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    The goal of this study was to identify genes that were differentially methylated and differentially expressed and their related signaling pathways in ovarian endometriosis tissue. First, the DNA methylation and gene expression profiles in the endometrial tissue of patients with ovarian endometriosis were studied using Illumina 450K methylation microarray analysis and the GSE141549 gene expression dataset. Second, differentially methylated and differentially expressed genes, herein referred to as differentially methylated/expressed genes, were identified and protein-protein interaction networks and functional analysis of these genes were determined. Third, qPCR and immunohistochemistry of patient samples was used to confirm the differential expression of a subset of differentially methylated/expressed genes. Finally, the GSE7305 dataset was used confirm the expression profile of differentially methylated/expressed genes and to determine the potential usefulness of these genes for diagnosis of endometriosis. A total of 37 hypermethylated low-expression genes and 66 hypomethylated high-expression genes were identified in ovarian endometriosis patients. Protein-protein interaction and functional analysis highlighted 8 hypermethylated low-expression genes (KRT19, KRT8, ESR1, PRL, SFN, IL20RA, IL2RB, and PAX8) and 4 hypomethylated high-expression genes (CYP11A1, NR5A1, ME1, and GSTM1). Significantly, both of these gene sets had a diagnostic value for patients with ovarian endometriosis. Signaling pathways that were identified included JAK-STAT (involving IL20RA and IL2RB), prolactin (involving PRL and ESR1), Staphylococcus aureus infection (involving KRT19), viral protein interaction with cytokine and cytokine receptor (involving IL20RA and IL2RB), cytokine-cytokine receptor interaction (involving IL20RA and IL2RB), and drug metabolism-cytochrome P450 (involving GSTM1). The differentially methylated/expressed genes and enriched signaling pathways identified in this study are likely to be associated with the process of ovarian endometriosis. © 2021. Society for Reproductive Investigation.

    Citation

    Haibo Zhang, Jianlei Wu, Yan Li, Ge Jin, Yunjie Tian, Shan Kang. Identification of Key Differentially Methylated/Expressed Genes and Pathways for Ovarian Endometriosis by Bioinformatics Analysis. Reproductive sciences (Thousand Oaks, Calif.). 2022 May;29(5):1630-1643

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    PMID: 34671938

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