Integrative transcriptomic analysis reveals diagnostic biomarkers for comorbidity of coronary artery disease and obstructive sleep apnea

Background The co-occurrence of coronary artery disease (CAD) and obstructive sleep apnea (OSA), termed CADOSA, leads to worse clinical outcomes than either condition alone, yet its molecular mechanisms remain unclear, necessitating biomarker discovery for improved diagnosis and personalized management. Methods This study enrolled 96 age-matched participants (24 healthy controls, 25 CAD, 23 OSA, and 24 CADOSA) for clinical assessment and PBMC transcriptomic profiling. Integrated bioinformatics analyses included differential gene expression (edgeR/DESeq2), pathway enrichment, protein-protein interaction networks and topological analysis, machine learning-based biomarker selection, and immune cell infiltration evaluation. Results CADOSA patients had more severe cardiac dysfunction (enlarged left ventricle), respiratory impairment (higher apnea-hypopnea index), and metabolic disturbances (elevated triglycerides/creatinine) compared to single-disease condition of CAD or OSA. Transcriptomics identified 832 CAD-specific, 166 OSA-specific, and 376 CADOSA-specific DEGs compared to the healthy control. The CADOSA exhibited both shared (impaired efferocytosis, neutrophil extracellular traps, and cytoskeletal abnormalities) and unique enriched pathways (NOD-like receptor/PPAR signaling pathway), predominantly associated with immune or metabolic dysregulation. Enhanced expression of S100A12 and MMP9 genes (AUC = 0.83 and 0.78, respectively) was identified as potential biomarkers for CADOSA, and their upregulation was further confirmed by qRT-PCR. Notably, S100A12 expression was correlated with increased monocyte infiltration, highlighting its role in inflammatory pathogenesis of CADOSA. Conclusions These findings reveal immune-metabolic dysregulation underlying CADOSA and provide potential diagnostic biomarkers and targeted therapeutic targets (S100A12 and MMP9) for CADOSA patients.