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

Abstract

Polycystic ovary syndrome (PCOS) is a common condition in reproductive-aged women that induces reproductive and metabolic derangements. Women with PCOS seem to have disturbances in lipid metabolism in the adipose tissue. Nevertheless, gene expression in adipose tissue of PCOS women and its relation to other disturbances have been fragmentarily investigated. 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) were selected in the studies. The integrative bioinformatics analyses of candidate genes were performed by gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and protein-protein interaction (PPI) network construction. Of these, 12 up-regulated genes and 12 down-regulated genes were identified and assessed as the most highly up-regulated and down-regulated genes in adipose tissue of women with PCOS. These DEGs that were annotated by KEGG analysis were mainly involved in PI3K-Akt, MAPK, Rap1, and Ras signaling pathways, and pathways in cancer such as hepatocellular carcinoma and gastric cancer, as well as metabolic pathways, and brain disorder pathways such as Alzheimer's disease and Huntington disease pathways. 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. Overall, these findings provide insight into the gene expression in adipose tissue of PCOS women and its relation to other disturbances.