A longitudinal observational population-based study of brain volume associated with changes in sleep timing from middle to late-lifeKim, Regina E Y; Kim, Hyeon Jin; Kim, Soriul; Abbott, Robert D; Thomas, Robert J; Yun, Chang-Ho; Lee, Hyang Woon; Shin, Chol
doi: 10.1093/sleep/zsaa233pmid: 33170277
Study ObjectivesSleep behaviors are related to brain structure and function, but the impact of long-term changes in sleep timing on brain health has not been clearly addressed. The purpose of this study was to examine the association of longitudinal changes in sleep timing from middle to late-life with gray matter volume (GMV), an important marker of brain aging.MethodsWe enrolled 1798 adults (aged 49–82 years, men 54.6%) who underwent magnetic resonance imaging (MRI) between 2011 and 2014. Midsleep time (MST) on free days corrected for sleep debt on workdays was adopted as a marker of sleep timing. Data on MST were available at the time of MRI assessment and at examinations that were given 9 years earlier (2003–2004). Longitudinal changes in MST over the 9-year period were derived and categorized into quartiles. Subjects in quartile 1 were defined as “advancers” (MST advanced ≥ 1 h) while those in quartile 4 were defined as “delayers” (MST delayed ≥ 0.2 h). Quartiles 2–3 defined a reference group (MST change was considered modest). The relationship of GMV with MST changes over 9 years was investigated.ResultsNine-year change in MST were significantly associated with GMV. Compared to the reference group, advancers had smaller GMVs in the frontal and temporal regions. A delay in MST was also associated with smaller cerebellar GMV.ConclusionsIn middle-to-late adulthood, the direction of change in MST is associated with GMV. While advancers and delayers in MST tend to present lower GMV, associations appear to differ across brain regions.
Residual, differential neurobehavioral deficits linger after multiple recovery nights following chronic sleep restriction or acute total sleep deprivationYamazaki, Erika M; Antler, Caroline A; Lasek, Charlotte R; Goel, Namni
doi: 10.1093/sleep/zsaa224pmid: 33274389
Study ObjectivesThe amount of recovery sleep needed to fully restore well-established neurobehavioral deficits from sleep loss remains unknown, as does whether the recovery pattern differs across measures after total sleep deprivation (TSD) and chronic sleep restriction (SR).MethodsIn total, 83 adults received two baseline nights (10–12-hour time in bed [TIB]) followed by five 4-hour TIB SR nights or 36-hour TSD and four recovery nights (R1–R4; 12-hour TIB). Neurobehavioral tests were completed every 2 hours during wakefulness and a Maintenance of Wakefulness Test measured physiological sleepiness. Polysomnography was collected on B2, R1, and R4 nights.ResultsTSD and SR produced significant deficits in cognitive performance, increases in self-reported sleepiness and fatigue, decreases in vigor, and increases in physiological sleepiness. Neurobehavioral recovery from SR occurred after R1 and was maintained for all measures except Psychomotor Vigilance Test (PVT) lapses and response speed, which failed to completely recover. Neurobehavioral recovery from TSD occurred after R1 and was maintained for all cognitive and self-reported measures, except for vigor. After TSD and SR, R1 recovery sleep was longer and of higher efficiency and better quality than R4 recovery sleep.ConclusionsPVT impairments from SR failed to reverse completely; by contrast, vigor did not recover after TSD; all other deficits were reversed after sleep loss. These results suggest that TSD and SR induce sustained, differential biological, physiological, and/or neural changes, which remarkably are not reversed with chronic, long-duration recovery sleep. Our findings have critical implications for the population at large and for military and health professionals.
Slow oscillation density and amplitude decrease across development in pediatric Duchenne and Becker muscular dystrophySimon, Katharine C; Malerba, Paola; Nakra, Neal; Harrison, Amy; Mednick, Sara C; Nagel, Marni
doi: 10.1093/sleep/zsaa240pmid: 33202016
Study ObjectivesFrom childhood through adolescence, brain rhythms during non-rapid eye movement (NREM) sleep show dramatic development that mirror underlying brain maturation. For example, the function and characteristics of slow oscillations (SOs, <1 Hz) in healthy children are linked to brain development, motor skill, and cognition. However, little is known of possible changes in pediatric populations with neurologic abnormalities.MethodsWe measured slow oscillations in 28 Duchenne and Becker muscular dystrophy male patients from age 4 to 20 years old during overnight in-lab clinical sleep studies. We compared our pediatric patients by age to evaluate the developmental changes of SOs from childhood to early and late adolescence.ResultsConsistent with the current neuro- and physically typical literature, we found greater slow oscillation density (count of SOs per minute of each sleep stage) in NREM N3 than N2, and significantly greater slow oscillation density in frontal compared to central and occipital regions. However, separating patients into age-defined groups (child, early adolescent, and late adolescent) revealed a significant age effect, with a specific decline in the rate and amplitude of SOs.ConclusionsWe found that with age, pediatric patients with Duchenne muscular dystrophy show a significant decline in slow oscillation density. Given the role that slow oscillations play in memory formation and retention, it is critical to developmentally characterize these brain rhythms in medically complex populations. Our work converges with previous pediatric sleep literature that promotes the use of sleep electroencephalographic markers as prognostic tools and identifies potential targets to promote our patients’ quality of life.
Complement promotes endothelial von Willebrand factor and angiopoietin-2 release in obstructive sleep apneaGao, Su; Emin, Memet; Thoma, Theodosia; Pastellas, Kalliopi; Castagna, Francesco; Shah, Riddhi; Jimenez, Alondra; Patel, Neha; Wei, Ying; Jelic, Sanja
doi: 10.1093/sleep/zsaa286pmid: 33351148
Study ObjectiveObstructive sleep apnea (OSA) is highly prevalent and triples vascular thromboembolic risk. Intermittent hypoxia (IH) during transient cessation of breathing in OSA impairs endothelial protection against complement. Complement activation stimulates the endothelial release of a pro-thrombotic von Willebrand factor (vWF). We investigated whether increased complement activity in OSA promotes the endothelial release of vWF and pro-inflammatory angiopoietin-2. We further investigated whether improving complement protection with statins reverses these changes.MethodsUsing endothelial cells (ECs) and blood collected from OSA patients (n = 109) and controls (n = 67), we assessed whether altered cellular localization of complement inhibitor CD59 in OSA modulates exocytosis of Weibel-Palade bodies (WPB), secretory granules that store vWF and angiopoietin-2. These interactions were also assessed in vitro in ECs exposed to normoxia or IH with or without recombinant complement C9 and with or without atorvastatin.ResultsCirculating levels of angiopoietin-2 were greater in OSA than controls and levels of vWF cleavage products correlated with OSA severity. In cultured ECs, IH enhanced complement-stimulated angiopoietin-2 and vWF release by reducing EC surface and increasing intracellular expression of complement inhibitor CD59. Intracellular CD59 co-localized with WPB in OSA. IH increased binding of intracellular CD59 to syntaxin-3, which dissociated syntaxin-3 from voltage-sensitive calcium channel Cav1.2, and activated WPB exocytosis in a calcium-dependent manner. Atorvastatin reversed IH-enhanced endothelial release of vWF and angiopoietin-2.ConclusionsIH promotes the complement-mediated release of vWF and angiopoietin-2, which may contribute to pro-thrombotic and pro-inflammatory conditions in OSA. Statin reversed these effects, suggesting a potential approach to reduce cardiovascular risk in OSA.
Sleep and high-risk behavior in military service members: a mega-analysis of four diverse U.S. Army unitsMantua, Janna; Bessey, Alexxa F; Mickelson, Carolyn A; Choynowski, Jake J; Noble, Jeremy J; Burke, Tina M; McKeon, Ashlee B; Sowden, Walter J
doi: 10.1093/sleep/zsaa221pmid: 33125489
Experimental sleep restriction and deprivation lead to risky decision-making. Further, in naturalistic settings, short sleep duration and poor sleep quality have been linked to real-world high-risk behaviors (HRB), such as reckless driving or substance use. Military populations, in general, tend to sleep less and have poorer sleep quality than nonmilitary populations due to a number of occupational, cultural, and psychosocial factors (e.g. continuous operations, stress, and trauma). Consequently, it is possible that insufficient sleep in this population is linked to HRB. To investigate this question, we combined data from four diverse United States Army samples and conducted a mega-analysis by aggregating raw, individual-level data (n = 2,296, age 24.7 ± 5.3). A negative binomial regression and a logistic regression were used to determine whether subjective sleep quality (Pittsburgh Sleep Quality Index [PSQI], Insomnia Severity Index [ISI], and duration [h]) predicted instances of military-specific HRB and the commission of any HRB (yes/no), respectively. Poor sleep quality slightly elevated the risk for committing HRBs (PSQI Exp(B): 1.12 and ISI Exp(B): 1.07), and longer duration reduced the risk for HRBs to a greater extent (Exp(B): 0.78), even when controlling for a number of relevant demographic factors. Longer sleep duration also predicted a decreased risk for commission of any HRB behaviors (Exp(B): 0.71). These findings demonstrate that sleep quality and duration (the latter factor, in particular) could be targets for reducing excessive HRB in military populations. These findings could therefore lead to unit-wide or military-wide policy changes regarding sleep and HRB.
Changes in EEG permutation entropy in the evening and in the transition from wake to sleepHou, Fengzhen; Zhang, Lulu; Qin, Baokun; Gaggioni, Giulia; Liu, Xinyu; Vandewalle, Gilles
doi: 10.1093/sleep/zsaa226pmid: 33159205
Quantifying the complexity of the EEG signal during prolonged wakefulness and during sleep is gaining interest as an additional mean to characterize the mechanisms associated with sleep and wakefulness regulation. Here, we characterized how EEG complexity, as indexed by Multiscale Permutation Entropy (MSPE), changed progressively in the evening prior to light off and during the transition from wakefulness to sleep. We further explored whether MSPE was able to discriminate between wakefulness and sleep around sleep onset and whether MSPE changes were correlated with spectral measures of the EEG related to sleep need during concomitant wakefulness (theta power—Ptheta: 4–8 Hz). To address these questions, we took advantage of large datasets of several hundred of ambulatory EEG recordings of individual of both sexes aged 25–101 years. Results show that MSPE significantly decreases before light off (i.e. before sleep time) and in the transition from wakefulness to sleep onset. Furthermore, MSPE allows for an excellent discrimination between pre-sleep wakefulness and early sleep. Finally, we show that MSPE is correlated with concomitant Ptheta. Yet, the direction of the latter correlation changed from before light-off to the transition to sleep. Given the association between EEG complexity and consciousness, MSPE may track efficiently putative changes in consciousness preceding sleep onset. An MSPE stands as a comprehensive measure that is not limited to a given frequency band and reflects a progressive change brain state associated with sleep and wakefulness regulation. It may be an effective mean to detect when the brain is in a state close to sleep onset.
Algorithm for automatic detection of self-similarity and prediction of residual central respiratory events during continuous positive airway pressureOppersma, Eline; Ganglberger, Wolfgang; Sun, Haoqi; Thomas, Robert J; Westover, M Brandon
doi: 10.1093/sleep/zsaa215pmid: 33057718
Study ObjectivesSleep-disordered breathing is a significant risk factor for cardiometabolic and neurodegenerative diseases. High loop gain (HLG) is a driving mechanism of central sleep apnea or periodic breathing. This study presents a computational approach that identifies “expressed/manifest” HLG via a cyclical self-similarity feature in effort-based respiration signals.MethodsWorking under the assumption that HLG increases the risk of residual central respiratory events during continuous positive airway pressure (CPAP), the full night similarity, computed during diagnostic non-CPAP polysomnography (PSG), was used to predict residual central events during CPAP (REC), which we defined as central apnea index (CAI) higher than 10. Central apnea labels are obtained both from manual scoring by sleep technologists and from an automated algorithm developed for this study. The Massachusetts General Hospital sleep database was used, including 2466 PSG pairs of diagnostic and CPAP titration PSG recordings.ResultsDiagnostic CAI based on technologist labels predicted REC with an area under the curve (AUC) of 0.82 ± 0.03. Based on automatically generated labels, the combination of full night similarity and automatically generated CAI resulted in an AUC of 0.85 ± 0.02. A subanalysis was performed on a population with technologist-labeled diagnostic CAI higher than 5. Full night similarity predicted REC with an AUC of 0.57 ± 0.07 for manual and 0.65 ± 0.06 for automated labels.ConclusionsThe proposed self-similarity feature, as a surrogate estimate of expressed respiratory HLG and computed from easily accessible effort signals, can detect periodic breathing regardless of admixed obstructive features such as flow limitation and can aid the prediction of REC.