Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

FinnGen, eMERGE Consortium

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10 -9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

Original languageEnglish (US)
Pages (from-to)560-572
Number of pages13
JournalNature Genetics
Volume54
Issue number5
DOIs
StatePublished - May 1 2022

Bibliographical note

Funding Information:
A complete list of acknowledgements and funding appears in the . This research was funded in part by the Wellcome Trust (grant numbers 064890, 072960, 083948, 084723, 085475, 086113, 088158, 090367, 090532, 095101, 098017, 098051, 098381, 098395, 101033, 101630, 104085, 106130, 200186, 200837, 202922, 203141, 206194, 212259, 212284, 212946 and 220457). For the purpose of open access, the authors have applied a CC-BY public copyright licence to any author accepted manuscript version arising from this submission.

Funding Information:
A. Mahajan is now an employee of Genentech and a holder of Roche stock. R.A.S. is now an employee of GlaxoSmithKline. V.S. is an employee of deCODE Genetics–Amgen. L.S.E. is now an employee of Bristol Myers Squibb. J.S.F. has consulted for Shionogi. T.M.F. has consulted for Sanofi and Boerhinger Ingelheim and received funding from GSK. H.C.G. holds the McMaster–Sanofi Population Health Institute Chair in Diabetes Research and Care; reports research grants from Eli Lilly, AstraZeneca, Merck, Novo Nordisk and Sanofi; reports honoraria for speaking from AstraZeneca, Boehringer Ingelheim, Eli Lilly, Novo Nordisk, DKSH, Zuellig, Roche and Sanofi; and reports consulting fees from Abbott, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Merck, Novo Nordisk, Pfizer, Sanofi, Kowa and Hanmi. M. Ingelsson is a paid consultant for BioArctic. R.L.-G. is a part-time consultant for Metabolon. A.E.L. is now an employee of the Regeneron Genetics Center and holds shares in Regeneron Pharmaceuticals. M.A.N. currently serves on the scientific advisory board for Clover Therapeutics and is an advisor to Neuron23. S.R.P. has received grant funding from Bayer Pharmaceuticals, Philips Respironics and Respicardia. N.S. has consulted for or been on speaker bureaus for Abbott, Amgen, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Hanmi, Novartis, Novo Nordisk, Sanofi and Pfizer and has received grant funding from AstraZeneca, Boehringer Ingelheim, Novartis and Roche Diagnostics. A.M.S. receives funding from Seven Bridges Genomics to develop tools for the NHLBI BioData Catalyst consortium. G.T. is an employee of deCODE Genetics–Amgen. U.T. is an employee of deCODE Genetics–Amgen. E. Ingelsson is now an employee of GlaxoSmithKline. B.M.P. serves on the steering committee of the Yale Open Data Access Project funded by Johnson & Johnson. R.C.W.M. reports research funding from AstraZeneca, Bayer, Novo Nordisk, Pfizer, Tricida and Sanofi and has consulted for or received speakers fees from AstraZeneca, Bayer and Boehringer Ingelheim, all of which have been donated to the Chinese University of Hong Kong to support diabetes research. D.O.M.-K. is a part-time clinical research consultant for Metabolon. S. Liu reports consulting payments and honoraria or promises of the same for scientific presentations or reviews at numerous venues, including but not limited to Barilla, by-Health, Ausa Pharmed, the Fred Hutchinson Cancer Center, Harvard University, the University of Buffalo, Guangdong General Hospital and the Academy of Medical Sciences; is a consulting member for Novo Nordisk; is a member of the data safety and monitoring board for a trial of pulmonary hypertension in patients with diabetes at Massachusetts General Hospital; receives royalties from UpToDate; and receives an honorarium from the American Society for Nutrition for his duties as an associate editor. K. Stefansson is an employee of deCODE Genetics–Amgen. K.J.G. consults for Genentech and holds stock in Vertex Pharmaceuticals. A.L.G.’s spouse is an employee of Genentech and holds stock options in Roche. M.I.M. has served on advisory panels for Pfizer, Novo Nordisk and Zoe Global; has received honoraria from Merck, Pfizer, Novo Nordisk and Eli Lilly and research funding from AbbVie, AstraZeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, Novo Nordisk, Pfizer, Roche, Sanofi Aventis, Servier and Takeda; is now an employee of Genentech and a holder of Roche stock. The remaining authors declare no competing interests. The views expressed in this article are those of the authors and do not necessarily represent those of the NHS, the NIHR or the UK Department of Health; the National Heart, Lung, and Blood Institute, the National Institutes of Health or the US Department of Health and Human Services.

Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.

Keywords

  • Diabetes Mellitus, Type 2/epidemiology
  • Ethnicity
  • Genetic Predisposition to Disease
  • Genome-Wide Association Study
  • Humans
  • Polymorphism, Single Nucleotide/genetics
  • Risk Factors

PubMed: MeSH publication types

  • Research Support, Non-U.S. Gov't
  • Meta-Analysis
  • Journal Article

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