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Maalouf CA, Alberti A, Soutourina J. Mediator complex in transcription regulation and DNA repair: Relevance for human diseases. DNA Repair (Amst) 2024; 141:103714. [PMID: 38943827 DOI: 10.1016/j.dnarep.2024.103714] [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: 03/21/2024] [Revised: 06/15/2024] [Accepted: 06/18/2024] [Indexed: 07/01/2024]
Abstract
The Mediator complex is an essential coregulator of RNA polymerase II transcription. More recent developments suggest Mediator functions as a link between transcription regulation, genome organisation and DNA repair mechanisms including nucleotide excision repair, base excision repair, and homologous recombination. Dysfunctions of these processes are frequently associated with human pathologies, and growing evidence shows Mediator involvement in cancers, neurological, metabolic and infectious diseases. The detailed deciphering of molecular mechanisms of Mediator functions, using interdisciplinary approaches in different biological models and considering all functions of this complex, will contribute to our understanding of relevant human diseases.
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Affiliation(s)
- Christelle A Maalouf
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Gif-sur-Yvette 91198, France
| | - Adriana Alberti
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Gif-sur-Yvette 91198, France
| | - Julie Soutourina
- Université Paris-Saclay, CEA, CNRS, Institute for Integrative Biology of the Cell (I2BC), Gif-sur-Yvette 91198, France.
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2
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Suzuki T, Bono H. A systematic exploration of unexploited genes for oxidative stress in Parkinson's disease. NPJ Parkinsons Dis 2024; 10:160. [PMID: 39154038 DOI: 10.1038/s41531-024-00776-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 08/05/2024] [Indexed: 08/19/2024] Open
Abstract
Human disease-associated gene data are accessible through databases, including the Open Targets Platform, DisGeNET, miRTex, RNADisease, and PubChem. However, missing data entries in such databases are anticipated because of curational errors, biases, and text-mining failures. Additionally, the extensive research on human diseases has led to challenges in registering comprehensive data. The lack of essential data in databases hinders knowledge sharing and should be addressed. Therefore, we propose an analysis pipeline to explore missing entries of unexploited genes in the human disease-associated gene databases. Using this pipeline for genes in Parkinson's disease with oxidative stress revealed two unexploited genes: nuclear protein 1 (NUPR1) and ubiquitin-like with PHD and ring finger domains 2 (UHRF2). This methodology enhances the identification of underrepresented disease-associated genes, facilitating easier access to potential human disease-related functional genes. This study aims to identify unexploited genes for further research and does not include independent experimental validation.
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Affiliation(s)
- Takayuki Suzuki
- Graduate School of Integrated Sciences for Life, Hiroshima University, 3-10-23 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-0046, Japan
| | - Hidemasa Bono
- Graduate School of Integrated Sciences for Life, Hiroshima University, 3-10-23 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-0046, Japan.
- Genome Editing Innovation Center, Hiroshima University, 3-10-23 Kagamiyama, Higashi-Hiroshima, Hiroshima, 739-0046, Japan.
- Database Center for Life Science (DBCLS), Joint Support-Center for Data Science Research, Research Organization of Information and Systems (ROIS), 178-4-4 Wakashiba, Kashiwa, Chiba, 277-0871, Japan.
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3
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Navarro E, Efthymiou AG, Parks M, Riboldi GM, Vialle RA, Udine E, Muller BZ, Humphrey J, Allan A, Argyrou CC, Lopes KDP, Münch A, Raymond D, Sachdev R, Shanker VL, Miravite J, Katsnelson V, Leaver K, Frucht S, Bressman SB, Marcora E, Saunders-Pullman R, Goate A, Raj T. LRRK2 G2019S variant is associated with transcriptional changes in Parkinson's disease human myeloid cells under proinflammatory environment. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.27.594821. [PMID: 38854101 PMCID: PMC11160623 DOI: 10.1101/2024.05.27.594821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
The G2019S mutation in the leucine-rich repeat kinase 2 (LRRK2) gene is a major risk factor for the development of Parkinson's disease (PD). LRRK2, although ubiquitously expressed, is highly abundant in cells of the innate immune system. Given the importance of central and peripheral immune cells in the development of PD, we sought to investigate the consequences of the G2019S mutation on microglial and monocyte transcriptome and function. We have generated large-scale transcriptomic profiles of isogenic human induced microglial cells (iMGLs) and patient derived monocytes carrying the G2019S mutation under baseline culture conditions and following exposure to the proinflammatory factors IFNγ and LPS. We demonstrate that the G2019S mutation exerts a profound impact on the transcriptomic profile of these myeloid cells, and describe corresponding functional differences in iMGLs. The G2019S mutation led to an upregulation in lipid metabolism and phagolysosomal pathway genes in untreated and LPS/IFNγ stimulated iMGLs, which was accompanied by an increased phagocytic capacity of myelin debris. We also identified dysregulation of cell cycle genes, with a downregulation of the E2F4 regulon. Transcriptomic characterization of human-derived monocytes carrying the G2019S mutation confirmed alteration in lipid metabolism associated genes. Altogether, these findings reveal the influence of G2019S on the dysregulation of the myeloid cell transcriptome under proinflammatory conditions.
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Affiliation(s)
- Elisa Navarro
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Instituto Universitario de Investigacion en Neuroquimica, Departamento de Bioquimica y Biologia Molecular, Facultad de Medicina, Universidad Complutense, Madrid, Spain
- Centro de Investigacion Biomedica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
- Instituto Ramon y Cajal de Investigacion Sanitaria (IRYCIS), Madrid, Spain
| | - Anastasia G. Efthymiou
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Madison Parks
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Giulietta M Riboldi
- The Marlene and Paolo Fresco Institute for Parkinson’s Disease and Movement Disorders, New York University Langone Health, New York, NY, USA
| | - Ricardo A. Vialle
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Rush Alzheimer’s Disease Center, Rush University Medical Center; Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center; Chicago, IL, 60612, USA
| | - Evan Udine
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Benjamin Z. Muller
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Jack Humphrey
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Amanda Allan
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Charlie Charalambos Argyrou
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Katia de Paiva Lopes
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Rush Alzheimer’s Disease Center, Rush University Medical Center; Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center; Chicago, IL, 60612, USA
| | - Alexandra Münch
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Deborah Raymond
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Neurology, Mount Sinai Beth Israel, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rivka Sachdev
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Neurology, Mount Sinai Beth Israel, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Vicki L. Shanker
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Neurology, Mount Sinai Beth Israel, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Joan Miravite
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Neurology, Mount Sinai Beth Israel, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Viktoryia Katsnelson
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Neurology, Mount Sinai Beth Israel, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Katherine Leaver
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Neurology, Mount Sinai Beth Israel, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steve Frucht
- The Marlene and Paolo Fresco Institute for Parkinson’s Disease and Movement Disorders, New York University Langone Health, New York, NY, USA
| | - Susan B Bressman
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Neurology, Mount Sinai Beth Israel, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Edoardo Marcora
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Rachel Saunders-Pullman
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Neurology, Mount Sinai Beth Israel, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alison Goate
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
| | - Towfique Raj
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Department of Genetics and Genomic Sciences & Icahn Genomics Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
- Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States of America
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4
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Wen C, Margolis M, Dai R, Zhang P, Przytycki PF, Vo DD, Bhattacharya A, Matoba N, Tang M, Jiao C, Kim M, Tsai E, Hoh C, Aygün N, Walker RL, Chatzinakos C, Clarke D, Pratt H, Peters MA, Gerstein M, Daskalakis NP, Weng Z, Jaffe AE, Kleinman JE, Hyde TM, Weinberger DR, Bray NJ, Sestan N, Geschwind DH, Roeder K, Gusev A, Pasaniuc B, Stein JL, Love MI, Pollard KS, Liu C, Gandal MJ. Cross-ancestry atlas of gene, isoform, and splicing regulation in the developing human brain. Science 2024; 384:eadh0829. [PMID: 38781368 DOI: 10.1126/science.adh0829] [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: 02/14/2023] [Accepted: 03/07/2024] [Indexed: 05/25/2024]
Abstract
Neuropsychiatric genome-wide association studies (GWASs), including those for autism spectrum disorder and schizophrenia, show strong enrichment for regulatory elements in the developing brain. However, prioritizing risk genes and mechanisms is challenging without a unified regulatory atlas. Across 672 diverse developing human brains, we identified 15,752 genes harboring gene, isoform, and/or splicing quantitative trait loci, mapping 3739 to cellular contexts. Gene expression heritability drops during development, likely reflecting both increasing cellular heterogeneity and the intrinsic properties of neuronal maturation. Isoform-level regulation, particularly in the second trimester, mediated the largest proportion of GWAS heritability. Through colocalization, we prioritized mechanisms for about 60% of GWAS loci across five disorders, exceeding adult brain findings. Finally, we contextualized results within gene and isoform coexpression networks, revealing the comprehensive landscape of transcriptome regulation in development and disease.
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Affiliation(s)
- Cindy Wen
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Michael Margolis
- 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
| | - Rujia Dai
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY 13210, USA
| | - Pan Zhang
- 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
| | - Pawel F Przytycki
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158, USA
| | - Daniel D Vo
- 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
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Nana Matoba
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Miao Tang
- 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
| | - Chuan Jiao
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY 13210, USA
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team Krebs, 75014 Paris, France
| | - Minsoo Kim
- 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
| | - Ellen Tsai
- 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
| | - Celine Hoh
- 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
| | - Nil Aygün
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Rebecca L Walker
- 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
| | - Christos Chatzinakos
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
- McLean Hospital, Belmont, MA 02478, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Declan Clarke
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Henry Pratt
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Mette A Peters
- CNS Data Coordination Group, Sage Bionetworks, Seattle, WA 98109, USA
| | - Mark Gerstein
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Nikolaos P Daskalakis
- Department of Psychiatry, Harvard Medical School, Boston, MA 02215, USA
- McLean Hospital, Belmont, MA 02478, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Andrew E Jaffe
- Lieber Institute for Brain Development, Baltimore, MD 21205, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
- Neumora Therapeutics, Watertown, MA 02472, USA
| | - Joel E Kleinman
- Lieber Institute for Brain Development, Baltimore, MD 21205, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Thomas M Hyde
- Lieber Institute for Brain Development, Baltimore, MD 21205, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Daniel R Weinberger
- Lieber Institute for Brain Development, Baltimore, MD 21205, USA
- Department of Psychiatry & Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Neuroscience, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Nicholas J Bray
- MRC Centre for Neuropsychiatric Genetics & Genomics, Division of Psychological Medicine & Clinical Neurosciences, Cardiff University School of Medicine, Cardiff CF24 4HQ, UK
| | - Nenad Sestan
- Department of Comparative Medicine, Yale University School of Medicine, New Haven, CT 06520, USA
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Daniel H Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Kathryn Roeder
- Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Alexander Gusev
- Department of Medical Oncology, Division of Population Sciences, Dana-Farber Cancer Institute, Boston, MA 02215, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Medical School, Boston, MA 02215, USA
- Division of Genetics, Brigham and Women's Hospital, Boston, MA 02215, USA
| | - Bogdan Pasaniuc
- Interdepartmental Program in Bioinformatics, 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 Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute for Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, 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
| | - Katherine S Pollard
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA 94158, USA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Chunyu Liu
- Department of Psychiatry, SUNY Upstate Medical University, Syracuse, NY 13210, USA
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - 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
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5
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Chew G, Mai AS, Ouyang JF, Qi Y, Chao Y, Wang Q, Petretto E, Tan EK. Transcriptomic imputation of genetic risk variants uncovers novel whole-blood biomarkers of Parkinson's disease. NPJ Parkinsons Dis 2024; 10:99. [PMID: 38719867 PMCID: PMC11078960 DOI: 10.1038/s41531-024-00698-y] [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: 07/29/2023] [Accepted: 03/28/2024] [Indexed: 05/12/2024] Open
Abstract
Blood-based gene expression signatures could potentially be used as biomarkers for PD. However, it is unclear whether genetically-regulated transcriptomic signatures can provide novel gene candidates for use as PD biomarkers. We leveraged on the Genotype-Tissue Expression (GTEx) database to impute whole-blood transcriptomic expression using summary statistics of three large-scale PD GWAS. A random forest classifier was used with the consensus whole-blood imputed gene signature (IGS) to discriminate between cases and controls. Outcome measures included Area under the Curve (AUC) of Receiver Operating Characteristic (ROC) Curve. We demonstrated that the IGS (n = 37 genes) is conserved across PD GWAS studies and brain tissues. IGS discriminated between cases and controls in an independent whole-blood RNA-sequencing study (1176 PD, 254 prodromal, and 860 healthy controls) with mean AUC and accuracy of 64.8% and 69.4% for PD cohort, and 78.8% and 74% for prodromal cohort. PATL2 was the top-performing imputed gene in both PD and prodromal PD cohorts, whose classifier performance varied with biological sex (higher performance for males and females in the PD and prodromal PD, respectively). Single-cell RNA-sequencing studies (scRNA-seq) of healthy humans and PD patients found PATL2 to be enriched in terminal effector CD8+ and cytotoxic CD4+ cells, whose proportions are both increased in PD patients. We demonstrated the utility of GWAS transcriptomic imputation in identifying novel whole-blood transcriptomic signatures which could be leveraged upon for PD biomarker derivation. We identified PATL2 as a potential biomarker in both clinical and prodromic PD.
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Affiliation(s)
- Gabriel Chew
- Duke-National University of Singapore Medical School, Singapore, Singapore
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Aaron Shengting Mai
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - John F Ouyang
- Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Yueyue Qi
- Duke-National University of Singapore Medical School, Singapore, Singapore
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
| | - Yinxia Chao
- Duke-National University of Singapore Medical School, Singapore, Singapore
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore
- Department of Neurology, Singapore General Hospital, Singapore, Singapore
| | - Qing Wang
- Department of Neurology, Zhujiang Hospital, Southern Medical University, Guangzhou, China
| | - Enrico Petretto
- Duke-National University of Singapore Medical School, Singapore, Singapore
| | - Eng-King Tan
- Duke-National University of Singapore Medical School, Singapore, Singapore.
- Department of Neurology, National Neuroscience Institute, Singapore, Singapore.
- Department of Neurology, Singapore General Hospital, Singapore, Singapore.
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6
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Choi E, Song J, Lee Y, Jeong Y, Jang W. Prioritizing susceptibility genes for the prognosis of male-pattern baldness with transcriptome-wide association study. Hum Genomics 2024; 18:34. [PMID: 38566255 PMCID: PMC10985920 DOI: 10.1186/s40246-024-00591-y] [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: 01/23/2024] [Accepted: 02/27/2024] [Indexed: 04/04/2024] Open
Abstract
BACKGROUND Male-pattern baldness (MPB) is the most common cause of hair loss in men. It can be categorized into three types: type 2 (T2), type 3 (T3), and type 4 (T4), with type 1 (T1) being considered normal. Although various MPB-associated genetic variants have been suggested, a comprehensive study for linking these variants to gene expression regulation has not been performed to the best of our knowledge. RESULTS In this study, we prioritized MPB-related tissue panels using tissue-specific enrichment analysis and utilized single-tissue panels from genotype-tissue expression version 8, as well as cross-tissue panels from context-specific genetics. Through a transcriptome-wide association study and colocalization analysis, we identified 52, 75, and 144 MPB associations for T2, T3, and T4, respectively. To assess the causality of MPB genes, we performed a conditional and joint analysis, which revealed 10, 11, and 54 putative causality genes for T2, T3, and T4, respectively. Finally, we conducted drug repositioning and identified potential drug candidates that are connected to MPB-associated genes. CONCLUSIONS Overall, through an integrative analysis of gene expression and genotype data, we have identified robust MPB susceptibility genes that may help uncover the underlying molecular mechanisms and the novel drug candidates that may alleviate MPB.
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Affiliation(s)
- Eunyoung Choi
- Department of Life Sciences, Dongguk University, Seoul, 04620, Republic of Korea
| | - Jaeseung Song
- Department of Life Sciences, Dongguk University, Seoul, 04620, Republic of Korea
| | - Yubin Lee
- Department of Life Sciences, Dongguk University, Seoul, 04620, Republic of Korea
| | - Yeonbin Jeong
- Department of Life Sciences, Dongguk University, Seoul, 04620, Republic of Korea
| | - Wonhee Jang
- Department of Life Sciences, Dongguk University, Seoul, 04620, Republic of Korea.
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7
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Wu YS, Zheng WH, Liu TH, Sun Y, Xu YT, Shao LZ, Cai QY, Tang YQ. Joint-tissue integrative analysis identifies high-risk genes for Parkinson's disease. Front Neurosci 2024; 18:1309684. [PMID: 38576865 PMCID: PMC10991821 DOI: 10.3389/fnins.2024.1309684] [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: 10/08/2023] [Accepted: 02/22/2024] [Indexed: 04/06/2024] Open
Abstract
The loss of dopaminergic neurons in the substantia nigra and the abnormal accumulation of synuclein proteins and neurotransmitters in Lewy bodies constitute the primary symptoms of Parkinson's disease (PD). Besides environmental factors, scholars are in the early stages of comprehending the genetic factors involved in the pathogenic mechanism of PD. Although genome-wide association studies (GWAS) have unveiled numerous genetic variants associated with PD, precisely pinpointing the causal variants remains challenging due to strong linkage disequilibrium (LD) among them. Addressing this issue, expression quantitative trait locus (eQTL) cohorts were employed in a transcriptome-wide association study (TWAS) to infer the genetic correlation between gene expression and a particular trait. Utilizing the TWAS theory alongside the enhanced Joint-Tissue Imputation (JTI) technique and Mendelian Randomization (MR) framework (MR-JTI), we identified a total of 159 PD-associated genes by amalgamating LD score, GTEx eQTL data, and GWAS summary statistic data from a substantial cohort. Subsequently, Fisher's exact test was conducted on these PD-associated genes using 5,152 differentially expressed genes sourced from 12 PD-related datasets. Ultimately, 29 highly credible PD-associated genes, including CTX1B, SCNA, and ARSA, were uncovered. Furthermore, GO and KEGG enrichment analyses indicated that these genes primarily function in tissue synthesis, regulation of neuron projection development, vesicle organization and transportation, and lysosomal impact. The potential PD-associated genes identified in this study not only offer fresh insights into the disease's pathophysiology but also suggest potential biomarkers for early disease detection.
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Affiliation(s)
- Ya-Shi Wu
- Department of Bioinformatics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
- Department of Cell Biology and Medical Genetics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Wen-Han Zheng
- Department of Cell Biology and Medical Genetics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Tai-Hang Liu
- Department of Bioinformatics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Yan Sun
- Department of Cell Biology and Medical Genetics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Yu-Ting Xu
- Department of Cell Biology and Medical Genetics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Li-Zhen Shao
- Department of Bioinformatics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Qin-Yu Cai
- Department of Bioinformatics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
| | - Ya Qin Tang
- Department of Bioinformatics, School of Basic Medical Sciences, Chongqing Medical University, Chongqing, China
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8
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Xu X, Khunsriraksakul C, Eales JM, Rubin S, Scannali D, Saluja S, Talavera D, Markus H, Wang L, Drzal M, Maan A, Lay AC, Prestes PR, Regan J, Diwadkar AR, Denniff M, Rempega G, Ryszawy J, Król R, Dormer JP, Szulinska M, Walczak M, Antczak A, Matías-García PR, Waldenberger M, Woolf AS, Keavney B, Zukowska-Szczechowska E, Wystrychowski W, Zywiec J, Bogdanski P, Danser AHJ, Samani NJ, Guzik TJ, Morris AP, Liu DJ, Charchar FJ, Tomaszewski M. Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets. Nat Commun 2024; 15:2359. [PMID: 38504097 PMCID: PMC10950894 DOI: 10.1038/s41467-024-46132-y] [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: 07/26/2023] [Accepted: 02/14/2024] [Indexed: 03/21/2024] Open
Abstract
Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.
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Affiliation(s)
- Xiaoguang Xu
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | | | - James M Eales
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sebastien Rubin
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - David Scannali
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sushant Saluja
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - David Talavera
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Havell Markus
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Lida Wang
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Maciej Drzal
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Akhlaq Maan
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Abigail C Lay
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Priscilla R Prestes
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Australia
| | - Jeniece Regan
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Avantika R Diwadkar
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Matthew Denniff
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Grzegorz Rempega
- Department of Urology, Medical University of Silesia, Katowice, Poland
| | - Jakub Ryszawy
- Department of Urology, Medical University of Silesia, Katowice, Poland
| | - Robert Król
- Department of General, Vascular and Transplant Surgery, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland
| | - John P Dormer
- Department of Cellular Pathology, University Hospitals of Leicester, Leicester, UK
| | - Monika Szulinska
- Department of Obesity, Metabolic Disorders Treatment and Clinical Dietetics, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - Marta Walczak
- Department of Internal Diseases, Metabolic Disorders and Arterial Hypertension, Poznan University of Medical Sciences, Poznan, Poland
| | - Andrzej Antczak
- Department of Urology and Uro-oncology, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - Pamela R Matías-García
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Melanie Waldenberger
- Institute of Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- Research Unit Molecular Epidemiology, Helmholtz Center Munich, Neuherberg, Germany
- German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Munich, Germany
| | - Adrian S Woolf
- Division of Cell Matrix Biology and Regenerative Medicine, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
- Royal Manchester Children's Hospital and Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Bernard Keavney
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
- Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust Manchester, Manchester Royal Infirmary, Manchester, UK
| | | | - Wojciech Wystrychowski
- Department of General, Vascular and Transplant Surgery, Faculty of Medical Sciences in Katowice, Medical University of Silesia, Katowice, Poland
| | - Joanna Zywiec
- Department of Internal Medicine, Diabetology and Nephrology, Zabrze, Medical University of Silesia, Katowice, Poland
| | - Pawel Bogdanski
- Department of Obesity, Metabolic Disorders Treatment and Clinical Dietetics, Karol Marcinkowski University of Medical Sciences, Poznan, Poland
| | - A H Jan Danser
- Department of Internal Medicine, Division of Pharmacology and Vascular Medicine, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Tomasz J Guzik
- Department of Internal Medicine, Jagiellonian University Medical College, Kraków, Poland
- Centre for Cardiovascular Sciences, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
- Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Kraków, Poland
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal & Dermatological Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Dajiang J Liu
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Fadi J Charchar
- Health Innovation and Transformation Centre, Federation University Australia, Ballarat, Australia
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- Department of Physiology, University of Melbourne, Melbourne, Australia
| | - Maciej Tomaszewski
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK.
- Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust Manchester, Manchester Royal Infirmary, Manchester, UK.
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9
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Yu E, Larivière R, Thomas RA, Liu L, Senkevich K, Rahayel S, Trempe JF, Fon EA, Gan-Or Z. Machine learning nominates the inositol pathway and novel genes in Parkinson's disease. Brain 2024; 147:887-899. [PMID: 37804111 PMCID: PMC10907089 DOI: 10.1093/brain/awad345] [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: 07/04/2023] [Revised: 09/01/2023] [Accepted: 09/24/2023] [Indexed: 10/08/2023] Open
Abstract
There are 78 loci associated with Parkinson's disease in the most recent genome-wide association study (GWAS), yet the specific genes driving these associations are mostly unknown. Herein, we aimed to nominate the top candidate gene from each Parkinson's disease locus and identify variants and pathways potentially involved in Parkinson's disease. We trained a machine learning model to predict Parkinson's disease-associated genes from GWAS loci using genomic, transcriptomic and epigenomic data from brain tissues and dopaminergic neurons. We nominated candidate genes in each locus and identified novel pathways potentially involved in Parkinson's disease, such as the inositol phosphate biosynthetic pathway (INPP5F, IP6K2, ITPKB and PPIP5K2). Specific common coding variants in SPNS1 and MLX may be involved in Parkinson's disease, and burden tests of rare variants further support that CNIP3, LSM7, NUCKS1 and the polyol/inositol phosphate biosynthetic pathway are associated with the disease. Functional studies are needed to further analyse the involvements of these genes and pathways in Parkinson's disease.
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Affiliation(s)
- Eric Yu
- Department of Human Genetics, McGill University, Montreal, Quebec H3A 0G4, Canada
- The Neuro (Montreal Neurological Institute-Hospital), Montreal, Quebec H3A 2B4, Canada
| | - Roxanne Larivière
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada
| | - Rhalena A Thomas
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada
- Early Drug Discovery Unit (EDDU), Montreal Neurological Institute-Hospital (The Neuro), Montreal, Quebec H3A 2B4, Canada
| | - Lang Liu
- Department of Human Genetics, McGill University, Montreal, Quebec H3A 0G4, Canada
- The Neuro (Montreal Neurological Institute-Hospital), Montreal, Quebec H3A 2B4, Canada
| | - Konstantin Senkevich
- The Neuro (Montreal Neurological Institute-Hospital), Montreal, Quebec H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada
| | - Shady Rahayel
- Centre for Advanced Research in Sleep Medicine, Hôpital du Sacré-Cœur de Montréal, Montreal, Quebec H4J 1C5, Canada
- Department of Medicine, University of Montreal, Montreal, Quebec H3C 3J7, Canada
| | - Jean-François Trempe
- Department of Pharmacology and Therapeutics and Centre de Recherche en Biologie Structurale, McGill University, Montreal, Quebec H3A 0G4, Canada
| | - Edward A Fon
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada
- Early Drug Discovery Unit (EDDU), Montreal Neurological Institute-Hospital (The Neuro), Montreal, Quebec H3A 2B4, Canada
| | - Ziv Gan-Or
- Department of Human Genetics, McGill University, Montreal, Quebec H3A 0G4, Canada
- The Neuro (Montreal Neurological Institute-Hospital), Montreal, Quebec H3A 2B4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec H3A 0G4, Canada
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10
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Chen H, Wang Z, Gong L, Wang Q, Chen W, Wang J, Ma X, Ding R, Li X, Zou X, Plass M, Lian C, Ni T, Wei GH, Li W, Deng L, Li L. A distinct class of pan-cancer susceptibility genes revealed by an alternative polyadenylation transcriptome-wide association study. Nat Commun 2024; 15:1729. [PMID: 38409266 PMCID: PMC10897204 DOI: 10.1038/s41467-024-46064-7] [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: 08/09/2023] [Accepted: 02/12/2024] [Indexed: 02/28/2024] Open
Abstract
Alternative polyadenylation plays an important role in cancer initiation and progression; however, current transcriptome-wide association studies mostly ignore alternative polyadenylation when identifying putative cancer susceptibility genes. Here, we perform a pan-cancer 3' untranslated region alternative polyadenylation transcriptome-wide association analysis by integrating 55 well-powered (n > 50,000) genome-wide association studies datasets across 22 major cancer types with alternative polyadenylation quantification from 23,955 RNA sequencing samples across 7,574 individuals. We find that genetic variants associated with alternative polyadenylation are co-localized with 28.57% of cancer loci and contribute a significant portion of cancer heritability. We further identify 642 significant cancer susceptibility genes predicted to modulate cancer risk via alternative polyadenylation, 62.46% of which have been overlooked by traditional expression- and splicing- studies. As proof of principle validation, we show that alternative alleles facilitate 3' untranslated region lengthening of CRLS1 gene leading to increased protein abundance and promoted proliferation of breast cancer cells. Together, our study highlights the significant role of alternative polyadenylation in discovering new cancer susceptibility genes and provides a strong foundational framework for enhancing our understanding of the etiology underlying human cancers.
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Affiliation(s)
- Hui Chen
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Zeyang Wang
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Lihai Gong
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Qixuan Wang
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Wenyan Chen
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Jia Wang
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Xuelian Ma
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Ruofan Ding
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Xing Li
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Xudong Zou
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China
| | - Mireya Plass
- Gene Regulation of Cell Identity Group, Regenerative Medicine Program, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet de Llobregat, Barcelona, 08908, Spain
- Program for Advancing Clinical Translation of Regenerative Medicine of Catalonia, P-CMR[C], L'Hospitalet de Llobregat, Barcelona, 08908, Spain
- Center for Networked Biomedical Research on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, 28029, Spain
| | - Cheng Lian
- Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, Shanghai Medical College of Fudan University, Shanghai, 200032, China
| | - Ting Ni
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center of Genetics and Development, Human Phenome Institute, School of Life Sciences and Huashan Hospital, Fudan University, Shanghai, 200438, China
| | - Gong-Hong Wei
- Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences, Shanghai Medical College of Fudan University, Shanghai, 200032, China
- Disease Networks Research Unit, Faculty of Biochemistry and Molecular Medicine & Biocenter Oulu, University of Oulu, Oulu, 90410, Finland
| | - Wei Li
- Division of Computational Biomedicine, Department of Biological Chemistry, School of Medicine, The University of California, Irvine, CA, 92697, USA.
| | - Lin Deng
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, 518055, China.
| | - Lei Li
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518055, China.
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11
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Shi JJ, Mao CY, Guo YZ, Fan Y, Hao XY, Li SJ, Tian J, Hu ZW, Li MJ, Li JD, Ma DR, Guo MN, Zuo CY, Liang YY, Xu YM, Yang J, Shi CH. Joint analysis of proteome, transcriptome, and multi-trait analysis to identify novel Parkinson's disease risk genes. Aging (Albany NY) 2024; 16:1555-1580. [PMID: 38240717 PMCID: PMC10866412 DOI: 10.18632/aging.205444] [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: 02/20/2023] [Accepted: 12/04/2023] [Indexed: 02/06/2024]
Abstract
Genome-wide association studies (GWAS) have identified multiple risk variants for Parkinson's disease (PD). Nevertheless, how the risk variants confer the risk of PD remains largely unknown. We conducted a proteome-wide association study (PWAS) and summary-data-based mendelian randomization (SMR) analysis by integrating PD GWAS with proteome and protein quantitative trait loci (pQTL) data from human brain, plasma and CSF. We also performed a large transcriptome-wide association study (TWAS) and Fine-mapping of causal gene sets (FOCUS), leveraging joint-tissue imputation (JTI) prediction models of 22 tissues to identify and prioritize putatively causal genes. We further conducted PWAS, SMR, TWAS, and FOCUS using a multi-trait analysis of GWAS (MTAG) to identify additional PD risk genes to boost statistical power. In this large-scale study, we identified 16 genes whose genetically regulated protein abundance levels were associated with Parkinson's disease risk. We undertook a large-scale analysis of PD and correlated traits, through TWAS and FOCUS studies, and discovered 26 casual genes related to PD that had not been reported in previous TWAS. 5 genes (CD38, GPNMB, RAB29, TMEM175, TTC19) showed significant associations with PD at both the proteome-wide and transcriptome-wide levels. Our study provides new insights into the etiology and underlying genetic architecture of PD.
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Affiliation(s)
- Jing-Jing Shi
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Cheng-Yuan Mao
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Ya-Zhou Guo
- School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang, China
| | - Yu Fan
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Xiao-Yan Hao
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Shuang-Jie Li
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Jie Tian
- Zhengzhou Railway Vocational and Technical College, Zhengzhou 450000, Henan, China
| | - Zheng-Wei Hu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Meng-Jie Li
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Jia-Di Li
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Dong-Rui Ma
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Meng-Nan Guo
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Chun-Yan Zuo
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Yuan-Yuan Liang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Yu-Ming Xu
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou 450000, Henan, China
| | - Jian Yang
- School of Life Sciences, Westlake University, Hangzhou 310024, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou 310024, Zhejiang, China
| | - Chang-He Shi
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
- NHC Key Laboratory of Prevention and Treatment of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
- Henan Key Laboratory of Cerebrovascular Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou 450000, Henan, China
- Institute of Neuroscience, Zhengzhou University, Zhengzhou 450000, Henan, China
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12
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Alvarado CX, Makarious MB, Weller CA, Vitale D, Koretsky MJ, Bandres-Ciga S, Iwaki H, Levine K, Singleton A, Faghri F, Nalls MA, Leonard HL. omicSynth: An open multi-omic community resource for identifying druggable targets across neurodegenerative diseases. Am J Hum Genet 2024; 111:150-164. [PMID: 38181731 PMCID: PMC10806756 DOI: 10.1016/j.ajhg.2023.12.006] [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: 07/19/2023] [Revised: 12/04/2023] [Accepted: 12/04/2023] [Indexed: 01/07/2024] Open
Abstract
Treatments for neurodegenerative disorders remain rare, but recent FDA approvals, such as lecanemab and aducanumab for Alzheimer disease (MIM: 607822), highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use summary-data-based Mendelian randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer disease, 3 amyotrophic lateral sclerosis (MIM: 105400), 5 Lewy body dementia (MIM: 127750), 46 Parkinson disease (MIM: 605909), and 9 progressive supranuclear palsy (MIM: 601104) target genes passing multiple test corrections (pSMR_multi < 2.95 × 10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics, classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these, 69.8% are expressed in the disease-relevant cell type from single-nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development, and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as riluzole in Alzheimer disease. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community.
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Affiliation(s)
- Chelsea X Alvarado
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA; Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; UCL Movement Disorders Centre, University College London, London WC1N 3BG, UK
| | - Cory A Weller
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Dan Vitale
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Mathew J Koretsky
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
| | - Sara Bandres-Ciga
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
| | - Hirotaka Iwaki
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Kristin Levine
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Andrew Singleton
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Faraz Faghri
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Hampton L Leonard
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA; German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.
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13
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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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14
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Andersen MS, Leikfoss IS, Brorson IS, Cappelletti C, Bettencourt C, Toft M, Pihlstrøm L. Epigenome-wide association study of peripheral immune cell populations in Parkinson's disease. NPJ Parkinsons Dis 2023; 9:149. [PMID: 37903812 PMCID: PMC10616224 DOI: 10.1038/s41531-023-00594-x] [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: 06/13/2023] [Accepted: 10/19/2023] [Indexed: 11/01/2023] Open
Abstract
Understanding the contribution of immune mechanisms to Parkinson's disease pathogenesis is an important challenge, potentially of major therapeutic implications. To further elucidate the involvement of peripheral immune cells, we studied epigenome-wide DNA methylation in isolated populations of CD14+ monocytes, CD19+ B cells, CD4+ T cells, and CD8+ T cells from Parkinson's disease patients and healthy control participants. We included 25 patients with a maximum five years of disease duration and 25 controls, and isolated four immune cell populations from each fresh blood sample. Epigenome-wide DNA methylation profiles were generated from 186 samples using the Illumina MethylationEpic array and association with disease status was tested using linear regression models. We identified six differentially methylated CpGs in CD14+ monocytes and one in CD8 + T cells. Four differentially methylated regions were identified in monocytes, including a region upstream of RAB32, a gene that has been linked to LRRK2. Methylation upstream of RAB32 correlated negatively with mRNA expression, and RAB32 expression was upregulated in Parkinson's disease both in our samples and in summary statistics from a previous study. Our epigenome-wide association study of early Parkinson's disease provides evidence for methylation changes across different peripheral immune cell types, highlighting monocytes and the RAB32 locus. The findings were predominantly cell-type-specific, demonstrating the value of isolating purified cell populations for genomic studies.
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Affiliation(s)
- Maren Stolp Andersen
- Department of Neurology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | | | | | | | - Conceicao Bettencourt
- Department of Neurodegenerative Disease and Queen Square Brain Bank for Neurological Disorders, Queen Square Institute of Neurology, University College London, London, UK
| | - Mathias Toft
- Department of Neurology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Lasse Pihlstrøm
- Department of Neurology, Oslo University Hospital, Oslo, Norway.
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15
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Gu XJ, Su WM, Dou M, Jiang Z, Duan QQ, Yin KF, Cao B, Wang Y, Li GB, Chen YP. Expanding causal genes for Parkinson's disease via multi-omics analysis. NPJ Parkinsons Dis 2023; 9:146. [PMID: 37865667 PMCID: PMC10590374 DOI: 10.1038/s41531-023-00591-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 10/12/2023] [Indexed: 10/23/2023] Open
Abstract
Genome‑wide association studies (GWASs) have revealed numerous loci associated with Parkinson's disease (PD). However, some potential causal/risk genes were still not revealed and no etiological therapies are available. To find potential causal genes and explore genetically supported drug targets for PD is urgent. By integrating the expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) datasets from multiple tissues (blood, cerebrospinal fluid (CSF) and brain) and PD GWAS summary statistics, a pipeline combing Mendelian randomization (MR), Steiger filtering analysis, Bayesian colocalization, fine mapping, Protein-protein network and enrichment analysis were applied to identify potential causal genes for PD. As a result, GPNMB displayed a robust causal role for PD at the protein level in the blood, CSF and brain, and transcriptional level in the brain, while the protective role of CD38 (in brain pQTL and eQTL) was also identified. We also found inconsistent roles of DGKQ on PD between protein and mRNA levels. Another 9 proteins (CTSB, ARSA, SEC23IP, CD84, ENTPD1, FCGR2B, BAG3, SNCA, FCGR2A) were associated with the risk for PD based on only a single pQTL after multiple corrections. We also identified some proteins' interactions with known PD causative genes and therapeutic targets. In conclusion, this study suggested GPNMB, CD38, and DGKQ may act in the pathogenesis of PD, but whether the other proteins involved in PD needs more evidence. These findings would help to uncover the genes underlying PD and prioritize targets for future therapeutic interventions.
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Affiliation(s)
- Xiao-Jing Gu
- Mental Health Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei-Ming Su
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Meng Dou
- Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, Sichuan, China
| | - Zheng Jiang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qing-Qing Duan
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Kang-Fu Yin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Bei Cao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yi Wang
- Department of Pathophysiology, West China College of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, China
| | - Guo-Bo Li
- Key Laboratory of Drug Targeting and Drug Delivery System of Ministry of Education, West China School of Pharmacy, Sichuan University, Chengdu, China
| | - Yong-Ping Chen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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16
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Snijders GJLJ, de Paiva Lopes K, Sneeboer MAM, Muller BZ, Gigase FAJ, Vialle RA, Missall R, Kubler R, Raj T, Humphrey J, de Witte LD. The human microglia responsome: a resource to better understand microglia states in health and disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.12.562067. [PMID: 37873223 PMCID: PMC10592813 DOI: 10.1101/2023.10.12.562067] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Microglia, the immune cells of the brain, are increasingly implicated in neurodegenerative disorders through genetic studies. However, how genetic risk factors for these diseases are related to microglial gene expression, microglial function, and ultimately disease, is still largely unknown. Microglia change rapidly in response to alterations in their cellular environment, which is regulated through changes in transcriptional programs, which are as yet poorly understood. Here, we compared the effects of a set of inflammatory and restorative stimuli (lipopolysaccharide, interferon-gamma, resiquimod, tumor necrosis factor-alpha, adenosine triphosphate, dexamethasone, and interleukin-4) on human microglial cells from 67 different donors (N = 398 samples) at the gene and transcript level. We show that microglia from different anatomical brain regions show distinct responses to inflammatory stimuli. We observed a greater overlap between human stimulated microglia and human monocytes than with mouse microglia. We define specific microglial signatures across conditions which are highly relevant for a wide range of biological functions and complex human diseases. Finally, we used our stimulation signatures to interpret associations from Alzheimer's disease (AD) genetic studies and microglia by integrating our inflammatory gene expression profiles with common genetic variants to map cis -expression QTLs (eQTLs). Together, we provide the most comprehensive transcriptomic database of the human microglia responsome. Highlights RNA-sequencing of 398 human microglial samples exposed to six different triggers.Microglia from different anatomical regions show distinct stimulation responses.Responses in human microglia show a greater overlap with human monocytes than murine microglia.Mapping of response Quantitative Trait Loci identifies interactions between genotype and effect of stimulation on gene expression.Our atlas provides a reference map for interpreting microglia signatures in health and disease.
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17
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Lauritsen J, Romero-Ramos M. The systemic immune response in Parkinson's disease: focus on the peripheral immune component. Trends Neurosci 2023; 46:863-878. [PMID: 37598092 DOI: 10.1016/j.tins.2023.07.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 05/19/2023] [Accepted: 07/24/2023] [Indexed: 08/21/2023]
Abstract
During Parkinson's disease (PD), both the central nervous system (CNS) and peripheral nervous system (PNS) are affected. In parallel, innate immune cells respond early to neuronal changes and alpha-synuclein (α-syn) pathology. Moreover, some of the affected neuronal groups innervate organs with a relevant role in immunity. Consequently, not only microglia, but also peripheral immune cells are altered, resulting in a systemic immune response. Innate and adaptive immune cells may participate in the neurodegenerative process by acting peripherally, infiltrating the brain, or releasing mediators that can protect or harm neurons. However, the sequence of the changes and the significance of each immune compartment in the disease remain to be clarified. In this review, we describe current understanding of the peripheral immune response in PD and discuss the road ahead.
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Affiliation(s)
- Johanne Lauritsen
- Department of Biomedicine, Health Faculty & Danish Research Institute of Translational Neuroscience - DANDRITE, Aarhus University, Aarhus, Denmark
| | - Marina Romero-Ramos
- Department of Biomedicine, Health Faculty & Danish Research Institute of Translational Neuroscience - DANDRITE, Aarhus University, Aarhus, Denmark.
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18
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Jeong Y, Song J, Lee Y, Choi E, Won Y, Kim B, Jang W. A Transcriptome-Wide Analysis of Psoriasis: Identifying the Potential Causal Genes and Drug Candidates. Int J Mol Sci 2023; 24:11717. [PMID: 37511476 PMCID: PMC10380797 DOI: 10.3390/ijms241411717] [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: 05/31/2023] [Revised: 07/14/2023] [Accepted: 07/19/2023] [Indexed: 07/30/2023] Open
Abstract
Psoriasis is a chronic inflammatory skin disease characterized by cutaneous eruptions and pruritus. Because the genetic backgrounds of psoriasis are only partially revealed, an integrative and rigorous study is necessary. We conducted a transcriptome-wide association study (TWAS) with the new Genotype-Tissue Expression version 8 reference panels, including some tissue and multi-tissue panels that were not used previously. We performed tissue-specific heritability analyses on genome-wide association study data to prioritize the tissue panels for TWAS analysis. TWAS and colocalization (COLOC) analyses were performed with eight tissues from the single-tissue panels and the multi-tissue panels of context-specific genetics (CONTENT) to increase tissue specificity and statistical power. From TWAS, we identified the significant associations of 101 genes in the single-tissue panels and 64 genes in the multi-tissue panels, of which 26 genes were replicated in the COLOC. Functional annotation and network analyses identified that the genes were associated with psoriasis and/or immune responses. We also suggested drug candidates that interact with jointly significant genes through a conditional and joint analysis. Together, our findings may contribute to revealing the underlying genetic mechanisms and provide new insights into treatments for psoriasis.
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Affiliation(s)
- Yeonbin Jeong
- Department of Life Sciences, Dongguk University, Seoul 04620, Republic of Korea
| | - Jaeseung Song
- Department of Life Sciences, Dongguk University, Seoul 04620, Republic of Korea
| | - Yubin Lee
- Department of Life Sciences, Dongguk University, Seoul 04620, Republic of Korea
| | - Eunyoung Choi
- Department of Life Sciences, Dongguk University, Seoul 04620, Republic of Korea
| | - Youngtae Won
- Department of Life Sciences, Dongguk University, Seoul 04620, Republic of Korea
| | - Byunghyuk Kim
- Department of Life Sciences, Dongguk University-Seoul, Goyang 10326, Republic of Korea
| | - Wonhee Jang
- Department of Life Sciences, Dongguk University, Seoul 04620, Republic of Korea
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19
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Alvarado CX, Makarious MB, Weller CA, Vitale D, Koretsky MJ, Bandres-Ciga S, Iwaki H, Levine K, Singleton A, Faghri F, Nalls MA, Leonard HL. omicSynth: an Open Multi-omic Community Resource for Identifying Druggable Targets across Neurodegenerative Diseases. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.06.23288266. [PMID: 37090611 PMCID: PMC10120805 DOI: 10.1101/2023.04.06.23288266] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Treatments for neurodegenerative disorders remain rare, although recent FDA approvals, such as Lecanemab and Aducanumab for Alzheimer's Disease, highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use Summary-data-based Mendelian Randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer's disease, 3 amyotrophic lateral sclerosis, 5 Lewy body dementia, 46 Parkinson's disease, and 9 Progressive supranuclear palsy target genes passing multiple test corrections (pSMR_multi < 2.95×10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics - classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these 69.8% are expressed in the disease relevant cell type from single nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as Riluzole in AD. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community [https://nih-card-ndd-smr-home-syboky.streamlit.app/].
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Affiliation(s)
- Chelsea X. Alvarado
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Mary B. Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK, WC1N 3BG
- UCL Movement Disorders Centre, University College London, London, UK, WC1N 3BG
| | - Cory A. Weller
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Dan Vitale
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Mathew J. Koretsky
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Sara Bandres-Ciga
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Hirotaka Iwaki
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Kristin Levine
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Andrew Singleton
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Faraz Faghri
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Mike A. Nalls
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Hampton L. Leonard
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
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20
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Sosero YL, Gan‐Or Z. LRRK2 and Parkinson's disease: from genetics to targeted therapy. Ann Clin Transl Neurol 2023; 10:850-864. [PMID: 37021623 PMCID: PMC10270275 DOI: 10.1002/acn3.51776] [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: 02/06/2023] [Revised: 03/07/2023] [Accepted: 03/27/2023] [Indexed: 04/07/2023] Open
Abstract
LRRK2 variants are implicated in both familial and sporadic PD. LRRK2-PD has a generally benign clinical presentation and variable pathology, with inconsistent presence of Lewy bodies and marked Alzheimer's disease pathology. The mechanisms underlying LRRK2-PD are still unclear, but inflammation, vesicle trafficking, lysosomal homeostasis, and ciliogenesis have been suggested, among others. As novel therapies targeting LRRK2 are under development, understanding the role and function of LRRK2 in PD is becoming increasingly important. Here, we outline the epidemiological, pathophysiological, and clinical features of LRRK2-PD, and discuss the arising therapeutic approaches targeting LRRK2 and possible future directions for research.
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Affiliation(s)
- Yuri L. Sosero
- Montreal Neurological InstituteMcGill UniversityMontréalQuébecH3A 1A1Canada
- Department of Human GeneticsMcGill UniversityMontréalQuébecH3A 1A1Canada
| | - Ziv Gan‐Or
- Montreal Neurological InstituteMcGill UniversityMontréalQuébecH3A 1A1Canada
- Department of Human GeneticsMcGill UniversityMontréalQuébecH3A 1A1Canada
- Department of Neurology and NeurosurgeryMcGill UniversityMontréalQuébecH3A 0G4Canada
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21
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Choong CJ, Aguirre C, Kakuda K, Beck G, Nakanishi H, Kimura Y, Shimma S, Nabekura K, Hideshima M, Doi J, Yamaguchi K, Nakajima K, Wadayama T, Hayakawa H, Baba K, Ogawa K, Takeuchi T, Badawy SMM, Murayama S, Nagano S, Goto Y, Miyanoiri Y, Nagai Y, Mochizuki H, Ikenaka K. Phosphatidylinositol-3,4,5-trisphosphate interacts with alpha-synuclein and initiates its aggregation and formation of Parkinson's disease-related fibril polymorphism. Acta Neuropathol 2023; 145:573-595. [PMID: 36939875 PMCID: PMC10119223 DOI: 10.1007/s00401-023-02555-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 02/28/2023] [Accepted: 03/01/2023] [Indexed: 03/21/2023]
Abstract
Lipid interaction with α-synuclein (αSyn) has been long implicated in the pathogenesis of Parkinson's disease (PD). However, it has not been fully determined which lipids are involved in the initiation of αSyn aggregation in PD. Here exploiting genetic understanding associating the loss-of-function mutation in Synaptojanin 1 (SYNJ1), a phosphoinositide phosphatase, with familial PD and analysis of postmortem PD brains, we identified a novel lipid molecule involved in the toxic conversion of αSyn and its relation to PD. We first established a SYNJ1 knockout cell model and found SYNJ1 depletion increases the accumulation of pathological αSyn. Lipidomic analysis revealed SYNJ1 depletion elevates the level of its substrate phosphatidylinositol-3,4,5-trisphosphate (PIP3). We then employed Caenorhabditis elegans model to examine the effect of SYNJ1 defect on the neurotoxicity of αSyn. Mutations in SYNJ1 accelerated the accumulation of αSyn aggregation and induced locomotory defects in the nematodes. These results indicate that functional loss of SYNJ1 promotes the pathological aggregation of αSyn via the dysregulation of its substrate PIP3, leading to the aggravation of αSyn-mediated neurodegeneration. Treatment of cultured cell line and primary neurons with PIP3 itself or with PIP3 phosphatase inhibitor resulted in intracellular formation of αSyn inclusions. Indeed, in vitro protein-lipid overlay assay validated that phosphoinositides, especially PIP3, strongly interact with αSyn. Furthermore, the aggregation assay revealed that PIP3 not only accelerates the fibrillation of αSyn, but also induces the formation of fibrils sharing conformational and biochemical characteristics similar to the fibrils amplified from the brains of PD patients. Notably, the immunohistochemical and lipidomic analyses on postmortem brain of patients with sporadic PD showed increased PIP3 level and its colocalization with αSyn. Taken together, PIP3 dysregulation promotes the pathological aggregation of αSyn and increases the risk of developing PD, and PIP3 represents a potent target for intervention in PD.
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Affiliation(s)
- Chi-Jing Choong
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - César Aguirre
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Keita Kakuda
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Goichi Beck
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | | | - Yasuyoshi Kimura
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Shuichi Shimma
- Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Kei Nabekura
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Makoto Hideshima
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Junko Doi
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Keiichi Yamaguchi
- Global Center for Medical Engineering and Informatics, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Kichitaro Nakajima
- Global Center for Medical Engineering and Informatics, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Tomoya Wadayama
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Hideki Hayakawa
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Kousuke Baba
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Kotaro Ogawa
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Toshihide Takeuchi
- Department of Neurology, Kindai University, 3-4-1 Kowakae, Higashiosaka City, Osaka, 577-8502, Japan
| | - Shaymaa Mohamed Mohamed Badawy
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.,Department of Agricultural Biochemistry, Faculty of Agriculture, Zagazig University, Zagazig, Egypt
| | - Shigeo Murayama
- Brain Bank for Neurodevelopmental, Neurological and Psychiatric Disorders, United Graduate School of Child Development, Osaka University, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Seiichi Nagano
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Yuji Goto
- Global Center for Medical Engineering and Informatics, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Yohei Miyanoiri
- Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - Yoshitaka Nagai
- Department of Neurology, Kindai University, 3-4-1 Kowakae, Higashiosaka City, Osaka, 577-8502, Japan
| | - Hideki Mochizuki
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
| | - Kensuke Ikenaka
- Department of Neurology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.
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22
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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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23
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Lee RMQ, Koh TW. Genetic modifiers of synucleinopathies-lessons from experimental models. OXFORD OPEN NEUROSCIENCE 2023; 2:kvad001. [PMID: 38596238 PMCID: PMC10913850 DOI: 10.1093/oons/kvad001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 03/04/2023] [Accepted: 03/07/2023] [Indexed: 04/11/2024]
Abstract
α-Synuclein is a pleiotropic protein underlying a group of progressive neurodegenerative diseases, including Parkinson's disease and dementia with Lewy bodies. Together, these are known as synucleinopathies. Like all neurological diseases, understanding of disease mechanisms is hampered by the lack of access to biopsy tissues, precluding a real-time view of disease progression in the human body. This has driven researchers to devise various experimental models ranging from yeast to flies to human brain organoids, aiming to recapitulate aspects of synucleinopathies. Studies of these models have uncovered numerous genetic modifiers of α-synuclein, most of which are evolutionarily conserved. This review discusses what we have learned about disease mechanisms from these modifiers, and ways in which the study of modifiers have supported ongoing efforts to engineer disease-modifying interventions for synucleinopathies.
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Affiliation(s)
- Rachel Min Qi Lee
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore, 117604, Singapore
| | - Tong-Wey Koh
- Temasek Life Sciences Laboratory, 1 Research Link, Singapore, 117604, Singapore
- Department of Biological Sciences, National University of Singapore, Block S3 #05-01, 16 Science Drive 4, Singapore, 117558, Singapore
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24
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Huggett SB, Ikeda AS, Yuan Q, Benca-Bachman CE, Palmer RHC. Genome- and transcriptome-wide splicing associations with alcohol use disorder. Sci Rep 2023; 13:3950. [PMID: 36894673 PMCID: PMC9998611 DOI: 10.1038/s41598-023-30926-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 03/03/2023] [Indexed: 03/11/2023] Open
Abstract
Genetic mechanisms of alternative mRNA splicing have been shown in the brain for a variety of neuropsychiatric traits, but not substance use disorders. Our study utilized RNA-sequencing data on alcohol use disorder (AUD) in four brain regions (n = 56; ages 40-73; 100% 'Caucasian'; PFC, NAc, BLA and CEA) and genome-wide association data on AUD (n = 435,563, ages 22-90; 100% European-American). Polygenic scores of AUD were associated with AUD-related alternative mRNA splicing in the brain. We identified 714 differentially spliced genes between AUD vs controls, which included both putative addiction genes and novel gene targets. We found 6463 splicing quantitative trait loci (sQTLs) that linked to the AUD differentially spliced genes. sQTLs were enriched in loose chromatin genomic regions and downstream gene targets. Additionally, the heritability of AUD was enriched for DNA variants in and around differentially spliced genes associated with AUD. Our study also performed splicing transcriptome-wide association studies (TWASs) of AUD and other drug use traits that unveiled specific genes for follow-up and splicing correlations across SUDs. Finally, we showed that differentially spliced genes between AUD vs control were also associated with primate models of chronic alcohol consumption in similar brain regions. Our study found substantial genetic contributions of alternative mRNA splicing in AUD.
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Affiliation(s)
- Spencer B Huggett
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
| | - Ami S Ikeda
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
| | - Qingyue Yuan
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
| | - Chelsie E Benca-Bachman
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA
| | - Rohan H C Palmer
- Behavioral Genetics of Addiction Laboratory, Department of Psychology, Emory University, 36 Eagle Row, Atlanta, GA, 30322, USA.
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25
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Bogetofte H, Ryan BJ, Jensen P, Schmidt SI, Vergoossen DLE, Barnkob MB, Kiani LN, Chughtai U, Heon-Roberts R, Caiazza MC, McGuinness W, Márquez-Gómez R, Vowles J, Bunn FS, Brandes J, Kilfeather P, Connor JP, Fernandes HJR, Caffrey TM, Meyer M, Cowley SA, Larsen MR, Wade-Martins R. Post-translational proteomics platform identifies neurite outgrowth impairments in Parkinson's disease GBA-N370S dopamine neurons. Cell Rep 2023; 42:112180. [PMID: 36870058 DOI: 10.1016/j.celrep.2023.112180] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 10/04/2022] [Accepted: 02/13/2023] [Indexed: 03/05/2023] Open
Abstract
Variants at the GBA locus, encoding glucocerebrosidase, are the strongest common genetic risk factor for Parkinson's disease (PD). To understand GBA-related disease mechanisms, we use a multi-part-enrichment proteomics and post-translational modification (PTM) workflow, identifying large numbers of dysregulated proteins and PTMs in heterozygous GBA-N370S PD patient induced pluripotent stem cell (iPSC) dopamine neurons. Alterations in glycosylation status show disturbances in the autophagy-lysosomal pathway, which concur with upstream perturbations in mammalian target of rapamycin (mTOR) activation in GBA-PD neurons. Several native and modified proteins encoded by PD-associated genes are dysregulated in GBA-PD neurons. Integrated pathway analysis reveals impaired neuritogenesis in GBA-PD neurons and identify tau as a key pathway mediator. Functional assays confirm neurite outgrowth deficits and identify impaired mitochondrial movement in GBA-PD neurons. Furthermore, pharmacological rescue of glucocerebrosidase activity in GBA-PD neurons improves the neurite outgrowth deficit. Overall, this study demonstrates the potential of PTMomics to elucidate neurodegeneration-associated pathways and potential drug targets in complex disease models.
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Affiliation(s)
- Helle Bogetofte
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK; Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, UK; Department of Neurobiology Research, Institute of Molecular Medicine, University of Southern Denmark, 5000 Odense C, Denmark; Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark
| | - Brent J Ryan
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK; Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, UK.
| | - Pia Jensen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark
| | - Sissel I Schmidt
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK; Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, UK; Department of Neurobiology Research, Institute of Molecular Medicine, University of Southern Denmark, 5000 Odense C, Denmark
| | - Dana L E Vergoossen
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK
| | - Mike B Barnkob
- Centre for Cellular Immunotherapy of Haematological Cancer Odense (CITCO), Department of Clinical Immunology, Odense University Hospital, University of Southern Denmark, 5000 Odense C, Denmark
| | - Lisa N Kiani
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK
| | - Uroosa Chughtai
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK
| | - Rachel Heon-Roberts
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK; Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, UK
| | - Maria Claudia Caiazza
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK; Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, UK
| | - William McGuinness
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK; Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, UK
| | - Ricardo Márquez-Gómez
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK; Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, UK
| | - Jane Vowles
- James Martin Stem Cell Facility, Sir William Dunn School of Pathology, University of Oxford, Oxford OX1 3RE, UK
| | - Fiona S Bunn
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK
| | - Janine Brandes
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK
| | - Peter Kilfeather
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK; Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, UK
| | - Jack P Connor
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK; Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, UK
| | - Hugo J R Fernandes
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK; Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, UK
| | - Tara M Caffrey
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK
| | - Morten Meyer
- Department of Neurobiology Research, Institute of Molecular Medicine, University of Southern Denmark, 5000 Odense C, Denmark; Department of Neurology, Odense University Hospital, 5000 Odense C, Denmark
| | - Sally A Cowley
- James Martin Stem Cell Facility, Sir William Dunn School of Pathology, University of Oxford, Oxford OX1 3RE, UK
| | - Martin R Larsen
- Department of Biochemistry and Molecular Biology, University of Southern Denmark, 5230 Odense M, Denmark
| | - Richard Wade-Martins
- Oxford Parkinson's Disease Centre, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3QX, UK; Kavli Institute for Nanoscience Discovery, University of Oxford, Dorothy Crowfoot Hodgkin Building, South Parks Road, Oxford OX1 3QU, UK.
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Mata I, Salles P, Cornejo-Olivas M, Saffie P, Ross OA, Reed X, Bandres-Ciga S. LRRK2: Genetic mechanisms vs genetic subtypes. HANDBOOK OF CLINICAL NEUROLOGY 2023; 193:133-154. [PMID: 36803807 DOI: 10.1016/b978-0-323-85555-6.00018-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
In 2004, the identification of pathogenic variants in the LRRK2 gene across several families with autosomal dominant late-onset Parkinson's disease (PD) revolutionized our understanding of the role of genetics in PD. Previous beliefs that genetics in PD was limited to rare early-onset or familial forms of the disease were quickly dispelled. Currently, we recognize LRRK2 p.G2019S as the most common genetic cause of both sporadic and familial PD, with more than 100,000 affected carriers across the globe. The frequency of LRRK2 p.G2019S is also highly variable across populations, with some regions of Asian or Latin America reporting close to 0%, contrasting to Ashkenazi Jews or North African Berbers reporting up to 13% and 40%, respectively. Patients with LRRK2 pathogenic variants are clinically and pathologically heterogeneous, highlighting the age-related variable penetrance that also characterizes LRRK2-related disease. Indeed, the majority of patients with LRRK2-related disease are characterized by a relatively mild Parkinsonism with less motor symptoms with variable presence of α-synuclein and/or tau aggregates, with pathologic pleomorphism widely described. At a functional cellular level, it is likely that pathogenic variants mediate a toxic gain-of-function of the LRRK2 protein resulting in increased kinase activity perhaps in a cell-specific manner; by contrast, some LRRK2 variants appear to be protective reducing PD risk by decreasing the kinase activity. Therefore, employing this information to define appropriate patient populations for clinical trials of targeted kinase LRRK2 inhibition strategies is very promising and demonstrates a potential future application for PD using precision medicine.
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Affiliation(s)
- Ignacio Mata
- Genomic Medicine Institute (GMI), Cleveland Clinic, Cleveland, OH, United States.
| | - Philippe Salles
- Corporación Centro de Trastornos del Movimiento (CETRAM), Lo Espejo, Santiago, Chile
| | - Mario Cornejo-Olivas
- Neurogenetics Research Center, Instituto Nacional de Ciencias Neurológicas, Lima, Peru
| | - Paula Saffie
- Corporación Centro de Trastornos del Movimiento (CETRAM), Lo Espejo, Santiago, Chile
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, United States
| | - Xylena Reed
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, United States
| | - Sara Bandres-Ciga
- Laboratory of Neurogenetics and Center for Alzheimer's and Related Dementias, National Institute on Aging, National Institutes of Health, Bethesda, MD, United States
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27
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Gui S, Martinez-Rivas FJ, Wen W, Meng M, Yan J, Usadel B, Fernie AR. Going broad and deep: sequencing-driven insights into plant physiology, evolution, and crop domestication. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2023; 113:446-459. [PMID: 36534120 DOI: 10.1111/tpj.16070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 12/12/2022] [Accepted: 12/13/2022] [Indexed: 06/17/2023]
Abstract
Deep sequencing is a term that has become embedded in the plant genomic literature in recent years and with good reason. A torrent of (largely) high-quality genomic and transcriptomic data has been collected and most of this has been publicly released. Indeed, almost 1000 plant genomes have been reported (www.plabipd.de) and the 2000 Plant Transcriptomes Project has long been completed. The EarthBioGenome project will dwarf even these milestones. That said, massive progress in understanding plant physiology, evolution, and crop domestication has been made by sequencing broadly (across a species) as well as deeply (within a single individual). We will outline the current state of the art in genome and transcriptome sequencing before we briefly review the most visible of these broad approaches, namely genome-wide association and transcriptome-wide association studies, as well as the compilation of pangenomes. This will include both (i) the most commonly used methods reliant on single nucleotide polymorphisms and short InDels and (ii) more recent examples which consider structural variants. We will subsequently present case studies exemplifying how their application has brought insight into either plant physiology or evolution and crop domestication. Finally, we will provide conclusions and an outlook as to the perspective for the extension of such approaches to different species, tissues, and biological processes.
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Affiliation(s)
- Songtao Gui
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | | | - Weiwei Wen
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Minghui Meng
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Jianbing Yan
- National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430070, China
| | - Björn Usadel
- IBG-4 Bioinformatics, Forschungszentrum Jülich, Wilhelm Johnen Str, BioSc, 52428, Jülich, Germany
- Institute for Biological Data Science, CEPLAS, Heinrich Heine University, 40225, Düsseldorf, Germany
| | - Alisdair R Fernie
- Max-Planck-Institute of Molecular Plant Physiology, Am Mühlenberg 1, Potsdam-Golm, 14476, Germany
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28
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Megat S, Mora N, Sanogo J, Roman O, Catanese A, Alami NO, Freischmidt A, Mingaj X, De Calbiac H, Muratet F, Dirrig-Grosch S, Dieterle S, Van Bakel N, Müller K, Sieverding K, Weishaupt J, Andersen PM, Weber M, Neuwirth C, Margelisch M, Sommacal A, Van Eijk KR, Veldink JH, Lautrette G, Couratier P, Camuzat A, Le Ber I, Grassano M, Chio A, Boeckers T, Ludolph AC, Roselli F, Yilmazer-Hanke D, Millecamps S, Kabashi E, Storkebaum E, Sellier C, Dupuis L. Integrative genetic analysis illuminates ALS heritability and identifies risk genes. Nat Commun 2023; 14:342. [PMID: 36670122 PMCID: PMC9860017 DOI: 10.1038/s41467-022-35724-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Accepted: 12/21/2022] [Indexed: 01/22/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) has substantial heritability, in part shared with fronto-temporal dementia (FTD). We show that ALS heritability is enriched in splicing variants and in binding sites of 6 RNA-binding proteins including TDP-43 and FUS. A transcriptome wide association study (TWAS) identified 6 loci associated with ALS, including in NUP50 encoding for the nucleopore basket protein NUP50. Independently, rare variants in NUP50 were associated with ALS risk (P = 3.71.10-03; odds ratio = 3.29; 95%CI, 1.37 to 7.87) in a cohort of 9,390 ALS/FTD patients and 4,594 controls. Cells from one patient carrying a NUP50 frameshift mutation displayed a decreased level of NUP50. Loss of NUP50 leads to death of cultured neurons, and motor defects in Drosophila and zebrafish. Thus, our study identifies alterations in splicing in neurons as critical in ALS and provides genetic evidence linking nuclear pore defects to ALS.
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Affiliation(s)
- Salim Megat
- Université de Strasbourg, Inserm, Mécanismes centraux et périphériques de la neurodégénérescence, UMR-S1118, Centre de Recherches en Biomédecine, Strasbourg, France.
| | - Natalia Mora
- Department of Molecular Neurobiology, Donders Institute for Brain, Cognition and Behaviour and Faculty of Science, Radboud University, Nijmegen, Netherlands
| | - Jason Sanogo
- Université de Strasbourg, Inserm, Mécanismes centraux et périphériques de la neurodégénérescence, UMR-S1118, Centre de Recherches en Biomédecine, Strasbourg, France
| | - Olga Roman
- Université de Strasbourg, Inserm, Mécanismes centraux et périphériques de la neurodégénérescence, UMR-S1118, Centre de Recherches en Biomédecine, Strasbourg, France
| | - Alberto Catanese
- Institute of Anatomy and Cell Biology, Ulm University, Ulm, Germany
- German Center for Neurodegenerative Diseases (DZNE) Ulm, Ulm, Germany
| | - Najwa Ouali Alami
- Clinical Neuroanatomy, Department of Neurology, Ulm University, Ulm, Germany
| | - Axel Freischmidt
- German Center for Neurodegenerative Diseases (DZNE) Ulm, Ulm, Germany
- Department of Neurology, Ulm University, Ulm, Germany
| | - Xhuljana Mingaj
- Laboratory of Translational Research for Neurological Disorders, Imagine Institute, Université de Paris, INSERM UMR 1163, 75015, Paris, France
| | - Hortense De Calbiac
- Laboratory of Translational Research for Neurological Disorders, Imagine Institute, Université de Paris, INSERM UMR 1163, 75015, Paris, France
| | - François Muratet
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
| | - Sylvie Dirrig-Grosch
- Université de Strasbourg, Inserm, Mécanismes centraux et périphériques de la neurodégénérescence, UMR-S1118, Centre de Recherches en Biomédecine, Strasbourg, France
| | - Stéphane Dieterle
- Université de Strasbourg, Inserm, Mécanismes centraux et périphériques de la neurodégénérescence, UMR-S1118, Centre de Recherches en Biomédecine, Strasbourg, France
| | - Nick Van Bakel
- Department of Molecular Neurobiology, Donders Institute for Brain, Cognition and Behaviour and Faculty of Science, Radboud University, Nijmegen, Netherlands
| | - Kathrin Müller
- German Center for Neurodegenerative Diseases (DZNE) Ulm, Ulm, Germany
- Institute of Human Genetics, Ulm University, Ulm, Germany
| | | | - Jochen Weishaupt
- Division for Neurodegenerative Diseases, Neurology Department, University Medicine Mannheim, Heidelberg University, Mannheim, Germany
| | | | - Markus Weber
- Neuromuscular Disease Unit/ALS Clinic, Kantonsspital St. Gallen, St. Gallen, Switzerland
| | - Christoph Neuwirth
- Neuromuscular Disease Unit/ALS Clinic, Kantonsspital St. Gallen, St. Gallen, Switzerland
| | - Markus Margelisch
- Institute for Pathology, Kanstonsspital St. Gallen, St. Gallen, Switzerland
| | - Andreas Sommacal
- Institute for Pathology, Kanstonsspital St. Gallen, St. Gallen, Switzerland
| | - Kristel R Van Eijk
- Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Jan H Veldink
- Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Géraldine Lautrette
- Service de Neurologie, Centre de Référence SLA et autres maladies du neurone moteur, CHU Dupuytren 1, Limoges, France
| | - Philippe Couratier
- Service de Neurologie, Centre de Référence SLA et autres maladies du neurone moteur, CHU Dupuytren 1, Limoges, France
| | - Agnès Camuzat
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
| | - Isabelle Le Ber
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
| | - Maurizio Grassano
- ALS Center "Rita Levi Montalcini" Department of Neuroscience, University of Turin, Turin, Italy
| | - Adriano Chio
- ALS Center "Rita Levi Montalcini" Department of Neuroscience, University of Turin, Turin, Italy
| | - Tobias Boeckers
- Institute of Anatomy and Cell Biology, Ulm University, Ulm, Germany
- German Center for Neurodegenerative Diseases (DZNE) Ulm, Ulm, Germany
| | - Albert C Ludolph
- German Center for Neurodegenerative Diseases (DZNE) Ulm, Ulm, Germany
- Department of Neurology, Ulm University, Ulm, Germany
| | - Francesco Roselli
- German Center for Neurodegenerative Diseases (DZNE) Ulm, Ulm, Germany
- Department of Neurology, Ulm University, Ulm, Germany
| | | | - Stéphanie Millecamps
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France
| | - Edor Kabashi
- Laboratory of Translational Research for Neurological Disorders, Imagine Institute, Université de Paris, INSERM UMR 1163, 75015, Paris, France
| | - Erik Storkebaum
- Department of Molecular Neurobiology, Donders Institute for Brain, Cognition and Behaviour and Faculty of Science, Radboud University, Nijmegen, Netherlands
| | - Chantal Sellier
- Université de Strasbourg, Inserm, Mécanismes centraux et périphériques de la neurodégénérescence, UMR-S1118, Centre de Recherches en Biomédecine, Strasbourg, France
| | - Luc Dupuis
- Université de Strasbourg, Inserm, Mécanismes centraux et périphériques de la neurodégénérescence, UMR-S1118, Centre de Recherches en Biomédecine, Strasbourg, France.
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29
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Humphrey J, Venkatesh S, Hasan R, Herb JT, de Paiva Lopes K, Küçükali F, Byrska-Bishop M, Evani US, Narzisi G, Fagegaltier D, Sleegers K, Phatnani H, Knowles DA, Fratta P, Raj T. Integrative transcriptomic analysis of the amyotrophic lateral sclerosis spinal cord implicates glial activation and suggests new risk genes. Nat Neurosci 2023; 26:150-162. [PMID: 36482247 DOI: 10.1038/s41593-022-01205-3] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 10/13/2022] [Indexed: 12/13/2022]
Abstract
Amyotrophic lateral sclerosis (ALS) is a progressively fatal neurodegenerative disease affecting motor neurons in the brain and spinal cord. In this study, we investigated gene expression changes in ALS via RNA sequencing in 380 postmortem samples from cervical, thoracic and lumbar spinal cord segments from 154 individuals with ALS and 49 control individuals. We observed an increase in microglia and astrocyte gene expression, accompanied by a decrease in oligodendrocyte gene expression. By creating a gene co-expression network in the ALS samples, we identified several activated microglia modules that negatively correlate with retrospective disease duration. We mapped molecular quantitative trait loci and found several potential ALS risk loci that may act through gene expression or splicing in the spinal cord and assign putative cell types for FNBP1, ACSL5, SH3RF1 and NFASC. Finally, we outline how common genetic variants associated with splicing of C9orf72 act as proxies for the well-known repeat expansion, and we use the same mechanism to suggest ATXN3 as a putative risk gene.
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Affiliation(s)
- Jack Humphrey
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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.
| | - Sanan Venkatesh
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Pamela Sklar Division of Psychiatric Genomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Rahat Hasan
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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
| | - Jake T Herb
- Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Katia de Paiva Lopes
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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
| | - Fahri Küçükali
- Complex Genetics of Alzheimer's Disease Group, Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | | | | | | | - Delphine Fagegaltier
- New York Genome Center, New York, NY, USA
- Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY, USA
| | - Kristel Sleegers
- Complex Genetics of Alzheimer's Disease Group, Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Hemali Phatnani
- New York Genome Center, New York, NY, USA
- Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY, USA
- Department of Neurology, Columbia University Irving Medical Center, Columbia University, New York, NY, USA
| | - David A Knowles
- New York Genome Center, New York, NY, USA
- Department of Computer Science, Columbia University, New York, NY, USA
| | - Pietro Fratta
- Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, London, UK
| | - Towfique Raj
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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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30
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Ren M, Yang Y, Heng KHY, Ng LY, Chong CYY, Ng YT, Gorur-Shandilya S, Lee RMQ, Lim KL, Zhang J, Koh TW. MED13 and glycolysis are conserved modifiers of α-synuclein-associated neurodegeneration. Cell Rep 2022; 41:111852. [PMID: 36543134 DOI: 10.1016/j.celrep.2022.111852] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 10/04/2022] [Accepted: 11/29/2022] [Indexed: 12/24/2022] Open
Abstract
α-Synuclein (α-syn) is important in synucleinopathies such as Parkinson's disease (PD). While genome-wide association studies (GWASs) of synucleinopathies have identified many risk loci, the underlying genes have not been shown for most loci. Using Drosophila, we screened 3,471 mutant chromosomes for genetic modifiers of α-synuclein and identified 12 genes. Eleven modifiers have human orthologs associated with diseases, including MED13 and CDC27, which lie within PD GWAS loci. Drosophila Skd/Med13 and glycolytic enzymes are co-upregulated by α-syn-associated neurodegeneration. While elevated α-syn compromises mitochondrial function, co-expressing skd/Med13 RNAi and α-syn synergistically increase the ratio of oxidized-to-reduced glutathione. The resulting neurodegeneration can be suppressed by overexpressing a glycolytic enzyme or treatment with deferoxamine, suggesting that compensatory glycolysis is neuroprotective. In addition, the functional relationship between α-synuclein, MED13, and glycolytic enzymes is conserved between flies and mice. We propose that hypoxia-inducible factor and MED13 are part of a druggable pathway for PD.
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Affiliation(s)
- Mengda Ren
- Temasek Life Sciences Laboratory, Singapore 117604, Singapore; Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308207, Singapore; National Neuroscience Institute, Singapore 308433, Singapore
| | - Ying Yang
- Department of Pathology, Zhejiang University First Affiliated Hospital and School of Medicine, Hangzhou, Zhejiang 310002, China
| | | | - Lu Yi Ng
- Temasek Life Sciences Laboratory, Singapore 117604, Singapore
| | | | - Yan Ting Ng
- Temasek Life Sciences Laboratory, Singapore 117604, Singapore
| | | | - Rachel Min Qi Lee
- Temasek Life Sciences Laboratory, Singapore 117604, Singapore; Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore
| | - Kah Leong Lim
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308207, Singapore; National Neuroscience Institute, Singapore 308433, Singapore
| | - Jing Zhang
- Department of Pathology, Zhejiang University First Affiliated Hospital and School of Medicine, Hangzhou, Zhejiang 310002, China; China National Health and Disease Human Brain Tissue Resource Center, Hangzhou, Zhejiang 310002, China
| | - Tong-Wey Koh
- Temasek Life Sciences Laboratory, Singapore 117604, Singapore; Department of Biological Sciences, National University of Singapore, Singapore 117558, Singapore.
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31
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Dang X, Zhang Z, Luo XJ. Mendelian Randomization Study Using Dopaminergic Neuron-Specific eQTL Nominates Potential Causal Genes for Parkinson's Disease. Mov Disord 2022; 37:2451-2456. [PMID: 36177513 DOI: 10.1002/mds.29239] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 09/02/2022] [Accepted: 09/13/2022] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Large-scale genome-wide association studies (GWASs) have reported multiple risk variants for Parkinson's disease (PD). However, little is known about how these reported risk variants confer risk of PD. OBJECTIVE To nominate genes whose genetically regulated expression in dopaminergic neurons may have a causal role in PD. METHODS We conducted a two-sample Mendelian randomization (MR) study by integrating large-scale genome-wide associations and expression quantitative trait loci (eQTL) data from dopaminergic neurons. RESULTS MR analysis nominated 10 risk genes whose genetically regulated expression in dopaminergic neurons may have a causal role in PD. These MR significant genes include FAM200B, NDUFAF2, NUP42, SH3GL2, STX1B, CCDC189, KAT8, PRSS36, VAMP4, and ZSWIM7. CONCLUSIONS We report the first MR study of PD by using dopaminergic neuron-specific eQTL and nominate novel risk genes for PD. Further functional characterization of the nominated risk genes will provide mechanistic insights into PD pathogenesis and potential therapeutic targets. © 2022 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Xinglun Dang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China
| | - Zhijun Zhang
- Zhongda Hospital, School of Life Sciences and Technology, Advanced Institute for Life and Health, Southeast University, Nanjing, China.,Department of Neurology, Affiliated Zhongda Hospital, Institution of Neuropsychiatry, Southeast University, Nanjing, China.,Department of Mental Health and Public Health, Faculty of Life and Health Sciences, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Xiong-Jian Luo
- Zhongda Hospital, School of Life Sciences and Technology, Advanced Institute for Life and Health, Southeast University, Nanjing, China.,Department of Neurology, Affiliated Zhongda Hospital, Institution of Neuropsychiatry, Southeast University, Nanjing, China
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32
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Castaldi PJ, Abood A, Farber CR, Sheynkman GM. Bridging the splicing gap in human genetics with long-read RNA sequencing: finding the protein isoform drivers of disease. Hum Mol Genet 2022; 31:R123-R136. [PMID: 35960994 PMCID: PMC9585682 DOI: 10.1093/hmg/ddac196] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 08/08/2022] [Accepted: 08/09/2022] [Indexed: 02/04/2023] Open
Abstract
Aberrant splicing underlies many human diseases, including cancer, cardiovascular diseases and neurological disorders. Genome-wide mapping of splicing quantitative trait loci (sQTLs) has shown that genetic regulation of alternative splicing is widespread. However, identification of the corresponding isoform or protein products associated with disease-associated sQTLs is challenging with short-read RNA-seq, which cannot precisely characterize full-length transcript isoforms. Furthermore, contemporary sQTL interpretation often relies on reference transcript annotations, which are incomplete. Solutions to these issues may be found through integration of newly emerging long-read sequencing technologies. Long-read sequencing offers the capability to sequence full-length mRNA transcripts and, in some cases, to link sQTLs to transcript isoforms containing disease-relevant protein alterations. Here, we provide an overview of sQTL mapping approaches, the use of long-read sequencing to characterize sQTL effects on isoforms, the linkage of RNA isoforms to protein-level functions and comment on future directions in the field. Based on recent progress, long-read RNA sequencing promises to be part of the human disease genetics toolkit to discover and treat protein isoforms causing rare and complex diseases.
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Affiliation(s)
- Peter J Castaldi
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
- Division of General Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Abdullah Abood
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Charles R Farber
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
- Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Gloria M Sheynkman
- Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
- Department of Biochemistry and Molecular Genetics, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
- Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA 22903, USA
- UVA Comprehensive Cancer Center, University of Virginia, Charlottesville, VA 22903, USA
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33
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Kim G, Jang G, Song J, Kim D, Lee S, Joo JWJ, Jang W. A transcriptome-wide association study of uterine fibroids to identify potential genetic markers and toxic chemicals. PLoS One 2022; 17:e0274879. [PMID: 36174000 PMCID: PMC9521910 DOI: 10.1371/journal.pone.0274879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Accepted: 09/06/2022] [Indexed: 11/30/2022] Open
Abstract
Uterine fibroid is one of the most prevalent benign tumors in women, with high socioeconomic costs. Although genome-wide association studies (GWAS) have identified several loci associated with uterine fibroid risks, they could not successfully interpret the biological effects of genomic variants at the gene expression levels. To prioritize uterine fibroid susceptibility genes that are biologically interpretable, we conducted a transcriptome-wide association study (TWAS) by integrating GWAS data of uterine fibroid and expression quantitative loci data. We identified nine significant TWAS genes including two novel genes, RP11-282O18.3 and KBTBD7, which may be causal genes for uterine fibroid. We conducted functional enrichment network analyses using the TWAS results to investigate the biological pathways in which the overall TWAS genes were involved. The results demonstrated the immune system process to be a key pathway in uterine fibroid pathogenesis. Finally, we carried out chemical–gene interaction analyses using the TWAS results and the comparative toxicogenomics database to determine the potential risk chemicals for uterine fibroid. We identified five toxic chemicals that were significantly associated with uterine fibroid TWAS genes, suggesting that they may be implicated in the pathogenesis of uterine fibroid. In this study, we performed an integrative analysis covering the broad application of bioinformatics approaches. Our study may provide a deeper understanding of uterine fibroid etiologies and informative notifications about potential risk chemicals for uterine fibroid.
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Affiliation(s)
- Gayeon Kim
- Department of Life Sciences, Dongguk University-Seoul, Seoul, Republic of Korea
| | - Gyuyeon Jang
- Department of Life Sciences, Dongguk University-Seoul, Seoul, Republic of Korea
| | - Jaeseung Song
- Department of Life Sciences, Dongguk University-Seoul, Seoul, Republic of Korea
| | - Daeun Kim
- Department of Life Sciences, Dongguk University-Seoul, Seoul, Republic of Korea
| | - Sora Lee
- Department of Life Sciences, Dongguk University-Seoul, Seoul, Republic of Korea
| | - Jong Wha J. Joo
- Department of Computer Science and Engineering, Dongguk University-Seoul, Seoul, South Korea
| | - Wonhee Jang
- Department of Life Sciences, Dongguk University-Seoul, Seoul, Republic of Korea
- * E-mail:
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34
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Kung PJ, Elsayed I, Reyes-Pérez P, Bandres-Ciga S. Immunogenetic Determinants of Parkinson’s Disease Etiology. JOURNAL OF PARKINSON'S DISEASE 2022; 12:S13-S27. [PMID: 35367971 PMCID: PMC9535568 DOI: 10.3233/jpd-223176] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Parkinson’s disease (PD) is increasingly recognised as a systemic disorder in which inflammation might play a causative role rather than being a consequence or an epiphenomenon of the neurodegenerative process. Although growing genetic evidence links the central and peripheral immune system with both monogenic and sporadic PD, our understanding on how the immune system contributes to PD pathogenesis remains a daunting challenge. In this review, we discuss recent literature aimed at exploring the role of known genes and susceptibility loci to PD pathogenesis through immune system related mechanisms. Furthermore, we outline shared genetic etiologies and interrelations between PD and autoimmune diseases and underlining challenges and limitations faced in the translation of relevant allelic and regulatory risk loci to immune-pathological mechanisms. Lastly, with the field of immunogenetics expanding rapidly, we place these insights into a future context highlighting the prospect of immune modulation as a promising disease-modifying strategy.
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Affiliation(s)
- Pin-Jui Kung
- Genome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, Taipei, Taiwan
| | - Inas Elsayed
- Faculty of Pharmacy, University of Gezira, Wad Medani, Sudan
- International Parkinson Disease Genomics Consortium (IPDGC)-Africa, University of Gezira, Wad Medani, Sudan
| | - Paula Reyes-Pérez
- Laboratorio Internacional de Investigacion sobre el Genoma Humano, Universidad Autonoma de México, Queretaro, Mexico
| | - Sara Bandres-Ciga
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
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35
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Shireby G, Dempster EL, Policicchio S, Smith RG, Pishva E, Chioza B, Davies JP, Burrage J, Lunnon K, Seiler Vellame D, Love S, Thomas A, Brookes K, Morgan K, Francis P, Hannon E, Mill J. DNA methylation signatures of Alzheimer's disease neuropathology in the cortex are primarily driven by variation in non-neuronal cell-types. Nat Commun 2022; 13:5620. [PMID: 36153390 PMCID: PMC9509387 DOI: 10.1038/s41467-022-33394-7] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 09/13/2022] [Indexed: 11/19/2022] Open
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by the progressive accumulation of amyloid-beta and neurofibrillary tangles of tau in the neocortex. We profiled DNA methylation in two regions of the cortex from 631 donors, performing an epigenome-wide association study of multiple measures of AD neuropathology. We meta-analyzed our results with those from previous studies of DNA methylation in AD cortex (total n = 2013 donors), identifying 334 cortical differentially methylated positions (DMPs) associated with AD pathology including methylomic variation at loci not previously implicated in dementia. We subsequently profiled DNA methylation in NeuN+ (neuronal-enriched), SOX10+ (oligodendrocyte-enriched) and NeuN-/SOX10- (microglia- and astrocyte-enriched) nuclei, finding that the majority of DMPs identified in 'bulk' cortex tissue reflect DNA methylation differences occurring in non-neuronal cells. Our study highlights the power of utilizing multiple measures of neuropathology to identify epigenetic signatures of AD and the importance of characterizing disease-associated variation in purified cell-types.
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Affiliation(s)
- Gemma Shireby
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Emma L Dempster
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Stefania Policicchio
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Rebecca G Smith
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Ehsan Pishva
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, The Netherlands
| | - Barry Chioza
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Jonathan P Davies
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Joe Burrage
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Katie Lunnon
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Dorothea Seiler Vellame
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Seth Love
- Dementia Research Group, University of Bristol Medical School (Translational Health Sciences), Bristol, UK
| | - Alan Thomas
- Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK
| | - Keeley Brookes
- Biosciences, School of Science & Technology, Nottingham Trent University, Nottingham, UK
| | - Kevin Morgan
- Human Genetics, School of Life Sciences, University of Nottingham, Nottingham, UK
| | - Paul Francis
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
- Wolfson Centre for Age-Related Diseases, King's College London, London, UK
| | - Eilis Hannon
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Jonathan Mill
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter Medical School, University of Exeter, Exeter, UK.
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36
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Genetic control of RNA splicing and its distinct role in complex trait variation. Nat Genet 2022; 54:1355-1363. [PMID: 35982161 PMCID: PMC9470536 DOI: 10.1038/s41588-022-01154-4] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 07/08/2022] [Indexed: 12/11/2022]
Abstract
Most genetic variants identified from genome-wide association studies (GWAS) in humans are noncoding, indicating their role in gene regulation. Previous studies have shown considerable links of GWAS signals to expression quantitative trait loci (eQTLs) but the links to other genetic regulatory mechanisms, such as splicing QTLs (sQTLs), are underexplored. Here, we introduce an sQTL mapping method, testing for heterogeneity between isoform-eQTLeffects (THISTLE), with improved power over competing methods. Applying THISTLE together with a complementary sQTL mapping strategy to brain transcriptomic (n = 2,865) and genotype data, we identified 12,794 genes with cis-sQTLs at P < 5 × 10−8, approximately 61% of which were distinct from eQTLs. Integrating the sQTL data into GWAS for 12 brain-related complex traits (including diseases), we identified 244 genes associated with the traits through cis-sQTLs, approximately 61% of which could not be discovered using the corresponding eQTL data. Our study demonstrates the distinct role of most sQTLs in the genetic regulation of transcription and complex trait variation. A powerful method for splicing quantitative trait loci (sQTL) mapping, THISTLE, is presented and applied to a collection of 2,865 brain samples. Integration with GWAS identifies 244 genes associated via cis-sQTLs, of which 61% were not identified using expression QTLs.
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37
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Kim YJ, Kim K, Lee H, Jeon J, Lee J, Yoon J. The Protein-Protein Interaction Network of Hereditary Parkinsonism Genes Is a Hierarchical Scale-Free Network. Yonsei Med J 2022; 63:724-734. [PMID: 35914754 PMCID: PMC9344267 DOI: 10.3349/ymj.2022.63.8.724] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 04/19/2022] [Accepted: 05/02/2022] [Indexed: 11/27/2022] Open
Abstract
PURPOSE Hereditary parkinsonism genes consist of causative genes of familial Parkinson's disease (PD) with a locus symbol prefix (PARK genes) and hereditary atypical parkinsonian disorders that present atypical features and limited responsiveness to levodopa (non-PARK genes). Although studies have shown that hereditary parkinsonism genes are related to idiopathic PD at the phenotypic, gene expression, and genomic levels, no study has systematically investigated connectivity among the proteins encoded by these genes at the protein-protein interaction (PPI) level. MATERIALS AND METHODS Topological measurements and physical interaction enrichment were performed to assess PPI networks constructed using some or all the proteins encoded by hereditary parkinsonism genes (n=96), which were curated using the Online Mendelian Inheritance in Man database and literature. RESULTS Non-PARK and PARK genes were involved in common functional modules related to autophagy, mitochondrial or lysosomal organization, catecholamine metabolic process, chemical synapse transmission, response to oxidative stress, neuronal apoptosis, regulation of cellular protein catabolic process, and vesicle-mediated transport in synapse. The hereditary parkinsonism proteins formed a single large network comprising 51 nodes, 83 edges, and three PPI pairs. The probability of degree distribution followed a power-law scaling behavior, with a degree exponent of 1.24 and a correlation coefficient of 0.92. LRRK2 was identified as a hub gene with the highest degree of betweenness centrality; its physical interaction enrichment score was 1.28, which was highly significant. CONCLUSION Both PARK and non-PARK genes show high connectivity at the PPI and biological functional levels.
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Affiliation(s)
- Yun Joong Kim
- Department of Neurology, Yonsei University College of Medicine, Seoul, Korea
- Department of Neurology, Yongin Severance Hospital, Yonsei University Health System, Yongin, Korea.
| | - Kiyong Kim
- Department of Electronic Engineering, Kyonggi University, Suwon, Korea.
| | - Heonwoo Lee
- Department of Computer Engineering, Hallym University, Chuncheon, Korea
| | - Junbeom Jeon
- Department of Computer Engineering, Hallym University, Chuncheon, Korea
| | - Jinwoo Lee
- Department of Computer Engineering, Hallym University, Chuncheon, Korea
| | - Jeehee Yoon
- Department of Computer Engineering, Hallym University, Chuncheon, Korea
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38
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Song J, Kim D, Lee S, Jung J, Joo JWJ, Jang W. Integrative transcriptome-wide analysis of atopic dermatitis for drug repositioning. Commun Biol 2022; 5:615. [PMID: 35729261 PMCID: PMC9213508 DOI: 10.1038/s42003-022-03564-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 06/07/2022] [Indexed: 12/13/2022] Open
Abstract
Atopic dermatitis (AD) is one of the most common inflammatory skin diseases, which significantly impact the quality of life. Transcriptome-wide association study (TWAS) was conducted to estimate both transcriptomic and genomic features of AD and detected significant associations between 31 expression quantitative loci and 25 genes. Our results replicated well-known genetic markers for AD, as well as 4 novel associated genes. Next, transcriptome meta-analysis was conducted with 5 studies retrieved from public databases and identified 5 additional novel susceptibility genes for AD. Applying the connectivity map to the results from TWAS and meta-analysis, robustly enriched perturbations were identified and their chemical or functional properties were analyzed. Here, we report the first research on integrative approaches for an AD, combining TWAS and transcriptome meta-analysis. Together, our findings could provide a comprehensive understanding of the pathophysiologic mechanisms of AD and suggest potential drug candidates as alternative treatment options. Integrative genomic and transcriptomic analyses on publicly available data-sets together with in silico drug repositioning identifies alternative therapeutic options to treat atopic dermatitis.
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Affiliation(s)
- Jaeseung Song
- Department of Life Sciences, Dongguk University-Seoul, 04620, Seoul, Republic of Korea
| | - Daeun Kim
- Department of Life Sciences, Dongguk University-Seoul, 04620, Seoul, Republic of Korea
| | - Sora Lee
- Department of Life Sciences, Dongguk University-Seoul, 04620, Seoul, Republic of Korea
| | - Junghyun Jung
- Department of Life Sciences, Dongguk University-Seoul, 04620, Seoul, Republic of Korea.,Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, 1985 Zonal Avenue, Los Angeles, CA, 90089, USA
| | - Jong Wha J Joo
- Department of Computer Science and Engineering, Dongguk University-Seoul, 04620, Seoul, Republic of Korea
| | - Wonhee Jang
- Department of Life Sciences, Dongguk University-Seoul, 04620, Seoul, Republic of Korea.
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39
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Huggett SB, Ikeda AS, McGeary JE, Kaun KR, Palmer RHC. Opioid Use Disorder and Alternative mRNA Splicing in Reward Circuitry. Genes (Basel) 2022; 13:genes13061045. [PMID: 35741807 PMCID: PMC9222793 DOI: 10.3390/genes13061045] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 05/30/2022] [Accepted: 06/01/2022] [Indexed: 02/06/2023] Open
Abstract
Opiate/opioid use disorder (OUD) is a chronic relapsing brain disorder that has increased in prevalence in the last two decades in the United States. Understanding the molecular correlates of OUD may provide key insights into the pathophysiology of this syndrome. Using publicly available RNA-sequencing data, our study investigated the possible role of alternative mRNA splicing in human brain tissue (dorsal-lateral prefrontal cortex (dlPFC), nucleus accumbens (NAc), and midbrain) of 90 individuals with OUD or matched controls. We found a total of 788 differentially spliced genes across brain regions. Alternative mRNA splicing demonstrated mostly tissue-specific effects, but a functionally characterized splicing change in the clathrin and AP-2-binding (CLAP) domain of the Bridging Integrator 1 (BIN1) gene was significantly linked to OUD across all brain regions. We investigated two hypotheses that may underlie differential splicing in OUD. First, we tested whether spliceosome genes were disrupted in the brains of individuals with OUD. Pathway enrichment analyses indicated spliceosome perturbations in OUD across brain regions. Second, we tested whether alternative mRNA splicing regions were linked to genetic predisposition. Using a genome-wide association study (GWAS) of OUD, we found no evidence that DNA variants within or surrounding differentially spliced genes were implicated in the heritability of OUD. Altogether, our study contributes to the understanding of OUD pathophysiology by providing evidence of a possible role of alternative mRNA splicing in OUD.
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Affiliation(s)
- Spencer B. Huggett
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, GA 30322, USA; (S.B.H.); (A.S.I.)
| | - Ami S. Ikeda
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, GA 30322, USA; (S.B.H.); (A.S.I.)
| | - John E. McGeary
- Providence Veterans Affairs Medical Center, Department of Psychiatry and Human Behavior, Brown University, Providence, RI 02908, USA;
| | - Karla R. Kaun
- Department of Neuroscience, Brown University, Providence, RI 02912, USA;
| | - Rohan H. C. Palmer
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, GA 30322, USA; (S.B.H.); (A.S.I.)
- Correspondence: ; Tel.: +1-(404)-727-7340; Fax: +1-(404)-727-0372
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40
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Olayinka OA, O’Neill NK, Farrer LA, Wang G, Zhang X. Molecular Quantitative Trait Locus Mapping in Human Complex Diseases. Curr Protoc 2022; 2:e426. [PMID: 35587224 PMCID: PMC9186089 DOI: 10.1002/cpz1.426] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Mapping quantitative trait loci (QTLs) for molecular traits from chromatin to metabolites (i.e., xQTLs) provides insight into the locations and effect modes of genetic variants that influence these molecular phenotypes and the propagation of functional consequences of each variant. xQTL studies indirectly interrogate the functional landscape of the molecular basis of complex diseases, including the impact of non-coding regulatory variants, the tissue specificity of regulatory elements, and their contribution to disease by integrating with genome-wide association studies (GWAS). We summarize a variety of molecular xQTL studies in human tissues and cells. In addition, using the Alzheimer's Disease Sequencing Project (ADSP) as an example, we describe the ADSP xQTL project, a collaborative effort across the ADSP Functional Genomics Consortium (ADSP-FGC). The project's ultimate goal is a reference map of Alzheimer's-related QTLs using existing datasets from multiple omics layers to help us study the consequences of genetic variants identified in the ADSP. xQTL studies enable the identification of the causal genes and pathways in GWAS loci, which will likely aid in the discovery of novel biomarkers and therapeutic targets for complex diseases. © 2022 Wiley Periodicals LLC.
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Affiliation(s)
- Oluwatosin A. Olayinka
- Bioinformatics Program, Boston University, Boston, MA, USA,Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Nicholas K. O’Neill
- Bioinformatics Program, Boston University, Boston, MA, USA,Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA
| | - Lindsay A. Farrer
- Bioinformatics Program, Boston University, Boston, MA, USA,Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA,Department of Neurology, Boston University School of Medicine, Boston, MA, USA,Department of Ophthalmology, Boston University School of Medicine, Boston, MA, USA,Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA,Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Gao Wang
- Department of Neurology, Columbia University, New York, NY, USA,Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA
| | - Xiaoling Zhang
- Bioinformatics Program, Boston University, Boston, MA, USA,Department of Medicine (Biomedical Genetics), Boston University School of Medicine, Boston, MA, USA,Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA,Correspondence: Xiaoling Zhang, M.D., Ph.D., , Boston University School of Medicine, 72 East Concord Street, E223, Boston, MA 02118
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41
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Xiang J, Meng X, Zhao Y, Wu FX, Li M. HyMM: hybrid method for disease-gene prediction by integrating multiscale module structure. Brief Bioinform 2022; 23:6547263. [PMID: 35275996 DOI: 10.1093/bib/bbac072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Revised: 01/18/2022] [Accepted: 02/13/2022] [Indexed: 11/12/2022] Open
Abstract
MOTIVATION Identifying disease-related genes is an important issue in computational biology. Module structure widely exists in biomolecule networks, and complex diseases are usually thought to be caused by perturbations of local neighborhoods in the networks, which can provide useful insights for the study of disease-related genes. However, the mining and effective utilization of the module structure is still challenging in such issues as a disease gene prediction. RESULTS We propose a hybrid disease-gene prediction method integrating multiscale module structure (HyMM), which can utilize multiscale information from local to global structure to more effectively predict disease-related genes. HyMM extracts module partitions from local to global scales by multiscale modularity optimization with exponential sampling, and estimates the disease relatedness of genes in partitions by the abundance of disease-related genes within modules. Then, a probabilistic model for integration of gene rankings is designed in order to integrate multiple predictions derived from multiscale module partitions and network propagation, and a parameter estimation strategy based on functional information is proposed to further enhance HyMM's predictive power. By a series of experiments, we reveal the importance of module partitions at different scales, and verify the stable and good performance of HyMM compared with eight other state-of-the-arts and its further performance improvement derived from the parameter estimation. CONCLUSIONS The results confirm that HyMM is an effective framework for integrating multiscale module structure to enhance the ability to predict disease-related genes, which may provide useful insights for the study of the multiscale module structure and its application in such issues as a disease-gene prediction.
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Affiliation(s)
- Ju Xiang
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha 410083, China; Department of Basic Medical Sciences & Academician Workstation, Changsha Medical University, Changsha, Hunan 410219, China
| | - Xiangmao Meng
- School of Computer Science and Engineering, Central South University, Changsha 410083, China
| | - Yichao Zhao
- School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China
| | - Fang-Xiang Wu
- Division of Biomedical Engineering and Department of Mechanical Engineering, University of Saskatchewan, Saskatoon, SK, S7N 5A9, Canada
| | - Min Li
- Hunan Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha 410083, China
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Martinez-Banaclocha M. N-Acetyl-Cysteine: Modulating the Cysteine Redox Proteome in Neurodegenerative Diseases. Antioxidants (Basel) 2022; 11:antiox11020416. [PMID: 35204298 PMCID: PMC8869501 DOI: 10.3390/antiox11020416] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 02/13/2022] [Accepted: 02/16/2022] [Indexed: 12/14/2022] Open
Abstract
In the last twenty years, significant progress in understanding the pathophysiology of age-associated neurodegenerative diseases has been made. However, the prevention and treatment of these diseases remain without clinically significant therapeutic advancement. While we still hope for some potential genetic therapeutic approaches, the current reality is far from substantial progress. With this state of the issue, emphasis should be placed on early diagnosis and prompt intervention in patients with increased risk of neurodegenerative diseases to slow down their progression, poor prognosis, and decreasing quality of life. Accordingly, it is urgent to implement interventions addressing the psychosocial and biochemical disturbances we know are central in managing the evolution of these disorders. Genomic and proteomic studies have shown the high molecular intricacy in neurodegenerative diseases, involving a broad spectrum of cellular pathways underlying disease progression. Recent investigations indicate that the dysregulation of the sensitive-cysteine proteome may be a concurrent pathogenic mechanism contributing to the pathophysiology of major neurodegenerative diseases, opening new therapeutic opportunities. Considering the incidence and prevalence of these disorders and their already significant burden in Western societies, they will become a real pandemic in the following decades. Therefore, we propose large-scale investigations, in selected groups of people over 40 years of age with decreased blood glutathione levels, comorbidities, and/or mild cognitive impairment, to evaluate supplementation of the diet with low doses of N-acetyl-cysteine, a promising and well-tolerated therapeutic agent suitable for long-term use.
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Chang EES, Ho PWL, Liu HF, Pang SYY, Leung CT, Malki Y, Choi ZYK, Ramsden DB, Ho SL. LRRK2 mutant knock-in mouse models: therapeutic relevance in Parkinson's disease. Transl Neurodegener 2022; 11:10. [PMID: 35152914 PMCID: PMC8842874 DOI: 10.1186/s40035-022-00285-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 01/26/2022] [Indexed: 12/24/2022] Open
Abstract
Mutations in the leucine-rich repeat kinase 2 gene (LRRK2) are one of the most frequent genetic causes of both familial and sporadic Parkinson’s disease (PD). Mounting evidence has demonstrated pathological similarities between LRRK2-associated PD (LRRK2-PD) and sporadic PD, suggesting that LRRK2 is a potential disease modulator and a therapeutic target in PD. LRRK2 mutant knock-in (KI) mouse models display subtle alterations in pathological aspects that mirror early-stage PD, including increased susceptibility of nigrostriatal neurotransmission, development of motor and non-motor symptoms, mitochondrial and autophagy-lysosomal defects and synucleinopathies. This review provides a rationale for the use of LRRK2 KI mice to investigate the LRRK2-mediated pathogenesis of PD and implications from current findings from different LRRK2 KI mouse models, and ultimately discusses the therapeutic potentials against LRRK2-associated pathologies in PD.
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Li C, Yang T, Ou R, Shang H. Overlapping Genetic Architecture Between Schizophrenia and Neurodegenerative Disorders. Front Cell Dev Biol 2022; 9:797072. [PMID: 35004692 PMCID: PMC8740133 DOI: 10.3389/fcell.2021.797072] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 12/06/2021] [Indexed: 02/05/2023] Open
Abstract
Epidemiological and clinical studies have suggested comorbidity between schizophrenia and several neurodegenerative disorders. However, little is known whether there exists shared genetic architecture. To explore their relationship from a genetic and transcriptomic perspective, we applied polygenic and linkage disequilibrium-informed methods to examine the genetic correlation between schizophrenia and amyotrophic lateral sclerosis (ALS), Parkinson’s disease, Alzheimer’s disease and frontotemporal dementia. We further combined genome-wide association summary statistics with large-scale transcriptomic datasets, to identify putative shared genes and explore related pathological tissues. We identified positive and significant correlation between schizophrenia and ALS at genetic (correlation 0.22; 95% CI: 0.16–0.28; p = 4.00E-04) and transcriptomic (correlation 0.08; 95% CI: 0.04–0.11; p = 0.034) levels. We further demonstrated that schizophrenia- and ALS-inferred gene expression overlap significantly in four tissues including skin, small intestine, brain cortex and lung, and highlighted three genes, namely GLB1L3, ZNHIT3 and TMEM194A as potential mediators of the correlation between schizophrenia and ALS. Our findings revealed overlapped gene expression profiles in specific tissues between schizophrenia and ALS, and identified novel potential shared genes. These results provided a better understanding for the pleiotropy of schizophrenia, and paved way for future studies to further elucidate the molecular drivers of schizophrenia.
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Affiliation(s)
- Chunyu Li
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Tianmi Yang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Ruwei Ou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
| | - Huifang Shang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, China
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Lopes KDP, Snijders GJL, Humphrey J, Allan A, Sneeboer MAM, Navarro E, Schilder BM, Vialle RA, Parks M, Missall R, van Zuiden W, Gigase FAJ, Kübler R, van Berlekom AB, Hicks EM, Bӧttcher C, Priller J, Kahn RS, de Witte LD, Raj T. Genetic analysis of the human microglial transcriptome across brain regions, aging and disease pathologies. Nat Genet 2022; 54:4-17. [PMID: 34992268 PMCID: PMC9245609 DOI: 10.1038/s41588-021-00976-y] [Citation(s) in RCA: 98] [Impact Index Per Article: 49.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 10/19/2021] [Indexed: 12/12/2022]
Abstract
Microglia have emerged as important players in brain aging and pathology. To understand how genetic risk for neurological and psychiatric disorders is related to microglial function, large transcriptome studies are essential. Here, we describe the transcriptome analysis of 255 primary human microglia samples isolated at autopsy from multiple brain regions of 100 human subjects. We performed systematic analyses to investigate various aspects of microglial heterogeneities, including brain region and aging. We mapped expression and splicing quantitative trait loci and showed that many neurological disease susceptibility loci are mediated through gene expression or splicing in microglia. Fine-mapping of these loci nominated candidate causal variants that are within microglia-specific enhancers, finding associations with microglia expression of USP6NL for Alzheimer’s disease and P2RY12 for Parkinson’s disease. We have built the most comprehensive catalog to date of genetic effects on the microglia transcriptome and propose candidate functional variants in neurological and psychiatric disorders.
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Affiliation(s)
- Katia de Paiva Lopes
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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 J L Snijders
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Mental Illness Research, Education and Clinical Center, James J Peters VA Medical Center, New York, NY, USA
| | - Jack Humphrey
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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
| | - Amanda Allan
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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
| | - Marjolein A M Sneeboer
- Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - Elisa Navarro
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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
| | - Brian M Schilder
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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
| | - Ricardo A Vialle
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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
| | - Madison Parks
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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
| | - Roy Missall
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Welmoed van Zuiden
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Frederieke A J Gigase
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Mental Illness Research, Education and Clinical Center, James J Peters VA Medical Center, New York, NY, USA
| | - Raphael Kübler
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Amber Berdenis van Berlekom
- Department of Translational Neuroscience, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, the Netherlands
| | - Emily M Hicks
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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
| | - Chotima Bӧttcher
- Department of Neuropsychiatry and Laboratory of Molecular Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Josef Priller
- Department of Neuropsychiatry and Laboratory of Molecular Psychiatry, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - René S Kahn
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Mental Illness Research, Education and Clinical Center, James J Peters VA Medical Center, New York, NY, USA
| | - Lot D de Witte
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Mental Illness Research, Education and Clinical Center, James J Peters VA Medical Center, New York, NY, USA.
| | - Towfique Raj
- 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 Genetics and Genomic Sciences & Icahn Institute for Data Science and Genomic Technology, 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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Brotman SM, Raulerson CK, Vadlamudi S, Currin KW, Shen Q, Parsons VA, Iyengar AK, Roman TS, Furey TS, Kuusisto J, Collins FS, Boehnke M, Laakso M, Pajukanta P, Mohlke KL. Subcutaneous adipose tissue splice quantitative trait loci reveal differences in isoform usage associated with cardiometabolic traits. Am J Hum Genet 2022; 109:66-80. [PMID: 34995504 PMCID: PMC8764203 DOI: 10.1016/j.ajhg.2021.11.019] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 11/23/2021] [Indexed: 01/13/2023] Open
Abstract
Alternate splicing events can create isoforms that alter gene function, and genetic variants associated with alternate gene isoforms may reveal molecular mechanisms of disease. We used subcutaneous adipose tissue of 426 Finnish men from the METSIM study and identified splice junction quantitative trait loci (sQTLs) for 6,077 splice junctions (FDR < 1%). In the same individuals, we detected expression QTLs (eQTLs) for 59,443 exons and 15,397 genes (FDR < 1%). We identified 595 genes with an sQTL and exon eQTL but no gene eQTL, which could indicate potential isoform differences. Of the significant sQTL signals, 2,114 (39.8%) included at least one proxy variant (linkage disequilibrium r2 > 0.8) located within an intron spanned by the splice junction. We identified 203 sQTLs that colocalized with 141 genome-wide association study (GWAS) signals for cardiometabolic traits, including 25 signals for lipid traits, 24 signals for body mass index (BMI), and 12 signals for waist-hip ratio adjusted for BMI. Among all 141 GWAS signals colocalized with an sQTL, we detected 26 that also colocalized with an exon eQTL for an exon skipped by the sQTL splice junction. At a GWAS signal for high-density lipoprotein cholesterol colocalized with an NR1H3 sQTL splice junction, we show that the alternative splice product encodes an NR1H3 transcription factor that lacks a DNA binding domain and fails to activate transcription. Together, these results detect splicing events and candidate mechanisms that may contribute to gene function at GWAS loci.
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Affiliation(s)
- Sarah M Brotman
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Chelsea K Raulerson
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | | | - Kevin W Currin
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Qiujin Shen
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Victoria A Parsons
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Apoorva K Iyengar
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Tamara S Roman
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Terrence S Furey
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Biology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio 70210, Finland
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Markku Laakso
- Institute of Clinical Medicine, Kuopio University Hospital, University of Eastern Finland, Kuopio 70210, Finland
| | - Päivi Pajukanta
- Institute for Precision Health, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA; Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
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47
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Ho D, Schierding W, Farrow SL, Cooper AA, Kempa-Liehr AW, O’Sullivan JM. Machine Learning Identifies Six Genetic Variants and Alterations in the Heart Atrial Appendage as Key Contributors to PD Risk Predictivity. Front Genet 2022; 12:785436. [PMID: 35047012 PMCID: PMC8762216 DOI: 10.3389/fgene.2021.785436] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 11/09/2021] [Indexed: 12/14/2022] Open
Abstract
Parkinson's disease (PD) is a complex neurodegenerative disease with a range of causes and clinical presentations. Over 76 genetic loci (comprising 90 SNPs) have been associated with PD by the most recent GWAS meta-analysis. Most of these PD-associated variants are located in non-coding regions of the genome and it is difficult to understand what they are doing and how they contribute to the aetiology of PD. We hypothesised that PD-associated genetic variants modulate disease risk through tissue-specific expression quantitative trait loci (eQTL) effects. We developed and validated a machine learning approach that integrated tissue-specific eQTL data on known PD-associated genetic variants with PD case and control genotypes from the Wellcome Trust Case Control Consortium. In so doing, our analysis ranked the tissue-specific transcription effects for PD-associated genetic variants and estimated their relative contributions to PD risk. We identified roles for SNPs that are connected with INPP5P, CNTN1, GBA and SNCA in PD. Ranking the variants and tissue-specific eQTL effects contributing most to the machine learning model suggested a key role in the risk of developing PD for two variants (rs7617877 and rs6808178) and eQTL associated transcriptional changes of EAF1-AS1 within the heart atrial appendage. Similarly, effects associated with eQTLs located within the Brain Cerebellum were also recognized to confer major PD risk. These findings were replicated in two additional, independent cohorts (the UK Biobank, and NeuroX) and thus warrant further mechanistic investigations to determine if these transcriptional changes could act as early contributors to PD risk and disease development.
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Affiliation(s)
- Daniel Ho
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - William Schierding
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom
| | - Sophie L. Farrow
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom
| | - Antony A. Cooper
- Australian Parkinsons Mission, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent’s Clinical School, UNSW Sydney, Sydney, NSW, Australia
| | | | - Justin M. O’Sullivan
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom
- Brain Research New Zealand, The University of Auckland, Auckland, New Zealand
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
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48
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O’Day C, Finkelstein DI, Diwakarla S, McQuade RM. A Critical Analysis of Intestinal Enteric Neuron Loss and Constipation in Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2022; 12:1841-1861. [PMID: 35848035 PMCID: PMC9535602 DOI: 10.3233/jpd-223262] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/26/2022] [Indexed: 06/06/2023]
Abstract
Constipation afflicts many patients with Parkinson's disease (PD) and significantly impacts on patient quality of life. PD-related constipation is caused by intestinal dysfunction, but the etiology of this dysfunction in patients is unknown. One possible cause is neuron loss within the enteric nervous system (ENS) of the intestine. This review aims to 1) Critically evaluate the evidence for and against intestinal enteric neuron loss in PD patients, 2) Justify why PD-related constipation must be objectively measured, 3) Explore the potential link between loss of enteric neurons in the intestine and constipation in PD, 4) Provide potential explanations for disparities in the literature, and 5) Outline data and study design considerations to improve future research. Before the connection between intestinal enteric neuron loss and PD-related constipation can be confidently described, future research must use sufficiently large samples representative of the patient population (majority diagnosed with idiopathic PD for at least 5 years), implement a consistent neuronal quantification method and study design, including standardized patient recruitment criteria, objectively quantify intestinal dysfunctions, publish with a high degree of data transparency and account for potential PD heterogeneity. Further investigation into other potential influencers of PD-related constipation is also required, including changes in the function, connectivity, mitochondria and/or α-synuclein proteins of enteric neurons and their extrinsic innervation. The connection between enteric neuron loss and other PD-related gastrointestinal (GI) issues, including gastroparesis and dysphagia, as well as changes in nutrient absorption and the microbiome, should be explored in future research.
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Affiliation(s)
- Chelsea O’Day
- Gut-Axis Injury & Repair Laboratory, Department of Medicine - Western Centre for Health Research and Education (WCHRE), The University of Melbourne, Sunshine Hospital, St Albans, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
- Australian Institute of Musculoskeletal Science (AIMSS), Western Centre for Health Research and Education (WCHRE) Level 3 and 4, Sunshine Hospital, St Albans, VIC, Australia
| | - David Isaac Finkelstein
- Parkinson’s Disease Laboratory, The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Shanti Diwakarla
- Gut-Axis Injury & Repair Laboratory, Department of Medicine - Western Centre for Health Research and Education (WCHRE), The University of Melbourne, Sunshine Hospital, St Albans, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
- Australian Institute of Musculoskeletal Science (AIMSS), Western Centre for Health Research and Education (WCHRE) Level 3 and 4, Sunshine Hospital, St Albans, VIC, Australia
| | - Rachel Mai McQuade
- Gut-Axis Injury & Repair Laboratory, Department of Medicine - Western Centre for Health Research and Education (WCHRE), The University of Melbourne, Sunshine Hospital, St Albans, VIC, Australia
- The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
- Australian Institute of Musculoskeletal Science (AIMSS), Western Centre for Health Research and Education (WCHRE) Level 3 and 4, Sunshine Hospital, St Albans, VIC, Australia
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Ke X, Tian X, Yao S, Wu H, Duan YY, Wang NN, Shi W, Yang TL, Dong SS, Huang D, Guo Y. Transcriptome-wide association study identifies multiple genes and pathways associated with thyroid function. Hum Mol Genet 2021; 31:1871-1883. [PMID: 34962261 DOI: 10.1093/hmg/ddab371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 12/03/2021] [Accepted: 12/20/2021] [Indexed: 11/12/2022] Open
Abstract
Thyroid dysfunction is a common endocrine disease measured by thyroid-stimulating hormone (TSH) level. Although more than 70 genetic loci associated with TSH have been reported through genome-wide association studies (GWASs), the variants can only explain a small fraction of the thyroid function heritability. To identify novel candidate genes for thyroid function, we conducted the first large-scale transcriptome-wide association study (TWAS) for thyroid function using GWAS-summary data for TSH levels in up to 119 715 individuals combined with pre-computed gene expression weights of six panels from four tissue types. The candidate genes identified by TWAS were further validated by TWAS replication and gene expression profiles. We identified 74 conditionally independent genes significantly associated with thyroid function, such as PDE8B (P = 1.67 × 10-282), PDE10A (P = 7.61 × 10-119), NR3C2 (P = 1.50 × 10-92), and CAPZB (P = 3.13 × 10-79). After TWAS replication using UKBB datasets, 26 genes were replicated for significant associations with thyroid-relevant diseases/traits. Among them, 16 gene were causal for their associations to thyroid-relevant diseases/traits and further validated in differential expression analyses, including two novel genes (MFSD6 and RBM47) that did not implicate in previous GWASs. Enrichment analyses detected several pathways associated with thyroid function, such as the cAMP signaling pathway (P = 7.27 × 10-4), hemostasis (P = 3.74 × 10-4), and platelet activation, signaling, and aggregation (P = 9.98 × 10-4). Our study identified multiple candidate genes and pathways associated with thyroid function, providing novel clues for revealing the genetic mechanisms of thyroid function and disease.
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Affiliation(s)
- Xin Ke
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China, 710049
| | - Xin Tian
- Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China
| | - Shi Yao
- National and Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China, 710004
| | - Hao Wu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China, 710049
| | - Yuan-Yuan Duan
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China, 710049
| | - Nai-Ning Wang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China, 710049
| | - Wei Shi
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China, 710049
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China, 710049.,National and Local Joint Engineering Research Center of Biodiagnosis and Biotherapy, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China, 710004
| | - Shan-Shan Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China, 710049.,Research Institute of Xi'an Jiaotong University, Hangzhou, Zhejiang, P. R. China
| | - Dageng Huang
- Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China
| | - Yan Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics & Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China, 710049.,Department of Orthopaedics, Honghui Hospital, Xi'an Jiaotong University, Xi'an, Shaanxi, P. R. China
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Schilder BM, Navarro E, Raj T. Multi-omic insights into Parkinson's Disease: From genetic associations to functional mechanisms. Neurobiol Dis 2021; 163:105580. [PMID: 34871738 PMCID: PMC10101343 DOI: 10.1016/j.nbd.2021.105580] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 11/17/2021] [Accepted: 12/02/2021] [Indexed: 02/07/2023] Open
Abstract
Genome-Wide Association Studies (GWAS) have elucidated the genetic components of Parkinson's Disease (PD). However, because the vast majority of GWAS association signals fall within non-coding regions, translating these results into an interpretable, mechanistic understanding of the disease etiology remains a major challenge in the field. In this review, we provide an overview of the approaches to prioritize putative causal variants and genes as well as summarise the primary findings of previous studies. We then discuss recent efforts to integrate multi-omics data to identify likely pathogenic cell types and biological pathways implicated in PD pathogenesis. We have compiled full summary statistics of cell-type, tissue, and phentoype enrichment analyses from multiple studies of PD GWAS and provided them in a standardized format as a resource for the research community (https://github.com/RajLabMSSM/PD_omics_review). Finally, we discuss the experimental, computational, and conceptual advances that will be necessary to fully elucidate the effects of functional variants and genes on cellular dysregulation and disease risk.
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Affiliation(s)
- Brian M Schilder
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, United Kingdom; UK Dementia Research Institute at Imperial College London, London, United Kingdom.
| | - Elisa Navarro
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Sección Departamental de Bioquímica y Biología Molecular, Facultad de Medicina, Universidad Complutense de Madrid, Madrid, Spain
| | - Towfique Raj
- Nash Family Department of Neuroscience & Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Ronald M. Loeb Center for Alzheimer's disease, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, United States; Estelle and Daniel Maggin Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, United States.
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