Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Anubha Mahajan; Cassandra N Spracklen; Weihua Zhang; Maggie C Y Ng; Lauren E Petty; Hidetoshi Kitajima; Grace Z Yu; Sina Rüeger; Leo Speidel; Young Jin Kim; Momoko Horikoshi; Josep M Mercader; Daniel Taliun; Sanghoon Moon; Soo-Heon Kwak; Neil R Robertson; Nigel W Rayner; Marie Loh; Bong-Jo Kim; Joshua Chiou; Irene Miguel-Escalada; Pietro Della Briotta Parolo; Kuang Lin; Fiona Bragg; Michael H Preuss; Fumihiko Takeuchi; Jana Nano; Xiuqing Guo; Amel Lamri; Masahiro Nakatochi; Robert A Scott; Jung-Jin Lee; Alicia Huerta-Chagoya; Mariaelisa Graff; Jin-Fang Chai; Esteban J Parra; Jie Yao; Lawrence F Bielak; Niels Grarup; Wei-Min Chen; Jette Bork-Jensen; Md Tariqul Islam; Marit E Jørgensen; Torben Jørgensen; Allan Linneberg; Daniel R Witte; Lars Lind; Ruth J F Loos; Torben Hansen; Oluf Pedersen; FinnGen

doi:10.1038/s41588-022-01058-3

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Anubha Mahajan, Cassandra N Spracklen, Weihua Zhang, Maggie C Y Ng, Lauren E Petty, Hidetoshi Kitajima, Grace Z Yu, Sina Rüeger, Leo Speidel, Young Jin Kim, Momoko Horikoshi, Josep M Mercader, Daniel Taliun, Sanghoon Moon, Soo-Heon Kwak, Neil R Robertson, Nigel W Rayner, Marie Loh, Bong-Jo Kim, Joshua ChiouIrene Miguel-Escalada, Pietro Della Briotta Parolo, Kuang Lin, Fiona Bragg, Michael H Preuss, Fumihiko Takeuchi, Jana Nano, Xiuqing Guo, Amel Lamri, Masahiro Nakatochi, Robert A Scott, Jung-Jin Lee, Alicia Huerta-Chagoya, Mariaelisa Graff, Jin-Fang Chai, Esteban J Parra, Jie Yao, Lawrence F Bielak, Niels Grarup, Wei-Min Chen, Jette Bork-Jensen, Md Tariqul Islam, Marit E Jørgensen, Torben Jørgensen, Allan Linneberg, Daniel R Witte, Lars Lind, Ruth J F Loos, Torben Hansen, Oluf Pedersen, FinnGen

Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review

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Abstract

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.

Originalsprog	Engelsk
Tidsskrift	Nature Genetics
Vol/bind	54
Udgave nummer	5
Sider (fra-til)	560-572
Antal sider	13
ISSN	1061-4036
DOI	https://doi.org/10.1038/s41588-022-01058-3
Status	Udgivet - 2022

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10.1038/s41588-022-01058-3

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translationAccepteret manuskript, 2,62 MBLicens: Andet

Citationsformater

Mahajan, A., Spracklen, C. N., Zhang, W., Ng, M. C. Y., Petty, L. E., Kitajima, H., Yu, G. Z., Rüeger, S., Speidel, L., Kim, Y. J., Horikoshi, M., Mercader, J. M., Taliun, D., Moon, S., Kwak, S.-H., Robertson, N. R., Rayner, N. W., Loh, M., Kim, B.-J., ... FinnGen (2022). Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation. Nature Genetics, 54(5), 560-572. https://doi.org/10.1038/s41588-022-01058-3

Mahajan, A, Spracklen, CN, Zhang, W, Ng, MCY, Petty, LE, Kitajima, H, Yu, GZ, Rüeger, S, Speidel, L, Kim, YJ, Horikoshi, M, Mercader, JM, Taliun, D, Moon, S, Kwak, S-H, Robertson, NR, Rayner, NW, Loh, M, Kim, B-J, Chiou, J, Miguel-Escalada, I, Della Briotta Parolo, P, Lin, K, Bragg, F, Preuss, MH, Takeuchi, F, Nano, J, Guo, X, Lamri, A, Nakatochi, M, Scott, RA, Lee, J-J, Huerta-Chagoya, A, Graff, M, Chai, J-F, Parra, EJ, Yao, J, Bielak, LF, Grarup, N, Chen, W-M, Bork-Jensen, J, Islam, MT, Jørgensen, ME, Jørgensen, T, Linneberg, A, Witte, DR, Lind, L, Loos, RJF , Hansen, T , Pedersen, O & FinnGen 2022, 'Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation', Nature Genetics, bind 54, nr. 5, s. 560-572. https://doi.org/10.1038/s41588-022-01058-3

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abstract = "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.",

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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

PY - 2022

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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

SN - 1061-4036

VL - 54

SP - 560

EP - 572

JO - Nature Genetics

JF - Nature Genetics

IS - 5

ER -