Bioinformatic Analysis Identifies Potential Key Genes in the Pathogenesis of Polycystic Ovary Syndrome

Author(s): Qian-Qian Liang, Dai-Jun Wang

Polycystic ovary syndrome (PCOS) is one of the factors leading to infertility; however, the specific pathogenesis of PCOS is still unclear. The purpose of this study was to determine the key changes in gene expression during the formation of PCOS and provide a theoretical basis for the clinical diagnosis and treatment of PCOS.We analyzed differentially expressed genes (DEGs) in the GSE34526 dataset from the online bioinformatics array research tool (BART) ( Then, the Database for Annotation, Visualization and Integrated Discovery (DAVID) ( online analysis software for gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) rich path analysis, STRING ( online analysis tool for protein-protein interaction (PPI) network, Cytoscape software for Mcode module and HUB gene analysis were used. To verify the HUB genes, the GSE59456 dataset was analyzed, and it includes female Sprague-Dawley rats that were implanted daily with silicone capsules that continuously released 5α-dehydrotestosterone (DHT) for 12 weeks to mimic the hyperandrogen state of women with PCOS and a control (CTL) group that received empty capsules.A total of 91 DEGs (7 upregulated and 84 downregulated) were found. Seven central HUB genes were identified, i.e., integrin alpha-M (ITGAM), cytochrome BMUR 245 beta chain (CYBB), toll like receptor 1 (TLR1), platelet activating factor receptor (PTAFR), CD163 molecule, caspase 1 (CASP1), and matrix metallopeptidase 9 (MMP9). The HUB genes were verified using GSE59456, and compared with the CTL group, the expression of the CYBB and CASP1 genes was reduced in the DHT group.The DEGs, HUB genes and signaling pathways identified in this study provide insights on the molecular mechanism underlying PCOS formation and reveal new targets for the diagnosis and treatment of PCOS.

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