Identification of novel biomarkers in obstructive sleep apnea <i>via</i> integrated bioinformatics analysis and experimental validation.

ABSTRACT:

Background

Obstructive sleep apnea (OSA) is a complex and multi-gene inherited disease caused by both genetic and environmental factors. However, due to the high cost of diagnosis and complex operation, its clinical application is limited. This study aims to explore potential target genes associated with OSA and establish a corresponding diagnostic model.

Methods

This study used microarray datasets from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) related to OSA and perform functional annotation and pathway analysis. The study employed multi-scale embedded gene co-expression network analysis (MEGENA) combined with least absolute shrinkage and selection operator (LASSO) regression analysis to select hub genes and construct a dia

SUBMITTER: Zhang K 

PROVIDER: S-EPMC10702330 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature