Abstract
BACKGROUND: Chronic obstructive pulmonary disease (COPD) stands as a predominant cause of global morbidity and mortality. This study aims to elucidate the relationship between pyroptosis-related genes (PRGs) and COPD diagnosis in the context of immune infiltration, ultimately proposing a PRG-based diagnostic model for predicting COPD outcomes. METHODS: Clinical data and PRGs of COPD patients were sourced from the GEO database. The "ConsensusClusterPlus" package was employed to generate molecular subtypes derived from PRGs that were identified through differential expression analysis and LASSO Cox analysis. A diagnostic signature including eight genes (CASP4, CASP5, ELANE, GPX4, NLRP1, GSDME, NOD1and IL18) was also constructed. Immune cell infiltration calculated by the ESTIMATE score, Stroma scores and Immune scores were also compared on the basis of pyroptosis-related molecular subtypes and the risk signature. We finally used qRT - PCR to detect the expression levels of eight genes in COPD patient and normal. RESULTS: The diagnostic model, anchored on eight PRGs, underwent validation with an independent experimental cohort. The area under the receiver operating characteristic (ROC) curves (AUC) for the diagnostic model showcased values of 0.809, 0.765, and 0.956 for the GSE76925, GSE8545, and GSE5058 datasets, respectively. Distinct expression patterns and clinical attributes of PRGs were observed between the comparative groups, with functional analysis underscoring a disparity in immune-related functions between them. CONCLUSION: In this study, we developed a potential as diagnostic biomarkers for COPD and have a significant role in modulating the immune response. Such insights pave the way for novel diagnostic and therapeutic strategies for COPD.