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).

In: Nature Genetics, Vol. 53, No. 6, 2021, p. 840-860.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Chen, J, Spracklen, CN, Marenne, G, Varshney, A, Corbin, LJ, Luan, J, Willems, SM, Wu, Y, Zhang, X, Horikoshi, M, Boutin, TS, Magi, R, Waage, J, Li-Gao, R, Chan, KHK, Yao, J, Anasanti, MD, Chu, AY, Claringbould, A, Heikkinen, J, Hong, J, Hottenga, J-J, Huo, S, Kaakinen, MA, Louie, T, Maerz, W, Moreno-Macias, H, Ndungu, A, Nelson, SC, Nolte, IM, North, KE, Appel, EVR, Liu, J, Sparso, T, Zhao, J-H, Astrup, A, Jørgensen, ME, Linneberg, A, Vestergaard, H, Bisgaard, H, Bønnelykke, K, Grarup, N, Hansen, T, Kovacs, P, Lind, L, Loos, RJF, Njølstad, I, Pedersen, O, Schwarz, P, Sorensen, TIA & Meta-Analysis of Glucose and Insulin-Related Trait Consortium (MAGIC) 2021, 'The trans-ancestral genomic architecture of glycemic traits', Nature Genetics, vol. 53, no. 6, pp. 840-860. https://doi.org/10.1038/s41588-021-00852-9

APA

Chen, J., Spracklen, C. N., Marenne, G., Varshney, A., Corbin, L. J., Luan, J., Willems, S. M., Wu, Y., Zhang, X., Horikoshi, M., Boutin, T. S., Magi, R., Waage, J., Li-Gao, R., Chan, K. H. K., Yao, J., Anasanti, M. D., Chu, A. Y., Claringbould, A., ... Meta-Analysis of Glucose and Insulin-Related Trait Consortium (MAGIC) (2021). The trans-ancestral genomic architecture of glycemic traits. Nature Genetics, 53(6), 840-860. https://doi.org/10.1038/s41588-021-00852-9

Vancouver

Chen J, Spracklen CN, Marenne G, Varshney A, Corbin LJ, Luan J et al. The trans-ancestral genomic architecture of glycemic traits. Nature Genetics. 2021;53(6):840-860. https://doi.org/10.1038/s41588-021-00852-9

Author

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). / The trans-ancestral genomic architecture of glycemic traits. In: Nature Genetics. 2021 ; Vol. 53, No. 6. pp. 840-860.

Bibtex

@article{7a119b76b33946e1a23e9c6a507b9d0b,
title = "The trans-ancestral genomic architecture of glycemic traits",
abstract = "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.",
keywords = "Wide association study, Insulin-resistance, Gene-expression, Disease risk, Variants, Glucose, Loci, Meta analysis, Mechanisms, Hemoglobin",
author = "Ji Chen and Spracklen, {Cassandra N.} and Ga{\"e}lle Marenne and Arushi Varshney and Corbin, {Laura J.} and Jian'an Luan and Willems, {Sara M} and Ying Wu and Xiaoshuai Zhang and Momoko Horikoshi and Boutin, {Thibaud S.} and Reedik Magi and Johannes Waage and Ruifang Li-Gao and Chan, {Kei Hang Katie} and Jie Yao and Anasanti, {Mila D.} and Chu, {Audrey Y.} and Annique Claringbould and Jani Heikkinen and Jaeyoung Hong and Jouke-Jan Hottenga and Shaofeng Huo and Kaakinen, {Marika A.} and Tin Louie and Winfried Maerz and Hortensia Moreno-Macias and Anne Ndungu and Nelson, {Sarah C.} and Nolte, {Ilja M.} and North, {Kari E.} and Appel, {Emil V. R.} and Jun Liu and Thomas Sparso and Jing-Hua Zhao and Arne Astrup and J{\o}rgensen, {Marit E.} and Allan Linneberg and Henrik Vestergaard and Hans Bisgaard and Klaus B{\o}nnelykke and Niels Grarup and Torben Hansen and Peter Kovacs and Lars Lind and Loos, {Ruth J. F.} and Inger Nj{\o}lstad and Oluf Pedersen and Peter Schwarz and Sorensen, {Thorkild I. A.} and {Meta-Analysis of Glucose and Insulin-Related Trait Consortium (MAGIC)}",
note = "CURIS 2021 NEXS 206",
year = "2021",
doi = "10.1038/s41588-021-00852-9",
language = "English",
volume = "53",
pages = "840--860",
journal = "Nature Genetics",
issn = "1061-4036",
publisher = "nature publishing group",
number = "6",

}

RIS

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