Chronic obstructive pulmonary disease (COPD) is a progressive inflammatory disease with pulmonary and extra-pulmonary complications. Due to the disease’s systemic nature, many investigations investigated the genetic alterations in various biological samples. We aimed to infer causal genes in COPD’s pathogenesis in different biological samples using elastic-net logistic regression and the Structural Equation Model. Samples of small airway epithelial cells, bronchoalveolar lavage macrophages, lung tissue biopsy, sputum, and blood samples were selected (135, 70, 235, 143, and 226 samples, respectively). Elastic-net Logistic Regression analysis was implemented to identify the most important genes involved in COPD progression. Thirty-three candidate genes were identified as essential factors in the pathogenesis of COPD and regulation of lung function. Recognized candidate genes in small airway epithelial (SAE) cells have the highest area under the ROC curve (AUC = 97%, SD = 3.9%). Our analysis indicates that macrophages and epithelial cells are more influential in COPD progression at the transcriptome level.
