Bioinformatics-based identification of key candidate genes and signaling pathways in patients with Parkinson's disease and obstructive sleep apnea.

Abstract

Existing evidence exhibits that obstructive sleep apnea (OSA) is a potential consequence of Parkinson's disease (PD) or a contributor to PD progression. This investigation aimed to detect potential critical genes and molecular mechanisms underlying interactions between PD and OSA through bioinformatics analyses. The Gene Expression Omnibus (GEO) database was employed to obtain the expression profiles GSE20163 and GSE135917. The identification of common genes connected to PD and OSA was performed utilizing weighted gene co-expression network analysis and the R 4.0.4 program. The Cytoscape program was utilized to generate a network of protein-protein interactions (PPI), and the CytoHubba plugin was utilized to detect hub genes. Subsequently, functional enrichment analyses of the hub genes were conducted. Markers with increased diagnostic values for PD and OSA were confirmed using the GEO datasets GSE8397 and GSE38792. Typically, 57 genes that are common were identified in PD and OSA. Among these common genes, the top 10 hub genes in the PPI network were chosen. The verified datasets confirmed the presence of three important genes: CADPS, CHGA, and SCG3. Functional enrichment analysis revealed that these hub genes mostly participate in GABAergic synapses. Our findings suggest that CADPS, CHGA, and SCG3 are key genes involved in molecular mechanisms underlying interactions between OSA and PD. Functional enrichment of hub genes indicated a link between GABAergic synapses and the shared pathogenesis of PD and OSA. These candidate genes and corresponding pathways offer novel insights regarding biological targets that underlie the transcriptional connection between OSA and PD.