Identification of potential biological processes and key genes in diabetes-related stroke through weighted gene co-expression network analysis.

ABSTRACT:

Background

Type 2 diabetes mellitus (T2DM) is an established risk factor for acute ischemic stroke (AIS). Although there are reports on the correlation of diabetes and stroke, data on its pathogenesis is limited. This study aimed to explore the underlying biological mechanisms and promising intervention targets of diabetes-related stroke.

Methods

Diabetes-related datasets (GSE38642 and GSE44035) and stroke-related datasets (GSE16561 and GSE22255) were obtained from the Gene Expression omnibus (GEO) database. The key modules for stroke and diabetes were identified by weight gene co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes Genomes (KEGG) analyses were employed in the key module. Genes in stroke- and diabetes-related key modules we

SUBMITTER: He Y 

PROVIDER: S-EPMC10762844 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature