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.

This review presents a detailed summary of the current literature regarding RLS and vitamin D deficiency. To our knowledge it is the first review of its kind. We review the prevalence of vitamin D deficiency in RLS as well as the evidence for the use of vitamin D supplementation in RLS management. We further examine the literature for proteomic and genetic evidence of a role for vitamin D in the pathogenesis of RLS. An alteration in vitamin D binding protein in RLS is one of the most consistent findings in the proteomic studies. Furthermore, we examine the interaction of vitamin D with calcium, phosphorus, and parathyroid hormone and the possible role of these connections in RLS. We also explore the possible nexus between RLS and vitamin D in renal disease, cardiovascular and cerebrovascular disease as well as inflammation. In addition, we review the potential interaction between vitamin D and RLS with iron, dopamine and other neurotransmitter systems including the endogenous opiate, serotoninergic, glutamatergic and adenosinergic systems. We also explore the role of vitamin D in RLS Augmentation (i.e., the paradoxical worsening of RLS symptoms when dopaminergic agents are used as a therapy for RLS). Although the literature is not entirely consistent in affirming vitamin D deficiency in RLS or the amelioration of RLS symptoms with vitamin D therapy, the collective studies overall indicate that vitamin D deficiency is common enough in RLS patients to suggest that RLS patients should have their vitamin D levels checked and any deficiency corrected as a standard of care. Highlights Patients with Restless Legs Syndrome (RLS) may be deficient in vitamin D and therapy with vitamin D may ameliorate RLS. We present the first review dedicated solely to evaluating the relationship between RLS and vitamin D and present a case for the role of vitamin D in RLS pathogenesis.

Background: Wearable motion sensors are gaining popularity for monitoring free-living physical activity among people with Parkinson disease (PD), but more evidence supporting the accuracy and precision of motion sensors for capturing step counts is required in people with PD. Objective: This study aimed to examine the accuracy and precision of 3 common consumer-grade motion sensors for measuring actual steps taken during prolonged periods of overground and treadmill walking in people with PD. Methods: A total of 31 ambulatory participants with PD underwent 6-min bouts of overground and treadmill walking at a comfortable speed. Participants wore 3 devices (Garmin Vivosmart 3, Fitbit One, and Fitbit Charge 2 HR), and a single researcher manually counted the actual steps taken. Accuracy and precision were based on absolute and relative metrics, including intraclass correlation coefficients (ICCs) and Bland-Altman plots. Results: Participants walked 628 steps over ground based on manual counting, and Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR devices had absolute (relative) error values of 6 (6/628, 1.0%), 8 (8/628, 1.3%), and 30 (30/628, 4.8%) steps, respectively. ICC values demonstrated excellent agreement between manually counted steps and steps counted by both Garmin Vivosmart (0.97) and Fitbit One (0.98) but poor agreement for Fitbit Charge 2 HR (0.47). The absolute (relative) precision values for Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR were 11.1 (11.1/625, 1.8%), 14.7 (14.7/620, 2.4%), and 74.4 (74.4/598, 12.4%) steps, respectively. ICC confidence intervals demonstrated low variability for Garmin Vivosmart (0.96 to 0.99) and Fitbit One (0.93 to 0.99) but high variability for Fitbit Charge 2 HR (–0.57 to 0.74). The Fitbit One device maintained high accuracy and precision values for treadmill walking, but both Garmin Vivosmart and Fitbit Charge 2 HR (the wrist-worn devices) had worse accuracy and precision for treadmill walking. Conclusions: The waist-worn sensor (Fitbit One) was accurate and precise in measuring steps with overground and treadmill walking. The wrist-worn sensors were accurate and precise only during overground walking. Similar research should inform the application of these devices in clinical research and practice involving patients with PD.