Identification of four key genes related to the diagnosis of chronic obstructive pulmonary disease using bioinformatics analysis

Introduction: Chronic obstructive pulmonary disease (COPD) is projected to become the third leading cause of death worldwide. Despite extensive research over the past few decades, effective treatments remain elusive, making disease prevention and control a global challenge. Methods: This study aimed to identify diagnostic key genes for COPD. We utilized the Gene Expression Omnibus database to obtain gene expression data specific to COPD. Differentially expressed genes (DEGs) were identified and analyzed through Gene Ontology, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis. Integrated weighted gene co-expression network analysis was employed to examine related gene modules. To pinpoint key genes, we used SVM-RFE, RF, and LASSO. We observed a significant difference in immune infiltration between COPD and normal groups, indicating potential interactions between immune cells and these genes. The identified key genes were further validated using external datasets. Discussion: are potential biomarkers for COPD. Targeting these diagnostic genes with specific drugs may potentially offer new avenues for COPD management; however, this hypothesis remains preliminary and requires further investigation, as the study does not directly assess therapeutic interventions.