TY - JOUR
T1 - The trans-ancestral genomic architecture of glycemic traits
AU - Lifelines Cohort Study
AU - The Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC)
AU - Chen, Ji
AU - Spracklen, Cassandra N.
AU - Marenne, Gaëlle
AU - Varshney, Arushi
AU - Corbin, Laura J.
AU - Luan, Jian’an
AU - Willems, Sara M.
AU - Wu, Ying
AU - Zhang, Xiaoshuai
AU - Horikoshi, Momoko
AU - Boutin, Thibaud S.
AU - Mägi, Reedik
AU - Waage, Johannes
AU - Li-Gao, Ruifang
AU - Chan, Kei Hang Katie
AU - Yao, Jie
AU - Anasanti, Mila D.
AU - Chu, Audrey Y.
AU - Claringbould, Annique
AU - Heikkinen, Jani
AU - Hong, Jaeyoung
AU - Hottenga, Jouke Jan
AU - Huo, Shaofeng
AU - Kaakinen, Marika A.
AU - Louie, Tin
AU - März, Winfried
AU - Moreno-Macias, Hortensia
AU - Ndungu, Anne
AU - Nelson, Sarah C.
AU - Nolte, Ilja M.
AU - North, Kari E.
AU - Raulerson, Chelsea K.
AU - Ray, Debashree
AU - Rohde, Rebecca
AU - Rybin, Denis
AU - Schurmann, Claudia
AU - Sim, Xueling
AU - Southam, Lorraine
AU - Stewart, Isobel D.
AU - Wang, Carol A.
AU - Wang, Yujie
AU - Wu, Peitao
AU - Zhang, Weihua
AU - Ahluwalia, Tarunveer S.
AU - Appel, Emil V.R.
AU - Bielak, Lawrence F.
AU - Brody, Jennifer A.
AU - Burtt, Noël P.
AU - Cabrera, Claudia P.
AU - Zeggini, Eleftheria
N1 - Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.
PY - 2021/6/1
Y1 - 2021/6/1
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85108020584
U2 - 10.1038/s41588-021-00852-9
DO - 10.1038/s41588-021-00852-9
M3 - Article
C2 - 34059833
AN - SCOPUS:85108020584
SN - 1061-4036
VL - 53
SP - 840
EP - 860
JO - Nature Genetics
JF - Nature Genetics
IS - 6
ER -
SDG 3 – Gute Gesundheit und Wohlergehen