Objectives. Obstructive sleep apnoea (OSA) is associated with an increased risk of cardiovascular disease, with alterations in coagulability suspected as the mediating factor. This study explored blood coagulability and breathing-related parameters during sleep in patients with OSA. Design. Cross-sectional observational study. Setting. Shanghai Sixth People’s Hospital. Participants. 903 patients diagnosed by standard polysomnography. Main Outcome and Measures. The relationships between coagulation markers and OSA were evaluated using Pearson’s correlation, binary logistic regression, and restricted cubic spline (RCS) analyses. Results. The platelet distribution width (PDW) and activated partial thromboplastin time (APTT) decreased significantly with increasing OSA severity (both p < 0.001 ). PDW was positively associated with the apnoea-hypopnea index (AHI), oxygen desaturation index (ODI), and microarousal index (MAI) (ß = 0.136, p < 0.001 ; ß = 0.155, p < 0.001 ; and ß = 0.091, p = 0.008 , respectively). APTT was negatively correlated with AHI (ß = −0.128, p < 0.001 ) and ODI (ß = −0.123, p = 0.001 ). PDW was negatively correlated with percentage of sleep time with oxygen saturation below 90%(CT90) (ß = −0.092, p = 0.009 ). The minimum arterial oxygen saturation (SaO2) correlated with PDW (ß = −0.098, p = 0.004 ), APTT (ß = 0.088, p = 0.013 ), and prothrombin time (PT) (ß = 0.106, p = 0.0003 ). ODI was risk factors for PDW abnormalities (odds ratio (OR) = 1.009, p = 0.009 ) after model adjustment. In the RCS, a nonlinear dose-effect relationship was demonstrated between OSA and the risk of PDW and APTT abnormalities. Conclusion. Our study revealed nonlinear relationships between PDW and APTT, and AHI and ODI, in OSA, with AHI and ODI increasing the risk of an abnormal PDW and thus also the cardiovascular risk. This trial is registered with ChiCTR1900025714.

Background and Objectives: The associations between objective sleep architecture and metabolic parameters have been rarely studied in patients with obstructive sleep apnea (OSA). Here, we evaluated the associations between objective sleep measures derived via polysomnography (PSG) and metabolic parameters.Methods: A total of 2,308 subjects with suspected OSA were included. We measured common metabolic parameters such as body mass index (BMI) and glucose, insulin, blood pressure, total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) levels. All subjects underwent full-night PSG. PSG sleep parameters included total sleep time (TST), time spent in slow-wave sleep (SWS) and rapid eye movement (REM) sleep, sleep efficiency, and the microarousal index (MAI).Results: The TST correlated with the BMI, glucose level, and systolic blood pressure. The SWS/TST ratio correlated with BMI and glucose, TC, and TG levels. The REM/TST ratio correlated with BMI, glucose, insulin, and TG levels, and diastolic blood pressure. We found significant relationships between sleep efficiency and BMI, glucose levels, and TG levels. The MAI was significantly correlated with all metabolic parameters. After adjustment for age, gender, smoking status, alcohol use, apnea hypopnea index, and oxygen desaturation index (ODI), multiple linear regression analysis showed that the MAI was independently associated with glucose level, TC, HDL, and LDL. REM/TST ratio was positively associated with diastolic blood pressure but negatively associated with glucose metabolism.Conclusions: Though some independent correlation between sleep and metabolic parameters was confirmed, only weak associations were observed, suggesting a clinically negligible influence of sleep structure. Further prospective studies are warranted to confirm our findings.

Background: Obstructive sleep apnea (OSA) is the most common type of sleep apnea that impacts the development or progression of many other disorders. Abnormal expression of N6-methyladenosine (m6A) RNA modification regulators have been found relating to a variety of human diseases. However, it is not yet known if m6A regulators are involved in the occurrence and development of OSA. Herein, we aim to explore the impact of m6A modification in severe OSA.Methods: We detected the differentially expressed m6A regulators in severe OSA microarray dataset GSE135917. The least absolute shrinkage and selection operator (LASSO) and support vector machines (SVM) were used to identify the severe OSA-related m6A regulators. Receiver operating characteristic (ROC) curves were performed to screen and verify the diagnostic markers. Consensus clustering algorithm was used to identify m6A patterns. And then, we explored the character of immune microenvironment, molecular functionals, protein-protein interaction networks and miRNA-TF coregulatory networks for each subcluster. Finally, the Connectivity Map (CMap) tools were used to tailor customized treatment strategies for different severe OSA subclusters. An independent dataset GSE38792 was used for validation.Results: We found that HNRNPA2B1, KIAA1429, ALKBH5, YTHDF2, FMR1, IGF2BP1 and IGF2BP3 were dysregulated in severe OSA patients. Among them, IGF2BP3 has a high diagnostic value in both independent datasets. Furthermore, severe OSA patients can be accurately classified into three m6A patterns (subcluster1, subcluster2, subcluster3). The immune response in subcluster3 was more active because it has high M0 Macrophages and M2 Macrophages infiltration and up-regulated human leukocyte antigens (HLAs) expression. Functional analysis showed that representative genes for each subcluster in severe OSA were assigned to histone methyltransferase, ATP synthesis coupled electron transport, virus replication, RNA catabolic, multiple neurodegeneration diseases pathway, et al. Moreover, our finding demonstrated cyclooxygenase inhibitors, several of adrenergic receptor antagonists and histamine receptor antagonists might have a therapeutic effect on severe OSA.Conclusion: Our study presents an overview of the expression pattern and crucial role of m6A regulators in severe OSA, which may provide critical insights for future research and help guide appropriate prevention and treatment options.

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