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Evaluation of type 2 diabetes genetic risk variants in Chinese adults: findings from 93,000 individuals from the China Kadoorie Biobank

AIMS/HYPOTHESIS: Genome-wide association studies (GWAS) have discovered many risk variants for type 2 diabetes. However, estimates of the contributions of risk variants to type 2 diabetes predisposition are often based on highly selected case–control samples, and reliable estimates of population-lev...

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Autores principales: Gan, Wei, Walters, Robin G., Holmes, Michael V., Bragg, Fiona, Millwood, Iona Y., Banasik, Karina, Chen, Yiping, Du, Huaidong, Iona, Andri, Mahajan, Anubha, Yang, Ling, Bian, Zheng, Guo, Yu, Clarke, Robert J., Li, Liming, McCarthy, Mark I., Chen, Zhengming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4901105/
https://www.ncbi.nlm.nih.gov/pubmed/27053236
http://dx.doi.org/10.1007/s00125-016-3920-9
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author Gan, Wei
Walters, Robin G.
Holmes, Michael V.
Bragg, Fiona
Millwood, Iona Y.
Banasik, Karina
Chen, Yiping
Du, Huaidong
Iona, Andri
Mahajan, Anubha
Yang, Ling
Bian, Zheng
Guo, Yu
Clarke, Robert J.
Li, Liming
McCarthy, Mark I.
Chen, Zhengming
author_facet Gan, Wei
Walters, Robin G.
Holmes, Michael V.
Bragg, Fiona
Millwood, Iona Y.
Banasik, Karina
Chen, Yiping
Du, Huaidong
Iona, Andri
Mahajan, Anubha
Yang, Ling
Bian, Zheng
Guo, Yu
Clarke, Robert J.
Li, Liming
McCarthy, Mark I.
Chen, Zhengming
author_sort Gan, Wei
collection PubMed
description AIMS/HYPOTHESIS: Genome-wide association studies (GWAS) have discovered many risk variants for type 2 diabetes. However, estimates of the contributions of risk variants to type 2 diabetes predisposition are often based on highly selected case–control samples, and reliable estimates of population-level effect sizes are missing, especially in non-European populations. METHODS: The individual and cumulative effects of 59 established type 2 diabetes risk loci were measured in a population-based China Kadoorie Biobank (CKB) study of 93,000 Chinese adults, including >7,100 diabetes cases. RESULTS: Association signals were directionally consistent between CKB and the original discovery GWAS: of 56 variants passing quality control, 48 showed the same direction of effect (binomial test, p = 2.3 × 10(−8)). We observed a consistent overall trend towards lower risk variant effect sizes in CKB than in case–control samples of GWAS meta-analyses (mean 19–22% decrease in log odds, p ≤ 0.0048), likely to reflect correction of both ‘winner’s curse’ and spectrum bias effects. The association with risk of diabetes of a genetic risk score, based on lead variants at 25 loci considered to act through beta cell function, demonstrated significant interactions with several measures of adiposity (BMI, waist circumference [WC], WHR and percentage body fat [PBF]; all p(interaction) < 1 × 10(−4)), with a greater effect being observed in leaner adults. CONCLUSIONS/INTERPRETATION: Our study provides further evidence of shared genetic architecture for type 2 diabetes between Europeans and East Asians. It also indicates that even very large GWAS meta-analyses may be vulnerable to substantial inflation of effect size estimates, compared with those observed in large-scale population-based cohort studies. ACCESS TO RESEARCH MATERIALS: Details of how to access China Kadoorie Biobank data and details of the data release schedule are available from www.ckbiobank.org/site/Data+Access. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00125-016-3920-9) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
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spelling pubmed-49011052016-06-27 Evaluation of type 2 diabetes genetic risk variants in Chinese adults: findings from 93,000 individuals from the China Kadoorie Biobank Gan, Wei Walters, Robin G. Holmes, Michael V. Bragg, Fiona Millwood, Iona Y. Banasik, Karina Chen, Yiping Du, Huaidong Iona, Andri Mahajan, Anubha Yang, Ling Bian, Zheng Guo, Yu Clarke, Robert J. Li, Liming McCarthy, Mark I. Chen, Zhengming Diabetologia Article AIMS/HYPOTHESIS: Genome-wide association studies (GWAS) have discovered many risk variants for type 2 diabetes. However, estimates of the contributions of risk variants to type 2 diabetes predisposition are often based on highly selected case–control samples, and reliable estimates of population-level effect sizes are missing, especially in non-European populations. METHODS: The individual and cumulative effects of 59 established type 2 diabetes risk loci were measured in a population-based China Kadoorie Biobank (CKB) study of 93,000 Chinese adults, including >7,100 diabetes cases. RESULTS: Association signals were directionally consistent between CKB and the original discovery GWAS: of 56 variants passing quality control, 48 showed the same direction of effect (binomial test, p = 2.3 × 10(−8)). We observed a consistent overall trend towards lower risk variant effect sizes in CKB than in case–control samples of GWAS meta-analyses (mean 19–22% decrease in log odds, p ≤ 0.0048), likely to reflect correction of both ‘winner’s curse’ and spectrum bias effects. The association with risk of diabetes of a genetic risk score, based on lead variants at 25 loci considered to act through beta cell function, demonstrated significant interactions with several measures of adiposity (BMI, waist circumference [WC], WHR and percentage body fat [PBF]; all p(interaction) < 1 × 10(−4)), with a greater effect being observed in leaner adults. CONCLUSIONS/INTERPRETATION: Our study provides further evidence of shared genetic architecture for type 2 diabetes between Europeans and East Asians. It also indicates that even very large GWAS meta-analyses may be vulnerable to substantial inflation of effect size estimates, compared with those observed in large-scale population-based cohort studies. ACCESS TO RESEARCH MATERIALS: Details of how to access China Kadoorie Biobank data and details of the data release schedule are available from www.ckbiobank.org/site/Data+Access. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00125-016-3920-9) contains peer-reviewed but unedited supplementary material, which is available to authorised users. Springer Berlin Heidelberg 2016-04-06 2016 /pmc/articles/PMC4901105/ /pubmed/27053236 http://dx.doi.org/10.1007/s00125-016-3920-9 Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Gan, Wei
Walters, Robin G.
Holmes, Michael V.
Bragg, Fiona
Millwood, Iona Y.
Banasik, Karina
Chen, Yiping
Du, Huaidong
Iona, Andri
Mahajan, Anubha
Yang, Ling
Bian, Zheng
Guo, Yu
Clarke, Robert J.
Li, Liming
McCarthy, Mark I.
Chen, Zhengming
Evaluation of type 2 diabetes genetic risk variants in Chinese adults: findings from 93,000 individuals from the China Kadoorie Biobank
title Evaluation of type 2 diabetes genetic risk variants in Chinese adults: findings from 93,000 individuals from the China Kadoorie Biobank
title_full Evaluation of type 2 diabetes genetic risk variants in Chinese adults: findings from 93,000 individuals from the China Kadoorie Biobank
title_fullStr Evaluation of type 2 diabetes genetic risk variants in Chinese adults: findings from 93,000 individuals from the China Kadoorie Biobank
title_full_unstemmed Evaluation of type 2 diabetes genetic risk variants in Chinese adults: findings from 93,000 individuals from the China Kadoorie Biobank
title_short Evaluation of type 2 diabetes genetic risk variants in Chinese adults: findings from 93,000 individuals from the China Kadoorie Biobank
title_sort evaluation of type 2 diabetes genetic risk variants in chinese adults: findings from 93,000 individuals from the china kadoorie biobank
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4901105/
https://www.ncbi.nlm.nih.gov/pubmed/27053236
http://dx.doi.org/10.1007/s00125-016-3920-9
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