School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Newcastle, NSW, Australia; UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
Public Health. 2017 Aug;149:31-38. doi: 10.1016/j.puhe.2017.04.003. Epub 2017 May 19.
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.
This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project.
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 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.
The models including environmental risk factors only had pseudo R 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 × 10-4.83 × 10) and increased the pseudo R 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.
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.
马来西亚的 2 型糖尿病（T2D）患病率高且呈上升趋势。虽然该疾病的环境（非遗传）危险因素已得到充分证实，但遗传变异和基因-环境相互作用在该人群中的作用仍研究不足。本研究旨在估计环境和遗传危险因素对马来西亚 T2D 的相对贡献，并评估可能解释额外风险变异的基因-环境相互作用的证据。
这是一项病例对照研究，包括来自马来西亚队列研究的 1604 名马来人、1654 名华人及 1728 名印度人。
通过拟合多变量逻辑回归模型并评估麦克法登伪 R 和受试者工作特征曲线下面积（AUC）来评估已知遗传和环境因素对 T2D 风险变异的解释比例。使用对数似然比卡方检验和 AUC 比较包含和不包含遗传风险评分（GRS）的模型。通过在祖先群体内和跨祖先群体进行逻辑回归评估遗传和环境危险因素之间的乘法交互作用。对 GRS 及其 62 个组成变体进行交互作用评估。
仅包含环境危险因素的模型的伪 R 值为 16.5-28.3%，AUC 为 0.75-0.83。包含聚合 62 个 T2D 相关风险变体的遗传评分可显著提高模型拟合度（似然比 P 值为 2.50×10-4.83×10），并使伪 R 增加约 1-2%，AUC 增加 1-3%。在进行多次测试调整后，GRS 或个体变体的基因-环境相互作用均无显著意义。对于个体变体，在 310 个测试关联中有 33 个关联具有名义统计学意义，0.001<P<0.05。
本研究表明，已知的遗传风险变体对马来西亚人群的总体 T2D 风险变异有显著但较小的贡献。如果涉及常见遗传变体的基因-环境相互作用存在，它们的影响可能很小，需要更大的样本量才能检测到。
