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; Yasuharu Tabara; Yang Hai; Valgerdur Steinthorsdottir; James P Cook; Mart Kals; Niels Grarup; Ellen M Schmidt; Ian Pan; Tamar Sofer; Ivan Brandslund; Marit E Jørgensen; FinnGen; eMERGE Consortium

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, Yasuharu Tabara, Yang Hai, Valgerdur Steinthorsdottir, James P Cook, Mart Kals, Niels Grarup, Ellen M Schmidt, Ian Pan, Tamar Sofer, Ivan Brandslund, Marit E Jørgensen, FinnGen, eMERGE Consortium

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

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
ISSN	1061-4036
DOI	https://doi.org/10.1038/s41588-022-01058-3
Status	Udgivet - 12. maj 2022

Dokumenter og links

10.1038/s41588-022-01058-3

https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/35551307/

SDU link

Tjek adgangen til materialet i Syddansk Universitetsbiblioteks søgemaskine

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., ... eMERGE Consortium (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

@article{912310f112154cf9b624a07928417dff,

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

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.",

keywords = "Diabetes Mellitus, Type 2/epidemiology, Ethnicity, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide/genetics, Risk Factors",

author = "Anubha Mahajan and Spracklen, {Cassandra N} and Weihua Zhang and Ng, {Maggie C Y} and Petty, {Lauren E} and Hidetoshi Kitajima and Yu, {Grace Z} and Sina R{\"u}eger and Leo Speidel and Kim, {Young Jin} and Momoko Horikoshi and Mercader, {Josep M} and Daniel Taliun and Sanghoon Moon and Soo-Heon Kwak and Robertson, {Neil R} and Rayner, {Nigel W} and Marie Loh and Bong-Jo Kim and Joshua Chiou and Irene Miguel-Escalada and {Della Briotta Parolo}, Pietro and Kuang Lin and Fiona Bragg and Preuss, {Michael H} and Fumihiko Takeuchi and Jana Nano and Xiuqing Guo and Amel Lamri and Masahiro Nakatochi and Scott, {Robert A} and Jung-Jin Lee and Alicia Huerta-Chagoya and Mariaelisa Graff and Jin-Fang Chai and Parra, {Esteban J} and Jie Yao and Bielak, {Lawrence F} and Yasuharu Tabara and Yang Hai and Valgerdur Steinthorsdottir and Cook, {James P} and Mart Kals and Niels Grarup and Schmidt, {Ellen M} and Ian Pan and Tamar Sofer and Ivan Brandslund and J{\o}rgensen, {Marit E} and FinnGen and {eMERGE Consortium}",

year = "2022",

month = may,

day = "12",

doi = "10.1038/s41588-022-01058-3",

language = "English",

volume = "54",

pages = "560--572",

journal = "Nature Genetics",

issn = "1061-4036",

publisher = "Nature Research",

number = "5",

}

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, Tabara, Y, Hai, Y, Steinthorsdottir, V, Cook, JP, Kals, M, Grarup, N, Schmidt, EM, Pan, I, Sofer, T, Brandslund, I , Jørgensen, ME, FinnGen & eMERGE Consortium 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

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 - Tabara, Yasuharu

AU - Hai, Yang

AU - Steinthorsdottir, Valgerdur

AU - Cook, James P

AU - Kals, Mart

AU - Grarup, Niels

AU - Schmidt, Ellen M

AU - Pan, Ian

AU - Sofer, Tamar

AU - Brandslund, Ivan

AU - Jørgensen, Marit E

AU - FinnGen

AU - eMERGE Consortium

PY - 2022/5/12

Y1 - 2022/5/12

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 -

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

Abstract

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SDU link

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