) experiments to measure their effects on MAPT expression. Finally, we integrated cCRE annotations into an analysis of genetic variation in neurodegeneration-affected individuals and control subjects. We identified both proximal and distal regulatory elements for MAPT and confirmed the regulatory function for several regions, including three regions centromeric to MAPT beyond the H1/H2 haplotype inversion breakpoint. We also found that rare and predicted damaging genetic variation in nominated CREs was nominally depleted in dementia-affected individuals relative to control subjects, consistent with the hypothesis that variants that disrupt MAPT enhancer activity, and thereby reduced MAPT expression, may be protective against neurodegenerative disease. Overall, this study provides compelling evidence for pursuing detailed knowledge of CREs for genes of interest to permit better understanding of disease risk.
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Affiliation(s)
- Brianne B Rogers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA; University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | | | - Shelby N Lauzon
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - M Natalie Davis
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Rebecca M Hauser
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Sydney C Roberts
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | | | | | - Erin A Barinaga
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Paige I Hall
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | | | - Jared W Taylor
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Mark Mackiewicz
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Brian S Roberts
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Sara J Cooper
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | | | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA.
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16
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Wang H, Chang TS, Dombroski BA, Cheng PL, Patil V, Valiente-Banuet L, Farrell K, Mclean C, Molina-Porcel L, Rajput A, De Deyn PP, Bastard NL, Gearing M, Kaat LD, Swieten JCV, Dopper E, Ghetti BF, Newell KL, Troakes C, de Yébenes JG, Rábano-Gutierrez A, Meller T, Oertel WH, Respondek G, Stamelou M, Arzberger T, Roeber S, Müller U, Hopfner F, Pastor P, Brice A, Durr A, Ber IL, Beach TG, Serrano GE, Hazrati LN, Litvan I, Rademakers R, Ross OA, Galasko D, Boxer AL, Miller BL, Seeley WW, Deerlin VMV, Lee EB, White CL, Morris H, de Silva R, Crary JF, Goate AM, Friedman JS, Leung YY, Coppola G, Naj AC, Wang LS, Dickson DW, Höglinger GU, Schellenberg GD, Geschwind DH, Lee WP. Whole-Genome Sequencing Analysis Reveals New Susceptibility Loci and Structural Variants Associated with Progressive Supranuclear Palsy. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.12.28.23300612. [PMID: 38234807 PMCID: PMC10793533 DOI: 10.1101/2023.12.28.23300612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Background Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs). Method In this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed. Results Our analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73×10-3) in PSP. Conclusions Through WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions.
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Affiliation(s)
- Hui Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy S Chang
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Beth A Dombroski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Po-Liang Cheng
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Vishakha Patil
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Leopoldo Valiente-Banuet
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kurt Farrell
- Department of Pathology, Department of Artificial Intelligence & Human Health, Nash Family, Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain, Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Catriona Mclean
- Victorian Brain Bank, The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Laura Molina-Porcel
- Alzheimer's disease and other cognitive disorders unit. Neurology Service, Hospital Clínic, Fundació Recerca Clínic Barcelona (FRCB). Institut d'Investigacions Biomediques August Pi I Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
- Neurological Tissue Bank of the Biobanc-Hospital Clínic-IDIBAPS, Barcelona, Spain
| | - Alex Rajput
- Movement Disorders Program, Division of Neurology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Peter Paul De Deyn
- Laboratory of Neurochemistry and Behavior, Experimental Neurobiology Unit, University of Antwerp, Wilrijk (Antwerp), Belgium
- Department of Neurology, University Medical Center Groningen, NL-9713 AV Groningen, Netherlands
| | | | - Marla Gearing
- Department of Pathology and Laboratory Medicine and Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | | | | | - Elise Dopper
- Netherlands Brain Bank and Erasmus University, Netherlands
| | - Bernardino F Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kathy L Newell
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Claire Troakes
- London Neurodegenerative Diseases Brain Bank, King's College London, London, UK
| | | | - Alberto Rábano-Gutierrez
- Fundación CIEN (Centro de Investigación de Enfermedades Neurológicas) - Centro Alzheimer Fundación Reina Sofía, Madrid, Spain
| | - Tina Meller
- Department of Neurology, Philipps-Universität, Marburg, Germany
| | | | - Gesine Respondek
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Maria Stamelou
- Parkinson's disease and Movement Disorders Department, HYGEIA Hospital, Athens, Greece
- European University of Cyprus, Nicosia, Cyprus
| | - Thomas Arzberger
- Department of Psychiatry and Psychotherapy, University Hospital Munich, Ludwig-Maximilians-University Munich, Germany
- Center for Neuropathology and Prion Research, Ludwig-Maximilians-University Munich, Germany
| | | | | | - Franziska Hopfner
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pau Pastor
- Unit of Neurodegenerative diseases, Department of Neurology, University Hospital Germans Trias i Pujol, Badalona, Barcelona, Spain
- Neurosciences, The Germans Trias i Pujol Research Institute (IGTP) Badalona, Badalona, Spain
| | - Alexis Brice
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Isabelle Le Ber
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | | | | | | | - Irene Litvan
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Rosa Rademakers
- VIB Center for Molecular Neurology, University of Antwerp, Belgium
- Department of Neuroscience, Mayo Clinic Jacksonville, FL, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic Jacksonville, FL, USA
| | - Douglas Galasko
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Adam L Boxer
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Willian W Seeley
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Vivanna M Van Deerlin
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Charles L White
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Huw Morris
- Departmento of Clinical and Movement Neuroscience, University College of London, London, UK
| | - Rohan de Silva
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London, UK
| | - John F Crary
- Department of Pathology, Department of Artificial Intelligence & Human Health, Nash Family, Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain, Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alison M Goate
- Department of Genetics and Genomic Sciences, New York, NY, USA; Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jeffrey S Friedman
- Friedman Bioventure, Inc., Del Mar, CA, USA; Department of Genetics and Genomic Sciences, New York, NY, USA
| | - Yuk Yee Leung
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Giovanni Coppola
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Adam C Naj
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Günter U Höglinger
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität (LMU) München; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; and Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel H Geschwind
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Wan-Ping Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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17
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Liu SJ, Casey-Clyde T, Cho NW, Swinderman J, Pekmezci M, Dougherty MC, Foster K, Chen WC, Villanueva-Meyer JE, Swaney DL, Vasudevan HN, Choudhury A, Pak J, Breshears JD, Lang UE, Eaton CD, Hiam-Galvez KJ, Stevenson E, Chen KH, Lien BV, Wu D, Braunstein SE, Sneed PK, Magill ST, Lim D, McDermott MW, Berger MS, Perry A, Krogan NJ, Hansen MR, Spitzer MH, Gilbert L, Theodosopoulos PV, Raleigh DR. Epigenetic reprogramming shapes the cellular landscape of schwannoma. Nat Commun 2024; 15:476. [PMID: 38216587 PMCID: PMC10786948 DOI: 10.1038/s41467-023-40408-5] [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: 02/06/2023] [Accepted: 05/25/2023] [Indexed: 01/14/2024] Open
Abstract
Mechanisms specifying cancer cell states and response to therapy are incompletely understood. Here we show epigenetic reprogramming shapes the cellular landscape of schwannomas, the most common tumors of the peripheral nervous system. We find schwannomas are comprised of 2 molecular groups that are distinguished by activation of neural crest or nerve injury pathways that specify tumor cell states and the architecture of the tumor immune microenvironment. Moreover, we find radiotherapy is sufficient for interconversion of neural crest schwannomas to immune-enriched schwannomas through epigenetic and metabolic reprogramming. To define mechanisms underlying schwannoma groups, we develop a technique for simultaneous interrogation of chromatin accessibility and gene expression coupled with genetic and therapeutic perturbations in single-nuclei. Our results elucidate a framework for understanding epigenetic drivers of tumor evolution and establish a paradigm of epigenetic and metabolic reprograming of cancer cells that shapes the immune microenvironment in response to radiotherapy.
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Affiliation(s)
- S John Liu
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
- Arc Institute, Palo Alto, CA, 94304, USA
| | - Tim Casey-Clyde
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Nam Woo Cho
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA
- Parker Institute for Cancer Immunotherapy, Chan Zuckerberg Biohub, and Departments of Otolaryngology, and Microbiology and Immunology, University of California San Francisco, San Francisco, CA, 94115, USA
| | - Jason Swinderman
- Arc Institute, Palo Alto, CA, 94304, USA
- Department of Urology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Melike Pekmezci
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Mark C Dougherty
- Departments of Otolaryngology and Neurosurgery, University of Iowa, Iowa City, IA, 52242, USA
| | - Kyla Foster
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - William C Chen
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Danielle L Swaney
- J. David Gladstone Institutes, California Institute for Quantitative Biosciences, Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Harish N Vasudevan
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Abrar Choudhury
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Joanna Pak
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
- Arc Institute, Palo Alto, CA, 94304, USA
| | - Jonathan D Breshears
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Ursula E Lang
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Dermatology, University of California San Francisco, San Francisco, CA, 94115, USA
| | - Charlotte D Eaton
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Kamir J Hiam-Galvez
- Parker Institute for Cancer Immunotherapy, Chan Zuckerberg Biohub, and Departments of Otolaryngology, and Microbiology and Immunology, University of California San Francisco, San Francisco, CA, 94115, USA
| | - Erica Stevenson
- J. David Gladstone Institutes, California Institute for Quantitative Biosciences, Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Kuei-Ho Chen
- J. David Gladstone Institutes, California Institute for Quantitative Biosciences, Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Brian V Lien
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
| | - David Wu
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Steve E Braunstein
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Penny K Sneed
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Stephen T Magill
- Department of Neurological Surgery, Northwestern University, Chicago, IL, 60611, USA
| | - Daniel Lim
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
| | | | - Mitchel S Berger
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Arie Perry
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Nevan J Krogan
- J. David Gladstone Institutes, California Institute for Quantitative Biosciences, Department of Cellular and Molecular Pharmacology, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Marlan R Hansen
- Departments of Otolaryngology and Neurosurgery, University of Iowa, Iowa City, IA, 52242, USA
| | - Matthew H Spitzer
- Parker Institute for Cancer Immunotherapy, Chan Zuckerberg Biohub, and Departments of Otolaryngology, and Microbiology and Immunology, University of California San Francisco, San Francisco, CA, 94115, USA
| | - Luke Gilbert
- Arc Institute, Palo Alto, CA, 94304, USA
- Department of Urology, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Philip V Theodosopoulos
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA
| | - David R Raleigh
- Department of Radiation Oncology, University of California San Francisco, San Francisco, CA, 94143, USA.
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, 94143, USA.
- Department of Pathology, University of California San Francisco, San Francisco, CA, 94143, USA.
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18
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Wu Z, Dong L, Tian Z, Yu C, Shu Q, Chen W, Li H. Integrative Analysis of the Age-Related Dysregulated Genes Reveals an Inflammation and Immunity-Associated Regulatory Network in Alzheimer's Disease. Mol Neurobiol 2024:10.1007/s12035-023-03900-z. [PMID: 38190023 DOI: 10.1007/s12035-023-03900-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2023] [Accepted: 12/11/2023] [Indexed: 01/09/2024]
Abstract
Alzheimer's disease (AD) is a neurodegenerative disease with a long incubation period. While extensive research has led to the construction of long non-coding RNA (lncRNA)-associated competing endogenous RNA (ceRNA) regulatory networks, which primarily derived from differential analyses between clinical AD patients and control individuals or mice, there remains a critical knowledge gap pertaining to the dynamic alterations in transcript expression profiles that occur with age, spanning from the pre-symptomatic stage to the onset of AD. In the present study, we examined the transcriptomic changes in AD model mice at three distinct stages: the unaffected (un-) stage, the pre-onset stage, and the late-onset stage, and identified 14, 57, and 99 differentially expressed mRNAs (DEmRs) in AD model mice at 3, 6, and 12 months, respectively. Among these, we pinpointed 16 mRNAs closely associated with inflammation and immunity and excavated their lncRNA-mRNA regulatory network based on a comprehensive analysis. Notably, our preliminary analysis suggested that four lncRNAs (NONMMUT102943, ENSMUST00000160309, NONMMUT083044, and NONMMUT126468), eight miRNAs (miR-34a-5p, miR-22-5p, miR-302a/b-3p, miR-340-5p, miR-376a/b-5p, and miR-487b-5p), and four mRNAs (C1qa, Cd68, Ctss, and Slc11a1) may play pivotal roles in orchestrating immune and inflammatory responses during the early stages of AD. Our study has unveiled age-related AD risk genes, and provided an analytical framework for constructing lncRNA-mRNA networks using time series data and correlation analysis. Most notably, we have successfully constructed a comprehensive regulatory ceRNA network comprising genes intricately linked to inflammatory and immune functions in AD.
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Affiliation(s)
- Zhuoze Wu
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Lei Dong
- School of Medical Imaging, North Sichuan Medical College, Nanchong, 637100, China
| | - Zhixiao Tian
- School of Medical Imaging, North Sichuan Medical College, Nanchong, 637100, China
| | - Chenhui Yu
- School of Medical Imaging, North Sichuan Medical College, Nanchong, 637100, China
| | - Qingrong Shu
- School of Medical Imaging, North Sichuan Medical College, Nanchong, 637100, China
| | - Wei Chen
- Institute of Basic Medicine and Forensic Medicine, North Sichuan Medical College, Nanchong, 637100, China
| | - Hao Li
- Department of Pathophysiology, School of Basic Medicine and Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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19
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Fair T, Pavlovic BJ, Schaefer NK, Pollen AA. Mapping cis- and trans-regulatory target genes of human-specific deletions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.27.573461. [PMID: 38234800 PMCID: PMC10793408 DOI: 10.1101/2023.12.27.573461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Deletion of functional sequence is predicted to represent a fundamental mechanism of molecular evolution1,2. Comparative genetic studies of primates2,3 have identified thousands of human-specific deletions (hDels), and the cis-regulatory potential of short (≤31 base pairs) hDels has been assessed using reporter assays4. However, how structural variant-sized (≥50 base pairs) hDels influence molecular and cellular processes in their native genomic contexts remains unexplored. Here, we design genome-scale libraries of single-guide RNAs targeting 7.2 megabases of sequence in 6,358 hDels and present a systematic CRISPR interference (CRISPRi) screening approach to identify hDels that modify cellular proliferation in chimpanzee pluripotent stem cells. By intersecting hDels with chromatin state features and performing single-cell CRISPRi (Perturb-seq) to identify their cis- and trans-regulatory target genes, we discovered 19 hDels controlling gene expression. We highlight two hDels, hDel_2247 and hDel_585, with tissue-specific activity in the liver and brain, respectively. Our findings reveal a molecular and cellular role for sequences lost in the human lineage and establish a framework for functionally interrogating human-specific genetic variants.
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Affiliation(s)
- Tyler Fair
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Bryan J Pavlovic
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Nathan K Schaefer
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
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20
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Humphrey J, Brophy E, Kosoy R, Zeng B, Coccia E, Mattei D, Ravi A, Efthymiou AG, Navarro E, Muller BZ, Snijders GJLJ, Allan A, Münch A, Kitata RB, Kleopoulos SP, Argyriou S, Shao Z, Francoeur N, Tsai CF, Gritsenko MA, Monroe ME, Paurus VL, Weitz KK, Shi T, Sebra R, Liu T, de Witte LD, Goate AM, Bennett DA, Haroutunian V, Hoffman GE, Fullard JF, Roussos P, Raj T. Long-read RNA-seq atlas of novel microglia isoforms elucidates disease-associated genetic regulation of splicing. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.01.23299073. [PMID: 38076956 PMCID: PMC10705658 DOI: 10.1101/2023.12.01.23299073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Microglia, the innate immune cells of the central nervous system, have been genetically implicated in multiple neurodegenerative diseases. We previously mapped the genetic regulation of gene expression and mRNA splicing in human microglia, identifying several loci where common genetic variants in microglia-specific regulatory elements explain disease risk loci identified by GWAS. However, identifying genetic effects on splicing has been challenging due to the use of short sequencing reads to identify causal isoforms. Here we present the isoform-centric microglia genomic atlas (isoMiGA) which leverages the power of long-read RNA-seq to identify 35,879 novel microglia isoforms. We show that the novel microglia isoforms are involved in stimulation response and brain region specificity. We then quantified the expression of both known and novel isoforms in a multi-ethnic meta-analysis of 555 human microglia short-read RNA-seq samples from 391 donors, the largest to date, and found associations with genetic risk loci in Alzheimer's disease and Parkinson's disease. We nominate several loci that may act through complex changes in isoform and splice site usage.
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Affiliation(s)
- Jack Humphrey
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Erica Brophy
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Roman Kosoy
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Biao Zeng
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Elena Coccia
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daniele Mattei
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ashvin Ravi
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Anastasia G. Efthymiou
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Elisa Navarro
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Biochemistry and Molecular Biology, Faculty of Medicine (Universidad Complutense de Madrid), Madrid, Spain
- Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
- Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), Madrid, Spain
| | - Benjamin Z. Muller
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gijsje JLJ Snijders
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Amanda Allan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alexandra Münch
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Reta Birhanu Kitata
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Steven P Kleopoulos
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Stathis Argyriou
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Zhiping Shao
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Nancy Francoeur
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Chia-Feng Tsai
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Marina A Gritsenko
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Matthew E Monroe
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Vanessa L Paurus
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Karl K Weitz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Tujin Shi
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Robert Sebra
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Tao Liu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA
| | - Lot D. de Witte
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Alison M. Goate
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Vahram Haroutunian
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA
| | - Gabriel E. Hoffman
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - John F. Fullard
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Panos Roussos
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, USA
- Mental Illness Research Education, and Clinical Center (VISN 2 South), James J. Peters VA Medical Center, Bronx, NY, USA
| | - Towfique Raj
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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21
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Vuic B, Milos T, Tudor L, Nikolac Perkovic M, Konjevod M, Nedic Erjavec G, Farkas V, Uzun S, Mimica N, Svob Strac D. Pharmacogenomics of Dementia: Personalizing the Treatment of Cognitive and Neuropsychiatric Symptoms. Genes (Basel) 2023; 14:2048. [PMID: 38002991 PMCID: PMC10671071 DOI: 10.3390/genes14112048] [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: 10/10/2023] [Revised: 10/30/2023] [Accepted: 11/02/2023] [Indexed: 11/26/2023] Open
Abstract
Dementia is a syndrome of global and progressive deterioration of cognitive skills, especially memory, learning, abstract thinking, and orientation, usually affecting the elderly. The most common forms are Alzheimer's disease, vascular dementia, and other (frontotemporal, Lewy body disease) dementias. The etiology of these multifactorial disorders involves complex interactions of various environmental and (epi)genetic factors and requires multiple forms of pharmacological intervention, including anti-dementia drugs for cognitive impairment, antidepressants, antipsychotics, anxiolytics and sedatives for behavioral and psychological symptoms of dementia, and other drugs for comorbid disorders. The pharmacotherapy of dementia patients has been characterized by a significant interindividual variability in drug response and the development of adverse drug effects. The therapeutic response to currently available drugs is partially effective in only some individuals, with side effects, drug interactions, intolerance, and non-compliance occurring in the majority of dementia patients. Therefore, understanding the genetic basis of a patient's response to pharmacotherapy might help clinicians select the most effective treatment for dementia while minimizing the likelihood of adverse reactions and drug interactions. Recent advances in pharmacogenomics may contribute to the individualization and optimization of dementia pharmacotherapy by increasing its efficacy and safety via a prediction of clinical outcomes. Thus, it can significantly improve the quality of life in dementia patients.
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Affiliation(s)
- Barbara Vuic
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (B.V.); (T.M.); (L.T.); (M.N.P.); (M.K.); (G.N.E.); (V.F.)
| | - Tina Milos
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (B.V.); (T.M.); (L.T.); (M.N.P.); (M.K.); (G.N.E.); (V.F.)
| | - Lucija Tudor
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (B.V.); (T.M.); (L.T.); (M.N.P.); (M.K.); (G.N.E.); (V.F.)
| | - Matea Nikolac Perkovic
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (B.V.); (T.M.); (L.T.); (M.N.P.); (M.K.); (G.N.E.); (V.F.)
| | - Marcela Konjevod
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (B.V.); (T.M.); (L.T.); (M.N.P.); (M.K.); (G.N.E.); (V.F.)
| | - Gordana Nedic Erjavec
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (B.V.); (T.M.); (L.T.); (M.N.P.); (M.K.); (G.N.E.); (V.F.)
| | - Vladimir Farkas
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (B.V.); (T.M.); (L.T.); (M.N.P.); (M.K.); (G.N.E.); (V.F.)
| | - Suzana Uzun
- Department for Biological Psychiatry and Psychogeriatry, University Hospital Vrapce, 10000 Zagreb, Croatia; (S.U.); (N.M.)
- School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
| | - Ninoslav Mimica
- Department for Biological Psychiatry and Psychogeriatry, University Hospital Vrapce, 10000 Zagreb, Croatia; (S.U.); (N.M.)
- School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
| | - Dubravka Svob Strac
- Laboratory for Molecular Neuropsychiatry, Division of Molecular Medicine, Rudjer Boskovic Institute, 10000 Zagreb, Croatia; (B.V.); (T.M.); (L.T.); (M.N.P.); (M.K.); (G.N.E.); (V.F.)
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22
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Min Y, Wang X, İş Ö, Patel TA, Gao J, Reddy JS, Quicksall ZS, Nguyen T, Lin S, Tutor-New FQ, Chalk JL, Mitchell AO, Crook JE, Nelson PT, Van Eldik LJ, Golde TE, Carrasquillo MM, Dickson DW, Zhang K, Allen M, Ertekin-Taner N. Cross species systems biology discovers glial DDR2, STOM, and KANK2 as therapeutic targets in progressive supranuclear palsy. Nat Commun 2023; 14:6801. [PMID: 37919278 PMCID: PMC10622416 DOI: 10.1038/s41467-023-42626-3] [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: 12/07/2022] [Accepted: 10/17/2023] [Indexed: 11/04/2023] Open
Abstract
Progressive supranuclear palsy (PSP) is a neurodegenerative parkinsonian disorder characterized by cell-type-specific tau lesions in neurons and glia. Prior work uncovered transcriptome changes in human PSP brains, although their cell-specificity is unknown. Further, systematic data integration and experimental validation platforms to prioritize brain transcriptional perturbations as therapeutic targets in PSP are currently lacking. In this study, we combine bulk tissue (n = 408) and single nucleus RNAseq (n = 34) data from PSP and control brains with transcriptome data from a mouse tauopathy and experimental validations in Drosophila tau models for systematic discovery of high-confidence expression changes in PSP with therapeutic potential. We discover, replicate, and annotate thousands of differentially expressed genes in PSP, many of which reside in glia-enriched co-expression modules and cells. We prioritize DDR2, STOM, and KANK2 as promising therapeutic targets in PSP with striking cross-species validations. We share our findings and data via our interactive application tool PSP RNAseq Atlas ( https://rtools.mayo.edu/PSP_RNAseq_Atlas/ ). Our findings reveal robust glial transcriptome changes in PSP, provide a cross-species systems biology approach, and a tool for therapeutic target discoveries in PSP with potential application in other neurodegenerative diseases.
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Affiliation(s)
- Yuhao Min
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Center for Clinical and Translational Science, Mayo Clinic, Rochester, MN, USA
- Mayo Clinic Graduate School of Biomedical Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Xue Wang
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Özkan İş
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Tulsi A Patel
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Junli Gao
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Joseph S Reddy
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Zachary S Quicksall
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Thuy Nguyen
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Shu Lin
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | - Jessica L Chalk
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | - Julia E Crook
- Center for Clinical and Translational Science, Mayo Clinic, Rochester, MN, USA
| | - Peter T Nelson
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA
- Department of Pathology & Laboratory Medicine, University of Kentucky, Lexington, KY, USA
| | - Linda J Van Eldik
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY, USA
- Department of Neuroscience, University of Kentucky, Lexington, KY, USA
| | - Todd E Golde
- Department of Pharmacology and Chemical Biology, Department of Neurology, Emory Center for Neurodegenerative Disease, Emory University, Atlanta, GA, USA
| | | | | | - Ke Zhang
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Mariet Allen
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA.
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA.
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23
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Krainc D, Martin WJ, Casey B, Jensen FE, Tishkoff S, Potter WZ, Hyman SE. Shifting the trajectory of therapeutic development for neurological and psychiatric disorders. Sci Transl Med 2023; 15:eadg4775. [PMID: 38190501 DOI: 10.1126/scitranslmed.adg4775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Accepted: 10/13/2023] [Indexed: 01/10/2024]
Abstract
Clinical trials for central nervous system disorders often enroll patients with unrecognized heterogeneous diseases, leading to costly trials that have high failure rates. Here, we discuss the potential of emerging technologies and datasets to elucidate disease mechanisms and identify biomarkers to improve patient stratification and monitoring of disease progression in clinical trials for neuropsychiatric disorders. Greater efforts must be centered on rigorously standardizing data collection and sharing of methods, datasets, and analytical tools across sectors. To address health care disparities in clinical trials, diversity of genetic ancestries and environmental exposures of research participants and associated biological samples must be prioritized.
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Affiliation(s)
- Dimitri Krainc
- Davee Department of Neurology, Simpson Querrey Center for Neurogenetics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | - Bradford Casey
- Michael J. Fox Foundation for Parkinson's Research, New York, NY, USA
| | - Frances E Jensen
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sarah Tishkoff
- Departments of Genetics and Biology, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Steven E Hyman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
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24
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Xu M, Liu Q, Bi R, Li Y, Li H, Kang WB, Yan Z, Zheng Q, Sun C, Ye M, Xiang BL, Luo XJ, Li M, Zhang DF, Yao YG. Coexistence of Multiple Functional Variants and Genes Underlies Genetic Risk Locus 11p11.2 of Alzheimer's Disease. Biol Psychiatry 2023; 94:743-759. [PMID: 37290560 DOI: 10.1016/j.biopsych.2023.05.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 05/25/2023] [Accepted: 05/26/2023] [Indexed: 06/10/2023]
Abstract
BACKGROUND Genome-wide association studies have identified dozens of genetic risk loci for Alzheimer's disease (AD), yet the underlying causal variants and biological mechanisms remain elusive, especially for loci with complex linkage disequilibrium and regulation. METHODS To fully untangle the causal signal at a single locus, we performed a functional genomic study of 11p11.2 (the CELF1/SPI1 locus). Genome-wide association study signals at 11p11.2 were integrated with datasets of histone modification, open chromatin, and transcription factor binding to distill potentially functional variants (fVars). Their allelic regulatory activities were confirmed by allele imbalance, reporter assays, and base editing. Expressional quantitative trait loci and chromatin interaction data were incorporated to assign target genes to fVars. The relevance of these genes to AD was assessed by convergent functional genomics using bulk brain and single-cell transcriptomic, epigenomic, and proteomic datasets of patients with AD and control individuals, followed by cellular assays. RESULTS We found that 24 potential fVars, rather than a single variant, were responsible for the risk of 11p11.2. These fVars modulated transcription factor binding and regulated multiple genes by long-range chromatin interactions. Besides SPI1, convergent evidence indicated that 6 target genes (MTCH2, ACP2, NDUFS3, PSMC3, C1QTNF4, and MADD) of fVars were likely to be involved in AD development. Disruption of each gene led to cellular amyloid-β and phosphorylated tau changes, supporting the existence of multiple likely causal genes at 11p11.2. CONCLUSIONS Multiple variants and genes at 11p11.2 may contribute to AD risk. This finding provides new insights into the mechanistic and therapeutic challenges of AD.
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Affiliation(s)
- Min Xu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Qianjin Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Rui Bi
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China; National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Yu Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Hongli Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Wei-Bo Kang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Zhongjiang Yan
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Quanzhen Zheng
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Chunli Sun
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Maosen Ye
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Bo-Lin Xiang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Xiong-Jian Luo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Deng-Feng Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China; National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
| | - Yong-Gang Yao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China; National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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25
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McAfee JC, Lee S, Lee J, Bell JL, Krupa O, Davis J, Insigne K, Bond ML, Zhao N, Boyle AP, Phanstiel DH, Love MI, Stein JL, Ruzicka WB, Davila-Velderrain J, Kosuri S, Won H. Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants. CELL GENOMICS 2023; 3:100404. [PMID: 37868037 PMCID: PMC10589626 DOI: 10.1016/j.xgen.2023.100404] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 02/23/2023] [Accepted: 08/21/2023] [Indexed: 10/24/2023]
Abstract
Genome-wide association studies (GWASs) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium makes it challenging to discern causal variants. We performed a massively parallel reporter assay (MPRA) on 5,173 fine-mapped schizophrenia GWAS variants in primary human neural progenitors and identified 439 variants with allelic regulatory effects (MPRA-positive variants). Transcription factor binding had modest predictive power, while fine-map posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit expressive quantitative trait loci signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. To predict the combinatorial effect of MPRA-positive variants on gene regulation, we propose an accessibility-by-contact model that combines MPRA-measured allelic activity with neuronal chromatin architecture.
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Affiliation(s)
- Jessica C. McAfee
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Sool Lee
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jiseok Lee
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jessica L. Bell
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Oleh Krupa
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jessica Davis
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- UCLA-DOE Institute for Genomics and Proteomics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Quantitative and Computational Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Kimberly Insigne
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- UCLA-DOE Institute for Genomics and Proteomics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Quantitative and Computational Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Marielle L. Bond
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Nanxiang Zhao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Alan P. Boyle
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Douglas H. Phanstiel
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Michael I. Love
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason L. Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - W. Brad Ruzicka
- Laboratory for Epigenomics in Human Psychopathology, McLean Hospital, Belmont, MA 02141, USA
- Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Sriram Kosuri
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- UCLA-DOE Institute for Genomics and Proteomics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Quantitative and Computational Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Rexach JE, Cheng Y, Chen L, Polioudakis D, Lin LC, Mitri V, Elkins A, Yin A, Calini D, Kawaguchi R, Ou J, Huang J, Williams C, Robinson J, Gaus SE, Spina S, Lee EB, Grinberg LT, Vinters H, Trojanowski JQ, Seeley WW, Malhotra D, Geschwind DH. Disease-specific selective vulnerability and neuroimmune pathways in dementia revealed by single cell genomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.29.560245. [PMID: 37808727 PMCID: PMC10557766 DOI: 10.1101/2023.09.29.560245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
The development of successful therapeutics for dementias requires an understanding of their shared and distinct molecular features in the human brain. We performed single-nuclear RNAseq and ATACseq in Alzheimer disease (AD), Frontotemporal degeneration (FTD), and Progressive Supranuclear Palsy (PSP), analyzing 40 participants, yielding over 1.4M cells from three brain regions ranging in vulnerability and pathological burden. We identify 35 shared disease-associated cell types and 14 that are disease-specific, replicating those previously identified in AD. Disease - specific cell states represent molecular features of disease-specific glial-immune mechanisms and neuronal vulnerability in each disorder, layer 4/5 intra-telencephalic neurons in AD, layer 2/3 intra-telencephalic neurons in FTD, and layer 5/6 near-projection neurons in PSP. We infer intrinsic disease-associated gene regulatory networks, which we empirically validate by chromatin footprinting. We find that causal genetic risk acts in specific neuronal and glial cells that differ across disorders, primarily non-neuronal cells in AD and specific neuronal subtypes in FTD and PSP. These data illustrate the heterogeneous spectrum of glial and neuronal composition and gene expression alterations in different dementias and identify new therapeutic targets by revealing shared and disease-specific cell states.
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Oliveros W, Delfosse K, Lato DF, Kiriakopulos K, Mokhtaridoost M, Said A, McMurray BJ, Browning JW, Mattioli K, Meng G, Ellis J, Mital S, Melé M, Maass PG. Systematic characterization of regulatory variants of blood pressure genes. CELL GENOMICS 2023; 3:100330. [PMID: 37492106 PMCID: PMC10363820 DOI: 10.1016/j.xgen.2023.100330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 03/29/2023] [Accepted: 04/28/2023] [Indexed: 07/27/2023]
Abstract
High blood pressure (BP) is the major risk factor for cardiovascular disease. Genome-wide association studies have identified genetic variants for BP, but functional insights into causality and related molecular mechanisms lag behind. We functionally characterize 4,608 genetic variants in linkage with 135 BP loci in vascular smooth muscle cells and cardiomyocytes by massively parallel reporter assays. High densities of regulatory variants at BP loci (i.e., ULK4, MAP4, CFDP1, PDE5A) indicate that multiple variants drive genetic association. Regulatory variants are enriched in repeats, alter cardiovascular-related transcription factor motifs, and spatially converge with genes controlling specific cardiovascular pathways. Using heuristic scoring, we define likely causal variants, and CRISPR prime editing finally determines causal variants for KCNK9, SFXN2, and PCGF6, which are candidates for developing high BP. Our systems-level approach provides a catalog of functionally relevant variants and their genomic architecture in two trait-relevant cell lines for a better understanding of BP gene regulation.
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Affiliation(s)
- Winona Oliveros
- Life Sciences Department, Barcelona Supercomputing Center, 08034 Barcelona, Catalonia, Spain
| | - Kate Delfosse
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Daniella F. Lato
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Katerina Kiriakopulos
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Milad Mokhtaridoost
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Abdelrahman Said
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Brandon J. McMurray
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - Jared W.L. Browning
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Kaia Mattioli
- Division of Genetics, Department of Medicine, Brigham & Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Guoliang Meng
- Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
| | - James Ellis
- Developmental and Stem Cell Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
| | - Seema Mital
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Ted Rogers Centre for Heart Research, Toronto, ON M5G 1X8, Canada
- Department of Pediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON M5G 0A4, Canada
| | - Marta Melé
- Life Sciences Department, Barcelona Supercomputing Center, 08034 Barcelona, Catalonia, Spain
| | - Philipp G. Maass
- Genetics & Genome Biology Program, The Hospital for Sick Children, Toronto, ON M5G 0A4, Canada
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
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Molloy CJ, Cooke J, Gatford NJF, Rivera-Olvera A, Avazzadeh S, Homberg JR, Grandjean J, Fernandes C, Shen S, Loth E, Srivastava DP, Gallagher L. Bridging the translational gap: what can synaptopathies tell us about autism? Front Mol Neurosci 2023; 16:1191323. [PMID: 37441676 PMCID: PMC10333541 DOI: 10.3389/fnmol.2023.1191323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 05/24/2023] [Indexed: 07/15/2023] Open
Abstract
Multiple molecular pathways and cellular processes have been implicated in the neurobiology of autism and other neurodevelopmental conditions. There is a current focus on synaptic gene conditions, or synaptopathies, which refer to clinical conditions associated with rare genetic variants disrupting genes involved in synaptic biology. Synaptopathies are commonly associated with autism and developmental delay and may be associated with a range of other neuropsychiatric outcomes. Altered synaptic biology is suggested by both preclinical and clinical studies in autism based on evidence of differences in early brain structural development and altered glutamatergic and GABAergic neurotransmission potentially perturbing excitatory and inhibitory balance. This review focusses on the NRXN-NLGN-SHANK pathway, which is implicated in the synaptic assembly, trans-synaptic signalling, and synaptic functioning. We provide an overview of the insights from preclinical molecular studies of the pathway. Concentrating on NRXN1 deletion and SHANK3 mutations, we discuss emerging understanding of cellular processes and electrophysiology from induced pluripotent stem cells (iPSC) models derived from individuals with synaptopathies, neuroimaging and behavioural findings in animal models of Nrxn1 and Shank3 synaptic gene conditions, and key findings regarding autism features, brain and behavioural phenotypes from human clinical studies of synaptopathies. The identification of molecular-based biomarkers from preclinical models aims to advance the development of targeted therapeutic treatments. However, it remains challenging to translate preclinical animal models and iPSC studies to interpret human brain development and autism features. We discuss the existing challenges in preclinical and clinical synaptopathy research, and potential solutions to align methodologies across preclinical and clinical research. Bridging the translational gap between preclinical and clinical studies will be necessary to understand biological mechanisms, to identify targeted therapies, and ultimately to progress towards personalised approaches for complex neurodevelopmental conditions such as autism.
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Affiliation(s)
- Ciara J. Molloy
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
| | - Jennifer Cooke
- Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Nicholas J. F. Gatford
- Kavli Institute for Nanoscience Discovery, Nuffield Department of Clinical Neurosciences, University of Oxford, Medical Sciences Division, Oxford, United Kingdom
| | - Alejandro Rivera-Olvera
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Sahar Avazzadeh
- Physiology and Cellular Physiology Research Laboratory, CÚRAM SFI Centre for Research in Medical Devices, School of Medicine, Human Biology Building, University of Galway, Galway, Ireland
| | - Judith R. Homberg
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Joanes Grandjean
- Physiology and Cellular Physiology Research Laboratory, CÚRAM SFI Centre for Research in Medical Devices, School of Medicine, Human Biology Building, University of Galway, Galway, Ireland
- Department of Medical Imaging, Radboud University Medical Centre, Nijmegen, Netherlands
| | - Cathy Fernandes
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Sanbing Shen
- Regenerative Medicine Institute, School of Medicine, University of Galway, Galway, Ireland
- FutureNeuro, The SFI Research Centre for Chronic and Rare Neurological Diseases, Royal College of Surgeons, Dublin, Ireland
| | - Eva Loth
- Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Deepak P. Srivastava
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Louise Gallagher
- Department of Psychiatry, School of Medicine, Trinity College Dublin, Dublin, Ireland
- The Hospital for SickKids, Toronto, ON, Canada
- The Peter Gilgan Centre for Research and Learning, SickKids Research Institute, Toronto, ON, Canada
- The Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
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Nott A, Holtman IR. Genetic insights into immune mechanisms of Alzheimer's and Parkinson's disease. Front Immunol 2023; 14:1168539. [PMID: 37359515 PMCID: PMC10285485 DOI: 10.3389/fimmu.2023.1168539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 04/17/2023] [Indexed: 06/28/2023] Open
Abstract
Microglia, the macrophages of the brain, are vital for brain homeostasis and have been implicated in a broad range of brain disorders. Neuroinflammation has gained traction as a possible therapeutic target for neurodegeneration, however, the precise function of microglia in specific neurodegenerative disorders is an ongoing area of research. Genetic studies offer valuable insights into understanding causality, rather than merely observing a correlation. Genome-wide association studies (GWAS) have identified many genetic loci that are linked to susceptibility to neurodegenerative disorders. (Post)-GWAS studies have determined that microglia likely play an important role in the development of Alzheimer's disease (AD) and Parkinson's disease (PD). The process of understanding how individual GWAS risk loci affect microglia function and mediate susceptibility is complex. A rapidly growing number of publications with genomic datasets and computational tools have formulated new hypotheses that guide the biological interpretation of AD and PD genetic risk. In this review, we discuss the key concepts and challenges in the post-GWAS interpretation of AD and PD GWAS risk alleles. Post-GWAS challenges include the identification of target cell (sub)type(s), causal variants, and target genes. Crucially, the prediction of GWAS-identified disease-risk cell types, variants and genes require validation and functional testing to understand the biological consequences within the pathology of the disorders. Many AD and PD risk genes are highly pleiotropic and perform multiple important functions that might not be equally relevant for the mechanisms by which GWAS risk alleles exert their effect(s). Ultimately, many GWAS risk alleles exert their effect by changing microglia function, thereby altering the pathophysiology of these disorders, and hence, we believe that modelling this context is crucial for a deepened understanding of these disorders.
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Affiliation(s)
- Alexi Nott
- Department of Brain Sciences, Imperial College London, London, United Kingdom
- UK Dementia Research Institute, Imperial College London, London, United Kingdom
| | - Inge R. Holtman
- Department of Biomedical Sciences of Cells and Systems, Section Molecular Neurobiology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
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Fabo T, Khavari P. Functional characterization of human genomic variation linked to polygenic diseases. Trends Genet 2023; 39:462-490. [PMID: 36997428 PMCID: PMC11025698 DOI: 10.1016/j.tig.2023.02.014] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/22/2023] [Accepted: 02/23/2023] [Indexed: 03/30/2023]
Abstract
The burden of human disease lies predominantly in polygenic diseases. Since the early 2000s, genome-wide association studies (GWAS) have identified genetic variants and loci associated with complex traits. These have ranged from variants in coding sequences to mutations in regulatory regions, such as promoters and enhancers, as well as mutations affecting mediators of mRNA stability and other downstream regulators, such as 5' and 3'-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNA. Recent research advances in genetics have utilized a combination of computational techniques, high-throughput in vitro and in vivo screening modalities, and precise genome editing to impute the function of diverse classes of genetic variants identified through GWAS. In this review, we highlight the vastness of genomic variants associated with polygenic disease risk and address recent advances in how genetic tools can be used to functionally characterize them.
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Affiliation(s)
- Tania Fabo
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA; Graduate Program in Genetics, Stanford University, Stanford, CA, USA; Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | - Paul Khavari
- Program in Epithelial Biology, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA; Graduate Program in Genetics, Stanford University, Stanford, CA, USA; Stanford University School of Medicine, Stanford University, Stanford, CA, USA; Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA.
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31
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Guo Q, Wu S, Geschwind DH. Characterization of Gene Regulatory Elements in Human Fetal Cortical Development: Enhancing Our Understanding of Neurodevelopmental Disorders and Evolution. Dev Neurosci 2023; 46:69-83. [PMID: 37231806 DOI: 10.1159/000530929] [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: 02/23/2023] [Accepted: 04/24/2023] [Indexed: 05/27/2023] Open
Abstract
The neocortex is the region that most distinguishes human brain from other mammals and primates [Annu Rev Genet. 2021 Nov;55(1):555-81]. Studying the development of human cortex is important in understanding the evolutionary changes occurring in humans relative to other primates, as well as in elucidating mechanisms underlying neurodevelopmental disorders. Cortical development is a highly regulated process, spatially and temporally coordinated by expression of essential transcriptional factors in response to signaling pathways [Neuron. 2019 Sep;103(6):980-1004]. Enhancers are the most well-understood cis-acting, non-protein-coding regulatory elements that regulate gene expression [Nat Rev Genet. 2014 Apr;15(4):272-86]. Importantly, given the conservation of both DNA sequence and molecular function of the majority of proteins across mammals [Genome Res. 2003 Dec;13(12):2507-18], enhancers [Science. 2015 Mar;347(6226):1155-9], which are far more divergent at the sequence level, likely account for the phenotypes that distinguish the human brain by changing the regulation of gene expression. In this review, we will revisit the conceptual framework of gene regulation during human brain development, as well as the evolution of technologies to study transcriptional regulation, with recent advances in genome biology that open a window allowing us to systematically characterize cis-regulatory elements in developing human brain [Hum Mol Genet. 2022 Oct;31(R1):R84-96]. We provide an update on work to characterize the suite of all enhancers in the developing human brain and the implications for understanding neuropsychiatric disorders. Finally, we discuss emerging therapeutic ideas that utilize our emerging knowledge of enhancer function.
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Affiliation(s)
- Qiuyu Guo
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California, USA
- Center for Autism Research and Treatment, Semel Institute, University of California Los Angeles, Los Angeles, California, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Sarah Wu
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California, USA
| | - Daniel H Geschwind
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California, USA
- Center for Autism Research and Treatment, Semel Institute, University of California Los Angeles, Los Angeles, California, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Institute of Precision Health, University of California Los Angeles, Los Angeles, California, USA
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Li E, Benitez C, Boggess SC, Koontz M, Rose IV, Draeger N, Teter OM, Samelson AJ, Ullian EM, Kampmann M. CRISPRi-based screens in iAssembloids to elucidate neuron-glia interactions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.26.538498. [PMID: 37163077 PMCID: PMC10168378 DOI: 10.1101/2023.04.26.538498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
The sheer complexity of the brain has complicated our ability to understand its cellular mechanisms in health and disease. Genome-wide association studies have uncovered genetic variants associated with specific neurological phenotypes and diseases. In addition, single-cell transcriptomics have provided molecular descriptions of specific brain cell types and the changes they undergo during disease. Although these approaches provide a giant leap forward towards understanding how genetic variation can lead to functional changes in the brain, they do not establish molecular mechanisms. To address this need, we developed a 3D co-culture system termed iAssembloids (induced multi-lineage assembloids) that enables the rapid generation of homogenous neuron-glia spheroids. We characterize these iAssembloids with immunohistochemistry and single-cell transcriptomics and combine them with large-scale CRISPRi-based screens. In our first application, we ask how glial and neuronal cells interact to control neuronal death and survival. Our CRISPRi-based screens identified that GSK3β inhibits the protective NRF2-mediated oxidative stress response in the presence of reactive oxygen species elicited by high neuronal activity, which was not previously found in 2D monoculture neuron screens. We also apply the platform to investigate the role of APOE-ε4, a risk variant for Alzheimer's Disease, in its effect on neuronal survival. This platform expands the toolbox for the unbiased identification of mechanisms of cell-cell interactions in brain health and disease.
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Affiliation(s)
- Emmy Li
- Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Camila Benitez
- TETRAD Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Steven C. Boggess
- Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA
| | - Mark Koontz
- Department of Ophthalmology, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Indigo V.L. Rose
- Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA
- Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Nina Draeger
- Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA
| | - Olivia M. Teter
- Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA
- UC Berkeley-UCSF Graduate Program in Bioengineering, University of California, San Francisco, San Francisco, CA, USA
| | - Avi J. Samelson
- Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA
| | - Erik M. Ullian
- Department of Ophthalmology, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Martin Kampmann
- Institute for Neurodegenerative Diseases, University of California, San Francisco, San Francisco, CA, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, San Francisco, CA, USA
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Rogers BB, Anderson AG, Lauzon SN, Davis MN, Hauser RM, Roberts SC, Rodriguez-Nunez I, Trausch-Lowther K, Barinaga EA, Taylor JW, Mackiewicz M, Roberts BS, Cooper SJ, Rizzardi LF, Myers RM, Cochran JN. MAPT expression is mediated by long-range interactions with cis-regulatory elements. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.07.531520. [PMID: 37090552 PMCID: PMC10120716 DOI: 10.1101/2023.03.07.531520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Background Tauopathies are a group of neurodegenerative diseases driven by abnormal aggregates of tau, a microtubule associated protein encoded by the MAPT gene. MAPT expression is absent in neural progenitor cells (NPCs) and increases during differentiation. This temporally dynamic expression pattern suggests that MAPT expression is controlled by transcription factors and cis-regulatory elements specific to differentiated cell types. Given the relevance of MAPT expression to neurodegeneration pathogenesis, identification of such elements is relevant to understanding genetic risk factors. Methods We performed HiC, chromatin conformation capture (Capture-C), single-nucleus multiomics (RNA-seq+ATAC-seq), bulk ATAC-seq, and ChIP-seq for H3K27Ac and CTCF in NPCs and neurons differentiated from human iPSC cultures. We nominated candidate cis-regulatory elements (cCREs) for MAPT in human NPCs, differentiated neurons, and pure cultures of inhibitory and excitatory neurons. We then assayed these cCREs using luciferase assays and CRISPR interference (CRISPRi) experiments to measure their effects on MAPT expression. Finally, we integrated cCRE annotations into an analysis of genetic variation in AD cases and controls. Results Using orthogonal genomics approaches, we nominated 94 cCREs for MAPT, including the identification of cCREs specifically active in differentiated neurons. Eleven regions enhanced reporter gene transcription in luciferase assays. Using CRISPRi, 5 of the 94 regions tested were identified as necessary for MAPT expression as measured by RT-qPCR and RNA-seq. Rare and predicted damaging genetic variation in both nominated and confirmed CREs was depleted in AD cases relative to controls (OR = 0.40, p = 0.004), consistent with the hypothesis that variants that disrupt MAPT enhancer activity, and thereby reduce MAPT expression, may be protective against neurodegenerative disease. Conclusions We identified both proximal and distal regulatory elements for MAPT and confirmed the regulatory function for several regions, including three regions centromeric to MAPT beyond the well-described H1/H2 haplotype inversion breakpoint. This study provides compelling evidence for pursuing detailed knowledge of CREs for genes of interest to permit better understanding of disease risk.
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Affiliation(s)
- Brianne B. Rogers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
- University of Alabama at Birmingham, Birmingham, AL, USA
| | | | | | | | | | | | | | | | | | - Jared W. Taylor
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Mark Mackiewicz
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | - Sara J. Cooper
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
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Fair T, Pollen AA. Genetic architecture of human brain evolution. Curr Opin Neurobiol 2023; 80:102710. [PMID: 37003107 DOI: 10.1016/j.conb.2023.102710] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 02/20/2023] [Accepted: 02/26/2023] [Indexed: 04/03/2023]
Abstract
Comparative studies of hominids have long sought to identify mutational events that shaped the evolution of the human nervous system. However, functional genetic differences are outnumbered by millions of nearly neutral mutations, and the developmental mechanisms underlying human nervous system specializations are difficult to model and incompletely understood. Candidate-gene studies have attempted to map select human-specific genetic differences to neurodevelopmental functions, but it remains unclear how to contextualize the relative effects of genes that are investigated independently. Considering these limitations, we discuss scalable approaches for probing the functional contributions of human-specific genetic differences. We propose that a systems-level view will enable a more quantitative and integrative understanding of the genetic, molecular and cellular underpinnings of human nervous system evolution.
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Affiliation(s)
- Tyler Fair
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA; Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA. https://twitter.com/@TylerFair_
| | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA; Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
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Balusu S, Praschberger R, Lauwers E, De Strooper B, Verstreken P. Neurodegeneration cell per cell. Neuron 2023; 111:767-786. [PMID: 36787752 DOI: 10.1016/j.neuron.2023.01.016] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 10/12/2022] [Accepted: 01/18/2023] [Indexed: 02/16/2023]
Abstract
The clinical definition of neurodegenerative diseases is based on symptoms that reflect terminal damage of specific brain regions. This is misleading as it tells little about the initial disease processes. Circuitry failures that underlie the clinical symptomatology are themselves preceded by clinically mostly silent, slowly progressing multicellular processes that trigger or are triggered by the accumulation of abnormally folded proteins such as Aβ, Tau, TDP-43, and α-synuclein, among others. Methodological advances in single-cell omics, combined with complex genetics and novel ways to model complex cellular interactions using induced pluripotent stem (iPS) cells, make it possible to analyze the early cellular phase of neurodegenerative disorders. This will revolutionize the way we study those diseases and will translate into novel diagnostics and cell-specific therapeutic targets, stopping these disorders in their early track before they cause difficult-to-reverse damage to the brain.
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Affiliation(s)
- Sriram Balusu
- VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium; KU Leuven Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
| | - Roman Praschberger
- VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium; KU Leuven Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
| | - Elsa Lauwers
- VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium; KU Leuven Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
| | - Bart De Strooper
- VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium; KU Leuven Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium; UK Dementia Research Institute, London, UK.
| | - Patrik Verstreken
- VIB-KU Leuven Center for Brain & Disease Research, Leuven, Belgium; KU Leuven Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium.
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Anderson AG, Rogers BB, Loupe JM, Rodriguez-Nunez I, Roberts SC, White LM, Brazell JN, Bunney WE, Bunney BG, Watson SJ, Cochran JN, Myers RM, Rizzardi LF. Single nucleus multiomics identifies ZEB1 and MAFB as candidate regulators of Alzheimer's disease-specific cis-regulatory elements. CELL GENOMICS 2023; 3:100263. [PMID: 36950385 PMCID: PMC10025452 DOI: 10.1016/j.xgen.2023.100263] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 12/06/2022] [Accepted: 01/12/2023] [Indexed: 02/05/2023]
Abstract
Cell type-specific transcriptional differences between brain tissues from donors with Alzheimer's disease (AD) and unaffected controls have been well documented, but few studies have rigorously interrogated the regulatory mechanisms responsible for these alterations. We performed single nucleus multiomics (snRNA-seq plus snATAC-seq) on 105,332 nuclei isolated from cortical tissues from 7 AD and 8 unaffected donors to identify candidate cis-regulatory elements (CREs) involved in AD-associated transcriptional changes. We detected 319,861 significant correlations, or links, between gene expression and cell type-specific transposase accessible regions enriched for active CREs. Among these, 40,831 were unique to AD tissues. Validation experiments confirmed the activity of many regions, including several candidate regulators of APP expression. We identified ZEB1 and MAFB as candidate transcription factors playing important roles in AD-specific gene regulation in neurons and microglia, respectively. Microglia links were globally enriched for heritability of AD risk and previously identified active regulatory regions.
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Affiliation(s)
| | - Brianne B. Rogers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
- University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jacob M. Loupe
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | | | - Lauren M. White
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | - William E. Bunney
- Department of Psychiatry and Human Behavior, College of Medicine, University of California, Irvine, Irvine, CA, USA
| | - Blynn G. Bunney
- Department of Psychiatry and Human Behavior, College of Medicine, University of California, Irvine, Irvine, CA, USA
| | - Stanley J. Watson
- Mental Health Research Institute, University of Michigan, Ann Arbor, MI, USA
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Zeng B, Bendl J, Deng C, Lee D, Misir R, Reach SM, Kleopoulos SP, Auluck P, Marenco S, Lewis DA, Haroutunian V, Ahituv N, Fullard JF, Hoffman GE, Roussos P. Genetic regulation of cell-type specific chromatin accessibility shapes the etiology of brain diseases. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.02.530826. [PMID: 37090548 PMCID: PMC10120699 DOI: 10.1101/2023.03.02.530826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Nucleotide variants in cell type-specific gene regulatory elements in the human brain are major risk factors of human disease. We measured chromatin accessibility in sorted neurons and glia from 1,932 samples of human postmortem brain and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTL). Only 10.4% of caQTL are shared between neurons and glia, supporting the cell type specificity of genetic regulation of the brain regulome. Incorporating allele specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms underlying disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs, identifying the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides novel insights into brain disease etiology.
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Affiliation(s)
- Biao Zeng
- Center for Disease Neurogenomics, 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
- Department of Genetics and Genomic Sciences, 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
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, 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
- Department of Genetics and Genomic Sciences, 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
| | - Chengyu Deng
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, 94158, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, 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
- Department of Genetics and Genomic Sciences, 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
| | - Ruth Misir
- Center for Disease Neurogenomics, 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
- Department of Genetics and Genomic Sciences, 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
| | - Sarah M. Reach
- Center for Disease Neurogenomics, 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
- Department of Genetics and Genomic Sciences, 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
| | - Steven P. Kleopoulos
- Center for Disease Neurogenomics, 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
- Department of Genetics and Genomic Sciences, 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
| | - Pavan Auluck
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA
| | - Stefano Marenco
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD, USA
| | - David A. Lewis
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Vahram Haroutunian
- Department of Psychiatry, 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 Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, Bronx, NY, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, 94158, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - John F. Fullard
- Center for Disease Neurogenomics, 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
- Department of Genetics and Genomic Sciences, 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
| | - Gabriel E. Hoffman
- Center for Disease Neurogenomics, 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
- Department of Genetics and Genomic Sciences, 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
| | - Panos Roussos
- Center for Disease Neurogenomics, 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
- Department of Genetics and Genomic Sciences, 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
- Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, Bronx, NY, USA
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Deng C, Whalen S, Steyert M, Ziffra R, Przytycki PF, Inoue F, Pereira DA, Capauto D, Norton S, Vaccarino FM, Pollen A, Nowakowski TJ, Ahituv N, Pollard KS. Massively parallel characterization of psychiatric disorder-associated and cell-type-specific regulatory elements in the developing human cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.15.528663. [PMID: 36824845 PMCID: PMC9949039 DOI: 10.1101/2023.02.15.528663] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
Nucleotide changes in gene regulatory elements are important determinants of neuronal development and disease. Using massively parallel reporter assays in primary human cells from mid-gestation cortex and cerebral organoids, we interrogated the cis-regulatory activity of 102,767 sequences, including differentially accessible cell-type specific regions in the developing cortex and single-nucleotide variants associated with psychiatric disorders. In primary cells, we identified 46,802 active enhancer sequences and 164 disorder-associated variants that significantly alter enhancer activity. Activity was comparable in organoids and primary cells, suggesting that organoids provide an adequate model for the developing cortex. Using deep learning, we decoded the sequence basis and upstream regulators of enhancer activity. This work establishes a comprehensive catalog of functional gene regulatory elements and variants in human neuronal development.
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Affiliation(s)
- Chengyu Deng
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco; San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco; San Francisco, CA, USA
| | - Sean Whalen
- Gladstone Institutes; San Francisco, CA, USA
| | - Marilyn Steyert
- Department of Anatomy, University of California, San Francisco; San Francisco, CA, USA
- Department of Psychiatry, University of California, San Francisco; San Francisco, CA, USA
- Department of Neurological Surgery, University of California, San Francisco; San Francisco, CA, USA
| | - Ryan Ziffra
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco; San Francisco, CA, USA
| | | | - Fumitaka Inoue
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University; Kyoto, Japan
| | - Daniela A. Pereira
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco; San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco; San Francisco, CA, USA
- Graduate Program of Genetics, Institute of Biological Sciences, Federal University of Minas Gerais; Belo Horizonte, Minas Gerais, Brazil
| | | | - Scott Norton
- Child Study Center, Yale University; New Haven, CT, USA
| | - Flora M. Vaccarino
- Child Study Center, Yale University; New Haven, CT, USA
- Department of Neuroscience, Yale University; New Haven, CT, USA
| | - Alex Pollen
- Department of Neurology, University of California, San Francisco; San Francisco, CA, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco; San Francisco, CA, USA
| | - Tomasz J. Nowakowski
- Department of Anatomy, University of California, San Francisco; San Francisco, CA, USA
- Department of Psychiatry, University of California, San Francisco; San Francisco, CA, USA
- Department of Neurological Surgery, University of California, San Francisco; San Francisco, CA, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco; San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco; San Francisco, CA, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco; San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco; San Francisco, CA, USA
| | - Katherine S. Pollard
- Institute for Human Genetics, University of California, San Francisco; San Francisco, CA, USA
- Gladstone Institutes; San Francisco, CA, USA
- Chan Zuckerberg Biohub, San Francisco; San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco; San Francisco, CA, USA
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39
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Dhuriya YK, Naik AA. CRISPR: a tool with potential for genomic reprogramming in neurological disorders. Mol Biol Rep 2023; 50:1845-1856. [PMID: 36507966 DOI: 10.1007/s11033-022-08136-z] [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: 09/18/2022] [Accepted: 11/17/2022] [Indexed: 12/14/2022]
Abstract
The intricate neural circuitry of the brain necessitates precise and synchronized transcriptional programs. Any disturbance during embryonic or adult development, whether caused by genetic or environmental factors, may result in refractory and recurrent neurological disorders. Inadequate knowledge of the pathogenic mechanisms underlying neurological disorders is the primary obstacle to the development of effective treatments, necessitating the development of alternative therapeutic approaches to identify rational molecular targets. Recently, with the evolution of CRISPR-Cas9 technology, an engineered RNA system provides precise and highly effective correction or silencing of disease-causing mutations by modulating expression and thereby avoiding the limitations of the RNA interference strategy. This article discusses the CRISPR-Cas9 technology, its mechanisms, and the limitations of the new technology. We provide a glimpse of how the far-reaching implications of CRISPR can open new avenues for the development of tools to combat neurological disorders, as well as a review of recent attempts by neuroscientists to launch therapeutic correction.
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Affiliation(s)
| | - Aijaz A Naik
- National Institute of Mental Health (NIMH), Bethesda, USA.
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40
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Hooked Up from a Distance: Charting Genome-Wide Long-Range Interaction Maps in Neural Cells Chromatin to Identify Novel Candidate Genes for Neurodevelopmental Disorders. Int J Mol Sci 2023; 24:ijms24021164. [PMID: 36674677 PMCID: PMC9863356 DOI: 10.3390/ijms24021164] [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: 11/30/2022] [Revised: 12/31/2022] [Accepted: 01/02/2023] [Indexed: 01/10/2023] Open
Abstract
DNA sequence variants (single nucleotide polymorphisms or variants, SNPs/SNVs; copy number variants, CNVs) associated to neurodevelopmental disorders (NDD) and traits often map on putative transcriptional regulatory elements, including, in particular, enhancers. However, the genes controlled by these enhancers remain poorly defined. Traditionally, the activity of a given enhancer, and the effect of its possible alteration associated to the sequence variants, has been thought to influence the nearest gene promoter. However, the obtainment of genome-wide long-range interaction maps in neural cells chromatin challenged this view, showing that a given enhancer is very frequently not connected to the nearest promoter, but to a more distant one, skipping genes in between. In this Perspective, we review some recent papers, who generated long-range interaction maps (by HiC, RNApolII ChIA-PET, Capture-HiC, or PLACseq), and overlapped the identified long-range interacting DNA segments with DNA sequence variants associated to NDD (such as schizophrenia, bipolar disorder and autism) and traits (intelligence). This strategy allowed to attribute the function of enhancers, hosting the NDD-related sequence variants, to a connected gene promoter lying far away on the linear chromosome map. Some of these enhancer-connected genes had indeed been already identified as contributive to the diseases, by the identification of mutations within the gene's protein-coding regions (exons), validating the approach. Significantly, however, the connected genes also include many genes that were not previously found mutated in their exons, pointing to novel candidate contributors to NDD and traits. Thus, long-range interaction maps, in combination with DNA variants detected in association with NDD, can be used as "pointers" to identify novel candidate disease-relevant genes. Functional manipulation of the long-range interaction network involving enhancers and promoters by CRISPR-Cas9-based approaches is beginning to probe for the functional significance of the identified interactions, and the enhancers and the genes involved, improving our understanding of neural development and its pathology.
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41
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Аpplication of massive parallel reporter analysis in biotechnology and medicine. КЛИНИЧЕСКАЯ ПРАКТИКА 2023. [DOI: 10.17816/clinpract115063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
The development and functioning of an organism relies on tissue-specific gene programs. Genome regulatory elements play a key role in the regulation of such programs, and disruptions in their function can lead to the development of various pathologies, including cancers, malformations and autoimmune diseases. The emergence of high-throughput genomic studies has led to massively parallel reporter analysis (MPRA) methods, which allow the functional verification and identification of regulatory elements on a genome-wide scale. Initially MPRA was used as a tool to investigate fundamental aspects of epigenetics, but the approach also has great potential for clinical and practical biotechnology. Currently, MPRA is used for validation of clinically significant mutations, identification of tissue-specific regulatory elements, search for the most promising loci for transgene integration, and is an indispensable tool for creating highly efficient expression systems, the range of application of which extends from approaches for protein development and design of next-generation therapeutic antibody superproducers to gene therapy. In this review, the main principles and areas of practical application of high-throughput reporter assays will be discussed.
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Zhou J, Wang ZB, Sun Y, Fu Y, Li D, Tan L. Cerebrospinal Fluid Complement 4 Levels Were Associated with Alzheimer's Disease Pathology and Cognition in Non-Demented Elderly. J Alzheimers Dis 2023; 96:1071-1081. [PMID: 38007670 DOI: 10.3233/jad-230513] [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] [Indexed: 11/27/2023]
Abstract
BACKGROUND Numerous studies have shown that the complement system plays an important role in Alzheimer's disease (AD). However, whether complement 4 (C4) protein in cerebrospinal fluid (CSF) was associated with AD pathology, especially in the early stage of AD, is still unclear. OBJECTIVE We aimed to explore the association of CSF C4 with AD pathology and cognition in the preclinical AD. METHODS The study included a total of 287 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Based on the A/T scheme, they were divided into four groups to access the changes of CSF C4 in the preclinical AD. Linear regression models were used to test the associations between CSF C4 and AD core biomarkers, namely Aβ42, P-tau, and T-tau. RESULTS The level of CSF C4 decreased in the A + T- group compared with the A-T- group (p = 0.04) and it increased in the A-T+ group compared to the A + T- group (p = 0.01). In pooled samples, C4 was significantly associated with AD core biomarkers (all p < 0.05), but only in the A + group after stratification according to the A/T scheme. Furthermore, CSF C4 levels at baseline were associated with longitudinal cognitive changes. CONCLUSIONS Our results showed that CSF C4 levels changed dynamically in the preclinical AD, and that the responses of CSF C4 to brain Aβ pathology, tau pathology and neurodegeneration were found only in the presence of amyloid plaques, both of which indicates the complex link between C4 and AD.
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Affiliation(s)
- Jie Zhou
- Department of Neurology, Qingdao Municipal Hospital, Nanjing Medical University, Nanjing, China
| | - Zhi-Bo Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan Sun
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yan Fu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Da Li
- Department of Neurology, Qingdao Municipal Hospital, Nanjing Medical University, Nanjing, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Nanjing Medical University, Nanjing, China
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
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Warden AS, Han C, Hansen E, Trescott S, Nguyen C, Kim R, Schafer D, Johnson A, Wright M, Ramirez G, Lopez-Sanchez M, Coufal NG. Tools for studying human microglia: In vitro and in vivo strategies. Brain Behav Immun 2023; 107:369-382. [PMID: 36336207 PMCID: PMC9810377 DOI: 10.1016/j.bbi.2022.10.008] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 09/11/2022] [Accepted: 10/13/2022] [Indexed: 11/06/2022] Open
Abstract
Microglia may only represent 10% of central nervous system (CNS) cells but they perform critical roles in development, homeostasis and neurological disease. Microglia are also environmentally regulated, quickly losing their transcriptomic and epigenetic signature after leaving the CNS. This facet of microglia biology is both fascinating and technically challenging influencing the study of the genetics and function of human microglia in a manner that recapitulates the CNS environment. In this review we provide a comprehensive overview of existing in vitro and in vivo methodology to study human microglia, such as immortalized cells lines, stem cell-derived microglia, cerebral organoids and xenotransplantation. Since there is currently no single method that completely recapitulates all hallmarks of human ex vivo adult homeostatic microglia, we also discuss the advantages and limitations of each existing model as a practical guide for researchers.
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Affiliation(s)
- Anna S Warden
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA; Sanford Consortium for Regenerative Medicine, La Jolla, CA 92037, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Claudia Han
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA
| | - Emily Hansen
- Sanford Consortium for Regenerative Medicine, La Jolla, CA 92037, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Samantha Trescott
- Sanford Consortium for Regenerative Medicine, La Jolla, CA 92037, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Celina Nguyen
- Sanford Consortium for Regenerative Medicine, La Jolla, CA 92037, USA
| | - Roy Kim
- Sanford Consortium for Regenerative Medicine, La Jolla, CA 92037, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Danielle Schafer
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA 92093, USA; Sanford Consortium for Regenerative Medicine, La Jolla, CA 92037, USA
| | - Avalon Johnson
- Sanford Consortium for Regenerative Medicine, La Jolla, CA 92037, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Madison Wright
- Sanford Consortium for Regenerative Medicine, La Jolla, CA 92037, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Gabriela Ramirez
- Sanford Consortium for Regenerative Medicine, La Jolla, CA 92037, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Mark Lopez-Sanchez
- Sanford Consortium for Regenerative Medicine, La Jolla, CA 92037, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA
| | - Nicole G Coufal
- Sanford Consortium for Regenerative Medicine, La Jolla, CA 92037, USA; Department of Pediatrics, University of California, San Diego, La Jolla, CA 92093, USA.
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Kircher M, Ludwig KU. Systematic assays and resources for the functional annotation of non-coding variants. MED GENET-BERLIN 2022; 34:275-286. [PMID: 37034418 PMCID: PMC10081529 DOI: 10.1515/medgen-2022-2161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Abstract
Identification of genetic variation in individual genomes is now a routine procedure in human genetic research and diagnostics. For many variants, however, insufficient evidence is available to establish a pathogenic effect, particularly for variants in non-coding regions. Furthermore, the sheer number of candidate variants renders testing in individual assays virtually impossible. While scalable approaches are being developed, the selection of methods and resources and the application of a given framework to a particular disease or trait remain major challenges. This limits the translation of results from both genome-wide association studies and genome sequencing. Here, we discuss computational and experimental approaches available for functional annotation of non-coding variation.
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Affiliation(s)
- Martin Kircher
- Institute of Human Genetics , University of Lübeck , Lübeck , Germany
- Berlin Institute of Health at Charité – Universitätsmedizin Berlin , Berlin , Germany
| | - Kerstin U. Ludwig
- Institute of Human Genetics, University Hospital Bonn , University of Bonn , Venusberg-Campus 1, Building 76 , Bonn , Germany
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45
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Oatman SR, Ertekin-Taner N. Dementia risk variants - hunting needles in a haystack. Nat Rev Neurol 2022; 18:705-706. [PMID: 36329345 DOI: 10.1038/s41582-022-00739-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA. .,Department of Neurology, Mayo Clinic, Jacksonville, FL, USA.
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46
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Lan AY, Corces MR. Deep learning approaches for noncoding variant prioritization in neurodegenerative diseases. Front Aging Neurosci 2022; 14:1027224. [PMID: 36466610 PMCID: PMC9716280 DOI: 10.3389/fnagi.2022.1027224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 10/24/2022] [Indexed: 11/19/2022] Open
Abstract
Determining how noncoding genetic variants contribute to neurodegenerative dementias is fundamental to understanding disease pathogenesis, improving patient prognostication, and developing new clinical treatments. Next generation sequencing technologies have produced vast amounts of genomic data on cell type-specific transcription factor binding, gene expression, and three-dimensional chromatin interactions, with the promise of providing key insights into the biological mechanisms underlying disease. However, this data is highly complex, making it challenging for researchers to interpret, assimilate, and dissect. To this end, deep learning has emerged as a powerful tool for genome analysis that can capture the intricate patterns and dependencies within these large datasets. In this review, we organize and discuss the many unique model architectures, development philosophies, and interpretation methods that have emerged in the last few years with a focus on using deep learning to predict the impact of genetic variants on disease pathogenesis. We highlight both broadly-applicable genomic deep learning methods that can be fine-tuned to disease-specific contexts as well as existing neurodegenerative disease research, with an emphasis on Alzheimer's-specific literature. We conclude with an overview of the future of the field at the intersection of neurodegeneration, genomics, and deep learning.
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Affiliation(s)
- Alexander Y. Lan
- Gladstone Institute of Neurological Disease, San Francisco, CA, United States
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, United States
- Department of Neurology, University of California San Francisco, San Francisco, CA, United States
| | - M. Ryan Corces
- Gladstone Institute of Neurological Disease, San Francisco, CA, United States
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA, United States
- Department of Neurology, University of California San Francisco, San Francisco, CA, United States
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Towards elucidating disease-relevant states of neurons and glia by CRISPR-based functional genomics. Genome Med 2022; 14:130. [PMID: 36401300 PMCID: PMC9673433 DOI: 10.1186/s13073-022-01134-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 11/02/2022] [Indexed: 11/19/2022] Open
Abstract
Our understanding of neurological diseases has been tremendously enhanced over the past decade by the application of new technologies. Genome-wide association studies have highlighted glial cells as important players in diseases. Single-cell profiling technologies are providing descriptions of disease states of neurons and glia at unprecedented molecular resolution. However, significant gaps remain in our understanding of the mechanisms driving disease-associated cell states, and how these states contribute to disease. These gaps in our understanding can be bridged by CRISPR-based functional genomics, a powerful approach to systematically interrogate gene function. In this review, we will briefly review the current literature on neurological disease-associated cell states and introduce CRISPR-based functional genomics. We discuss how advances in CRISPR-based screens, especially when implemented in the relevant brain cell types or cellular environments, have paved the way towards uncovering mechanisms underlying neurological disease-associated cell states. Finally, we will delineate current challenges and future directions for CRISPR-based functional genomics to further our understanding of neurological diseases and potential therapeutic strategies.
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Cheng F, Geschwind D. Human Molecular Genetics Review Issue 2022. Hum Mol Genet 2022; 31:R1-R3. [PMID: 36268970 PMCID: PMC9989729 DOI: 10.1093/hmg/ddac219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 08/30/2022] [Accepted: 08/30/2022] [Indexed: 11/04/2022] Open
Affiliation(s)
- Feixiong Cheng
- To whom correspondence should be addressed at: Feixiong Cheng, Ph.D., Genomic Medicine Institute, Cleveland Clinic Lerner Research Institute, 9500 Euclid Ave, Cleveland, OH 44195, USA. ; Daniel Geschwind, M.D., Ph.D., Departments of Neurology, Psychiatry and Human Genetics, and Institute of Precision Health, David Geffen School of Medicine, University of California, Los Angeles, 695 Charles E Young Dr South, Los Angeles, CA 90095.
| | - Daniel Geschwind
- To whom correspondence should be addressed at: Feixiong Cheng, Ph.D., Genomic Medicine Institute, Cleveland Clinic Lerner Research Institute, 9500 Euclid Ave, Cleveland, OH 44195, USA. ; Daniel Geschwind, M.D., Ph.D., Departments of Neurology, Psychiatry and Human Genetics, and Institute of Precision Health, David Geffen School of Medicine, University of California, Los Angeles, 695 Charles E Young Dr South, Los Angeles, CA 90095.
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Minton K. Decoding noncoding variation in dementia. Nat Rev Genet 2022; 23:649. [PMID: 36075982 DOI: 10.1038/s41576-022-00531-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Hong CC. The grand challenge of discovering new cardiovascular drugs. FRONTIERS IN DRUG DISCOVERY 2022; 2:1027401. [PMID: 37123434 PMCID: PMC10134778 DOI: 10.3389/fddsv.2022.1027401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
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