4.4 Article

WGCNA Analysis Identifies Polycystic Ovary Syndrome-Associated Circular RNAs That Interact with RNA-Binding Proteins and Sponge miRNAs

Journal

INTERNATIONAL JOURNAL OF GENERAL MEDICINE
Volume 14, Issue -, Pages 8737-8751

Publisher

DOVE MEDICAL PRESS LTD
DOI: 10.2147/IJGM.S335108

Keywords

circular RNAs; competitive endogenous RNAs; polycystic ovary syndrome; RNA-binding proteins; weighted gene co-expression network analysis

Funding

  1. Medical Research Fund of Guangdong Province [A2020575]
  2. CSCO-Pilot Cancer Research Fund [Y-2019AZQN-1049]

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The study identified key circRNAs in PCOS patients compared to controls, with differential expression analysis revealing DECs, DEMs, and DEGs in the database. WGCNA analysis yielded PCOS-related modules and identified specific circRNAs associated with PCOS.
Objective: Dysfunction of cumulus granulosa cells has been suggested as a contributor to abnormal folliculogenesis and the development of polycystic ovary syndrome (PCOS), but the underlying molecular mechanisms remain unclear. Recent studies indicate that circular RNAs (circRNAs) exert important roles for diseases. We aimed to screen crucial circRNAs of PCOS patients and predict their functions. Methods: The high-throughput datasets of circRNAs (GSE145296), microRNAs (miRNAs; GSE72274) and messenger RNAs (mRNAs; GSE155489) in cumulus cells of PCOS patients and controls were collected from the Gene Expression Omnibus database. Differentially expressed circRNAs (DECs), miRNAs (DEMs) and protein-coding genes (DEGs) were identified by the limma method. The weighted correlation network analysis (WGCNA) was conducted using the DECs to mine PCOS-associated modules. Hub DECs in modules were defined as both of vertical bar gene significance vertical bar and vertical bar module membership vertical bar >0.8. The downstream effectors of hub DECs were predicted by constructing DEC-DEM-DEG ceRNA and DEC-RNA binding protein (RBP) networks. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to explore the functions of circRNAs. Results: A total of 3614 DECs, 3544 DEGs and 1469 DEMs were identified between PCOS and controls. WGCNA analysis yielded five PCOS-related modules, of which 190 DECs were hub circRNAs. Seventeen hub DECs, nine DEMs, and 315 DEGs were identified to construct the ceRNA network, while 56 hub DECs and two DEGs (MBNL2, RBPMS) constituted the circRNA-RBP network. Five hub DECs (hsa_circ_0063309, hsa_circ_0054275, hsa_circ_0056196, hsa_circ_0018108 and hsa_circ_0070987) were overlapped between ceRNA and DEC-MBNL2 regulatory networks and thus they may be pivotal for PCOS. Furthermore, hsa_circ_0099109 could interact with the RBP gene RBPMS. Function analyses showed these circRNAs were inflammation-, apoptosis- or steroidogenesis-related. Conclusion: Aberrant expression of six circRNAs that function as RBP regulators or miRNA sponges may be possible mechanisms underlying the pathogenesis of PCOS by affecting apoptosis and steroidogenesis in cumulus cells.

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