A genome-wide gene-environment interaction analysis for tobacco smoke and lung cancer susceptibility

• Published in: Carcinogenesis (New York) Vol. 35; no. 7; pp. 1528 - 1535
• Main Authors: Zhang, Ruyang, Chu, Minjie, Zhao, Yang, Wu, Chen, Guo, Huan, Shi, Yongyong, Dai, Juncheng, Wei, Yongyue, Jin, Guangfu, Ma, Hongxia, Dong, Jing, Yi, Honggang, Bai, Jianling, Gong, Jianhang, Sun, Chongqi, Zhu, Meng, Wu, Tangchun, Hu, Zhibin, Lin, Dongxin, Shen, Hongbing, Chen, Feng
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 01.07.2014
• Subjects: Algorithms; Case-Control Studies; China; Follow-Up Studies; Gene-Environment Interaction; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; Lung Neoplasms - etiology; Nicotiana - adverse effects; Original Manuscript; Polymorphism, Single Nucleotide - genetics; Prognosis; Risk Factors; Smoking - adverse effects; Smoking - genetics; Tobacco Use Disorder - complications; Tobacco Use Disorder - genetics; China
• ISSN: 0143-3334; 1460-2180
• DOI: 10.1093/carcin/bgu076

Tobacco smoke is the major environmental risk factor underlying lung carcinogenesis. However, approximately one-tenth smokers develop lung cancer in their lifetime indicating there is significant individual variation in susceptibility to lung cancer. And, the reasons for this are largely unknown. In particular, the genetic variants discovered in genome-wide association studies (GWAS) account for only a small fraction of the phenotypic variations for lung cancer, and gene-environment interactions are thought to explain the missing fraction of disease heritability. The ability to identify smokers at high risk of developing cancer has substantial preventive implications. Thus, we undertook a gene-smoking interaction analysis in a GWAS of lung cancer in Han Chinese population using a two-phase designed case-control study. In the discovery phase, we evaluated all pair-wise (591 370) gene-smoking interactions in 5408 subjects (2331 cases and 3077 controls) using a logistic regression model with covariate adjustment. In the replication phase, promising interactions were validated in an independent population of 3023 subjects (1534 cases and 1489 controls). We identified interactions between two single nucleotide polymorphisms and smoking. The interaction P values are 6.73 × 10(-) (6) and 3.84 × 10(-) (6) for rs1316298 and rs4589502, respectively, in the combined dataset from the two phases. An antagonistic interaction (rs1316298-smoking) and a synergetic interaction (rs4589502-smoking) were observed. The two interactions identified in our study may help explain some of the missing heritability in lung cancer susceptibility and present strong evidence for further study of these gene-smoking interactions, which are benefit to intensive screening and smoking cessation interventions.