bioRxivGeneticsPreprint
The Trans-Ancestral Genomic Architecture of Glycaemic Traits
Ji CheniD, Cassandra Nichole SprackleniD, Gaëlle MarenneiD, Arushi VarshneyiD, Laura J. CorbiniD, Jian’an LuaniD, Sara M. WillemsiD, Ying WuiD, Xiaoshuai ZhangiD, Momoko HorikoshiiD, Thibaud BoutiniD, Reedik MägiiD, Johannes WaageiD, Achilleas PitsillidesiD, Ruifang Li‐GaoiD, Kei Hang, Jie YaoiD, Mila Desi AnasantiiD, Audrey Y. ChuiD, Annique ClaringbouldiD, Jani HeikkineniD, Jaeyoung HongiD, Jouke‐Jan HottengaiD, Shaofeng HuoiD, Marika KaakineniD, , Michael H PreussiD
Abstract
Glycaemic traits are used to diagnose and monitor type 2 diabetes, and cardiometabolic health. To date, most genetic studies of glycaemic traits have focused on individuals of European ancestry. Here, we aggregated genome-wide association studies in up to 281,416 individuals without diabetes (30% non-European ancestry) with fasting glucose, 2h-glucose post-challenge, glycated haemoglobin, and fasting insulin data. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P<5x10-8), 80% with no significant evidence of between-ancestry heterogeneity. Analyses restricted to European ancestry individuals with equivalent sample size would have led to 24 fewer new loci. Compared to single-ancestry, 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 understanding of diabetes pathophysiology by use of trans-ancestry studies for improved power and resolution.
- organism: human
- assay: GWAS summary statistics
- research focus: fine-mapping
- approach: statistical model
- Citations
- 7
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