Uncovering sodium overload-associated gene signatures in chronic obstructive pulmonary disease through integrated bioinformatics and machine learning.

Background: Airway epithelial cells depend on tightly regulated ion transport, and disturbed sodium handling has been linked to mucus dehydration, oxidative stress and epithelial injury in obstructive lung disease. How sodium/ion-homeostasis-related transcription is organised in chronic obstructive pulmonary disease (COPD), and whether it converges with the disease's broader expression architecture, has not been systematically examined. This study aimed to identify sodium-overload-associated genes in COPD and evaluate a compact epithelial gene panel across multiple validation platforms. Methods: Two bulk lung-transcriptomic cohorts were integrated and analysed with differential expression, weighted gene co-expression network analysis (WGCNA) and a locked sodium-overload-related gene (SORG) set defined a priori from GeneCards. Candidate genes were characterised by functional enrichment and protein-protein interaction analysis, benchmarked across twelve machine-learning algorithms, and then examined in an independent external cohort, a mucus-score sensitivity analysis, single-cell RNA sequencing and quantitative polymerase chain reaction (qPCR; 13 COPD and 12 non-COPD controls). Results: Seven genes lay at the intersection of differential expression, the COPD-associated co-expression module and the sodium-overload set, enriched for xenobiotic-metabolism and oxidative-stress pathways. A reduced three-gene panel ( Conclusions: Sodium/ion-homeostasis-related transcription is associated with a stressed airway-epithelial state in COPD. The three-gene panel is best read as a compact, biologically interpretable framework-annotation-guided rather than evidence of causal sodium overload, and not a stand-alone diagnostic-that warrants validation in larger, prospectively matched cohorts.