Integrating genomic and exposomic data identifies endocrine disruptors potentially associated with chronic obstructive pulmonary disease

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a complex disorder driven by both genetic susceptibility and environmental exposures. Endocrine-disrupting chemicals (EDCs) are widespread environmental contaminants that interfere with hormonal and immune pathways, yet their molecular links to COPD remain insufficiently defined.

METHODS: We integrated exposomic and genomic data to systematically evaluate EDC-related molecular mechanisms in COPD. Chemical-gene interactions were curated from the TEDX and CTD to identify EDC-associated genes. Two-sample Mendelian randomization (MR) was performed to assess genetically supported associations between gene expression and COPD risk. Bayesian colocalization analysis was applied to determine whether shared genetic variants underlie both gene expression and COPD susceptibility. Network analyses were conducted to map EDC-gene interactions and protein-protein interaction (PPI) landscapes.

RESULTS: Among 4207 EDC-associated genes with available cis-eQTLs, MR identified 30 genes significantly associated with COPD after FDR correction. Colocalization analysis prioritized 18 genes with strong or moderate evidence of a shared genetic signal, including TCF19, MAP1LC3B, and IRF1. Network analyses revealed extensive interactions between these genes and multiple EDCs, such as bisphenol A, triclosan, and formaldehyde. Functional connectivity highlighted pathways related to immune regulation, autophagy, and epigenetic control.

CONCLUSION: This integrative translational exposomics framework identifies genetically supported links between EDC-related genes and COPD risk. The findings provide mechanistic insights into how environmental endocrine disruptors may contribute to COPD pathogenesis and offer prioritized molecular targets for future experimental validation and environmental health interventions.