Exploring common circulating diagnostic biomarkers for sleep disorders and stroke based on machine learning.

ABSTRACT:

Background and objectives

Sleep disorders (SD) and stroke have long been health concerns. Sleep disorders are known to be a risk factor for stroke, and in recent years it has also been shown that the prevalence of sleep disorders is increased in stroke patients. We inferred that there is some inevitable connection between the two. This study aims to identify common molecular biomarkers and pathways connecting SD and stroke by integrating bioinformatics and machine learning approaches.

Methods

We analyzed transcriptome data from the GEO dataset to identify differentially expressed genes (DEGs). Key biological processes, as well as metabolic pathways, were highlighted by GO and KGEE enrichment analyses. Co-expression modules were then identified in the SD and stroke datasets b

SUBMITTER: Yu H 

PROVIDER: S-EPMC12611825 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature