Identification of key genes and mechanisms of epicardial adipose tissue in patients with diabetes through bioinformatic analysis.

ABSTRACT:

Background

In recent years, peri-organ fat has emerged as a diagnostic and therapeutic target in metabolic diseases, including diabetes mellitus. Here, we performed a comprehensive analysis of epicardial adipose tissue (EAT) transcriptome expression differences between diabetic and non-diabetic participants and explored the possible mechanisms using various bioinformatic tools.

Methods

RNA-seq datasets GSE108971 and GSE179455 for EAT between diabetic and non-diabetic patients were obtained from the public functional genomics database Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were identified using the R package DESeq2, then Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were analyzed. Next, a PPI (protei

SUBMITTER: Yang H 

PROVIDER: S-EPMC9500152 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature