Bioinformatic Analysis Identifies Potential Key Genes in the Pathogenesis of Polycystic Ovary Syndrome
Article Information
Qian-Qian Liang1*, Dai-Jun Wang2
1Division of Health Management, Yuncheng central hospital, Eighth Clinical Medical College of ShanXi Medical University, Shanxi, China
2Department of Human Anatomy, Weifang Medical University, Shandong, China.
*Corresponding author: Qian-Qian Liang, Division of Health Management, Yuncheng central hospital, Eighth Clinical Medical College of ShanXi Medical University, Shanxi, China.Dai-Jun Wang, Department of Human Anatomy, Weifang Medical University, Shandong, China
Received: 01 April 2021; Accepted: 18 April 2022; Published: 22 April 2022
Citation:
Qian-Qian Liang, Dai-Jun Wang. Bioinformatic Analysis Identifies Potential Key Genes in the Pathogenesis of Polycystic Ovary Syndrome. Journal of Bioinformatics and Systems Biology 5 (2022): 78-92.
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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) (bart.salk.edu). Then, the Database for Annotation, Visualization and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/) online analysis software for gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) rich path analysis, STRING (https://string-db.org/) 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.
Keywords
Polycystic ovary syndrome; Ovarian granulosa cells; genes; GSE34526; GEO59456
Polycystic ovary syndrome articles; Ovarian granulosa cells articles; genes articles; GSE34526 articles; GEO59456 articles
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Article Details
1. Background
Polycystic ovary syndrome (PCOS) is a common reproductive endocrine disease in women of childbearing age, and it has an incidence of 5.6-16% and is increasing annually. PCOS is considered a systemic multisystem disease that includes hyperandrogenemia, anovulation, irregular menstruation, infertility and metabolic abnormalities, including insulin resistance and hyperlipidemia [1, 2]. PCOS has many causal factors, including genetic and psychosocial factors, poor living habits and environmental factors (e.g., chemicals: pesticides, industrial pollutants; and personal care products: perfumes, deodorants, hair dyes, perfume compounds and bisphenol A). The specific etiology and pathogenesis of the disease are not currently clear [3-6]. Ovarian granulosa cells (GCs) are secreted and play an important role in the process of folliculogenesis [7], and understanding the gene expression of PCOS GCs is of great significance for effective diagnosis and treatment. In previous literature, potential differentially expressed genes in the GSE34526 gene expression profile were assessed by gene ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, PPI network and Mcode module analyses; however, HUB gene analyses have not been performed [8-12].
In this study, we used the online bioinformatics array research tool (BART) to analyze the original microarray dataset GSE34526 (healthy samples and PCOS female ovarian GCs) for differentially expressed genes (DEGs). GO enrichment, KEGG pathway, PPI network, Mcode module and Hub analyses and verification were performed to determine the genes, pathways and molecular mechanisms related to ovarian granulosa cells in women with PCOS to provide a theoretical basis for the clinical diagnosis, treatment and prevention of PCOS.
Impact Factor: * 4.2
CiteScore: 2.9 
Acceptance Rate: 11.01% 
Time to first decision: 10.4 days 
Time from article received to acceptance: 2-3 weeks 
