Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Zhang R

PROVIDER: S-EPMC4076813 | biostudies-literature | 2014 Jul

REPOSITORIES: biostudies-literature

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

Zhang Ruyang R Chu Minjie M Zhao Yang Y Wu Chen C Guo Huan H Shi Yongyong Y Dai Juncheng J Wei Yongyue Y Jin Guangfu G Ma Hongxia H Dong Jing J Yi Honggang H Bai Jianling J Gong Jianhang J Sun Chongqi C Zhu Meng M Wu Tangchun T Hu Zhibin Z Lin Dongxin D Shen Hongbing H Chen Feng F

Carcinogenesis 20140322 7

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 ...[more]

PMID: 24658283

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Project description:Occupational asbestos exposure has been found to increase lung cancer risk in epidemiologic studies.We conducted an asbestos exposure-gene interaction analyses among several Caucasian populations who were current or ex-smokers. The discovery phase included 833 Caucasian cases and 739 Caucasian controls, and used a genome-wide association study (GWAS) to identify single-nucleotide polymorphisms (SNP) with gene-asbestos interaction effects. The top ranked SNPs from the discovery phase were replicated within the International Lung and Cancer Consortium (ILCCO). First, in silico replication was conducted in those groups that had GWAS and asbestos exposure data, including 1,548 cases and 1,527 controls. This step was followed by de novo genotyping to replicate the results from the in silico replication, and included 1,539 cases and 1,761 controls. Multiple logistic regression was used to assess the SNP-asbestos exposure interaction effects on lung cancer risk.We observed significantly increased lung cancer risk among MIRLET7BHG (MIRLET7B host gene located at 22q13.31) polymorphisms rs13053856, rs11090910, rs11703832, and rs12170325 heterozygous and homozygous variant allele(s) carriers (P < 5 × 10(-7) by likelihood ratio test; df = 1). Among the heterozygous and homozygous variant allele(s) carriers of polymorphisms rs13053856, rs11090910, rs11703832, and rs12170325, each unit increase in the natural log-transformed asbestos exposure score was associated with age-, sex-, smoking status, and center-adjusted ORs of 1.34 [95% confidence interval (CI), 1.18-1.51], 1.24 (95% CI, 1.14-1.35), 1.28 (95% CI, 1.17-1.40), and 1.26 (95% CI, 1.15-1.38), respectively, for lung cancer risk.Our findings suggest that MIRLET7BHG polymorphisms may be important predictive markers for asbestos exposure-related lung cancer.To our knowledge, our study is the first report using a systematic genome-wide analysis in combination with detailed asbestos exposure data and replication to evaluate asbestos-associated lung cancer risk.

Dataset Information

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

Publications

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

Similar Datasets

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