Integrating epidemiological and transcriptomic data reveals novel lipid metabolic drivers of obstructive sleep apnea

Background Obstructive sleep apnea (OSA), which is a condition characterized by persistent upper airway blockage during sleep and is related to dyslipidemia, lacks a clear molecular explanation. This study aims to investigate lipid‒OSA correlations, identify potential biomarkers, and explore underlying molecular pathways. Methods Data collected from the National Health and Nutrition Examination Survey (NHANES) from 2005–2008 and 2015–2018 were analyzed to investigate the relationships between OSA and lipid profiles. This work was completed through multiple regression analysis and sensitivity analysis. Concurrently, we identified differentially expressed lipid metabolism-related genes (DELMRGs) by integrating lipid-related genes with OSA transcriptome data (GSE135917). Bioinformatics approaches revealed functional mechanisms via gene expression and immune infiltration profiling, revealing dyslipidemia-OSA pathogenic pathways Results According to NHANES research, TG and LDL-C levels were positively correlated with OSA incidence, whereas HDL-C was inversely related ( p  < 0.001). Additionally, the relationship between TG levels and OSA risk was inverted U shaped ( p for nonlinearity < 0.05). Transcriptomics identified 34 DELMRGs, with CYP3A4, CYP4A22, and MED18 emerging as key genes via bioinformatics. Immune cell infiltration analysis revealed altered cell composition, with key DELMRGs linked to immune dysregulation. Gene set enrichment analysis revealed key pathways linked to these genes, and regulatory networks, including TF–gene and gene–miRNA networks, were constructed, suggesting their mechanistic role in OSA pathogenesis. Conclusions This study highlights the close association between dyslipidemia and OSA and identifies three key DELMRGs as potential mechanistic contributors, offering new insights and potential directions for future research.