Polymorphisms identified through genome-wide association studies and their associations with type 2 diabetes in Chinese, Malays, and Asian-Indians in Singapore.

Context: Novel type 2 diabetes mellitus (T2DM) susceptibility loci, identified through genome-wide association studies (GWAS), have been replicated in many European and Japanese populations. However, the association in other East Asian populations is less well characterized.
Objective: To examine the effects of SNPs in CDKAL1, CDKN2A/B, IGF2BP2, HHEX, SLC30A8, PKN2, LOC387761, and KCNQ1 on risk of T2DM in Chinese, Malays, and Asian-Indians in Singapore.
Design: We genotyped these candidate single-nucleotide polymorphisms (SNPs) in subjects from three major ethnic groups in Asia, namely, the Chinese (2196 controls and 1541 cases), Malays (2257 controls and 1076 cases), and Asian-Indians (364 controls and 246 cases). We also performed a metaanalysis of our results with published studies in East Asians.
Results: In Chinese, SNPs in CDKAL1 [odds ratio (OR) = 1.19; P = 2 x 10(-4)], HHEX (OR = 1.15; P = 0.013), and KCNQ1 (OR = 1.21; P = 3 x 10(-4)) were significantly associated with T2DM. Among Malays, SNPs in CDKN2A/B (OR = 1.22; P = 3.7 x 10(-4)), HHEX (OR = 1.12; P = 0.044), SLC30A8 (OR = 1.12; P = 0.037), and KCNQ1 (OR = 1.19-1.25; P = 0.003-2.5 x 10(-4)) showed significant association with T2DM. The combined analysis of the three ethnic groups revealed significant associations between SNPs in CDKAL1 (OR = 1.13; P = 3 x 10(-4)), CDKN2A/B (OR = 1.16; P = 9 x 10(-5)), HHEX (OR = 1.14; P = 6 x 10(-4)), and KCNQ1 (OR = 1.16-1.20; P = 3 x 10(-4) to 3 x 10(-6)) with T2DM. SLC30A8 (OR = 1.06; P = 0.039) showed association only after adjustment for gender and body mass index. Metaanalysis with data from other East Asian populations showed similar effect sizes to those observed in populations of European ancestry.
Conclusions: SNPs at T2DM susceptibility loci identified through GWAS in populations of European ancestry show similar effects in Asian populations. Failure to detect these effects across different populations may be due to issues of power owing to limited sample size, lower minor allele frequency, or differences in genetic effect sizes.