Weighted Risk Score-Based Multifactor Dimensionality Reduction to Detect Gene-Gene Interactions inNasopharyngeal Carcinoma

International Journal of Molecular Sciences

Fu-Tian Luo¹  Chao-Feng Li¹  Yi-Xin Zeng²  Wei-Hua Jia² 

[1] 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;

关键词: gene-gene interaction;    weighted risk score;    multifactor dimensionality reduction;    nasopharyngeal carcinoma;   

DOI  :  10.3390/ijms150610724

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown