International Journal of General Medicine (Sep 2021)
Identification of Three Potential circRNA Biomarkers of Polycystic Ovary Syndrome by Bioinformatics Analysis and Validation
Abstract
Pengyu Huang,* Shengrong Du,* Yunhong Lin,* Zhiqing Huang, Haiyan Li, Gangxin Chen, Suzhu Chen, Qingfen Chen, Lincui Da, Hang Shi, Wei Wei, Lei Yang, Yan Sun, Beihong Zheng Reproductive Medicine Center, Fujian Maternity and Child Health Hospital, Affiliated Hospital of Fujian Medical University, Fuzhou, 350001, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yan Sun; Beihong Zheng Email [email protected]; [email protected]: It is well known that circRNAs are closely involved in the progression of various diseases. However, their functions and potential regulatory mechanisms in polycystic ovary syndrome (PCOS) remain largely unknown. In the present study, our aim was to investigate the potential diagnostic value of circRNAs in PCOS.Methods: The circRNA dataset GSE145296, mRNA dataset GSE155489 and miRNA GSE138572 were downloaded from Gene Expression Omnibus (GEO) database. Then, differentially expressed genes (DEGs) were identified. Based on the potential interactions, a network of cirRNA-related competing endogenous RNAs (ceRNAs) was constructed. Biological functions were predicted by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. For further validation, qRT-PCR method was used to detect the expression level of the candidate circRNAs. Then, receiver operating characteristics (ROC) were constructed to evaluate the diagnostic value of the three differentially expressed circRNA (DE-circRNA).Results: We constructed a network of cirRNA-related ceRNA network. Hsa_circ_0075691, hsa_circ_0075692 and hsa_circ_0085997 were validate to be dysregulated in PCOS.Conclusion: Hsa_circ_0075691, hsa_circ_0075692 and hsa_circ_0085997 may be potential diagnostic biomarkers of PCOS, but their specific regulatory mechanisms still need to be further studied.Keywords: polycystic ovary syndrome, circRNA, biomarkers, bioinformatics