Meta-analysis of gene expression profiles of lean and obese PCOS to identify differentially regulated pathways and risk of comorbidities

Computational and Structural Biotechnology Journal
Susan Idicula-ThomasGary D Bader

Abstract

Polycystic ovary syndrome (PCOS) is a complex multigenic disorder and women with PCOS suffer from several comorbidities. Although, obesity is a known risk factor for PCOS, the incidence of lean women with PCOS is on the rise. A systematic and comparative study on lean and obese PCOS with respect to genes, pathways and comorbidity analysis has not been attempted so far. Analysis of differentially expressed genes (DEGs) across tissue types for lean and obese PCOS revealed that the majority of them were downregulated for lean and obese PCOS. Ovarian and endometrial tissues shared several commonly dysregulated genes, suggesting shared PCOS pathophysiology mechanisms exist across tissues. Several pathways for cellular homeostasis, such as inflammation and immune response, insulin signaling, steroidogenesis, hormonal and metabolic signaling, regulation of gonadotrophic hormone secretion, cell structure and signaling that are known to be affected in PCOS were found to be enriched in our gene expression analysis of lean and obese PCOS. The gene-disease network is denser for obese PCOS with a higher comorbidity score as compared to lean PCOS.

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Datasets Mentioned

BETA
GSE5090
GSE43264
GSE98421
GSE6798
GSE10946
GPL570

Software Mentioned

affy
R
Gene Set Enrichment Analysis ( GSEA )
biomaRt
iRegulon Cytoscape app
AutoAnnotate
GSVA
oligo
GPL570
Cytoscape

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