Objective: Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation.Study design: This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project.Methods: The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R-2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants.Results: The models including environmental risk factors only had pseudo R2 values of 16.5 -28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 x 10(-4) -4.83 x 10(-)12) and increased the pseudo R2 by about 1-2% and AUC by 1-3%. None of the gene environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05.Conclusion: This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection. (C) 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Aims: While genome-wide association studies (GWAS) have identified numerous type 2 diabetes risk variants across diverse populations, the Malaysian population remains unstudied to date. We characterised the effects association of known type 2 diabetes risk variants in Malaysian subjects of Malay, Chinese and Indian ancestry from The Malaysian Cohort project. Methods: Using the MetaboChip array, 1,604 Malays (722 cases, 882 controls), 1,654 Chinese (819 cases, 835 controls) and 1,728 Indians (851 cases, 877 controls) were genotyped. First, 62 candidate SNPs previously associated with type 2 diabetes were assessed for association via logistic regression within ancestral groups, and then across ancestral groups via meta-analysis. Second, estimated odds ratios were assessed for excess directional concordance with previously studied populations. Third, a genetic risk score (GRS) aggregating allele dosage across the candidate SNPs was tested for association within and across ancestral groups. Results: After Bonferroni correction, 7 individual SNPs were associated with type 2 diabetes in the combined Malaysian sample. We observed a highly significant excess in concordance of effect directions between Malaysian and previously studied populations. The GRS was strongly associated with type 2 diabetes in all Malaysian groups, explaining from 1.0 to 1.7% of total type 2 diabetes risk variance. Conclusion: This study suggests substantial overlap of the genetic risk alleles underlying type 2 diabetes in Malaysian and other populations.

AIMS:To characterize the association with Type 2 diabetes of known Type 2 diabetes risk variants in people in Malaysia of Malay, Chinese and Indian ancestry who participated in the Malaysian Cohort project. METHODS:We genotyped 1604 people of Malay ancestry (722 cases, 882 controls), 1654 of Chinese ancestry (819 cases, 835 controls) and 1728 of Indian ancestry (851 cases, 877 controls). First, 62 candidate single-nucleotide polymorphisms previously associated with Type 2 diabetes were assessed for association via logistic regression within ancestral groups and then across ancestral groups using a meta-analysis. Second, estimated odds ratios were assessed for excess directional concordance with previously studied populations. Third, a genetic risk score aggregating allele dosage across the candidate single-nucleotide polymorphisms was tested for association within and across ancestral groups. RESULTS:After Bonferroni correction, seven individual single-nucleotide polymorphisms were associated with Type 2 diabetes in the combined Malaysian sample. We observed a highly significant excess in concordance of effect directions between Malaysian and previously studied populations. The genetic risk score was strongly associated with Type 2 diabetes in all Malaysian groups, explaining from 1.0 to 1.7% of total Type 2 diabetes risk variance. CONCLUSION:This study suggests there is substantial overlap of the genetic risk alleles underlying Type 2 diabetes in Malaysian and other populations.