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dc.date.accessioned |
2022-06-03T06:15:47Z |
|
dc.date.available |
2022-06-03T06:15:47Z |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Nature Genetics.2022;54(5):560-572. |
en_US |
dc.identifier.issn |
1061-4036 |
|
dc.identifier.uri |
http://repository.kln.ac.lk/handle/123456789/24629 |
|
dc.description |
Indexed in MEDLINE. |
en_US |
dc.description.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. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Nature Publishing Company, New York |
en_US |
dc.subject |
Diabetes |
en_US |
dc.subject |
Populations |
en_US |
dc.title |
Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation |
en_US |
dc.type |
Article |
en_US |