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Exploring the pathogenesis linking primary aldosteronism and obstructive sleep apnea via bioinformatic analysis
Lanlan Zhao1, Yuehua Dong2, Ying Wei1
1Department of Endocrinology and Rare Diseases, The Second Hospital of Hebei Medical University, Shijiazhuang, China.
Abstract:
Primary aldosteronism (PA) and obstructive sleep apnea (OSA) are both considered independent risk factors for hypertension, which can lead to an increase in cardiovascular disease incidence and mortality. Clinical studies have found a bidirectional relationship between OSA and PA. However, the underlying mechanism between them is not yet clear. This study aims to investigate the shared genetic characteristics and potential molecular mechanisms of PA and OSA. We obtained microarray datasets of aldosterone-producing adenoma (APA) and OSA from the gene expression omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to select co-expression modules associated with APA and OSA, and common genes of the two diseases were obtained by intersection. Subsequently, hub genes for APA and OSA were identified through functional enrichment analysis, protein-protein interaction (PPI), datasets, and public database. Finally, we predicted the transcription factors (TFs) and mirRNAs of the hub genes. In total, 52 common genes were obtained by WGCNA. The Gene Ontology (GO) of common genes includes interleukin-1 response, cytokine activity, and chemokine receptor binding. Functional enrichment analysis highlighted the TNF, IL-17 signaling, and cytokine-cytokine receptor interactions related to APA and OSA. Through PPI, datasets, and public databases verification, we identified 5 hub genes between APA and OSA (IL6, ATF3, PTGS2, CCL2, and CXCL2). Our study identified shared 5 hub genes between APA and OSA (IL6, ATF3, PTGS2, CCL2, and CXCL2). Through bioinformatics analysis, we found that the 2 disorders showed relative similarity in terms of inflammation, stress, and impaired immune function. The identification of hub genes may offer potential biomarkers for the diagnosis and prognosis of PA and OSA.
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