The trans-ancestral genomic architecture of glycemic traits

Ji Chen, Cassandra N. Spracklen, Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC), Lifelines Cohort Study, Gaëlle Marenne, Arushi Varshney, Laura J. Corbin, Jian'an Luan, Sara M. Willems, Ying Wu, Xiaoshuai Zhang, Momoko Horikoshi, Thibaud S. Boutin, Reedik Mägi, Johannes Waage, Ruifang Li-Gao, Kei Hang Katie Chan, Jie Yao, Mila D. Anasanti, Audrey Y. ChuAnnique Claringbould, Jani Heikkinen, Jaeyoung Hong, Jouke Jan Hottenga, Shaofeng Huo, Marika A. Kaakinen, Tin Louie, Winfried März, Hortensia Moreno-Macias, Anne Ndungu, Sarah C. Nelson, Ilja M. Nolte, Kari E. North, Chelsea K. Raulerson, Debashree Ray, Rebecca Rohde, Ayse Demirkan, Symen Ligthart, Jun Liu, Raymond Noordam, Niek Verweij, Jing Hua Zhao, Wei Zhao, Najaf Amin, Abbas Dehghan, M. Arfan Ikram, Shih Yi Lin, Andre Uitterlinden, Torben Hansen, Simin Liu, Ya X. Wang, Tien Yin Wong, F. (Fernando) Rivadeneira, C.M. (Cornelia) van Duijn, AP Morris, I Barroso

Research output: Contribution to journalArticleAcademicpeer-review

74 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)840-860
Number of pages21
JournalNature Genetics
Issue number6
Early online date21 Mar 2021
Publication statusPublished - 1 Jun 2021


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