The trans-ancestral genomic architecture of glycemic traits
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The trans-ancestral genomic architecture of glycemic traits. / Chen, Ji; Spracklen, Cassandra N.; Marenne, Gaëlle; Varshney, Arushi; Corbin, Laura J.; Luan, Jian'an; Willems, Sara M; Wu, Ying; Zhang, Xiaoshuai; Horikoshi, Momoko; Boutin, Thibaud S.; Magi, Reedik; Waage, Johannes; Li-Gao, Ruifang; Chan, Kei Hang Katie; Yao, Jie; Anasanti, Mila D.; Chu, Audrey Y.; Claringbould, Annique; Heikkinen, Jani; Hong, Jaeyoung; Hottenga, Jouke-Jan; Huo, Shaofeng; Kaakinen, Marika A.; Louie, Tin; Maerz, Winfried; Moreno-Macias, Hortensia; Ndungu, Anne; Nelson, Sarah C.; Nolte, Ilja M.; North, Kari E.; Appel, Emil V. R.; Liu, Jun; Sparso, Thomas; Zhao, Jing-Hua; Astrup, Arne; Jørgensen, Marit E.; Linneberg, Allan; Vestergaard, Henrik; Bisgaard, Hans; Bønnelykke, Klaus; Grarup, Niels; Hansen, Torben; Kovacs, Peter; Lind, Lars; Loos, Ruth J. F.; Njølstad, Inger; Pedersen, Oluf; Schwarz, Peter; Sorensen, Thorkild I. A.; Meta-Analysis of Glucose and Insulin-Related Trait Consortium (MAGIC).
I: Nature Genetics, Bind 53, Nr. 6, 2021, s. 840-860.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - The trans-ancestral genomic architecture of glycemic traits
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 - Magi, 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 - Maerz, Winfried
AU - Moreno-Macias, Hortensia
AU - Ndungu, Anne
AU - Nelson, Sarah C.
AU - Nolte, Ilja M.
AU - North, Kari E.
AU - Appel, Emil V. R.
AU - Liu, Jun
AU - Sparso, Thomas
AU - Zhao, Jing-Hua
AU - Astrup, Arne
AU - Jørgensen, Marit E.
AU - Linneberg, Allan
AU - Vestergaard, Henrik
AU - Bisgaard, Hans
AU - Bønnelykke, Klaus
AU - Grarup, Niels
AU - Hansen, Torben
AU - Kovacs, Peter
AU - Lind, Lars
AU - Loos, Ruth J. F.
AU - Njølstad, Inger
AU - Pedersen, Oluf
AU - Schwarz, Peter
AU - Sorensen, Thorkild I. A.
AU - Meta-Analysis of Glucose and Insulin-Related Trait Consortium (MAGIC)
N1 - CURIS 2021 NEXS 206
PY - 2021
Y1 - 2021
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 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.
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 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.
KW - Wide association study
KW - Insulin-resistance
KW - Gene-expression
KW - Disease risk
KW - Variants
KW - Glucose
KW - Loci
KW - Meta analysis
KW - Mechanisms
KW - Hemoglobin
U2 - 10.1038/s41588-021-00852-9
DO - 10.1038/s41588-021-00852-9
M3 - Journal article
C2 - 34059833
VL - 53
SP - 840
EP - 860
JO - Nature Genetics
JF - Nature Genetics
SN - 1061-4036
IS - 6
ER -
ID: 271535671