Integrated bioinformatics approach reveals methylation-regulated differentially expressed genes in obesity.

ABSTRACT:

Objective

To identify DNA methylation and gene expression profiles involved in obesity by implementing an integrated bioinformatics approach.

Materials and methods

Gene expression (GSE94752, GSE55200, and GSE48964) and DNA methylation (GSE67024 and GSE111632) datasets were obtained from the GEO database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) in subcutaneous adipose tissue of patients with obesity were identified using GEO2R. Methylation-regulated DEGs (MeDEGs) were identified by overlapping DEGs and DMGs. The protein-protein interaction (PPI) network was constructed with the STRING database and analyzed using Cytoscape. Functional modules and hub-bottleneck genes were identified by using MCODE and CytoHubba plugins. Functional enric

SUBMITTER: Duarte GCK 

PROVIDER: S-EPMC10665070 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature