• Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, School of Public Health, Medical College of Soochow University, Suzhou, China.
• Duke Cancer Institute, Duke University Medical Center, Durham, North Carolina.
• Community and Family Medicine, Geisel School of Medicine, Dartmouth College, Hanover, New Hampshire.
• Massachusetts General Hospital, Boston, Massachusetts.
• Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada.
• Public Health Ontario, Toronto, Ontario, Canada.
• Genetic Epidemiology Group, International Agency for Research on Cancer (IARC), Lyon, France.
• Department of Genetic Epidemiology, University Medical Center, Georg-August-University Göttingen, Göttingen, Germany.
• Division of Genetics and Epidemiology, The Institute of Cancer Research, London, United Kingdom.
• Genetic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland.

The fatty acids (FAs) metabolism is suggested to play a pivotal role in the development of lung cancer, and we explored that by conducting a pathway-based analysis. We performed a meta-analysis of published datasets of six genome wide association studies (GWASs) from the Transdisciplinary Research in Cancer of the Lung (TRICL) consortium, which included 12 160 cases with lung cancer and 16 838 cancer-free controls. A total of 30 722 single-nucleotide polymorphisms (SNPs) from 317 genes relevant to FA metabolic pathways were identified. An additional dataset from the Harvard Lung Cancer Study with 984 cases and 970 healthy controls was also added to the final meta-analysis. In the initial meta-analysis, 26 of 28 SNPs that passed false discovery rate multiple tests were mapped to the CYP4F3 gene. Among the 26 top ranked hits was a proxy SNP, CYP4F3 rs4646904 (P = 8.65 × 10^-6 , FDR = 0.018), which is suggested to change splicing pattern/efficiency and to be associated with gene expression levels. However, after adding data of rs4646904 from the Harvard GWAS, the significance in the combined analysis was reduced to P = 3.52 × 10^-3 [odds ratio (OR) = 1.07, 95% confidence interval (95%CI) = 1.03-1.12]. Interestingly, the small Harvard dataset also pointed to the same direction of the association in subgroups of smokers (OR = 1.07) and contributed to a combined OR of 1.13 (95% CI = 1.06-1.20, P = 6.70 × 10^-5 ). The results suggest that a potentially functional SNP in CYP4F3 (rs4646904) may contribute to the etiology of lung cancer, especially in smokers. Additional mechanistic studies are warranted to unravel the potential biological significance of the finding.