Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
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Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. / Mahajan, Anubha; Spracklen, Cassandra N; Zhang, Weihua; Ng, Maggie C Y; Petty, Lauren E; Kitajima, Hidetoshi; Yu, Grace Z; Rüeger, Sina; Speidel, Leo; Kim, Young Jin; Horikoshi, Momoko; Mercader, Josep M; Taliun, Daniel; Moon, Sanghoon; Kwak, Soo-Heon; Robertson, Neil R; Rayner, Nigel W; Loh, Marie; Kim, Bong-Jo; Chiou, Joshua; Miguel-Escalada, Irene; Della Briotta Parolo, Pietro; Lin, Kuang; Bragg, Fiona; Preuss, Michael H; Takeuchi, Fumihiko; Nano, Jana; Guo, Xiuqing; Lamri, Amel; Nakatochi, Masahiro; Scott, Robert A; Lee, Jung-Jin; Huerta-Chagoya, Alicia; Graff, Mariaelisa; Chai, Jin-Fang; Parra, Esteban J; Yao, Jie; Bielak, Lawrence F; Grarup, Niels; Chen, Wei-Min; Bork-Jensen, Jette; Islam, Md Tariqul; Jørgensen, Marit E; Jørgensen, Torben; Linneberg, Allan; Witte, Daniel R; Lind, Lars; Loos, Ruth J F; Hansen, Torben; Pedersen, Oluf; FinnGen.
In: Nature Genetics, Vol. 54, No. 5, 2022, p. 560-572.Research output: Contribution to journal › Journal article › peer-review
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TY - JOUR
T1 - Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation
AU - Mahajan, Anubha
AU - Spracklen, Cassandra N
AU - Zhang, Weihua
AU - Ng, Maggie C Y
AU - Petty, Lauren E
AU - Kitajima, Hidetoshi
AU - Yu, Grace Z
AU - Rüeger, Sina
AU - Speidel, Leo
AU - Kim, Young Jin
AU - Horikoshi, Momoko
AU - Mercader, Josep M
AU - Taliun, Daniel
AU - Moon, Sanghoon
AU - Kwak, Soo-Heon
AU - Robertson, Neil R
AU - Rayner, Nigel W
AU - Loh, Marie
AU - Kim, Bong-Jo
AU - Chiou, Joshua
AU - Miguel-Escalada, Irene
AU - Della Briotta Parolo, Pietro
AU - Lin, Kuang
AU - Bragg, Fiona
AU - Preuss, Michael H
AU - Takeuchi, Fumihiko
AU - Nano, Jana
AU - Guo, Xiuqing
AU - Lamri, Amel
AU - Nakatochi, Masahiro
AU - Scott, Robert A
AU - Lee, Jung-Jin
AU - Huerta-Chagoya, Alicia
AU - Graff, Mariaelisa
AU - Chai, Jin-Fang
AU - Parra, Esteban J
AU - Yao, Jie
AU - Bielak, Lawrence F
AU - Grarup, Niels
AU - Chen, Wei-Min
AU - Bork-Jensen, Jette
AU - Islam, Md Tariqul
AU - Jørgensen, Marit E
AU - Jørgensen, Torben
AU - Linneberg, Allan
AU - Witte, Daniel R
AU - Lind, Lars
AU - Loos, Ruth J F
AU - Hansen, Torben
AU - Pedersen, Oluf
AU - FinnGen
N1 - © 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.
PY - 2022
Y1 - 2022
N2 - We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.
AB - We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.
KW - Diabetes Mellitus, Type 2/epidemiology
KW - Ethnicity
KW - Genetic Predisposition to Disease
KW - Genome-Wide Association Study
KW - Humans
KW - Polymorphism, Single Nucleotide/genetics
KW - Risk Factors
U2 - 10.1038/s41588-022-01058-3
DO - 10.1038/s41588-022-01058-3
M3 - Journal article
C2 - 35551307
VL - 54
SP - 560
EP - 572
JO - Nature Genetics
JF - Nature Genetics
SN - 1061-4036
IS - 5
ER -
ID: 308116769