Comprehensive analysis of DNA methylation and gene expression profiles in gestational diabetes mellitus. Issue 26 (2nd July 2021)

• Record Type: Journal Article
• Authors: He, Jing; Liu, Kang; Hou, Xiaohong; Lu, Jieqiang
• Other Names: Perovic. Milan section editor.
• Is Part Of: Medicine. Volume 100:Issue 26(2021)
• Publication Date: 2021-07-02
• Subjects: bioinformatics -- differentially expressed genes -- differentially methylated genes -- gestational diabetes mellitus -- methylation-regulated differentially expressed genes; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000026497
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: Gestational diabetes mellitus (GDM) has a high prevalence during pregnancy. This research aims to identify genes and their pathways related to GDM by combining bioinformatics analysis. The DNA methylation and gene expression profiles data set was obtained from Gene Expression Omnibus. Differentially expressed genes (DEG) and differentially methylated genes (DMG) were screened by R package limma. The methylation-regulated differentially expressed genes (MeDEGs) were obtained by overlapping the DEGs and DMGs. A protein–protein interaction network was constructed using the search tool for searching interacting genes. The results are visualized in Cytoscape. Disease-related miRNAs and pathways were retrieved from Human MicroRNA Disease Database and Comparative Toxic Genome Database. Real-time quantitative PCR further verified the expression changes of these genes in GDM tissues and normal tissues. After overlapping DEGs and DMGs, 138 MeDEGs were identified. These genes were mainly enriched in the biological processes of the "immune response, " "defense response, " and "response to wounding." Pathway enrichment shows that these genes are involved in "Antigen processing and presentation, " "Graft-versus-host disease, " "Type I diabetes mellitus, " and "Allograft rejection." Six mRNAs (including superoxide dismutase 2 ( SOD2 ), mitogen-activated protein kinase kinase kinase kinase 3 ( MAP4K3 ), dual specificity phosphatase 5 ( DUSP5 ), p21-activated kinases 2 ( PAK2 ), serine protease inhibitor clade E member 1 ( SERPINE1 ), and protein phosphatase 1 regulatory subunit 15B ( PPP1R15B )) were identified as being related to GDM. The results obtained by real-time quantitative PCR are consistent with the results of the microarray analysis. This study identified new types of MeDEGs and discovered their related pathways and functions in GDM, which may be used as molecular targets and diagnostic biomarkers for the precise diagnosis and treatment of GDM.