Language
English
Publication Date
6-1-2026
Journal
American Journal of Respiratory and Critical Care Medicine
DOI
10.1093/ajrccm/aamaf097
PMID
41738161
Abstract
Rationale: Genetically predicted molecular traits provide a cost-effective approach for identifying biomarkers and uncovering underlying biological mechanisms. We extended this framework to investigate gene-smoking interactions in lung cancer susceptibility.
Objectives: To identify trans-omics gene-smoking interactions affecting lung cancer risk and to assess how biomarkers modify effect of smoking.
Methods: We conducted the first trans-omics gene-smoking interaction study of lung cancer by integrating consortium-scale individual genotype data (27 737 cases vs 449 910 noncases) from the International Lung Cancer OncoArray Consortium (ILCCO-OncoArray), Transdisciplinary Research Into Cancer of the Lung (TRICL), Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), and the UK Biobank (UKB) with alliance-based summary-level molecular quantitative trait loci (xQTL) data, involving DNA methylation, gene expression, protein, and metabolite. Based on the identified biomarkers, we developed a molecular modifying score (MMS) to delineate gene-smoking interaction patterns and stratify smokers at high risk of lung cancer.
Measurements and main results: Eight biomarkers showing significant interactions with smoking were identified through a 2-phase analytic strategy, comprising CpG sites in the nicotinic acetylcholine receptor region and gene RP11-326C3.14. The MMS, constructed by integrating these biomarkers with their effect estimates derived from meta-analysis of all available datasets, effectively stratified lung cancer risk among smokers. Trans-omics integrative analysis revealed functional relationships across molecular layers, particularly implicating the NELFE gene in smoking-related carcinogenesis pathways.
Conclusions: The trans-omics association study (xWAS) framework enables systematic discovery of trans-omics gene-environment interactions. The MMS effectively delineates the patterns of the interaction effects and facilitates risk stratification. Additionally, we launched a free online platform, LungCancer-xWAS-GxE (http://bigdata.njmu.edu.cn/LungCancer-xWAS-GxE/).
Keywords
Humans, Lung Neoplasms, Smoking, Female, DNA Methylation, Gene-Environment Interaction, Male, Quantitative Trait Loci, Multiomics, Genetic Predisposition to Disease, Middle Aged, Genome-Wide Association Study, gene–smoking interaction, genome-wide association study, lung cancer, trans-omics, xWAS
Published Open-Access
yes
Recommended Citation
Xie, Ning; Xu, Xiaowen; Wang, Yanru; et al., "A Trans-Omics Gene-Smoking Interaction Study of Lung Cancer Based on Consortium Data" (2026). Faculty, Staff and Students Publications. 7002.
https://digitalcommons.library.tmc.edu/baylor_docs/7002