Possible cross‑talk between atrial fibrillation and obstructive sleep apnea revealed by transcriptomic analysis

Area of Science:

• Genomics and Bioinformatics
• Cardiovascular Research
• Sleep Medicine

Background:

• Obstructive sleep apnea (OSA) is highly prevalent in patients with atrial fibrillation (AF).
• A significant comorbidity exists between OSA and AF, suggesting shared underlying mechanisms.
• Investigating these shared pathways is crucial for understanding and managing these conditions.

Purpose of the Study:

• To explore the molecular mechanisms linking OSA and AF using transcriptome data.
• To identify common differentially expressed genes (DEGs) associated with both conditions.
• To develop a predictive diagnostic model for OSA risk in AF patients.

Main Methods:

• Transcriptome data for AF and OSA were analyzed using Weighted Gene Co-expression Network Analysis (WGCNA).
• Protein-protein interaction networks were constructed to identify hub genes.
• A diagnostic model was built using identified hub genes and validated with ROC curves.

Main Results:

• 1,462 DEGs were identified for the OSA-AF comorbidity.
• Five hub genes (IFNG, IL4, IL15, CD19, FASLG) were selected.
• The diagnostic model demonstrated excellent predictive performance in validation datasets, with elevated activated macrophages observed in both conditions.

Conclusions:

• Five hub genes (IFNG, IL4, IL15, CD19, FASLG) are common to both OSA and AF.
• A diagnostic model based on these genes can effectively predict OSA risk in AF patients.
• This finding provides a potential tool for early risk assessment and intervention.