Global Transcriptional Profiling of Granulosa Cells from Polycystic Ovary Syndrome Patients: Comparative Analyses of Patients with or without History of Ovarian Hyperstimulation Syndrome Reveals Distinct Biomarkers and Pathways

Abstract

Ovarian hyperstimulation syndrome (OHSS) is often a complication of polycystic ovarian syndrome (PCOS), the most frequent disorder of the endocrine system, which affects women in their reproductive years. The etiology of OHSS is multifactorial, though the factors involved are not apparent. In an attempt to unveil the molecular basis of OHSS, we conducted transcriptome analysis of total RNA extracted from granulosa cells from PCOS patients with a history of OHSS (n = 6) and compared them to those with no history of OHSS (n = 18). We identified 59 significantly dysregulated genes (48 down-regulated, 11 up-regulated) in the PCOS with OHSS group compared to the PCOS without OHSS group (p-value < 0.01, fold change >1.5). Functional, pathway and network analyses revealed genes involved in cellular development, inflammatory and immune response, cellular growth and proliferation (including DCN, VIM, LIFR, GRN, IL33, INSR, KLF2, FOXO1, VEGF, RDX, PLCL1, PAPPA, and ZFP36), and significant alterations in the PPAR, IL6, IL10, JAK/STAT and NF-κB signaling pathways. Array findings were validated using quantitative RT-PCR. To the best of our knowledge, this is the largest cohort of Saudi PCOS cases (with or without OHSS) to date that was analyzed using a transcriptomic approach. Our data demonstrate alterations in various gene networks and pathways that may be involved in the pathophysiology of OHSS. Further studies are warranted to confirm the findings.

Keywords: biomarker; functional pathway; gene ontology; genome-wide gene expression; network analyses; ovarian hyperstimulation syndrome (OHSS); polycystic ovarian syndrome (PCOS); transcriptome.

Figure 1

Global transcriptional changes associated with history of OHSS. (A) The unsupervised principal component analysis (PCA) and (B) two-dimensional hierarchical clustering analysis clearly distinguished individuals with PCOS with a positive history of OHSS from those without OHSS (A,B, respectively). The expression level of each gene across the samples is normalized to [−3, 3]. Hierarchical clustering was performed using Pearson’s correlation with average linkage clustering. Pink spheres indicate OHSS, blue spheres indicate PCOS (without OHSS). Red and green in the heatmap denote highly and weakly expressed genes, respectively. (C) Over-represented biological functions and (D) significantly altered canonical pathways associated with DEG (up- or down-regulated) in OHSS patients. X-axis indicates the significance (−log p-value) of the functional/pathway association that is dependent on the number of genes in a class as well as biological relevance. The threshold line represents a p-value of 0.05.

Figure 2

Gene interaction network analysis of significantly dysregulated genes in OHSS group. Top-scoring gene interaction networks with high relevancy scores are shown. Nodes represent genes and the edges indicate biological relationship between the nodes. Straight and dashed lines represent direct or indirect gene-to-gene interactions, respectively. The functional class of the gene product are represented with different shapes (see legend). Red/green indicated up- (down-) regulated in OHSS compared to PCOS group. The color intensity is correlated with fold change.