The present study aimed to identify potentially important biomarkers associated with polycystic ovary syndrome (PCOS) by integrating DNA methylation with transcriptome profiling. The transcription (E‑MTAB‑3768) and methylation (E‑MTAB‑3777) datasets were retrieved from ArrayExpress. Paired transcription and methylation profiling data of 10 cases of PCOS and 10 healthy controls were available for screening differentially expressed genes (DEGs) and differentially methylated genes (DMGs). Genes with a negative correlation between expression levels and methylation levels were retained by correlation analysis to construct a protein‑protein interaction (PPI) network. Subsequently, functional and pathway enrichment analyses were performed to identify genes in the PPI network. Additionally, a disease‑associated pathway network was also established. A total of 491 overlapping genes, and the expression levels of 237 genes, were negatively correlated with their methylation levels. Functional enrichment analysis revealed that genes in the PPI network were mainly involved with biological processes of cellular response to stress, negative regulation of the biosynthetic process, and regulation of cell proliferation. The constructed pathway network associated with PCOS led to the identification of four important genes (SPP1, F2R, IL12B and RBP4) and two important pathways (Jak‑STAT signaling pathway and neuroactive ligand‑receptor interaction). Taken, together, the results from the present study have revealed numerous important genes with abnormal DNA methylation levels and altered mRNA expression levels, along with their associated functions and pathways. These findings may contribute to an improved understanding of the possible pathophysiology of PCOS.
Keywords: polycystic ovary syndrome; dna methylation; transcriptome.