Prediction of shared gene signatures and biological mechanisms between polycystic ovary syndrome and asthma: Based on weighted gene coexpression network analysis

Abstract

Objective: Several clinical studies have shown an association between polycystic ovary syndrome (PCOS) and asthma; however, the molecular link between these conditions remains unclear. In this study, we conducted a reanalysis and repurposing of existing databases in order to depict the common key genes, related signaling pathways, and similarity of the immune microenvironment between PCOS and asthma.

Methods: PCOS and asthma data sets were downloaded, and common signal pathways were identified by using gene set enrichment analysis. Identified common susceptibility genes were explored by intersecting the weighted gene coexpression network analysis module genes for both diseases. Then, we performed protein-protein interaction, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analyses of the common susceptibility genes. Finally, we analyzed the immune environment of PCOS and asthma.

Results: We identified five hub genes, namely, MMP9, CDC42, CD44, CD19, and BCL2L1, and uncovered that these five hub genes showed a tendency to be upregulated in both PCOS and asthma and possessed good diagnostic ability. In addition, we revealed that both PCOS and asthma were significantly enriched in the FcεRI-mediated signaling pathway. Moreover, we found that both PCOS and asthma exhibited infiltration of similar types of immune cells, such as monocytes, suggesting that the two diseases have similar pathological features.

Conclusion: PCOS and asthma share common causative genes with a similar immune environment. Taken together, we uncovered previously unsuspected traits for comprehensive diagnosis and treatment of PCOS and asthma in the future.

Keywords: asthma; bioinformatics analysis; polycystic ovary syndrome.