Pathway and network-based analysis of genome-wide association studies and RT-PCR validation in polycystic ovary syndrome

Int J Mol Med. 2017 Nov;40(5):1385-1396. doi: 10.3892/ijmm.2017.3146. Epub 2017 Sep 20.

Abstract

The purpose of this study was to identify promising candidate genes and pathways in polycystic ovary syndrome (PCOS). Microarray dataset GSE345269 obtained from the Gene Expression Omnibus database includes 7 granulosa cell samples from PCOS patients, and 3 normal granulosa cell samples. Differentially expressed genes (DEGs) were screened between PCOS and normal samples. Pathway enrichment analysis was conducted for DEGs using ClueGO and CluePedia plugin of Cytoscape. A Reactome functional interaction (FI) network of the DEGs was built using ReactomeFIViz, and then network modules were extracted, followed by pathway enrichment analysis for the modules. Expression of DEGs in granulosa cell samples was measured using quantitative RT-PCR. A total of 674 DEGs were retained, which were significantly enriched with inflammation and immune-related pathways. Eight modules were extracted from the Reactome FI network. Pathway enrichment analysis revealed significant pathways of each module: module 0, Regulation of RhoA activity and Signaling by Rho GTPases pathways shared ARHGAP4 and ARHGAP9; module 2, GlycoProtein VI-mediated activation cascade pathway was enriched with RHOG; module 3, Thromboxane A2 receptor signaling, Chemokine signaling pathway, CXCR4-mediated signaling events pathways were enriched with LYN, the hub gene of module 3. Results of RT-PCR confirmed the finding of the bioinformatic analysis that ARHGAP4, ARHGAP9, RHOG and LYN were significantly upregulated in PCOS. RhoA-related pathways, GlycoProtein VI-mediated activation cascade pathway, ARHGAP4, ARHGAP9, RHOG and LYN may be involved in the pathogenesis of PCOS.

MeSH terms

  • Biomarkers
  • Case-Control Studies
  • Cluster Analysis
  • Computational Biology / methods
  • Female
  • Gene Expression Profiling / methods
  • Gene Regulatory Networks*
  • Genetic Predisposition to Disease*
  • Genome-Wide Association Study* / methods
  • Humans
  • Polycystic Ovary Syndrome / genetics*
  • Polycystic Ovary Syndrome / metabolism*
  • Reverse Transcriptase Polymerase Chain Reaction
  • Signal Transduction*
  • Transcriptome

Substances

  • Biomarkers