Machine learning identifies potential diagnostic biomarkers associated with ferroptosis in obstructive sleep apnea.

ABSTRACT: Obstructive sleep apnea (OSA) is the most common sleep apnea-related disorder, with a high prevalence and a range of associated complications. Ferroptosis is a new mode of cell death that is involved in the development of OSA, but the mechanism has remained elusive. In the present study, ferroptosis-related genes in OSA were assessed and their potential clinical value was discussed. Data were downloaded and merged, and screened for differentially expressed genes (DEGs) through the Gene Expression Omnibus database. The OSA ferroptosis-related genes were obtained after intersecting with the downloaded ferroptosis-related genes. Subsequently, key ferroptosis-associated differential genes were obtained using two machine learning methods (the least absolute shrinkage and selection operators and

SUBMITTER: Chen B 

PROVIDER: S-EPMC11947867 | biostudies-literature | 2025 May

REPOSITORIES: biostudies-literature