Fig. 1

Analysis workflow of the study. Hub genes for chronic obstructive pulmonary disease (COPD) recognition were identified through integrated analysis of multi-center lung tissue sequencing data from COPD patients, employing weighted gene co-expression network analysis (WGCNA) and multiple machine learning algorithms to establish a predictive gene model. Mendelian randomization analysis was subsequently applied to prioritize a central candidate gene. Functional exploration of this hub gene was conducted using single-cell RNA sequencing data derived from both human COPD specimens and murine experimental models. Clinical relevance was further validated by correlating its expression levels with disease severity metrics and spirometric parameters in primary COPD cohorts and independent validation datasets. Mechanistic investigations were completed through functional assays in an in vitro cellular model to evaluate its biological relevance in COPD pathogenesis