Comparative Meta-analysis of Adipose Tissue Transcriptomics Data in PCOS Patients and Healthy Controls Women

Abstract Background Women with polycystic ovary syndrome (PCOS) seem to have disturbances in lipid metabolism in subcutaneous adipose tissue. Nevertheless, gene expression in subcutaneous adipose tissue of PCOS women and its relation to other disturbances have been fragmentarily investigated. Methods and results We utilized microarray data to identify the most important up and down-regulated candidate genes in adipose tissue of PCOS women in contrast to healthy women using the meta-analysis technique. Microarray data produced from three independent experiments (n=3) conducted on adipose tissue in women with PCOS were retrieved from ArrayExpress. Then, the datasets were merged using the metaSeq package in Rstudio and differentially expressed genes (DEGs) in studies were selected. The integrative bioinformatics analyses of candidates were performed by gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Protein-protein interaction (PPI) network construction. Twelve up-regulated genes and twelve down-regulated genes were identified and assessed as the most important DEGs. These the most important DEGs that were annotated by KEGG analysis were mainly involved in PI3K-Akt signaling pathway, pathways in cancer, breast cancer, metabolic pathways, ovarian steroidogenesis, and insulin secretion. In the PPI networks, PRDM10, FGFR2, IGF1R, and FLT1 were the key nodes in the up-regulated networks, while the NDUFAB1 and NME2 proteins were key in the down-regulated networks. Conclusion Overall, these findings provide a comprehensive system biology based insight into the gene expression in subcutaneous adipose tissue of PCOS women and its relation to other disturbances.