'NDC Learning Series' - Wellbeing, feeding, and sleep recording

We were delighted to welcome Dr. Ann Ozsivadjian, Dr. Vicki Ford, and Dr. Charlie Tyack to discuss 'Wellbeing, feeding, and sleep'. The Chair of this session was Dr. Max Davie.

Tick-Borne Encephalitis Affects Sleep-Wake Behavior and Locomotion in Infant Rats

Background/Aims: Tick-borne encephalitis (TBE) is a disease affecting the central nervous system. Over the last decade, the incidence of TBE has steadily increased in Europe and Asia despite the availably of effective vaccines. Up to 50% of patients after TBE suffer from post-encephalitic syndrome that may develop into long-lasting morbidity. Altered sleep-wake functions have been reported by patients after TBE. The mechanisms causing these disorders in TBE are largely unknown to date. As a first step toward a better understanding of the pathology of TBEV-inducing sleep dysfunctions, we assessed parameters of sleep structure in an established infant rat model of TBE.Methods: 13-day old Wistar rats were infected with 1 x 106 FFU Langat virus (LGTV). On day 4, 9, and 21 post infection, Rotarod (balance and motor coordination) and open field tests (general locomotor activity) were performed and brains from representative animals were collected in each subgroup. On day 28 the animals were implanted with a telemetric EEG/EMG system. Sleep recording was continuously performed for 24 consecutive hours starting at day 38 post infection and visually scored for Wake, NREM, and REM in 4 seconds epochs.Results: As a novelty of this study, infected animals showed a significant larger percentage of time spend awake during the dark phase and less NREM and REM compared to the control animals (p < 0.01 for all comparisons). Furthermore, it was seen, that during the dark phase the wake bout length in infected animals was prolonged (p = 0.043) and the fragmentation index decreased (p = 0.0085) in comparison to the control animals. LGTV-infected animals additionally showed a reduced rotarod performance ability at day 4 (p = 0.0011) and day 9 (p = 0.0055) and day 21 (p = 0.0037). A lower locomotor activity was also seen at day 4 (p = 0.0196) and day 9 (p = 0.0473). Conclusion: Our data show that experimental TBE in infant rats affects sleep-wake behavior, leads to decreased spontaneous locomotor activity, and impaired moto-coordinative function.

Interhemispheric asymmetry during NREM sleep in the dog

Functional hemispheric asymmetry was evidenced in many species during sleep. Dogs seem to show hemispheric asymmetry during wakefulness; however, their asymmetric neural activity during sleep was not yet explored. The present study investigated interhemispheric asymmetry in family dogs using non-invasive polysomnography. EEG recordings during 3-h-long afternoon naps were carried out (N = 19) on two occasions at the same location. Hemispheric asymmetry was assessed during NREM sleep, using bilateral EEG channels. To include periods with high homeostatic sleep pressure and to reduce the variance of the time spent in NREM sleep between dogs, the first two sleep cycles were analysed. Left hemispheric predominance of slow frequency range was detected in the first sleep cycle of sleep recording 1, compared to the baseline level of zero asymmetry as well as to the first sleep cycle of sleep recording 2. Regarding the strength of hemispheric asymmetry, we found greater absolute hemispheric asymmetry in the second sleep cycle of sleep recording 1 and 2 in the frequency ranges of alpha, sigma and beta, compared to the first sleep cycle. Differences between sleep recordings and consecutive sleep cycles might be indicative of adaptation-like processes, but do not closely resemble the results described in humans.

Hospital-Based Polysomnography May Overestimate Obstructive Sleep Apnoea Severity: Comparison of Hospital-Based and Home-Based Measurements with a Single-Lead Electrocardiogram Patch

Purpose: Obstructive sleep apnoea (OSA) is a global health concern, and polysomnography (PSG) is the gold standard for assessing OSA severity. However, the sleep parameters of home-based and in-laboratory PSG vary because of environmental factors, and the magnitude of these discrepancies remains unclear.Methods: We enrolled 125 Taiwanese patients who underwent PSG while wearing a single-lead electrocardiogram patch (RootiRx). After the PSG, all participants were instructed to continue wearing the RootiRx over the 3 subsequent nights. Scores on OSA indexes, namely the apnoea–hypopnea index, chest effort index (CEI), cyclic variation of heart rate index (CVHRI), and combined CVHRI and CEI (Rx index), were determined. The patients were divided into 3 groups based on PSG-determined OSA severity. The variables (various severity groups and environmental measurements) were subjected to mean comparisons and their correlations were examined by Pearson’s correlation coefficient. Results: The hospital-based CVHRI, CEI, and Rx index differed significantly among the severity groups. All 3 groups exhibited a significantly lower percentage of supine sleep time in the home-based assessment relative to in the hospital-based assessment. Significant positive correlations were noted between the variations in the supine percentage (∆Supine%) and the OSA indexes. For the patients with high sleep efficiency (≥ 80%), significant correlations were observed between the ∆Supine% and ∆Rx index.Conclusion: The high supine percentage of sleep may cause OSA indexes’ overestimation in hospital-based PSG. Sleep recording at home with patch-type wearable devices may aid accurate OSA diagnosis.

High nocturnal sleep fragmentation is associated with low T lymphocyte P2Y11 protein levels in narcolepsy type 1

Study Objectives Narcolepsy type 1 (NT1) is associated with hypocretin neuron loss. However, there are still unexplained phenotypic NT1 features. We investigated the associations between clinical and sleep phenotypic characteristics, the NT1-associated P2RY11 polymorphism rs2305795, and P2Y11 protein levels in T lymphocytes in patients with NT1, their first-degree relatives and unrelated controls. Methods The P2RY11 SNP was genotyped in 100 patients (90/100 H1N1-(Pandemrix)-vaccinated), 119 related and 123 non-related controls. CD4 and CD8 T lymphocyte P2Y11 protein levels were quantified using flow cytometry in 167 patients and relatives. Symptoms and sleep recording parameters were also collected. Results We found an association between NT1 and the rs2305795 A allele (OR = 2, 95% CI (1.3, 3.0), p = 0.001). T lymphocyte P2Y11 protein levels were significantly lower in patients and relatives homozygous for the rs2305795 risk A allele (CD4: p = 0.012; CD8: p = 0.007). The nocturnal sleep fragmentation index was significantly negatively correlated with patients’ P2Y11 protein levels (CD4: p = 0.004; CD8: p = 0.006). Mean MSLT sleep latency, REM-sleep latency, and core clinical symptoms were not associated with P2Y11 protein levels. Conclusions We confirmed that the P2RY11 polymorphism rs2305795 is associated with NT1 also in a mainly H1N1-(Pandemrix)-vaccinated cohort. We demonstrated that homozygosity for the A risk allele is associated with lower P2Y11 protein levels. A high level of nocturnal sleep fragmentation was associated with low P2Y11 levels in patients. This suggests that P2Y11 has a previously unknown function in sleep-wake stabilization that affects the severity of NT1.

DeepSleep convolutional neural network allows accurate and fast detection of sleep arousal

Sleep arousals are transient periods of wakefulness punctuated into sleep. Excessive sleep arousals are associated with symptoms such as sympathetic activation, non-restorative sleep, and daytime sleepiness. Currently, sleep arousals are mainly annotated by human experts through looking at 30-second epochs (recorded pages) manually, which requires considerable time and effort. Here we present a deep learning approach for automatically segmenting sleep arousal regions based on polysomnographic recordings. Leveraging a specific architecture that ‘translates’ input polysomnographic signals to sleep arousal labels, this algorithm ranked first in the “You Snooze, You Win” PhysioNet Challenge. We created an augmentation strategy by randomly swapping similar physiological channels, which notably improved the prediction accuracy. Our algorithm enables fast and accurate delineation of sleep arousal events at the speed of 10 seconds per sleep recording. This computational tool would greatly empower the scoring process in clinical settings and accelerate studies on the impact of arousals.

Subacute Ingestion of Caffeine and Oolong Tea Increases Fat Oxidation without Affecting Energy Expenditure and Sleep Architecture: A Randomized, Placebo-Controlled, Double-Blinded Cross-Over Trial

Ingesting oolong tea or caffeine acutely increases energy expenditure, and oolong tea, but not caffeine, stimulates fat oxidation. The acute effects of caffeine, such as increased heart rate and interference with sleep, diminish over 1–4 days, known as caffeine tolerance. During each 14-day session of the present study, 12 non-obese males consumed oolong tea (100 mg caffeine, 21.4 mg gallic acid, 97 mg catechins and 125 mg polymerized polyphenol), caffeine (100 mg), or placebo at breakfast and lunch. On day 14 of each session, 24-h indirect calorimetry and polysomnographic sleep recording were performed. Caffeine and oolong tea increased fat oxidation by ~20% without affecting energy expenditure over 24-h. The decrease in the respiratory quotient by oolong tea was greater than that by caffeine during sleep. The effect of oolong tea on fat oxidation was salient in the post-absorptive state. These findings suggest a role of unidentified ingredients in oolong tea to stimulate fat oxidation, and this effect is partially suppressed in a postprandial state. Two weeks of caffeine or oolong tea ingestion increased fat oxidation without interfering with sleep. The effects of subacute ingestion of caffeine and oolong tea differed from the acute effects, which is a particularly important consideration regarding habitual tea consumption.

Feasibility and Acceptability of Wearable Sleep Electroencephalogram Device Use in Adolescents: Observational Study

Background Adolescence is an important life stage for the development of healthy behaviors, which have a long-lasting impact on health across the lifespan. Sleep undergoes significant changes during adolescence and is linked to physical and psychiatric health; however, sleep is rarely assessed in routine health care settings. Wearable sleep electroencephalogram (EEG) devices may represent user-friendly methods for assessing sleep among adolescents, but no studies to date have examined the feasibility and acceptability of sleep EEG wearables in this age group. Objective The goal of the research was to investigate the feasibility and acceptability of sleep EEG wearable devices among adolescents aged 11 to 17 years. Methods A total of 104 adolescents aged 11 to 17 years participated in 7 days of at-home sleep recording using a self-administered wearable sleep EEG device (Zmachine Insight+, General Sleep Corporation) as well as a wristworn actigraph. Feasibility was assessed as the number of full nights of successful recording completed by adolescents, and acceptability was measured by the wearable acceptability survey for sleep. Feasibility and acceptability were assessed separately for the sleep EEG device and wristworn actigraph. Results A total of 94.2% (98/104) of adolescents successfully recorded at least 1 night of data using the sleep EEG device (mean number of nights 5.42; SD 1.71; median 6, mode 7). A total of 81.6% (84/103) rated the comfort of the device as falling in the comfortable to mildly uncomfortable range while awake. A total of 40.8% (42/103) reported typical sleep while using the device, while 39.8% (41/103) indicated minimal to mild device-related sleep disturbances. A minority (32/104, 30.8%) indicated changes in their sleep position due to device use, and very few (11/103, 10.7%) expressed dissatisfaction with their experience with the device. A similar pattern was observed for the wristworn actigraph device. Conclusions Wearable sleep EEG appears to represent a feasible, acceptable method for sleep assessment among adolescents and may have utility for assessing and treating sleep disturbances at a population level. Future studies with adolescents should evaluate strategies for further improving usability of such devices, assess relationships between sleep EEG–derived metrics and health outcomes, and investigate methods for incorporating data from these devices into emerging digital interventions and applications. Trial Registration ClinicalTrials.gov NCT03843762; https://clinicaltrials.gov/ct2/show/NCT03843762

Feasibility and Acceptability of Wearable Sleep Electroencephalogram Device Use in Adolescents: Observational Study (Preprint)

BACKGROUND Adolescence is an important life stage for the development of healthy behaviors, which have a long-lasting impact on health across the lifespan. Sleep undergoes significant changes during adolescence and is linked to physical and psychiatric health; however, sleep is rarely assessed in routine health care settings. Wearable sleep electroencephalogram (EEG) devices may represent user-friendly methods for assessing sleep among adolescents, but no studies to date have examined the feasibility and acceptability of sleep EEG wearables in this age group. OBJECTIVE The goal of the research was to investigate the feasibility and acceptability of sleep EEG wearable devices among adolescents aged 11 to 17 years. METHODS A total of 104 adolescents aged 11 to 17 years participated in 7 days of at-home sleep recording using a self-administered wearable sleep EEG device (Zmachine Insight+, General Sleep Corporation) as well as a wristworn actigraph. Feasibility was assessed as the number of full nights of successful recording completed by adolescents, and acceptability was measured by the wearable acceptability survey for sleep. Feasibility and acceptability were assessed separately for the sleep EEG device and wristworn actigraph. RESULTS A total of 94.2% (98/104) of adolescents successfully recorded at least 1 night of data using the sleep EEG device (mean number of nights 5.42; SD 1.71; median 6, mode 7). A total of 81.6% (84/103) rated the comfort of the device as falling in the comfortable to mildly uncomfortable range while awake. A total of 40.8% (42/103) reported typical sleep while using the device, while 39.8% (41/103) indicated minimal to mild device-related sleep disturbances. A minority (32/104, 30.8%) indicated changes in their sleep position due to device use, and very few (11/103, 10.7%) expressed dissatisfaction with their experience with the device. A similar pattern was observed for the wristworn actigraph device. CONCLUSIONS Wearable sleep EEG appears to represent a feasible, acceptable method for sleep assessment among adolescents and may have utility for assessing and treating sleep disturbances at a population level. Future studies with adolescents should evaluate strategies for further improving usability of such devices, assess relationships between sleep EEG–derived metrics and health outcomes, and investigate methods for incorporating data from these devices into emerging digital interventions and applications. CLINICALTRIAL ClinicalTrials.gov NCT03843762; https://clinicaltrials.gov/ct2/show/NCT03843762