Bioinformatics identification of microRNAs involved in polycystic ovary syndrome based on microarray data.

Polycystic ovary syndrome (PCOS) is the most common endocrine disease in women of reproductive age. MicroRNAs (miRNAs or miRs) serve important roles in the physiological and pathological process of PCOS. To identify PCOS­associated miRNAs, the dataset GSE84376 was extracted from the Gene Expression Omnibus database. Differentially expressed miRNAs (DE­miRNAs) were obtained from Gene­Cloud Biotechnology Information and potential target genes were predicted using TargetScan, DIANA­microT­CDS, miRDB and miRTarBase tools. Gene Ontology enrichment analysis was performed using Metascape and a protein­protein interaction network was constructed using Cytoscape. Transcription factors were obtained from FunRich. DE­miRNAs were verified by reverse transcription­quantitative PCR. At the screening phase, there were seven DE­miRNAs in the PCOS group not present in the control group. In total, 935 target genes were identified, which are involved in the development and maturation of oocytes. Mitogen­activated protein kinase 1, phosphatase and tensin homolog, cAMP responsive element binding protein 1, signal transducer and activator of transcription 3, interferon Î³, Fms­related tyrosine kinase 1, transcription factor p65, insulin receptor substrate 1, DnaJ homolog superfamily C member 10 and casein kinase 2 α 1 were identified as the top 10 hub genes in the protein­protein interaction network. Specificity protein 1 was the most enriched transcription factor. At the validation phase, the levels of Homo sapiens (hsa)­miR­3188 and hsa­miR­3135b were significantly higher in the PCOS group than in the control group. In addition, the expression level of hsa­miR­3135b was significantly correlated with the number of oocytes retrieved, the fertilization rate and the cleavage rate (P<0.05). The present bioinformatics study on miRNAs may offer a novel understanding of the mechanism of PCOS, and may serve to identify novel miRNA therapeutic targets.

Identification and potential value of candidate microRNAs in granulosa cells of polycystic ovary syndrome.

BACKGROUND: Polycystic Ovary Syndrome (PCOS) is a major cause of anovulatory infertility. Some studies showed that miRNAs were used as diagnostic/prognostic biomarkers for various diseases. OBJECTIVE: To identify candidate miRNAs in Granulosa Cells (GCs) of PCOS and evaluate their potential values for PCOS diagnosis. METHODS: We screened differentially expressed miRNAs in GCs between PCOS and controls by the microarray data from the GEO database. GCs were collected from 21 controls and 24 PCOS. The candidate miRNAs were verified by qRT-PCR. The correlation was investigated between candidate miRNAs and clinical characteristics in participants. Diagnostic value of candidate miRNAs was analyzed by receiver operating characteristic (ROC) curve. RESULTS: Seven miRNAs were differentially expressed in PCOS compared with controls. Furthermore, the validation results demonstrated that hsa-miR-3188 and hsa-miR-3135b showed higher levels in GCs with PCOS patients (p< 0.05). In addition, the expressions of hsa-miR-3188 and hsa-miR-3135b were negative correlated with FSH and hsa-miR-3188 was positive correlated with BMI (p< 0.05). ROC analysis indicated that hsa-miR-3188 and hsa-miR-3135b could differentiate PCOS from controls, and the hsa-miR-3188/3135b improved the predictive accuracy for PCOS. CONCLUSIONS: The expressions of hsa-miR-3188 and hsa-miR-3135b in human GCs were significantly associated with PCOS. Moreover, the hsa-miR-3188/3135b has certain diagnostic value for distinguishing PCOS.