The trans-ancestral genomic architecture of glycemic traits

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...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Nature genetics Ročník 53; číslo 6; s. 840 - 860
Hlavní autoři: Marenne, Gaëlle, Horikoshi, Momoko, Chu, Audrey Y., Hong, Jaeyoung, Hottenga, Jouke-Jan, Kaakinen, Marika A., Moreno-Macias, Hortensia, Nolte, Ilja M., Raulerson, Chelsea K., Chen, Brian H., Hai, Yang, He, Jing, Heianza, Yoriko, Huang, Tao, Huerta-Chagoya, Alicia, Jensen, Richard A., Lange, Leslie A., Langefeld, Carl D., Li, Man, Nag, Abhishek, Pistis, Giorgio, Raffield, Laura, Robertson, Neil R., Rueedi, Rico, Ryan, Kathleen, Saxena, Richa, van der Most, Peter J., Wang, Nan, Warren, Helen R., Wilsgaard, Tom, Wong, Andrew, Zafarmand, Mohammad Hadi, Baldassarre, Damiano, Beekman, Marian, Bergman, Richard N., Bornstein, Stefan R., Campbell, Archie, Chang, Yi Cheng, Eiriksdottir, Gudny, Han, Sohee, Hartman, Catharina A., Ichihara, Sahoko, Katsuya, Tomohiro, Khor, Chiea Chuen, Kolcic, Ivana, Kuulasmaa, Teemu, Lemaitre, Rozenn N., Lin, Shih-Yi, Linneberg, Allan, Matsuda, Fumihiko, Moon, Sanghoon, Ohyagi, Yasumasa, Qi, Qibin, Sandow, Kevin, Thuesen, Betina, van Dam, Rob M., Willems van Dijk, Ko, Adair, Linda S., Boehnke, Michael, Bønnelykke, Klaus, Boomsma, D. I., Buchanan, Thomas A., Chambers, John C., Chasman, Daniel I., Chen, Yii-Der Ida, Collins, Francis S., Cucca, Francesco, de Silva, H. Janaka, Ferrucci, Luigi, Florez, Jose C., Franks, Paul W., Grimsgaard, Sameline, Guo, Xiuqing, Huang, Wei, Kato, Norihiro, Koistinen, Heikki A., Kuh, Diana, Kumari, Meena, Launer, Lenore J., Mook-Kanamori, Dennis O., Pedersen, Oluf, Pramstaller, Peter P., Province, Michael A., Psaty, Bruce M., Rosendaal, Frits R., Shu, Xiao-ou, Tai, E. Shyong, Timpson, Nicholas J., Tusie, Teresa, Uusitupa, Matti, Vrijkotte, Tanja G. M., Wei, Wen B., Willemsen, Gonneke, Wong, Tien-Yin, Xiang, Anny H., Yokota, Mitsuhiro, Zeggini, Eleftheria, McCarthy, Mark I., Dupuis, Josée, Parker, Stephen C. J.
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Nature Publishing Group US 01.06.2021
Nature Publishing Group
Témata:
ISSN:1061-4036, 1546-1718, 1546-1718
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí: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. 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.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
PMCID: PMC7610958
Denote shared authorship contributions
Current address: Genentech, South San Francisco, CA
ISSN:1061-4036
1546-1718
1546-1718
DOI:10.1038/s41588-021-00852-9