Abstract
BACKGROUND: Clinical observational studies have highlighted differences in plasma lipid profiles between lung carcinoma patients and healthy individuals. However, the causal relationship underlying these differences remains unclear. This study aims to investigate the bidirectional causal relationship between 179 plasma lipids and lung carcinoma. METHODS: A bivariate two-sample Mendelian randomization (MR) study was conducted using data from public genome-wide association studies (GWAS). The primary analytical technique employed was the inverse variance weighting method (IVW), with MR-Egger, weighted-median, and weighted mode as supplementary methods. Sensitivity analyses including Cochran's Q test and MR-Egger intercept test were performed to ensure the robustness of the results. RESULTS: Mendelian randomization analysis revealed positive associations between levels of certain plasma lipidome-Sterol ester 27:1/20:5 levels (OR 1.162, 95% confidence interval (CI) 1.077-1254, P 1.15e(-4)), Phosphatidylcholine (PC) 20:4_0:0 levels (OR 1.112, 95%CI 1.051-1.176, P 2.33e(-4)), PC 17:0_20:4 levels (OR 1.108, 95%CI 1.051-1.167, P 1.33e(-4), PC 18:0_20:4 levels (OR 1.094, 95%CI 1.046-1.144, P 8.08e(-5)), PC O-16:0:4 levels (OR 1.180, 95%CI 1.089-1.277, P4.61e(-5)), PC O-16:1_20:4 levels (OR 1.155, 95%CI 1.077-1.239, P 5.00e(-5))-with the risk of lung carcinoma. Conversely, PC 15:0_18:2 levels (OR 0.823, 95%CI 0.760-0.892, P1.95e(-6)), PC 16:0_18:2 levels (OR 0.863, 95%CI 0.801-0.931, P 1.28e(-4)), PC 16:1_18:2 levels (OR 0.856, 95%CI 0.791-0.926, P 1.13e(-4)), PC 18:1_18:2 levels (OR 0.847, 95%CI 0.77-0.911, P 9.15e(-6)) were inversely associated with the risk of lung carcinoma. Reverse Mendelian randomization analysis indicated that lung carcinoma did not have a significant causal effect on the 179 plasma lipids. CONCLUSION: Our study reveals the causal relationship between plasma lipidome and lung cancer, provides preliminary genetic evidence, and provides a new idea for understanding the pathogenesis of lung cancer and finding promising therapeutic targets.