Circadian rhythm disruption and immune infiltration are both closely associated with the development of Obstructive sleep apnea (OSA) disease and a variety of cardiovascular and neurological complications, but their interactions with OSA disease are not clear. In this study, we used bioinformatics to investigate the roles of circadian rhythm disruption and immune microenvironments in OSA.
We analyzed differential genes and their associated functional pathways in the circadian rhythm-associated OSA dataset, then regrouped OSA samples using the differential genes and explored differences in immune cell infiltration between the two different subgroups. Meanwhile, we used two machine learning algorithms to further define circadian rhythm-related signature genes and to explore the relationship between key genes and immune cell infiltration. Finally, we searched for the transcription factors of the key differential gene JUN.
We screened 15 circadian rhythm-related differential genes in the OSA-related dataset and further defined 3 signature genes by machine learning algorithms. Immunoassays showed a significant increase in resting mast cell infiltration and a decrease in monocyte infiltration in the OSA group. The results of our animal experiments also confirmed that the expression of these 3 key genes, as well as the immune cell infiltration, showed a trend consistent with the results of the bioinformatics analysis.
In conclusion, this study reveals the interaction between circadian rhythm disruption and immune infiltration in OSA, providing new insights into the potential pathogenesis of OSA.