全基因组关联研究
生物
遗传关联
荟萃分析
遗传学
2型糖尿病
人口分层
1000基因组计划
人口
计算生物学
遗传谱系
进化生物学
基因
单核苷酸多态性
基因型
糖尿病
人口学
医学
内科学
内分泌学
社会学
作者
Anubha Mahajan,Cassandra N. Spracklen,Weihua Zhang,Maggie C. Y. Ng,Lauren E. Petty,Hidetoshi Kitajima,Grace Z. Yu,Sina Rüeger,Leo Speidel,Young Jin Kim,Momoko Horikoshi,Josep M. Mercader,Daniel Taliun,Sanghoon Moon,Soo‐Heon Kwak,Neil Robertson,Nigel W. Rayner,Marie Loh,Bong-Jo Kim,Joshua Chiou
出处
期刊:Nature Genetics
[Nature Portfolio]
日期:2022-05-01
卷期号:54 (5): 560-572
被引量:493
标识
DOI:10.1038/s41588-022-01058-3
摘要
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. 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.
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