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Obstructive sleep apnea (OSA), a disease associated with excessive sleepiness and increased cardiovascular risk, affects an estimated 1 billion people worldwide. The present study examined proteomic biomarkers indicative of presence, severity, and treatment response in OSA. Participants (n = 1391) of the Stanford Technology Analytics and Genomics in Sleep study had blood collected and completed an overnight polysomnography for scoring the apnea–hypopnea index (AHI). A highly multiplexed aptamer-based array (SomaScan) was used to quantify 5000 proteins in all plasma samples. Two separate intervention-based cohorts with sleep apnea (n = 41) provided samples pre- and post-continuous/positive airway pressure (CPAP/PAP). Multivariate analyses identified 84 proteins (47 positively, 37 negatively) associated with AHI after correction for multiple testing. Of the top 15 features from a machine learning classifier for AHI ≥ 15 vs. AHI < 15 (Area Under the Curve (AUC) = 0.74), 8 were significant markers of both AHI and OSA from multivariate analyses. Exploration of pre- and post-intervention analysis identified 5 of the 84 proteins to be significantly decreased following CPAP/PAP treatment, with pathways involving endothelial function, blood coagulation, and inflammatory response. The present study identified PAI-1, tPA, and sE-Selectin as key biomarkers and suggests that endothelial dysfunction and increased coagulopathy are important consequences of OSA, which may explain the association with cardiovascular disease and stroke.
Idiopathic REM sleep behavior disorder (iRBD) is a very strong predictor for later development of Parkinson's disease (PD), and is characterized by REM sleep without atonia (RSWA), resulting in increased muscle activity during REM sleep. Abundant studies have shown the loss of atonia during REM sleep, but our aim was to investigate whether iRBD and PD patients have increased muscle activity in both REM and NREM sleep compared to healthy controls. This was achieved by developing a semi-automatic algorithm for quantification of mean muscle activity per second during all sleep stages for the enrolled patients. The three groups examined included patients suffering from iRBD, PD and healthy control subjects (CO). To determine muscle activity, a baseline and threshold were established after pre-processing of the raw surface electromyography (sEMG) signal. The signal was then segmented according to the different sleep stages and muscle activity beyond the threshold was counted. The results were evaluated statistically using the two-sided Mann-Whitney U-test. The results suggested that iRBD patients also exhibit distinctive muscle activity characteristics in NREM sleep, however not as evident as in REM sleep, leading to the conclusion that RSWA still is the most distinct characteristic of RBD. Furthermore, the muscle activity of PD patients was comparable to that of controls with only slightly elevated amplitudes.
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