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


METHODS
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.
Tan
Jonathan T
JT
Department of Epidemiology and Public Health, Yong Loo Lin School of Medicine, National University of Singapore, Singapore.
Ng
Daniel P K
DP
Nurbaya
Siti
S
Ye
Sandra
S
Lim
Xiu Li
XL
Leong
Helen
H
Seet
Lin Tze
LT
Siew
Wei Fong
WF
Kon
Winston
W
Wong
Tien Yin
TY
Saw
Seang Mei
SM
Aung
Tin
T
Chia
Kee Seng
KS
Lee
Jeannette
J
Chew
Suok Kai
SK
Seielstad
Mark
M
Tai
E Shyong
ES
D000293:Adolescent; D000328:Adult; D000368:Aged; D044466:Asian People / Q000235:genetics*; D016022:Case-Control Studies; D015331:Cohort Studies; D004252:DNA Mutational Analysis / Q000379:methods; D003924:Diabetes Mellitus, Type 2 / Q000208:ethnology / Q000235:genetics*; D020022:Genetic Predisposition to Disease; D055106:Genome-Wide Association Study; D006801:Humans; D007194:India / Q000208:ethnology; D008296:Malaysia / Q000208:ethnology; D015201:Meta-Analysis as Topic; D008875:Middle Aged; D020641:Polymorphism, Single Nucleotide / Q000502:physiology; D012846:Singapore; D055815:Young Adult