Screening and Verification COPD-OSA Overlap Syndrome Core Genes Using Bioinformatics.

BACKGROUND

When obstructive sleep apnea (OSA) and chronic obstructive pulmonary disease (COPD) coexist in a patient, it is called overlap syndrome (OS). However, the molecular mechanisms underpinning OS are unclear. To address this, we explored potential OS mechanisms using bioinformatics.

METHODS

OSA and COPD gene expression datasets were obtained from the Gene Expression Omnibus (GEO) database. Differential expression and weighted gene co-expression network analyses (WGCNA) were performed to identify common differentially expressed genes (DEGs) in OSA and COPD, and perform functional enrichment analysis. DEGs were validated in an external COPD gene expression dataset using receiver operating characteristic (ROC) curves and box plots. Positive results were initially identified as core genes, and were then validated by analyzing core genes in healthy controls, patients with OSA alone and patients with OS using RT-qPCR.

RESULTS

Through differential expression gene analysis, 9 common DEGs for OSA and COPD were identified. Through WGCNA analysis, 128 common key module genes for OSA and COPD were identified. By taking the intersection of the identified 9 DEGs and the 128 common key module genes from WGCNA, 5 key genes were determined. Preliminary validation in the external gene expression dataset for COPD revealed that was a potential hub gene for OS. Compared with the control group, the expression of was significantly downregulated in the COPD group ( = 0.019). The diagnostic value was evaluated using the ROC curve, and the results showed that the AUC was 0.857 (95% CI: 0.614-1.000). Finally, RT-qPCR confirmed that the expression levels of in OSA and OS were significantly lower than those in the healthy control group ( < 0.05), and it was a hub gene significantly associated with OS.

CONCLUSION

Our research identified hub gene that may provide new directions for further mechanistic research on OS.