Bioinformatics analysis of the common targets of miR-223-3p, miR-122-5p, and miR-93-5p in polycystic ovarian syndrome.

Abstract

Polycystic ovarian syndrome (PCOS) is one of the most common gynecological endocrine disorders. MicroRNAs (miRNAs) play extensive roles in the pathogenesis of PCOS and can serve as potential diagnostic markers. However, most studies focused on the regulatory mechanisms of individual miRNAs, and the combined regulatory effects of multiple miRNAs remain unclear. The aim of this study was to identify the common targets of miR-223-3p, miR-122-5p, and miR-93-5p; and assess the transcript levels of some of these targets in PCOS rat ovaries. Transcriptome profiles of granulosa cells from PCOS patients were obtained from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). A total of 1,144 DEGs were screened, 204 of which were upregulated and 940 were downregulated. According to the miRWalk algorithm, 4,284 genes were targeted by all three miRNAs at the same time, and intersection with DEGs was used to obtain candidate target genes. A total of 265 candidate target genes were screened, and the detected target genes were subjected to Gene ontology (GO) and KEGG pathway enrichment, followed by PPI network analysis. Then, qRT-PCR was used to determine the levels of 12 genes in PCOS rat ovaries. The expressions of 10 of these genes were found to be consistent with our bioinformatics results. In conclusion, JMJD1C, PLCG2, SMAD3, FOSL2, TGFB1, TRIB1, GAS7, TRIM25, NFYA, and CALCRL may participate in the development of PCOS. Our findings contribute to the identification of biomarkers that may promote the effective prevention and treatment of PCOS in the future.