Functional microarray analysis of differentially expressed genes in granulosa cells from women with polycystic ovary syndrome related to MAPK/ERK signaling

Sci Rep. 2015 Oct 13:5:14994. doi: 10.1038/srep14994.

Abstract

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age. Although its aetiology and pathogenesis remain unclear, recent studies suggest that the dysfunction of granulosa cells may partly be responsible. This study aimed to use cDNA microarray technology to compare granulosa cell gene expression profiles in women with and without PCOS to identify genes that may be aetiologically implicated in the pathogenesis of PCOS. The study cohort included 12 women undergoing in vitro fertilization, six with PCOS and six without PCOS. Differential gene expression profiles were classified by post-analyses of microarray data, followed by western blot analyses to confirm the microarray data of selected genes. In total, 243 genes were differentially expressed (125 upregulated and 118 downregulated) between the PCOS and non-PCOS granulosa cells. These genes are involved in reproductive system development, amino acid metabolism and cellular development and proliferation. Comparative analysis revealed genes involved in the mitogen-activated protein kinase/extracellular regulated kinase (MAPK/ERK) signaling pathways. Western blot analyses confirmed that mitogen-activated protein kinase kinase kinase 4 and phospho-ERK1/2 were decreased in PCOS granulosa cells. This study identified candidate genes involved in MAPK/ERK signaling pathways that may influence the function of granulosa cells in PCOS.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Biomarkers
  • Case-Control Studies
  • Cluster Analysis
  • Female
  • Gene Expression Profiling
  • Gene Expression Regulation*
  • Gene Regulatory Networks
  • Granulosa Cells / metabolism*
  • Humans
  • MAP Kinase Signaling System*
  • Polycystic Ovary Syndrome / diagnosis
  • Polycystic Ovary Syndrome / genetics*
  • Polycystic Ovary Syndrome / metabolism*
  • Reproducibility of Results
  • Transcriptome*

Substances

  • Biomarkers