Pathway analysis for genome-wide association study of lung cancer in Han Chinese population

Abstract

Genome-wide association studies (GWAS) have identified a number of genetic variants associated with lung cancer risk. However, these loci explain only a small fraction of lung cancer hereditability and other variants with weak effect may be lost in the GWAS approach due to the stringent significance level after multiple comparison correction. In this study, in order to identify important pathways involving the lung carcinogenesis, we performed a two-stage pathway analysis in GWAS of lung cancer in Han Chinese using gene set enrichment analysis (GSEA) method. Predefined pathways by BioCarta and KEGG databases were systematically evaluated on Nanjing study (Discovery stage: 1,473 cases and 1,962 controls) and the suggestive pathways were further to be validated in Beijing study (Replication stage: 858 cases and 1,115 controls). We found that four pathways (achPathway, metPathway, At1rPathway and rac1Pathway) were consistently significant in both studies and the P values for combined dataset were 0.012, 0.010, 0.022 and 0.005 respectively. These results were stable after sensitivity analysis based on gene definition and gene overlaps between pathways. These findings may provide new insights into the etiology of lung cancer.