Association of accelerated biological aging with obstructive sleep apnea symptoms and identification of a candidate biomarker gene signature - PubMed
5 hours ago
- #Machine learning
- #Obstructive sleep apnea
- #Biological aging
- Obstructive sleep apnea (OSA) is linked to cardiovascular, metabolic, and neurocognitive complications, but diagnosis is complex and resource-intensive.
- Accelerated biological aging may contribute to OSA pathophysiology, with higher KDM-Age and PhenoAge accelerations associated with increased OSA risk.
- Thirty aging-related differentially expressed genes (DEGs) were identified, enriched in senescence, inflammatory, and immune pathways.
- Three hub genes—RBBP4, UCHL1, and ERRFI1—were selected by machine learning and showed good discriminative potential in validation datasets and a CIH mouse model.
- An integrated three-gene predictive model demonstrated promising discriminative ability and was used to create a nomogram for OSA risk assessment.