A Combined Bioinformatics and Clinical Validation Study Identifies MDM2, FKBP5 and CTNNA1 as Diagnostic Gene...

Chronic obstructive pulmonary disease (COPD) is often diagnosed after significant lung damage has already occurred, highlighting a need for minimally invasive biomarkers for early detection of COPD development. This study aims to identify transcriptional biomarkers in peripheral blood mononuclear cells (PBMCs). A Weighted Gene Co-Expression Network Analysis (WGCNA) was performed on the GSE146560 transcriptomic dataset. Hub genes were cross-validated using independent transcriptomic data (GSE94916), topology analysis of a COPD-related protein-protein interaction (PPI) network, and a text-mining approach. The top candidate genes were validated using RT-qPCR in a clinical cohort, consisting of 28 COPD patients and 13 healthy volunteers, and their diagnostic value was evaluated using receiver operating characteristic (ROC) analysis. WGCNA identified four gene modules significantly correlated with COPD, the functional annotation of which revealed their enrichment in immune and tissue remodeling pathways. Further analysis of the PPI network topology structure and gene expression revealed a hub gene signature that was significantly upregulated in PBMCs of COPD patients, including MDM2 (6.3-fold, p < 0.001), FKBP5 (7.0-fold, p < 0.001), and CTNNA1 (10.0-fold, p < 0.001). ROC analysis demonstrated high diagnostic accuracy for these genes, with AUC values of 0.849, p < 0.001, for MDM2, 0.957, p < 0.001, for FKBP5, and 0.958, p < 0.001, for CTNNA1. MDM2, FKBP5, and CTNNA1 represent promising, readily accessible PBMC biomarkers for COPD diagnosis.