TY - JOUR
T1 - Evaluation of type 2 diabetes genetic risk variants in Chinese adults
T2 - findings from 93,000 individuals from the China Kadoorie Biobank
AU - Gan, Wei
AU - Walters, Robin G
AU - Holmes, Michael V
AU - Bragg, Fiona
AU - Millwood, Iona Y
AU - Banasik, Karina
AU - Chen, Yiping
AU - Du, Huaidong
AU - Iona, Andri
AU - Mahajan, Anubha
AU - Yang, Ling
AU - Bian, Zheng
AU - Guo, Yu
AU - Clarke, Robert J
AU - Li, Liming
AU - McCarthy, Mark I
AU - Chen, Zhengming
AU - China Kadoorie Biobank Collaborative Group
PY - 2016/7/1
Y1 - 2016/7/1
N2 - 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 pinteraction < 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.
AB - 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 pinteraction < 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.
U2 - 10.1007/s00125-016-3920-9
DO - 10.1007/s00125-016-3920-9
M3 - Journal article
C2 - 27053236
SN - 0012-186X
VL - 59
SP - 1446
EP - 1457
JO - Diabetologia
JF - Diabetologia
IS - 7
ER -
