The trans-ancestral genomic architecture of glycemic traits

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  • Ji Chen
  • Cassandra N. Spracklen
  • Gaëlle Marenne
  • Arushi Varshney
  • Laura J. Corbin
  • Jian'an Luan
  • Sara M Willems
  • Ying Wu
  • Xiaoshuai Zhang
  • Momoko Horikoshi
  • Thibaud S. Boutin
  • Reedik Magi
  • Johannes Waage
  • Ruifang Li-Gao
  • Kei Hang Katie Chan
  • Jie Yao
  • Mila D. Anasanti
  • Audrey Y. Chu
  • Annique Claringbould
  • Jani Heikkinen
  • Jaeyoung Hong
  • Jouke-Jan Hottenga
  • Shaofeng Huo
  • Marika A. Kaakinen
  • Tin Louie
  • Winfried Maerz
  • Hortensia Moreno-Macias
  • Anne Ndungu
  • Sarah C. Nelson
  • Ilja M. Nolte
  • Kari E. North
  • Emil V. R. Appel
  • Jun Liu
  • Thomas Sparso
  • Jing-Hua Zhao
  • Arne Astrup
  • Marit E. Jørgensen
  • Linneberg, Allan René
  • Henrik Vestergaard
  • Hans Bisgaard
  • Bønnelykke, Klaus
  • Grarup, Niels
  • Hansen, Torben
  • Peter Kovacs
  • Lars Lind
  • Ruth J. F. Loos
  • Inger Njølstad
  • Pedersen, Oluf Borbye
  • Schwarz, Peter
  • Sørensen, Thorkild I.A.
  • Meta-Analysis of Glucose and Insulin-Related Trait Consortium (MAGIC)

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 x 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.

OriginalsprogEngelsk
TidsskriftNature Genetics
Vol/bind53
Udgave nummer6
Sider (fra-til)840-860
Antal sider41
ISSN1061-4036
DOI
StatusUdgivet - 2021

Bibliografisk note

CURIS 2021 NEXS 206

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