Multi-ancestry genome-wide association meta-analysis of Parkinson's disease
Although over 90 independent risk variants have been identified for Parkinson's disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson's disease with 49,049...
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Medicine, Health and Life Sciences Genetic predisposition to disease Parkinson disease |
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Medicine, Health and Life Sciences Genetic predisposition to disease Parkinson disease Kim, Jonggeol Jeffrey Vitale, Dan Otani, Diego Véliz Lian, Michelle Mulan Heilbron, Karl Iwaki, Hirotaka Lake, Julie Solsberg, Caroline Warly Leonard, Hampton Makarious, Mary B. Tan, Eng-King Singleton, Andrew B. Bandres-Ciga, Sara Noyce, Alastair J. Blauwendraat, Cornelis Nalls, Mike A. Foo, Jia Nee Mata, Ignacio Multi-ancestry genome-wide association meta-analysis of Parkinson's disease |
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Although over 90 independent risk variants have been identified for Parkinson's disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson's disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations. National Medical Research Council Singapore (Open Fund Large
Collaborative Grant MOH-000207 to E.-K.T.) (Open Fund Individual
Research Grant MOH-000559 to J.N.F.); and Singapore Ministry of
Education Academic Research Fund (Tier 2 MOE-T2EP30220-0005
and Tier 3 MOE-MOET32020-0004 to J.N.F.). P |
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Lee Kong Chian School of Medicine (LKCMedicine) |
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Lee Kong Chian School of Medicine (LKCMedicine) Kim, Jonggeol Jeffrey Vitale, Dan Otani, Diego Véliz Lian, Michelle Mulan Heilbron, Karl Iwaki, Hirotaka Lake, Julie Solsberg, Caroline Warly Leonard, Hampton Makarious, Mary B. Tan, Eng-King Singleton, Andrew B. Bandres-Ciga, Sara Noyce, Alastair J. Blauwendraat, Cornelis Nalls, Mike A. Foo, Jia Nee Mata, Ignacio |
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Article |
author |
Kim, Jonggeol Jeffrey Vitale, Dan Otani, Diego Véliz Lian, Michelle Mulan Heilbron, Karl Iwaki, Hirotaka Lake, Julie Solsberg, Caroline Warly Leonard, Hampton Makarious, Mary B. Tan, Eng-King Singleton, Andrew B. Bandres-Ciga, Sara Noyce, Alastair J. Blauwendraat, Cornelis Nalls, Mike A. Foo, Jia Nee Mata, Ignacio |
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Kim, Jonggeol Jeffrey |
title |
Multi-ancestry genome-wide association meta-analysis of Parkinson's disease |
title_short |
Multi-ancestry genome-wide association meta-analysis of Parkinson's disease |
title_full |
Multi-ancestry genome-wide association meta-analysis of Parkinson's disease |
title_fullStr |
Multi-ancestry genome-wide association meta-analysis of Parkinson's disease |
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Multi-ancestry genome-wide association meta-analysis of Parkinson's disease |
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multi-ancestry genome-wide association meta-analysis of parkinson's disease |
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2024 |
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https://hdl.handle.net/10356/176214 |
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sg-ntu-dr.10356-1762142024-05-19T15:38:23Z Multi-ancestry genome-wide association meta-analysis of Parkinson's disease Kim, Jonggeol Jeffrey Vitale, Dan Otani, Diego Véliz Lian, Michelle Mulan Heilbron, Karl Iwaki, Hirotaka Lake, Julie Solsberg, Caroline Warly Leonard, Hampton Makarious, Mary B. Tan, Eng-King Singleton, Andrew B. Bandres-Ciga, Sara Noyce, Alastair J. Blauwendraat, Cornelis Nalls, Mike A. Foo, Jia Nee Mata, Ignacio Lee Kong Chian School of Medicine (LKCMedicine) Genome Institute of Singapore, A*STAR Medicine, Health and Life Sciences Genetic predisposition to disease Parkinson disease Although over 90 independent risk variants have been identified for Parkinson's disease using genome-wide association studies, most studies have been performed in just one population at a time. Here we performed a large-scale multi-ancestry meta-analysis of Parkinson's disease with 49,049 cases, 18,785 proxy cases and 2,458,063 controls including individuals of European, East Asian, Latin American and African ancestry. In a meta-analysis, we identified 78 independent genome-wide significant loci, including 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300 and PPP6R2) and fine-mapped 6 putative causal variants at 6 known PD loci. By combining our results with publicly available eQTL data, we identified 25 putative risk genes in these novel loci whose expression is associated with PD risk. This work lays the groundwork for future efforts aimed at identifying PD loci in non-European populations. National Medical Research Council Singapore (Open Fund Large Collaborative Grant MOH-000207 to E.-K.T.) (Open Fund Individual Research Grant MOH-000559 to J.N.F.); and Singapore Ministry of Education Academic Research Fund (Tier 2 MOE-T2EP30220-0005 and Tier 3 MOE-MOET32020-0004 to J.N.F.). P Ministry of Education (MOE) National Medical Research Council (NMRC) Published version This work was supported by the following grants and institutions: Intramural Research Program of the National Institutes of Health (NIH), National Institute on Aging (NIA), NIH, Department of Health and Human Services (A.B.S., C.B. and M.A.N.); National Institute of Neurological Disorders and Stroke (project numbers ZO1 AG000535 and ZIA AG000949 to A.B.S., C.B. and M.A.N.) (grant number R01NS112499 to I.M.); Parkinson’s Foundation (Stanley Fahn Junior Faculty Award and an International Research Grants Program award to I.M.), Michael J Fox Foundation (to I.M. and A.J.N); Aligning Science Across Parkinson’s Global Parkinson’s Genetic Project (ASAP-GP2) (to I.M. and A.J.N); American Parkinson’s Disease Association (to I.M.); National Medical Research Council Singapore (Open Fund Large Collaborative Grant MOH-000207 to E.-K.T.) (Open Fund Individual Research Grant MOH-000559 to J.N.F.); and Singapore Ministry of Education Academic Research Fund (Tier 2 MOE-T2EP30220-0005 and Tier 3 MOE-MOET32020-0004 to J.N.F.). Participation in this project was part of a competitive contract awarded to Data Tecnica International by the NIH to support open science research. This research has been conducted using the UK Biobank Resource under Application Number 33601. We want to acknowledge the participants and investigators of FinnGen study. We thank the research participants and employees of 23andMe. Data used in the preparation of this article were obtained from Global Parkinson’s Genetics Program (GP2). GP2 is funded by the Aligning Science Against Parkinson’s (ASAP) initiative and implemented by the Michael J. Fox Foundation for Parkinson’s Research (https://gp2.org). For a complete list of GP2 members, see https://gp2.org. This work used the computational resources of the NIH HPC Biowulf cluster (http://hpc.nih.gov). 2024-05-14T02:12:40Z 2024-05-14T02:12:40Z 2024 Journal Article Kim, J. J., Vitale, D., Otani, D. V., Lian, M. M., Heilbron, K., Iwaki, H., Lake, J., Solsberg, C. W., Leonard, H., Makarious, M. B., Tan, E., Singleton, A. B., Bandres-Ciga, S., Noyce, A. J., Blauwendraat, C., Nalls, M. A., Foo, J. N. & Mata, I. (2024). Multi-ancestry genome-wide association meta-analysis of Parkinson's disease. Nature Genetics, 56(1), 27-36. https://dx.doi.org/10.1038/s41588-023-01584-8 1061-4036 https://hdl.handle.net/10356/176214 10.1038/s41588-023-01584-8 38155330 2-s2.0-85180652227 1 56 27 36 en MOH-000207 MOH-000559 MOE-T2EP30220-0005 MOE-MOET32020-0004 Nature Genetics Open Access - This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2023 application/pdf |