Integrated Bioinformatics Methods Were Employed to Investigate Potential Molecular Links Between Obstructive Sleep Apnea and Sarcoidosis

Background Previous studies have established a frequent coexistence of obstructive sleep apnea (OSA) and sarcoidosis, yet the molecular mechanisms linking these conditions are not well understood. Methods This study employed integrated bioinformatics analysis and Mendelian randomization (MR) to identify potential mechanisms and infer causal relationships between OSA and sarcoidosis. Genetic instruments associated with OSA and sarcoidosis were screened, and bidirectional MR analysis was conducted to explore the causal relationship between the two conditions. Colocalization analysis was conducted to identify genes potentially associated with both OSA and sarcoidosis. Subsequently, differential expression analysis and weighted gene coexpression network analysis (WGCNA) were performed using data from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). In addition, eight machine learning algorithms were used to construct a nomogram based on the importance scores of DEGs and to identify hub genes. The results were validated using multiple methods. Results MR analysis confirmed a causal relationship between OSA and sarcoidosis ( p = 0.0018 OR = 1.39 95% CI 1.18–1.59). We identified 35 genes associated with both OSA and sarcoidosis, among which 6 were found to be differentially expressed. KRT72, DEFA4, RNASE3, and LTF were identified as signature genes. Based on these genes, nomograms were constructed to quantitatively predict the risk of comorbid OSA and sarcoidosis. Conclusion This study indicates a causal relationship between OSA and sarcoidosis. The potential mechanisms underlying this comorbidity involve immune dysregulation, inflammatory responses, and altered DNA repair and methylation. Additional contributing factors include dysregulated apoptosis, immune microenvironment remodeling, autophagy, and neural activity.