Mendelian randomization analysis of environmental pollution factors and head and neck cancer risk: a causal inference study integrating autophagy-related genes

Abstract

Background: Head and neck squamous cell carcinoma (HNSC) is a significant global health challenge. While traditional risk factors are well-established, the role of environmental pollutants in HNSC development remains unclear. Objective: To investigate the causal relationship between environmental pollution factors and HNSC risk using Mendelian Randomization (MR) analysis. Methods: Two-sample MR analysis was performed using genome-wide association study data from the IEU OpenGWAS project and HNSC RNA-seq data from TCGA. Environmental pollution-associated genes (MRGs) were identified and analyzed along with autophagy-related genes (ATGs) in HNSC samples. Cox proportional hazards models were used to develop a clinical prediction model. Results: MR analysis revealed significant causal relationships between nitrogen dioxide air pollution, nitrogen oxides air pollution, PM2.5, and increased HNSC risk. Nine MRGs were identified, with four (IRF4, LINGO1, PTHLH, RSRC1) differentially expressed in HNSC. A six-factor clinical prediction model (IRF4, LINGO1, PTHLH, RSRC1, Age, USP10) showed good predictive performance for HNSC survival (C-index = 0.63, 10-year AUC = 0.761). Tumor mutation burden and immune cell infiltration analyses provided further insights into HNSC biology. Conclusion: This study provides evidence for causal relationships between specific air pollutants and HNSC risk, and identifies potential gene targets for further investigation. The developed clinical prediction model may aid in HNSC prognosis and personalized treatment strategies.