T cells in patients with narcolepsy target self-antigens of hypocretin neurons.

Narcolepsy is a chronic sleep disorder caused by the loss of neurons that produce hypocretin. The close association with HLA-DQB1*06:02, evidence for immune dysregulation and increased incidence upon influenza vaccination together suggest that this disorder has an autoimmune origin. However, there is little evidence of autoreactive lymphocytes in patients with narcolepsy. Here we used sensitive cellular screens and detected hypocretin-specific CD4+ T cells in all 19 patients that we tested; T cells specific for tribbles homologue 2-another self-antigen of hypocretin neurons-were found in 8 out of 13 patients. Autoreactive CD4+ T cells were polyclonal, targeted multiple epitopes, were restricted primarily by HLA-DR and did not cross-react with influenza antigens. Hypocretin-specific CD8+ T cells were also detected in the blood and cerebrospinal fluid of several patients with narcolepsy. Autoreactive clonotypes were serially detected in the blood of the same-and even of different-patients, but not in healthy control individuals. These findings solidify the autoimmune aetiology of narcolepsy and provide a basis for rapid diagnosis and treatment of this disease.

Role of sleep in neurodegeneration: the consensus report of the 5th Think Tank World Sleep Forum.

Sleep abnormalities may represent an independent risk factor for neurodegeneration. An international expert group convened in 2021 to discuss the state-of-the-science in this domain. The present article summarizes the presentations and discussions concerning the importance of a strategy for studying sleep- and circadian-related interventions for early detection and prevention of neurodegenerative diseases. An international expert group considered the current state of knowledge based on the most relevant publications in the previous 5 years; discussed the current challenges in the field of relationships among sleep, sleep disorders, and neurodegeneration; and identified future priorities. Sleep efficiency and slow wave activity during non-rapid eye movement (NREM) sleep are decreased in cognitively normal middle-aged and older adults with Alzheimer's disease (AD) pathology. Sleep deprivation increases amyloid-ß (Aß) concentrations in the interstitial fluid of experimental animal models and in cerebrospinal fluid in humans, while increased sleep decreases Aß. Obstructive sleep apnea (OSA) is a risk factor for dementia. Studies indicate that positive airway pressure (PAP) treatment should be started in patients with mild cognitive impairment or AD and comorbid OSA. Identification of other measures of nocturnal hypoxia and sleep fragmentation could better clarify the role of OSA as a risk factor for neurodegeneration. Concerning REM sleep behavior disorder (RBD), it will be crucial to identify the subset of RBD patients who will convert to a specific neurodegenerative disorder. Circadian sleep-wake rhythm disorders (CSWRD) are strong predictors of caregiver stress and institutionalization, but the absence of recommendations or consensus statements must be considered. Future priorities include to develop and validate existing and novel comprehensive assessments of CSWRD in patients with/at risk for dementia. Strategies for studying sleep-circadian-related interventions for early detection/prevention of neurodegenerative diseases are required. CSWRD evaluation may help to identify additional biomarkers for phenotyping and personalizing treatment of neurodegeneration.

Unfolding the role of exercise in the management of sleep disorders.

Sleep disorders are prevalent among the general population and even more in individuals suffering from chronic diseases. Recent data reveal promising effects of physical exercise as a non-pharmacological approach for improving sleep and managing various sleep disorders. However, more studies with proper design and methodology should be conducted in the future to obtain a clearer understanding of the subject. The role of exercise in preventing and improving sleep disorders is probably much higher than what is currently exploited. To fully exploit the potential benefit of physical activity on sleep disorders in the future, it is necessary to identify the relevant tools to assess sleep-wake disorders and establish specific exercise protocols tailored to different sleep disorders. The present manuscript aims to review the literature on the use of exercise in managing selected sleep disorders. Regular exercise, including short-term aerobic activity, resistance training, and mind-body exercises, can effectively improve sleep quality, particularly in cases of insomnia and sleep-disordered breathing. Additionally, increasing evidence supports the effectiveness of aerobic and strength training, and body-mind exercises such as yoga in managing sleep-related movement disorders. Exercise can be a safe, affordable, and efficient tool in enhancing sleep quality and improving sleep disorders. Per se, regular exercise could play an adjuvant role alongside with established therapies, or a valid alternative when the pharmacological approach is limited by side effects, interactions, or inefficacy. More research is needed to define how exercise affects the physiology of sleep, and consequently how to use exercise in patients with sleep disorders.

Origin, synchronization, and propagation of sleep slow waves in children.

STUDY OBJECTIVES: Sleep slow wave activity, as measured using EEG delta power (<4 Hz), undergoes significant changes throughout development, mirroring changes in brain function and anatomy. Yet, age-dependent variations in the characteristics of individual slow waves have not been thoroughly investigated. Here we aimed at characterizing individual slow wave properties such as origin, synchronization, and cortical propagation at the transition between childhood and adulthood. METHODS: We analyzed overnight high-density (256 electrodes) EEG recordings of healthy typically developing children (N = 21, 10.3 ± 1.5 years old) and young healthy adults (N = 18, 31.1 ± 4.4 years old). All recordings were preprocessed to reduce artifacts, and NREM slow waves were detected and characterized using validated algorithms. The threshold for statistical significance was set at p = 0.05. RESULTS: The slow waves of children were larger and steeper, but less widespread than those of adults. Moreover, they tended to mainly originate from and spread over more posterior brain areas. Relative to those of adults, the slow waves of children also displayed a tendency to more strongly involve and originate from the right than the left hemisphere. The separate analysis of slow waves characterized by high and low synchronization efficiency showed that these waves undergo partially distinct maturation patterns, consistent with their possible dependence on different generation and synchronization mechanisms. CONCLUSIONS: Changes in slow wave origin, synchronization, and propagation at the transition between childhood and adulthood are consistent with known modifications in cortico-cortical and subcortico-cortical brain connectivity. In this light, changes in slow-wave properties may provide a valuable yardstick to assess, track, and interpret physiological and pathological development.

Automatic video analysis and classification of sleep-related hypermotor seizures and disorders of arousal.

OBJECTIVE: Sleep-related hypermotor epilepsy (SHE) is a focal epilepsy with seizures occurring mostly during sleep. SHE seizures present different motor characteristics ranging from dystonic posturing to hyperkinetic motor patterns, sometimes associated with affective symptoms and complex behaviors. Disorders of arousal (DOA) are sleep disorders with paroxysmal episodes that may present analogies with SHE seizures. Accurate interpretation of the different SHE patterns and their differentiation from DOA manifestations can be difficult and expensive, and can require highly skilled personnel not always available. Furthermore, it is operator dependent. METHODS: Common techniques for human motion analysis, such as wearable sensors (e.g., accelerometers) and motion capture systems, have been considered to overcome these problems. Unfortunately, these systems are cumbersome and they require trained personnel for marker and sensor positioning, limiting their use in the epilepsy domain. To overcome these problems, recently significant effort has been spent in studying automatic methods based on video analysis for the characterization of human motion. Systems based on computer vision and deep learning have been exploited in many fields, but epilepsy has received limited attention. RESULTS: In this paper, we present a pipeline composed of a set of three-dimensional convolutional neural networks that, starting from video recordings, reached an overall accuracy of 80% in the classification of different SHE semiology patterns and DOA. SIGNIFICANCE: The preliminary results obtained in this study highlight that our deep learning pipeline could be used by physicians as a tool to support them in the differential diagnosis of the different patterns of SHE and DOA, and encourage further investigation.

Clinical and instrumental features in 82 patients with insufficient sleep syndrome.

Insufficient sleep syndrome possibly represents the worldwide leading cause of daytime sleepiness, but remains poorly recognised and studied. The aim of this case series is to comprehensively describe a cohort of patients with insufficient sleep syndrome. Eighty-two patients were studied concerning demographic and socio-economic features, medical, psychiatric and sleep comorbidities, substance use, sleep symptoms, actigraphy, video-polysomnography, multiple sleep latency tests and treatment. The typical patient with insufficient sleep syndrome is a middle-aged adult (with no difference of gender), employed, who has a family, often carrying psychiatric and neurological comorbidities, in particular headache, anxiety and depression. Other sleep disorders, especially mild sleep apnea and bruxism, were common as well. Actigraphy was a valuable tool in the characterisation of insufficient sleep syndrome, showing a sleep restriction during weekdays, associated with a recovery rebound of night sleep during weekends and a high amount of daytime sleep. An over- or underestimation of sleeping was common, concerning both the duration of night sleep and daytime napping. The average daily sleep considering both daytime and night-time, weekdays and weekends corresponds to the recommended minimal normal duration, meaning that the burden of insufficient sleep syndrome could mainly depend on sleep fragmentation and low quality. Sleep efficiency was elevated both in actigraphy and video-polysomnography. Multiple sleep latency tests evidenced a tendency toward sleep-onset rapid eye movement periods. Our study offers a comprehensive characterisation of patients with insufficient sleep syndrome, and clarifies their sleeping pattern, opening avenues for management and treatment of the disorder. Current options seem not adapted, and in our opinion a cognitive-behavioural psychotherapy protocol should be developed.

Protein tyrosine phosphatase receptor type delta (PTPRD) gene in an animal model of restless legs syndrome.

The pathophysiology of the restless legs syndrome (RLS) is related to dopaminergic dysfunction, reduced iron and variations in gene expression, such as the protein tyrosine phosphatase receptor type delta gene (PTPRD). Animal models could be key to achieving a mechanistic understanding of RLS and to facilitate efficient platforms for evaluating new therapeutics. Thus, the aim of this study was to evaluate the expression of PTPRD, of genes and proteins associated with RLS, the sleep patterns and the cardiovascular parameters in an animal model of RLS (spontaneously hypertensive rat [SHR]). Rats were divided into two groups: (i) Wistar-Kyoto and (ii) SHR. Cardiovascular parameters were assessed by tail plethysmography. Polysomnography was used to analyse the sleep pattern (24 h). For the PTPRD analyses, quantitative polymerase chain reaction (qPCR) and indirect enzyme-linked immunosorbent assay (ELISA) techniques were used. To evaluate the tyrosine hydroxylase enzyme, dopamine transporter (DAT) and type 2 dopaminergic receptor, qPCR and Western Blotting techniques were used. For the quantification of iron, ferritin and transferrin, the ELISA method was used. SHRs had higher blood pressure, alterations in sleep pattern, lower expression of protein content of PTPRD, lower expression of DAT, and lower serum concentrations of ferritin. These data suggest that the behavioural, physiological, and molecular changes observed in SHRs provide a useful animal model of RLS, reinforcing the importance of this strain as an animal model of this sleep disorder.

Multiple sleep-wake disturbances after stroke predict an increased risk of cardio-cerebrovascular events or death: A prospective cohort study.

BACKGROUND AND PURPOSE: Contradictory evidence on the impact of single sleep-wake-disturbances (SWD), such as sleep-disorderd breating (SDB) or insomnia, in patients with stroke, on the risk of subsequent cardio- and cerebrovascular events (CCE) and death, exists. Very recent studies in the general population suggest that the presence of multiple SWD increases cardio-cerebrovascular risk. Hence, the aim of this study was to asssess whether a novel score capturing the burden of multiple SWD, a so called "sleep burden index", is predictive for subsequent CCE including death in a prospectively followed cohort of stroke patients. METHODS: Patients with acute ischemic stroke or transient ischemic attack (TIA) were prospectively recruited. Four SWD were analyzed: (i) SDB with respirography; (ii) insomnia (defined using the insomnia severity index [ISI]); (iii) restless legs syndrome (RLS; defined using the International RLS Study Group rating scale); and (iv) self-estimated sleep duration at 1 and 3 months. A "sleep burden index", calculated using the mean of z-transformed values from assessments of these four SWD, was created. The occurrence of CCE was recorded over a mean ± standard deviation (SD) follow-up of 3.2 ± 0.3 years. RESULTS: We assessed 437 patients (87% ischemic stroke, 13% TIA, 64% males) with a mean ± SD age of 65.1 ± 13.0 years. SDB (respiratory event index ≥ 5/h) was present in 66.2% of these patients. Insomnia (ISI ≥ 10), RLS and extreme sleep duration affected 26.2%, 6.4% and 13.7% of the patients 3 months post-stroke. Seventy out of the 437 patients (16%) had at least one CCE during the follow-up. The sleep burden index was associated with a higher risk for subsequent CCE, including death (odds ratio 1.80 per index unit, 95% confidence interval 1.19-2.72; p = 0.0056). CONCLUSION: The presence of multiple SWDs constitutes a risk for subsequent CCE (including death) within the first 3 years following stroke. Larger systematic studies should assess the utility of the sleep burden index for patients' risk stratification in clinical practice.

Sleep microstructure in attention deficit hyperactivity disorder according to the underlying sleep phenotypes.

The analysis of sleep microstructure in attention deficit hyperactivity disorder (ADHD) revealed an under-representation of the EEG slow component during NREM sleep. Previous studies either excluded or did not characterize objectively sleep disorders, which notoriously affect sleep architecture. The present study aimed to investigate the cyclic alternating pattern in a real clinical sample of children with ADHD, in whom sleep disorders could be considered. Twenty-seven consecutively enrolled drug-naïve children (mean age, 10.53 years; nine females) and 23 controls (mean age, 10.22 years; 11 females) underwent a full sleep investigation, including attended video-polysomnography. Visual cyclic alternating pattern analysis was performed in a blinded way. Children with ADHD had one or more sleep disorders (a narcolepsy-like phenotype was found in two cases, sleep onset insomnia in three cases, arousal disorder in one case, movement disorder phenotype in six cases and obstructive sleep apnea in 11 cases, and six children had sleep-related epileptiform discharges). Children with ADHD and normal controls showed a similar microstructure with a cyclic alternating pattern rate of about 50%. Children with obstructive sleep apnea had a significantly higher cyclic alternating pattern rate during stage N3. Despite not reaching statistical differences, a lower cyclic alternating pattern rate and A1 index were found in children without epileptic abnormalities/obstructive sleep apnea. Our analysis might allow differentiation of the "primary form" of ADHD associated with a decrease of NREM instability from those forms associated with sleep apnea and epileptic activity.

A calibrated model with a single-generator simulating polysomnographically recorded periodic leg movements.

The aim of this study was to assess, with numerical simulations, if the complex mechanism of two (or more) interacting spinal/supraspinal structures generating periodic leg movements can be modelled with a single-generator approach. For this, we have developed the first phenomenological model to generate periodic leg movements in-silico. We defined the onset of a movement in one leg as the firing of a neuron integrating excitatory and inhibitory inputs from the central nervous system, while the duration of the movement was defined in accordance to statistical evidence. For this study, polysomnographic leg movement data from 32 subjects without periodic leg movements and 65 subjects with periodic leg movements were used. The proportion of single-leg and double-leg inputs, as well as their strength and frequency, were calibrated on the without periodic leg movements dataset. For periodic leg movements subjects, we added a periodic excitatory input common to both legs, and the distributions of the generator period and intensity were fitted to their dataset. Besides the many simplifying assumptions - the strongest being the stationarity of the generator processes during sleep - the model-simulated data did not differ significantly, to a large extent, from the real polysomnographic data. This represents convincing preliminary support for the validity of our single-generator model for periodic leg movements. Future model extensions will pursue the ambitious project of a supportive diagnostic and therapeutic tool, helping the specialist with realistic forecasting, and with cross-correlations and clustering with other patient meta-data.