Integrative Analysis of Core Genes and Biological Process Involved in Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) is a common gynecological endocrine disordered disease, affecting the function of the ovaries in women of reproductive age. However, there are limited curative therapies for PCOS due to lack of reliable candidates. Hence, this study aimed to identify hub pathogenic genes and potential therapeutic targets for PCOS using bioinformatics tools. We obtained the expression profiles of 29 PCOS samples and 24 normal samples from three Gene Expression Omnibus (GEO) datasets. Then, the differentially expressed genes (DEGs) were screened, which were subjected to functional enrichment analyses. Moreover, we found 30 ferroptosis-related genes out of the 89 DEGs. Among the top 10 significant ferroptosis-related DEGs, 8 genes showed good predictive performance. We constructed interaction network of top three ferroptosis-related DEGs (SLC38A1, ACO1, DDIT3). Finally, real-time PCR was performed to test the relative expression of these genes. In conclusions, we have identified ferroptosis-related DEGs as core genes and potential therapeutic targets of PCOS based on comprehensive bioinformatics analysis. The findings are conducive to understanding of the pathogenesis of PCOS and paving the way towards curative therapies.