The trans-ancestral genomic architecture of glycemic traits

生物 遗传学 遗传建筑学 血糖性 基因 进化生物学 糖尿病 表型 计算生物学 内分泌学
作者
Jihua Chen,Cassandra N. Spracklen,Gaëlle Marenne,Arushi Varshney,Laura J. Corbin,Jian’an Luan,Sara M. Willems,Ying Wu,Xiaoshuai Zhang,Momoko Horikoshi,Thibaud Boutin,Reedik Mägi,Johannes Waage,Ruifang Li‐Gao,Kei Hang Katie Chan,Jie Yao,Mila Desi Anasanti,Audrey Y. Chu,Annique Claringbould,Jani Heikkinen
出处
期刊:Nature Genetics [Springer Nature]
卷期号:53 (6): 840-860 被引量:823
标识
DOI:10.1038/s41588-021-00852-9
摘要

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10−8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.
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