Li Chao-Feng, Luo Fu-Tian, Zeng Yi-Xin, Jia Wei-Hua
Department of Medical Statistics and Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Guangzhou 510060, China.
Int J Mol Sci. 2014 Jun 13;15(6):10724-37. doi: 10.3390/ijms150610724.
Determining the complex relationships between diseases, polymorphisms in human genes and environmental factors is challenging. Multifactor dimensionality reduction (MDR) has been proven to be capable of effectively detecting the statistical patterns of epistasis, although classification accuracy is required for this approach. The imbalanced dataset can cause seriously negative effects on classification accuracy. Moreover, MDR methods cannot quantitatively assess the disease risk of genotype combinations. Hence, we introduce a novel weighted risk score-based multifactor dimensionality reduction (WRSMDR) method that uses the Bayesian posterior probability of polymorphism combinations as a new quantitative measure of disease risk. First, we compared the WRSMDR to the MDR method in simulated datasets. Our results showed that the WRSMDR method had reasonable power to identify high-order gene-gene interactions, and it was more effective than MDR at detecting four-locus models. Moreover, WRSMDR reveals more information regarding the effect of genotype combination on the disease risk, and the result was easier to determine and apply than with MDR. Finally, we applied WRSMDR to a nasopharyngeal carcinoma (NPC) case-control study and identified a statistically significant high-order interaction among three polymorphisms: rs2860580, rs11865086 and rs2305806.
确定疾病、人类基因多态性和环境因素之间的复杂关系具有挑战性。多因素降维法（MDR）已被证明能够有效地检测上位性的统计模式，尽管这种方法需要分类准确性。不平衡数据集会对分类准确性产生严重负面影响。此外，MDR方法无法定量评估基因型组合的疾病风险。因此，我们引入了一种基于加权风险评分的新型多因素降维法（WRSMDR），该方法使用多态性组合的贝叶斯后验概率作为疾病风险的新定量指标。首先，我们在模拟数据集中将WRSMDR与MDR方法进行了比较。我们的结果表明，WRSMDR方法在识别高阶基因-基因相互作用方面具有合理的效能，并且在检测四位点模型方面比MDR更有效。此外，WRSMDR揭示了更多关于基因型组合对疾病风险影响的信息，并且结果比MDR更容易确定和应用。最后，我们将WRSMDR应用于一项鼻咽癌（NPC）病例对照研究，并确定了三种多态性（rs2860580、rs11865086和rs2305806）之间具有统计学意义的高阶相互作用。
