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Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
Univ Oxford, Oxford Ctr Diabet Endocrinol & Metab, Radcliffe Dept Med, Oxford, England.;Univ Oxford, Wellcome Ctr Human Genet, Nuffield Dept Med, Oxford, England.;Genentech Inc, San Francisco, CA 94080 USA..ORCID iD: 0000-0001-5585-3420
Univ North Carolina Chapel Hill, Dept Genet, Chapel Hill, NC USA.;Univ Massachusetts, Dept Epidemiol & Biostat, Amherst, MA 01003 USA..
Imperial Coll London, Dept Epidemiol & Biostat, London, England.;London North West Healthcare NHS Trust, Dept Cardiol, Ealing Hosp, London, England..
Vanderbilt Univ Sch Med, Vanderbilt Genet Inst, Div Genet Med, Nashville, TN USA.;Wake Forest Sch Med, Ctr Genom & Personalized Med Res, Winston Salem, NC 27101 USA.;Wake Forest Sch Med, Dept Biochem, Winston Salem, NC 27101 USA..
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2022 (English)In: Nature Genetics, ISSN 1061-4036, E-ISSN 1546-1718, Vol. 54, no 5, p. 560-572Article in journal (Refereed) Published
Abstract [en]

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 x 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. Genome-wide association and fine-mapping analyses in ancestrally diverse populations implicate candidate causal genes and mechanisms underlying type 2 diabetes. Trans-ancestry genetic risk scores enhance transferability across populations.
Place, publisher, year, edition, pages
Springer Nature Springer Nature, 2022. Vol. 54, no 5, p. 560-572
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Medical Genetics and Genomics
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URN: urn:nbn:se:uu:diva-476118DOI: 10.1038/s41588-022-01058-3ISI: 000794118000004PubMedID: 35551307OAI: oai:DiVA.org:uu-476118DiVA, id: diva2:1665553
Available from: 2022-06-07 Created: 2022-06-07 Last updated: 2025-02-10Bibliographically approved

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Giedraitis, VilmantasIngelsson, MartinLind, LarsIngelsson, Erik

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