Yaoqin Wang1, Suming Xu1, Yonglian Wang1, Gaimei Qi1, Yan Hou2, Chunqing Sun2, Xueqing Wu1. 1. Center of Reproductive Medicine, Children's Hospital of Shanxi and Women Health Center of Shanxi, Taiyuan, Shanxi 030013, China. 2. Shanxi Medical University, Taiyuan, Shanxi 030001, China.
Abstract
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.
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 PCOSpatients (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.