Sleep and circadian rhythm disruption in psychiatric and neurodegenerative disease

Actigraphic monitoring of sleep and circadian rest-activity rhythm in individuals with major depressive disorder or depressive symptoms: A meta-analysis

BACKGROUND

Disrupted sleep and rest-activity pattern are common clinical features in depressed individuals. This meta-analysis compared sleep and circadian rest-activity rhythms in people with major depressive disorder (MDD) or depressive symptoms and healthy controls.

METHODS

Eligible studies were identified in five databases up to December 2023. The search yielded 53 studies with a total of 11,115 participants, including 4000 depressed participants and 7115 healthy controls.

RESULTS

Pooled meta-analyses demonstrated that depressed individuals have significantly longer sleep latency (SMD = 0.23, 95 % CI: 0.12 to 0.33) and wake time after sleep onset (SMD = 0.37, 95 % CI: 0.22 to 0.52), lower sleep efficiency (SMD = -0.41, 95 % CI: -0.56 to -0.25), more nocturnal awakenings (SMD = 0.58, 95 % CI: 0.29 to 0.88), lower MESOR (SMD = -0.54, 95 % CI: -0.81 to -0.28), amplitude (SMD = -0.33, 95 % CI: -0.57 to -0.09), and interdaily stability (SMD = -0.17, 95 % CI: -0.28 to -0.05), less daytime (SMD = -0.79, 95 % CI: -1.08 to -0.49) and total activities (SMD = -0.89, 95 % CI: -1.28 to -0.50) when compared with healthy controls.

LIMITATIONS

Most of the included studies reported separate sleep and activity parameters instead of 24-hour rest-activity rhythms. The variabilities among actigraphy devices and the types of participants recruited also impede precise comparisons.

CONCLUSIONS

The findings emerging from this study offered a better understanding of sleep and rest-activity rhythm in individuals with MDD or depressive symptoms. Future studies could advocate for deriving objective, distinctive 24-hour rest-activity profiles contributing to the risk of depression.

PROSPERO REGISTRATION NUMBER

CRD42021259780.

The role of nitric oxide and hormone signaling in chronic stress, anxiety, depression and post-traumatic stress disorder

This paper provides a summary of the role of nitric oxide (NO) and hormones in the development of chronic stress, anxiety, depression, and post-traumatic stress disorder (PTSD). These mental health conditions are prevalent globally and involve complex molecular interactions. Although there is a significant amount of research and therapeutic options available, the underlying mechanisms of these disorders are still not fully understood. The primary pathophysiologic processes involved in chronic stress, anxiety, depression, and PTSD include dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, the intracellular influence of neuronal nitric oxide synthase (nNOS) on transcription factors, an inflammatory response with the formation of nitrergic oxidative species, and reduced serotonergic transmission in the dorsal raphe nucleus. Despite the extensive literature on this topic, there is a great need for further research to clarify the complexities inherent in these pathways, with the primary aim of improving psychiatric care.

The rhythm of mental health: the relationship of chronotype with psychiatric trait dimensions and diurnal variation in psychiatric symptoms

To advance the emergence of circadian-based therapies, this study characterized how psychiatric symptoms fluctuate across the day and vary between individuals. Using a dimensional approach, we determined how chronotype relates to 13 psychiatric traits, and modeled the temporal development of symptoms throughout the day using generalized additive mixed effects models. In this preregistered study, a subclinical sample completed 13 psychiatric trait scales and a chronotype scale at baseline (N = 515, n = 404 women, 109 men, n = 2 non-binary, M age = 32.4 years, range 18-77), followed by 22 psychiatric symptoms and behaviors rated repeatedly between ~08:00-00:00 (n = 410). Key findings are that 11 out of 13 psychiatric traits were associated with being an evening-type, ranging from depression to obsessive comulsive disorder, social anxiety, and delusional ideation, while only mania was associated with being a morning-type. Four distinct psychiatric trait factors were identified, each predicting worse symptom levels throughout the day. Fatigue-related symptoms exhibited strong time-of-day changes with evening-types experiencing worse fatigue in the morning and morning-types in the evening. Evening-types had considerably lower drive and motivation than morning-types from morning to early evening. Evening-types also had more pronounced negative emotional symptoms and ADHD-type symptoms in the evening, particularly among those high in psychiatric trait factors. These findings identified important research targets that hold promise for improving mental health outcomes, such as strategies to boost morning motivation. Furthermore, the results emphasize the relevance of incorporating circadian factors, including chronotype, into translational psychiatric research and interventions.

Risks of mental disorders among inpatients with burn injury: A nationwide cohort study

OBJECTIVE

This investigation identified the association between burn injuries and the risk of mental disorders in patients with no documented pre-existing psychiatric comorbidities. We also examined the relationship of injury severity and the types of injury with the likelihood of receiving new diagnoses of mental disorders.

METHODS

This population-based retrospective cohort study used administrative data extracted from the Taiwanese National Health Insurance Research Database (NHIRD) between 2000 and 2013. In total, 10,045 burn survivors were matched with a reference cohort of 40,180 patients without burn injuries and were followed to determine if any mental disorder was diagnosed. Patients diagnosed with mental disorders in the five years before study initiation were excluded to ensure incident diagnoses throughout the research duration. Generalized estimating equations in Cox proportional hazard regression models were used for data analysis.

RESULTS

In general, burn injury survivors have a 1.21-fold risk of being diagnosed with new mental disorders relative to patients without burn injuries. Total body surface area (TBSA) of ≧ 30% (aHR: 1.49, 95% CI: 1.36-1.63) and third- or fourth-degree burns (aHR: 1.49, 95% CI: 1.37-1.63) had a significantly greater risk of being diagnosed with mental disorders in comparison to the reference cohort. Patients TBSA 10-29% (aHR: 0.85, 95% CI: 0.77-0.93) and first- or second-degree burn victims (aHR: 0.89, 95% CI: 0.81-0.97) had relatively lower risk of mental disorders than the reference cohort.

CONCLUSION

Burn injuries were associated with an increased risk of mental disorders. Additional research in this field could elucidate this observation, especially if the inherent limitations of the NHIRD can be overcome.

Eveningness chronotype influences social functioning by deteriorating depressive symptoms in remitted patients with schizophrenia

Sleep and circadian rhythm disruption (SCRD) is common in schizophrenia patients, who also typically experience impaired social functioning. While various factors influence social functioning in schizophrenia, the specific impact of sleep and circadian rhythm disruption remains unclear. This study aimed to investigate the connection between chronotype and social functioning in remitted schizophrenia patients, examining the mediating roles of depression and sleep quality. The study included 185 patients diagnosed with schizophrenia based on DSM-5 criteria. After categorizing the patients into morningness, eveningness, or intermediate chronotypes using the Morningness-Eveningness Questionnaire(MEQ), they were assessed with the Positive and Negative Syndrome Scale(PANSS), Calgary Depression Scale for Schizophrenia(CDSS), Personal and Social Performance Scale(PSPS) and Pittsburgh Sleep Quality Index(PSQI). The eveningness chronotype group showed higher CDSS and PSQI scores and lower PWBS and PSPS-Total scores than the other groups (p < 0.05). A hierarchical linear regression model assessed MEQ, PSQI, and CDSS scores' effects on PSPS total scores. MEQ scores' significance diminished when CDSS scores were included. Eveningness chronotype, particularly with increased depressive symptoms, negatively impacts social functioning in remitted schizophrenia patients.These findings contribute to the understudied area of chronotype in schizophrenia and its impact on social functioning, including its interaction with sleep..

Sleep interventions for adults admitted to psychiatric inpatient settings: A systematic scoping review

Sleep disturbances are common, affecting over half of adults with a mental disorder. For those admitted to a psychiatric ward, difficulties with sleep, particularly insomnia, are compounded by factors relating to the inpatient setting. We conducted a scoping review of sleep intervention studies involving adults admitted to psychiatric settings. We categorised the different types of sleep interventions and identified the effects on sleep and other mental and physical health outcomes. Instruments used to measure sleep were also examined. The search strategy yielded 4780 studies, of which 28 met the inclusion criteria. There was evidence of more non-pharmacological than pharmacological interventions having been tested in inpatient settings. Results indicated that non-pharmacological interventions based on cognitive behaviour therapy for insomnia improve sleep and may improve mental and physical health. Several distinct sleep measures were used in the studies. Gaps in the literature were identified, highlighting the importance of research into a wider range of sleep interventions tested against robust controls, using validated measures of sleep with evaluation of additional mental and physical health outcomes among a large sample size of adults in the psychiatric inpatient settings.

Correlates of Sleep Disturbance Experienced by Informal Caregivers of Persons Living with Dementia: A Systematic Review

OBJECTIVES

This study aims to comprehensively review and update the literature concerning the correlates of sleep disturbance among caregivers of persons living with Alzheimer's disease and related dementias to identify gaps in the literature and antecedent targets for interventions.

METHODS

We searched PubMed, CINAHL, PsycINFO, and Embase using terms related to "sleep," "caregiver," and "dementia."

RESULTS

Thirty-six articles were included in this review. Based on the antecedents within the 3P model of insomnia, predisposing factors associated with caregiver sleep included caregiver demographics, and physiological factors like genotype and biomarkers. Precipitating factors related to caregiver sleep included caregiving status and responsibilities, and person living with dementia factors.

CONCLUSIONS

Sleep disturbance is a significant issue for caregivers of persons living with dementia. However, this review has identified multiple precipitating factors that are modifiable targets for interventions to improve or enhance caregiver sleep.

CLINICAL IMPLICATIONS

Numerous predisposing and precipitating factors contribute to caregivers of persons living with dementia being susceptible to sleep disturbance. Healthcare providers should ask patients about their caregiving status during annual visits. Healthcare providers should also evaluate caregivers' sleep patterns, and the predisposing and precipitating factors of sleep disturbance, with a focus on the modifiable factors, to enable timely intervention.

ZleepAnlystNet: a novel deep learning model for automatic sleep stage scoring based on single-channel raw EEG data using separating training

Numerous models for sleep stage scoring utilizing single-channel raw EEG signal have typically employed CNN and BiLSTM architectures. While these models, incorporating temporal information for sequence classification, demonstrate superior overall performance, they often exhibit low per-class performance for N1-stage, necessitating an adjustment of loss function. However, the efficacy of such adjustment is constrained by the training process. In this study, a pioneering training approach called separating training is introduced, alongside a novel model, to enhance performance. The developed model comprises 15 CNN models with varying loss function weights for feature extraction and 1 BiLSTM for sequence classification. Due to its architecture, this model cannot be trained using an end-to-end approach, necessitating separate training for each component using the Sleep-EDF dataset. Achieving an overall accuracy of 87.02%, MF1 of 82.09%, Kappa of 0.8221, and per-class F1-socres (W 90.34%, N1 54.23%, N2 89.53%, N3 88.96%, and REM 87.40%), our model demonstrates promising performance. Comparison with sleep technicians reveals a Kappa of 0.7015, indicating alignment with reference sleep stags. Additionally, cross-dataset validation and adaptation through training with the SHHS dataset yield an overall accuracy of 84.40%, MF1 of 74.96% and Kappa of 0.7785 when tested with the Sleep-EDF-13 dataset. These findings underscore the generalization potential in model architecture design facilitated by our novel training approach.

The microbiota drives diurnal rhythms in tryptophan metabolism in the stressed gut

Chronic stress disrupts microbiota-gut-brain axis function and is associated with altered tryptophan metabolism, impaired gut barrier function, and disrupted diurnal rhythms. However, little is known about the effects of acute stress on the gut and how it is influenced by diurnal physiology. Here, we used germ-free and antibiotic-depleted mice to understand how microbiota-dependent oscillations in tryptophan metabolism would alter gut barrier function at baseline and in response to an acute stressor. Cecal metabolomics identified tryptophan metabolism as most responsive to a 15-min acute stressor, while shotgun metagenomics revealed that most bacterial species exhibiting rhythmicity metabolize tryptophan. Our findings highlight that the gastrointestinal response to acute stress is dependent on the time of day and the microbiome, with a signature of stress-induced functional alterations in the ileum and altered tryptophan metabolism in the colon.

Digital Dietary Behaviors in Individuals With Depression: Real-World Behavioral Observation

BACKGROUND

Depression is often accompanied by changes in behavior, including dietary behaviors. The relationship between dietary behaviors and depression has been widely studied, yet previous research has relied on self-reported data which is subject to recall bias. Electronic device-based behavioral monitoring offers the potential for objective, real-time data collection of a large amount of continuous, long-term behavior data in naturalistic settings.

OBJECTIVE

The study aims to characterize digital dietary behaviors in depression, and to determine whether these behaviors could be used to detect depression.

METHODS

A total of 3310 students (2222 healthy controls [HCs], 916 with mild depression, and 172 with moderate-severe depression) were recruited for the study of their dietary behaviors via electronic records over a 1-month period, and depression severity was assessed in the middle of the month. The differences in dietary behaviors across the HCs, mild depression, and moderate-severe depression were determined by ANCOVA (analyses of covariance) with age, gender, BMI, and educational level as covariates. Multivariate logistic regression analyses were used to examine the association between dietary behaviors and depression severity. Support vector machine analysis was used to determine whether changes in dietary behaviors could detect mild and moderate-severe depression.

RESULTS

The study found that individuals with moderate-severe depression had more irregular eating patterns, more fluctuated feeding times, spent more money on dinner, less diverse food choices, as well as eating breakfast less frequently, and preferred to eat only lunch and dinner, compared with HCs. Moderate-severe depression was found to be negatively associated with the daily 3 regular meals pattern (breakfast-lunch-dinner pattern; OR 0.467, 95% CI 0.239-0.912), and mild depression was positively associated with daily lunch and dinner pattern (OR 1.460, 95% CI 1.016-2.100). These changes in digital dietary behaviors were able to detect mild and moderate-severe depression (accuracy=0.53, precision=0.60), with better accuracy for detecting moderate-severe depression (accuracy=0.67, precision=0.64).

CONCLUSIONS

This is the first study to develop a profile of changes in digital dietary behaviors in individuals with depression using real-world behavioral monitoring. The results suggest that digital markers may be a promising approach for detecting depression.

High-frequency neural activity dysregulation is associated with sleep and psychiatric disorders in BMAL1-deficient animal models

Sleep disturbance led by BMAL1-deficiency has been recognized both in rodent and non-human primate models. Yet it remained unclear how their diurnal brain oscillations were affected upon BMAL1 ablation and what caused the discrepancy in the quantity of sleep between the two species. Here, we investigated diurnal electroencephalographs of BMAL1-deficient mice and cynomolgus monkeys at young adult age and uncovered a shared defect of dysregulated high-frequency oscillations by Kullback-Leibler divergence analysis. We found beta and gamma oscillations were significantly disturbed in a day versus night manner in BMAL1-deficient monkeys, while in mice the beta band difference was less evident. Notably, the dysregulation of beta oscillations was particularly associated with psychiatric behaviors in BMAL1-deficient monkeys, including the occurrence of self-injuring and delusion-like actions. As such psychiatric phenotypes were challenging to uncover in rodent models, our results offered a unique method to study the correlation between circadian clock dysregulation and psychiatric disorders.

ALPL regulates pro-angiogenic capacity of mesenchymal stem cells through ATP-P2X7 axis controlled exosomes secretion

BACKGROUND

Early-onset bone dysplasia is a common manifestation of hypophosphatasia (HPP), an autosomal inherited disease caused by ALPL mutation. ALPL ablation induces prototypical premature bone ageing characteristics, resulting in impaired osteogenic differentiation capacity of human bone marrow mesenchymal stem cells (hBMMSCs). As angiogenesis is tightly coupled with osteogenesis, it also plays a necessary role in sustaining bone homeostasis. We have previously observed a decrease in expression of angiogenesis marker gene CD31 in the metaphysis of long bone in Alpl+/- mice. However, the role of ALPL in regulation of angiogenesis in bone has remained largely unknown.

METHODS

Exosomes derived from Normal and HPP hBMMSCs were isolated and identified by ultracentrifugation, transmission electron microscopy, and nanoparticle size measurement. The effects of ALPL on the angiogenic capacity of hBMMSCs from HPP patients were assessed by immunofluorescence, tube formation, wound healing and migration assay. exo-ELISA and Western Blot were used to evaluate the exosomes secretion of hBMMSCs from HPP, and the protein expression of VEGF, PDGFBB, Angiostatin and Endostatin in exosomes respectively.

RESULTS

We verified that ALPL ablation resulted in impaired pro-angiogenic capacity of hBMMSCs, accounting for reduced migration and tube formation of human umbilical vein endothelial cells, as the quantities and proteins composition of exosomes varied with ALPL expression. Mechanistically, loss of function of ALPL enhanced ATP release. Additional ATP, in turn, led to markedly elevated level of ATP receptor P2X7, which consequently promoted exosomes secretion, resulting in a decreased capacity to promote angiogenesis. Conversely, inhibition of P2X7 increased the angiogenic induction capacity by preventing excessive release of anti-angiogenic exosomes in ALPL deficient-hBMMSCs.

CONCLUSION

The ALPL-ATP axis regulates the pro-angiogenic ability of hBMMSCs by controlling exosomes secretion through the P2X7 receptor. Thus, P2X7 may be proved as an effective therapeutic target for accelerating neovascularization in ALPL-deficient bone defects.

The Positive Association between Melatonin-Containing Food Consumption and Older Adult Life Satisfaction, Psychoemotional State, and Cognitive Function

The purpose of this study was to test the hypothesis that melatonin-containing food (FMT) consumption is associated with a better sleep schedule and cognitive and psychoemotional state in older adults. A cross-sectional study of 557 (79% females) older adults living in the community with a mean age of 68.9 ± 7.7, ranging from 50 to 90 years, was conducted. The study, conducted in May and September 2023 using a face-to-face interview, collected personal data and assessed FMT intake during the day (FMTday) and for dinner (FMTdinner), life satisfaction, positive and negative affect, depression severity, cognitive functions, and sleep characteristics. Multiple regression and logistic regression analysis, adjusted for co-factors, were used to assess the association between the studied indicators. Multiple regression analysis showed that older adults with higher FMT consumption are more satisfied with life (FMTdinner: β = 0.107; ∆R2 = 0.011; p = 0.020), have a lower level of depression (FMTday: β = -0.124; ∆R2 = 0.015; p = 0.003), and higher scores in positive affect (FMTday: β = 0.169; ∆R2 = 0.016; p = 0.007; FMTdinner: β = 0.136; ∆R2 = 0.019; p = 0.003). Logistic regression analysis showed that older adults with higher FMT consumption are less likely to have depression (FMTday: OR, 0.614; 95% CI, 0.436-0.864; p = 0.005; FMTdinner: OR, 0.671; 95% CI, 0.476-0.945; p = 0.023), and they perform better on logical thinking tests (FMTday: OR, 2.066; 95% CI, 1.131-2.204; p = 0.013; FMTdinner: OR, 1.887; 95% CI, 1.183-2.138; p = 0.033). A greater life satisfaction as well as a decrease in the cognitive impairment and psychoemotional state of older adults is associated with a higher consumption of melatonin-containing foods.

Sleep deprivation in early life: Cellular and behavioral impacts

Sleep deprivation has become increasingly prevalent in contemporary society, and the consequences of this reality such as cognitive impairment and metabolic disorders, are widely investigated in the scientific scenario. However, the impact of sleep deprivation on the health of future generations is a challenge, and researchers are focusing their attention on this issue. Thus, this review aims to describe the impact of sleep deprivation in early life in animal models, particularly rodents, discussing the molecular physiology impacted by prolonged wakefulness in early life, as well as the changes that interfere with neurodevelopmental processes. Additionally, it explores the changes impacting metabolic mechanisms and discusses both the short- and long-term consequences of these processes on endocrine, behavioral, and cognitive functions. Finally, we briefly address some strategies to mitigate the adverse effects of sleep deprivation.

The monoaminergic pathways are involved in the antidepressant-like effect of quercetin

Quercetin, a plant-derived flavonoid, is an antioxidant and has demonstrated antidepressant and anti-inflammatory activities in several animal models. However, there is scanty information on the underlying mechanisms of its antidepressant property. This present study aimed at assessing the involvement of monoaminergic systems in the antidepressant-like activity of quercetin in experimental animals. Mice received varying doses of quercetin (25, 50 &100 mg/kg daily) and were then subjected to open field test (OPF), despair tests, the reserpine test, and the yohimbine lethality test (YLT). In addition, monoaminergic involvement was investigated by combining quercetin (100 mg/kg) with dopaminergic antagonists (haloperidol and sulpiride), adrenergic blockers (prazosin, propranolol and yohimbine), and serotonergic blockers/inhibitors (metergoline). The results showed that quercetin produced significant anti-immobility effects in the forced swim test (FST) and tail suspension test (TST), suggesting antidepressant activity. In addition, the potentiation of yohimbine lethality by quercetin further indicates its antidepressant-like property. This antidepressant action demonstrated was, however, blocked when quercetin was co-administered with dopaminergic, adrenergic and serotonergic antagonists, suggesting involvement of the monoaminergic system in the antidepressant action of quercetin. Nevertheless, quercetin did not significantly alter the locomotor activity of mice, which implies lack of stimulant effect. Taken together, these outcomes suggest that monoaminergic systems are likely involved in the anti-depressant effect of quercetin in mice.

Protective role of madecassoside from Centella asiatica against protein L-isoaspartyl methyltransferase deficiency-induced neurodegeneration

Protein L-isoaspartyl methyltransferase (PIMT/PCMT1) could repair l-isoaspartate (L-isoAsp) residues formed by deamidation of asparaginyl (Asn) residues or isomerization of aspartyl (Asp) residues in peptides and proteins during aging. Aside from abnormal accumulation of L-isoAsp, PIMT knockout (KO) mice mirrors some neuropathological hallmarks such as anxiety-like behaviors, impaired spatial memory and aberrant synaptic plasticity in the hippocampus of neurodegenerative diseases (NDs), including Alzheimer's disease (AD) and related dementias, and Parkinson's disease (PD). While some reports indicate the neuroprotective effect of madecassoside (MA) as a triterpenoid saponin component of Centella asiatica, its role against NDs-related anxiety and cognitive impairment remains unclear. Therefore, we investigated the effect of MA against anxiety-related behaviors in PIMT deficiency-induced mouse model of NDs. Results obtained from the elevated plus maze (EPM) test revealed that MA treatment alleviated anxiety-like behaviors in PIMT knockout mice. Furthermore, Real-time PCR, electroencephalogram (EEG) recordings, transmission electron microscopy analysis and ELISA were carried out to evaluate the expression of clock genes, sleep and synaptic function, respectively. The PIMT knockout mice were characterized by abnormal clock patterns, sleep disturbance and synaptic dysfunction, which could be improved by MA administration. Collectively, these findings suggest that MA exhibits neuroprotective effects associated with improved circadian rhythms sleep-wake cycle and synaptic plasticity in PIMT deficient mice, which could be translated to ameliorate anxiety-related symptoms and cognitive impairments in NDs.

Relationship of Sleep Disorder with Neurodegenerative and Psychiatric Diseases: An Updated Review

Sleep disorders affect many people worldwide and can accompany neurodegenerative and psychiatric diseases. Sleep may be altered before the clinical manifestations of some of these diseases appear. Moreover, some sleep disorders affect the physiological organization and function of the brain by influencing gene expression, accelerating the accumulation of abnormal proteins, interfering with the clearance of abnormal proteins, or altering the levels of related hormones and neurotransmitters, which can cause or may be associated with the development of neurodegenerative and psychiatric diseases. However, the detailed mechanisms of these effects are unclear. This review mainly focuses on the relationship between and mechanisms of action of sleep in Alzheimer's disease, depression, and anxiety, as well as the relationships between sleep and Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis. This summary of current research hotspots may provide researchers with better clues and ideas to develop treatment solutions for neurodegenerative and psychiatric diseases associated with sleep disorders.

Developmental alcohol exposure is exhausting: Sleep and the enduring consequences of alcohol exposure during development

Prenatal alcohol exposure is the leading nongenetic cause of human intellectual impairment. The long-term impacts of prenatal alcohol exposure on health and well-being are diverse, including neuropathology leading to behavioral, cognitive, and emotional impairments. Additionally negative effects also occur on the physiological level, such as the endocrine, cardiovascular, and immune systems. Among these diverse impacts is sleep disruption. In this review, we describe how prenatal alcohol exposure affects sleep, and potential mechanisms of those effects. Furthermore, we outline the evidence that sleep disruption across the lifespan may be a mediator of some cognitive and behavioral impacts of developmental alcohol exposure, and thus may represent a promising target for treatment.

Sleep and circadian rhythm disruptions in behavioral variant frontotemporal dementia

INTRODUCTION

Sleep and rest-activity rhythm alterations are common in neurodegenerative diseases. However, their characterization in patients with behavioral variant frontotemporal dementia (bvFTD) has proven elusive. We investigated rest-activity rhythm alterations, sleep disturbances, and their neural correlates in bvFTD.

METHODS

Twenty-seven bvFTD patients and 25 healthy controls completed sleep questionnaires and underwent 7 days of actigraphy while concurrently maintaining a sleep diary. Cortical complexity and thickness were calculated from T1-weighted magnetic resonance (MR) images.

RESULTS

Compared to controls, bvFTD patients showed longer time in bed (95% confidence interval [CI]: 79.31, 321.83) and total sleep time (95% CI: 24.38, 321.88), lower sleep efficiency (95% CI: -12.58, -95.54), and rest-activity rhythm alterations in the morning and early afternoon. Increased sleep duration was associated with reduced cortical thickness in frontal regions.

DISCUSSION

Patients with bvFTD showed longer sleep duration, lower sleep quality, and rest-activity rhythm alterations. Actigraphy could serve as a cost-effective and accessible tool for ecologically monitoring changes in sleep duration in bvFTD patients.

HIGHLIGHTS

We assessed sleep and circadian rhythms in behavioral variant frontotemporal dementia (bvFTD) using actigraphy. Patients with bvFTD show increased sleep duration and reduced sleep quality. Patients with bvFTD show rest-activity alterations in the morning and early afternoon. Sleep duration is associated with reduced cortical thickness in frontal regions. These alterations may represent an early sign of neurodegeneration.

Daily light exposure profiles and the association with objective sleep quality in patients with Parkinson's disease: The PHASE study

STUDY OBJECTIVES

Light information crucially influences the sleep initiation and continuity. The purpose of this study was to compare daily light exposure between patients with Parkinson's disease (PD) and non-PD older adults and evaluate the association of daily light exposure with objective sleep measures in patients with PD.

METHODS

In this cross-sectional study of 189 outpatients with PD and 1101 community dwelling older adults (controls), daily light exposure was measured using wrist light meters during the daytime and light meters set in the bedrooms during the nighttime, and objective sleep quality was measured by wrist actigraphy.

RESULTS

The median duration of exposure to ≥1000 lux light was significantly shorter in patients with PD than in controls. The median nighttime light intensity was higher in patients with PD than in controls. Among patients with PD, multivariable analysis suggested that the highest quartile of exposure to ≥1000 lux light during the daytime was linked to significantly higher sleep efficiency by 8.0% and shorter wake after sleep onset (WASO) by 36.9 min than the lowest quartile. During the nighttime, the highest quartile of mean light intensity had significantly lower sleep efficiency by 6.8%, longer WASO by 24.1 min, longer sleep onset latency, and higher fragmentation index, than the lowest quartile. Importantly, daytime and nighttime light levels were independently associated with objective sleep measures.

CONCLUSION

The present study illustrated that greater daytime light exposure and lower nighttime light exposure are significantly associated with better objective sleep measures in patients with PD.

Mediterranean Diet and Sleep Features: A Systematic Review of Current Evidence

The prevalence of sleep disorders, characterized by issues with quality, timing, and sleep duration is increasing globally. Among modifiable risk factors, diet quality has been suggested to influence sleep features. The Mediterranean diet is considered a landmark dietary pattern in terms of quality and effects on human health. However, dietary habits characterized by this cultural heritage should also be considered in the context of overall lifestyle behaviors, including sleep habits. This study aimed to systematically revise the literature relating to adherence to the Mediterranean diet and sleep features in observational studies. The systematic review comprised 23 reports describing the relation between adherence to the Mediterranean diet and different sleep features, including sleep quality, sleep duration, daytime sleepiness, and insomnia symptoms. The majority of the included studies were conducted in the Mediterranean basin and reported a significant association between a higher adherence to the Mediterranean diet and a lower likelihood of having poor sleep quality, inadequate sleep duration, excessive daytime sleepiness or symptoms of insomnia. Interestingly, additional studies conducted outside the Mediterranean basin showed a relationship between the adoption of a Mediterranean-type diet and sleep quality, suggesting that biological mechanisms sustaining such an association may exist. In conclusion, current evidence suggests a relationship between adhering to the Mediterranean diet and overall sleep quality and different sleep parameters. The plausible bidirectional association should be further investigated to understand whether the promotion of a healthy diet could be used as a tool to improve sleep quality.

Overtime work is related to nonrestorative sleep independently of short sleep time among a Japanese occupational population

OBJECTIVE

The symptoms of insomnia are defined as difficulty falling asleep, difficulty staying asleep, and early awakening. Although also a symptom of insomnia, nonrestorative sleep (NRS) is clearly more associated with objective indices than other insomnia symptoms. However, the link between NRS and overtime work duration is poorly understood.

METHODS

The results of a single year's medical examinations were investigated for 26,144 Japanese office workers who were 30 to 59 years old. NRS status and lifestyle were collected through a computer-assisted medical interview. The subjects were asked about the presence or absence of NRS and their lifestyles in the most recent two to three months. The subjects were asked about their sleep times and average overtime durations per month (< 20 h/month, ≥ 20 but < 40 h/month, ≥ 40 but < 60 h/month, and ≥ 60 h/month). The relationships between NRS and overtime work duration adjusted for sleep time were also analyzed.

RESULTS

The proportion of subjects with NRS showed a stepwise increase as overtime work hours increased. A logistic regression analysis was performed using NRS as an objective variable. The multivariate analysis demonstrated that overtime work duration (OR, 1.13; 95% CI 1.10-1.17; P < 0.001; per one-category increase) was an independent determinant of NRS.

CONCLUSION

For office workers, long hours of overtime work increased the NRS prevalence at any sleep duration.

Multi-Modal Sleep Stage Classification With Two-Stream Encoder-Decoder

Sleep staging serves as a fundamental assessment for sleep quality measurement and sleep disorder diagnosis. Although current deep learning approaches have successfully integrated multimodal sleep signals, enhancing the accuracy of automatic sleep staging, certain challenges remain, as follows: 1) optimizing the utilization of multi-modal information complementarity, 2) effectively extracting both long- and short-range temporal features of sleep information, and 3) addressing the class imbalance problem in sleep data. To address these challenges, this paper proposes a two-stream encode-decoder network, named TSEDSleepNet, which is inspired by the depth sensitive attention and automatic multi-modal fusion (DSA2F) framework. In TSEDSleepNet, a two-stream encoder is used to extract the multiscale features of electrooculogram (EOG) and electroencephalogram (EEG) signals. And a self-attention mechanism is utilized to fuse the multiscale features, generating multi-modal saliency features. Subsequently, the coarser-scale construction module (CSCM) is adopted to extract and construct multi-resolution features from the multiscale features and the salient features. Thereafter, a Transformer module is applied to capture both long- and short-range temporal features from the multi-resolution features. Finally, the long- and short-range temporal features are restored with low-layer details and mapped to the predicted classification results. Additionally, the Lovász loss function is applied to alleviate the class imbalance problem in sleep datasets. Our proposed method was tested on the Sleep-EDF-39 and Sleep-EDF-153 datasets, and it achieved classification accuracies of 88.9% and 85.2% and Macro-F1 scores of 84.8% and 79.7%, respectively, thus outperforming conventional traditional baseline models. These results highlight the efficacy of the proposed method in fusing multi-modal information. This method has potential for application as an adjunct tool for diagnosing sleep disorders.

The Effect of Tele-Savvy on Sleep Quality and Insomnia in Caregivers of Persons Living with Dementia

Introduction

Sleep disturbance is prevalent in caregivers of persons living with dementia (PLwD). Tele-Savvy, a 7-week virtual psychoeducational intervention, enhances caregivers' competence and self-care, and reduces depression. While not explicitly designed to do so, Tele-Savvy can potentially improve caregivers' disturbed sleep. The present study aimed to examine the longitudinal effects of Tele-Savvy on caregivers' sleep quality and insomnia.

Methods

This was a secondary data analysis of a 3-arm randomized control trial [Tele-Savvy (active treatment), Healthy Living (attention control), and usual care (waitlist control)]. Multilevel mixed modeling with intent-to-treat principles tested for group, time, and group-by-time effects. Effect sizes were estimated for all changes from baseline to the initial 6-month post-intervention point. Following completion of the 6-month post-randomization delay, we examined combined outcomes for Tele-Savvy.

Results

Participants (n=137; mean age 64.7 years) were predominantly female (68.6%) and White (68.6%). We found no initial group-by-time effects for the Pittsburgh Sleep Quality Index (PSQI) and the Insomnia Severity Index (ISI). For the combined Tele-Savvy group, there was a statistically significant improvement in ISI scores across time (p=0.050). The combined Tele-Savvy effect size for PSQI was d=0.126 and ISI was d=0.310.

Discussion

Tele-Savvy resulted in a significant long-term reduction in insomnia symptoms in this sample of caregivers of PLwD and demonstrated a positive trend for improvement in their sleep quality. Since sleep disturbance is so prevalent among caregivers of PLwD, the inclusion of sleep health education into psychoeducation caregiver interventions may yield even better outcomes for caregivers.

Comparison of Polysomnography, Single-Channel Electroencephalogram, Fitbit, and Sleep Logs in Patients With Psychiatric Disorders: Cross-Sectional Study

BACKGROUND

Sleep disturbances are core symptoms of psychiatric disorders. Although various sleep measures have been developed to assess sleep patterns and quality of sleep, the concordance of these measures in patients with psychiatric disorders remains relatively elusive.

OBJECTIVE

This study aims to examine the degree of agreement among 3 sleep recording methods and the consistency between subjective and objective sleep measures, with a specific focus on recently developed devices in a population of individuals with psychiatric disorders.

METHODS

We analyzed 62 participants for this cross-sectional study, all having data for polysomnography (PSG), Zmachine, Fitbit, and sleep logs. Participants completed questionnaires on their symptoms and estimated sleep duration the morning after the overnight sleep assessment. The interclass correlation coefficients (ICCs) were calculated to evaluate the consistency between sleep parameters obtained from each instrument. Additionally, Bland-Altman plots were used to visually show differences and limits of agreement for sleep parameters measured by PSG, Zmachine, Fitbit, and sleep logs.

RESULTS

The findings indicated a moderate agreement between PSG and Zmachine data for total sleep time (ICC=0.46; P<.001), wake after sleep onset (ICC=0.39; P=.002), and sleep efficiency (ICC=0.40; P=.006). In contrast, Fitbit demonstrated notable disagreement with PSG (total sleep time: ICC=0.08; wake after sleep onset: ICC=0.18; sleep efficiency: ICC=0.10) and exhibited particularly large discrepancies from the sleep logs (total sleep time: ICC=-0.01; wake after sleep onset: ICC=0.05; sleep efficiency: ICC=-0.02). Furthermore, subjective and objective concordance among PSG, Zmachine, and sleep logs appeared to be influenced by the severity of the depressive symptoms and obstructive sleep apnea, while these associations were not observed between the Fitbit and other sleep instruments.

CONCLUSIONS

Our study results suggest that Fitbit accuracy is reduced in the presence of comorbid clinical symptoms. Although user-friendly, Fitbit has limitations that should be considered when assessing sleep in patients with psychiatric disorders.

Oral nano-antioxidants improve sleep by restoring intestinal barrier integrity and preventing systemic inflammation

Sleep deprivation (SD) is a severe public health threat that can cause systemic inflammation and nerve damage. Few effective and side-effect-free drugs are available to address SD. However, the bidirectional communications between the brain and gut provide new strategies for anti-SD therapeutics. Here we explored oral delivery of fullerene nano-antioxidants (FNAO) in the SD model to improve sleep by regulating abnormal intestinal barrier and systemic inflammation via the brain-gut axis. SD caused excessive reactive oxygen species (ROS) production and hyperactive inflammatory responses in the intestines of zebrafish and mouse models, leading to disturbed sleep patterns and reduced brain nerve activity. Of note, based on the property of the conjugated π bond of the C60 structure to absorb unpaired electrons, oral FNAO efficiently reduced the excessive ROS in the intestines, maintained redox homeostasis and intestinal barrier integrity, and ameliorated intestinal and systemic inflammation, resulting in superior sleep improvement. Our findings suggest that maintaining intestinal homeostasis may be a promising avenue for SD-related nerve injury therapy.

Contributions of residential traffic noise to depression and mental wellbeing in Hong Kong: A prospective cohort study

Prior studies on the association between traffic noise and mental health have been mostly conducted in settings with lower population densities. However, evidence is lacking in high population-density settings where traffic noise is more pervasive and varies by topography and the vertical elevation of the residential unit. This study aimed to assess the mental health impact of residential traffic noise in one of the world's most urbanised populations. Data were analysed from 13,401 participants aged ≥15 years in a prospective cohort in Hong Kong from 2009 to 2014. Residential traffic noise level was estimated using 3D-geocoding and validated models that accounted for sound propagation in a highly vertical landscape. The 24-h day-night exposure to traffic noise, denoted as Ldn, was estimated with a 10-dB(A) penalty for night hours. Probable depression and mental wellbeing were assessed using the Patient Health Questionnaire-9 and the Short Form Health Questionnaire SF-12v2, respectively. Mixed effect regressions with random intercepts were used to examine the association between traffic noise and mental health outcomes. Residential road traffic noise (for each increment of 10 A-weighted decibels [dB(A)] 24-h average exposure) was associated with probable depression (odds ratio (OR) = 1.17, 95% CI: 1.05, 1.31), and poorer mental wellbeing (mean difference = -0.19, 95% CI: 0.31, -0.06), adjusting for sociodemographics, smoking, body mass index, self-reported health, proximity to green space, and neighbourhood characteristics (average household income, population density, and Gini coefficient). The results were robust to further adjustment for air pollution. In stratified analyses, residential traffic noise was associated with probable depression and poorer mental wellbeing among students and individuals aged 15-34 years. Residential traffic noise was associated with probable depression and poorer mental wellbeing in a highly urbanised setting. As traffic noise is increasing in urban settings, the public health impact of noise pollution could be substantial.

Mapping the associations of daily pain, sleep, and psychological distress in a U.S. sample

Chronic pain, sleep problems, and psychological distress (PD) can be disabling conditions and previous research has shown that they are associated. The nuances of the comorbid nature of these conditions may be important to understand for those who treat these conditions. This study examined the bidirectional associations of these health factors concurrently and over time in a sample of U.S. adults (N = 1,008, Mage = 57.68) from the Midlife in the United States (MIDUS) study. Participants reported on their daily pain, sleep quantity, and psychological distress over eight days. A modified Random Intercept Cross-lagged Panel Model was used to analyze the relations, starting with the whole sample and then a comparison of those with and without chronic pain. Results indicated that nightly variation in sleep quantity predicted next day psychological distress for both groups. Sleep quantity also predicted next-day pain, but only for individuals with chronic pain. Associations between pain and psychological distress were found both at the daily level and individual (between-person) level. This between-person association was stronger for those with chronic pain. The lagged associations between sleep, and both pain and psychological distress for the chronic pain group indicate that, increased quantity of sleep predicts decreased next-day pain and psychological distress. Providers could consider this unidirectional lagged relationship when prioritizing treatment for patients with these comorbid conditions. Future research may examine whether responsive, just-in-time treatments might intervene after participants wake from a poor night's sleep to counteract the negative effects of reduced sleep on PD and pain.

Daily rhythm in cortical chloride homeostasis underpins functional changes in visual cortex excitability

Cortical activity patterns are strongly modulated by fast synaptic inhibition mediated through ionotropic, chloride-conducting receptors. Consequently, chloride homeostasis is ideally placed to regulate activity. We therefore investigated the stability of baseline [Cl-]i in adult mouse neocortex, using in vivo two-photon imaging. We found a two-fold increase in baseline [Cl-]i in layer 2/3 pyramidal neurons, from day to night, with marked effects upon both physiological cortical processing and seizure susceptibility. Importantly, the night-time activity can be converted to the day-time pattern by local inhibition of NKCC1, while inhibition of KCC2 converts day-time [Cl-]i towards night-time levels. Changes in the surface expression and phosphorylation of the cation-chloride cotransporters, NKCC1 and KCC2, matched these pharmacological effects. When we extended the dark period by 4 h, mice remained active, but [Cl-]i was modulated as for animals in normal light cycles. Our data thus demonstrate a daily [Cl-]i modulation with complex effects on cortical excitability.

Circadian Rhythm Changes in Healthy Aging and Mild Cognitive Impairment

Disruptions in circadian rhythms can occur in healthy aging; however, these changes are more severe and pervasive in individuals with age-related and neurodegenerative diseases, such as dementia. Circadian rhythm alterations are also present in preclinical stages of dementia, for example, in patients with mild cognitive impairments (MCI); thus, providing a unique window of opportunity for early intervention in neurodegenerative disorders. Nonetheless, there is a lack of studies examining the association between relevant changes in circadian rhythms and their relationship with cognitive dysfunctions in MCI individuals. In this review, circadian system alterations occurring in MCI patients are examined compared to healthy aging individuals while also considering their association with MCI neurocognitive alterations. The main findings are that abnormal circadian changes in rest-activity, core body temperature, melatonin, and cortisol rhythms appear in the MCI stage and that these circadian rhythm disruptions are associated with some of the neurocognitive deficits observed in MCI patients. In addition, preliminary evidence indicates that interventions aimed at restoring regular circadian rhythms may prevent or halt the progress of neurodegenerative diseases and mitigate their related cognitive impairments. Future longitudinal studies with repeated follow-up assessments are needed to establish the translational potential of these findings in clinical practice.

Social jetlag and trajectories of mood symptoms and reward responsiveness in individuals at low-risk, high-risk, and with bipolar spectrum disorders: An ecological momentary assessment study

A specific type of sleep disruption, social jetlag, involves an incongruence of sleep time between weekends and weekdays. This study investigated relationships between social jetlag and mood symptom lability and trajectories of daily reward responsiveness and mood symptoms. Participants (N = 130) from three groups (moderate reward sensitivity, high reward sensitivity, and high reward sensitivity with a diagnosed bipolar spectrum disorder [BSD]) were recruited from an ongoing longitudinal study based on their self-reported reward sensitivity and a diagnostic interview. For this study, they completed 20 days of ecological momentary assessment (EMA) of reward responsiveness and mood symptoms and a daily sleep diary. Social jetlag was significantly associated with differences in trajectories of depressive symptoms between groups. Specifically, greater social jetlag was associated with a greater increase in depressive symptoms over the 20 days for participants in the high reward sensitivity and BSD groups compared to the moderate reward sensitivity group. Social jetlag also was significantly associated with depressive symptom lability during the EMA period, but this finding was reduced to a trend toward significance when controlling for self-reported sleep duration. The study adds to the literature with methodological strengths including the EMA design and assessment of symptom and reward responsiveness trajectories.

Causal associations between sleep traits and brain structure: a bidirectional Mendelian randomization study

BACKGROUND

Emerging evidence suggests bidirectional causal relationships between sleep disturbance and psychiatric disorders, but the underlying mechanisms remain unclear. Understanding the bidirectional causality between sleep traits and brain imaging-derived phenotypes (IDPs) will help elucidate the mechanisms. Although previous studies have identified a range of structural differences in the brains of individuals with sleep disorders, it is still uncertain whether grey matter (GM) volume alterations precede or rather follow from the development of sleep disorders.

RESULTS

After Bonferroni correction, the forward MR analysis showed that insomnia complaint remained positively associated with the surface area (SA) of medial orbitofrontal cortex (β, 0.26; 95% CI, 0.15-0.37; P = 5.27 × 10-6). In the inverse MR analysis, higher global cortical SA predisposed individuals less prone to suffering insomnia complaint (OR, 0.89; 95%CI, 0.85-0.94; P = 1.51 × 10-5) and short sleep (≤ 6 h; OR, 0.98; 95%CI, 0.97-0.99; P = 1.51 × 10-5), while higher SA in posterior cingulate cortex resulted in a vulnerability to shorter sleep durations (β, - 0.09; 95%CI, - 0.13 to - 0.05; P = 1.21 × 10-5).

CONCLUSIONS

Sleep habits not only result from but also contribute to alterations in brain structure, which may shed light on the possible mechanisms linking sleep behaviours with neuropsychiatric disorders, and offer new strategies for prevention and intervention in psychiatric disorders and sleep disturbance.

A Review of Recurrent Neural Network-Based Methods in Computational Physiology

Artificial intelligence and machine learning techniques have progressed dramatically and become powerful tools required to solve complicated tasks, such as computer vision, speech recognition, and natural language processing. Since these techniques have provided promising and evident results in these fields, they emerged as valuable methods for applications in human physiology and healthcare. General physiological recordings are time-related expressions of bodily processes associated with health or morbidity. Sequence classification, anomaly detection, decision making, and future status prediction drive the learning algorithms to focus on the temporal pattern and model the nonstationary dynamics of the human body. These practical requirements give birth to the use of recurrent neural networks (RNNs), which offer a tractable solution in dealing with physiological time series and provide a way to understand complex time variations and dependencies. The primary objective of this article is to provide an overview of current applications of RNNs in the area of human physiology for automated prediction and diagnosis within different fields. Finally, we highlight some pathways of future RNN developments for human physiology.

Automatic sleep staging by a hybrid model based on deep 1D-ResNet-SE and LSTM with single-channel raw EEG signals

Sleep staging is crucial for assessing sleep quality and diagnosing sleep disorders. Recent advances in deep learning methods with electroencephalogram (EEG) signals have shown remarkable success in automatic sleep staging. However, the use of deeper neural networks may lead to the issues of gradient disappearance and explosion, while the non-stationary nature and low signal-to-noise ratio of EEG signals can negatively impact feature representation. To overcome these challenges, we proposed a novel lightweight sequence-to-sequence deep learning model, 1D-ResNet-SE-LSTM, to classify sleep stages into five classes using single-channel raw EEG signals. Our proposed model consists of two main components: a one-dimensional residual convolutional neural network with a squeeze-and-excitation module to extract and reweight features from EEG signals, and a long short-term memory network to capture the transition rules among sleep stages. In addition, we applied the weighted cross-entropy loss function to alleviate the class imbalance problem. We evaluated the performance of our model on two publicly available datasets; Sleep-EDF Expanded consists of 153 overnight PSG recordings collected from 78 healthy subjects and ISRUC-Sleep includes 100 PSG recordings collected from 100 subjects diagnosed with various sleep disorders, and obtained an overall accuracy rate of 86.39% and 81.97%, respectively, along with corresponding macro average F1-scores of 81.95% and 79.94%. Our model outperforms existing sleep staging models in terms of overall performance metrics and per-class F1-scores for several sleep stages, particularly for the N1 stage, where it achieves F1-scores of 59.00% and 55.53%. The kappa coefficient is 0.812 and 0.766 for the Sleep-EDF Expanded and ISRUC-Sleep datasets, respectively, indicating strong agreement with certified sleep experts. We also investigated the effect of different weight coefficient combinations and sequence lengths of EEG epochs used as input to the model on its performance. Furthermore, the ablation study was conducted to evaluate the contribution of each component to the model's performance. The results demonstrate the effectiveness and robustness of the proposed model in classifying sleep stages, and highlights its potential to reduce human clinicians' workload, making sleep assessment and diagnosis more effective. However, the proposed model is subject to several limitations. Firstly, the model is a sequence-to-sequence network, which requires input sequences of EEG epochs. Secondly, the weight coefficients in the loss function could be further optimized to balance the classification performance of each sleep stage. Finally, apart from the channel attention mechanism, incorporating more advanced attention mechanisms could enhance the model's effectiveness.

Links between Sleep Apnoea and Insomnia in a British Cohort

Poor sleep is a major public health problem with implications for a wide range of critical health outcomes. Insomnia and sleep apnoea are the two most common causes of poor sleep, and recent studies have shown that these disorders frequently co-occur. Comorbid insomnia and sleep apnoea can substantially impair quality of life and increase the overall risk of mortality. However, the causal and physiological links between sleep apnoea and insomnia are unclear. It is also unknown whether having a higher risk for one condition can increase the risk of developing the other. Here, we investigated links between sleep apnoea and insomnia in a British population using a combination of self-reported questionnaires and causal inference. We found that 54.3% of the cohort had moderate insomnia, 9.4% had moderate sleep apnoea, and that 6.2% scored high for both conditions. Importantly, having a higher risk of sleep apnoea was associated with a higher risk of insomnia and vice versa. To determine the causal directionality between sleep apnoea and insomnia, we used Mendelian randomisation and found evidence that sleep apnoea could cause insomnia, but not the reverse. To elucidate how both sleep apnoea and insomnia were linked to each other, we looked at the behavioural markers of poor sleep. We found that feeling fatigued after sleeping and having noticeable sleep problems were linked to a higher burden of both sleep apnoea and insomnia. In conclusion, our results show that sleep apnoea increases the risk of developing insomnia, and both conditions can result in fatigue. We highlight the importance of considering and treating the symptoms of both conditions.

Sleep behavior traits and associations with opioid-related adverse events: a cohort study

STUDY OBJECTIVES

Opioid-related adverse events (OAEs), including opioid use disorders, overdose, and death, are serious public health concerns. OAEs are often associated with disrupted sleep, but the long-term relationship between poor sleep and subsequent OAE risk remains unknown. This study investigates whether sleep behavior traits are associated with incident OAEs in a large population cohort.

METHODS

444 039 participants (mean age ± SD 57 ± 8 years) from the UK Biobank reported their sleep behavior traits (sleep duration, daytime sleepiness, insomnia-like complaints, napping, and chronotype) between 2006 and 2010. The frequency/severity of these traits determined a poor sleep behavior impacts score (0-9). Incident OAEs were obtained from hospitalization records during 12-year median follow-up. Cox proportional hazards models examined the association between sleep and OAEs.

RESULTS

Short and long sleep duration, frequent daytime sleepiness, insomnia symptoms, and napping, but not chronotype, were associated with increased OAE risk in fully adjusted models. Compared to the minimal poor sleep behavior impacts group (scores of 0-1), the moderate (4-5) and significant (6-9) groups had hazard ratios of 1.47 (95% confidence interval [1.27, 1.71]), p < 0.001, and 2.19 ([1.82, 2.64], p < 0.001), respectively. The latter risk magnitude is greater than the risk associated with preexisting psychiatric illness or sedative-hypnotic medication use. In participants with moderate/significant poor sleep impacts (vs. minimal), subgroup analysis revealed that age <65 years was associated with a higher OAE risk than in those ≥65 years.

CONCLUSIONS

Certain sleep behavior traits and overall poor sleep impacts are associated with an increased risk for opioid-related adverse events.

The association between shift work exposure and cognitive impairment among middle-aged and older adults: Results from the Canadian Longitudinal Study on Aging (CLSA)

BACKGROUND

Shift work, especially rotating and night shift work, has been linked to a wide range of detrimental health outcomes. Occupational factors like shift work and their potential impact on cognitive functions have received little attention, and the evidence is inconclusive. The objective of our study is to explore associations between shift work exposure and cognitive impairment indicators based on comparisons with the normative standards from the Canadian population.

METHODS

Cross-sectional analyses were performed using baseline Canadian Longitudinal Study on Aging database, including 47,811 middle-aged and older adults (45-85 years). Three derived shift work variables were utilized: ever exposed to shift work, shift work exposure in longest job, and shift work exposure in current job. Four cognitive function tests were utilized, Rey Auditory Verbal Learning Tests (immediate and delayed) representing memory domain, and Animal Fluency, and Mental Alteration, representing the executive function domain. All cognitive test scores included in study were normalized and adjusted for the participant's age, sex, education and language of test administration (English and French), which were then compared to normative data to create "cognitive impairment' variables. Unadjusted and adjusted multivariable logistic regression models were used to determine associations between shift work variables and cognitive impairment individually (memory and executive function domains), and also for overall cognitive impairment.

RESULT

Overall, one in every five individuals (21%) reported having been exposed to some kind of shift work during their jobs. Exposure to night shift work (both current and longest job) was associated with overall cognitive impairment. In terms of domain-based measures, night shift work (longest job) was associated with memory function impairment, and those exposed to rotating shift work (both current and longest job) showed impairment on executive function measures, when compared to daytime workers.

CONCLUSION

This study suggests disruption to the circadian rhythm, due to shift work has negative impact on cognitive function in middle-aged and older adults and this warrants further investigation.

Ventral pallidal glutamatergic neurons regulate wakefulness and emotion through separated projections

Insomnia is often comorbid with depression, but the underlying neuronal circuit mechanism remains elusive. Recently, we reported that GABAergic ventral pallidum (VP) neurons control wakefulness associated with motivation. However, whether and how other subtypes of VP neurons regulate arousal and emotion are largely unknown. Here, we report glutamatergic VP (VPVglut2) neurons control wakefulness and depressive-like behaviors. Physiologically, the calcium activity of VPVglut2 neurons was increased during both NREM sleep-to-wake transitions and depressive/anxiety-like behaviors in mice. Functionally, activation of VPVglut2 neurons was sufficient to increase wakefulness and induce anxiety/depressive-like behaviors, whereas inhibition attenuated both. Dissection of the circuit revealed that separated projections of VPVglut2 neurons to the lateral hypothalamus and lateral habenula promote arousal and depressive-like behaviors, respectively. Our results demonstrate a subtype of VP neurons is responsible for wakefulness and emotion through separated projections, and may provide new lines for the intervention of insomnia and depression in patients.

Disruption in the regulation of casein kinase 2 in circadian rhythm leads to pathological states: cancer, diabetes and neurodegenerative disorders

Introduction

Circadian rhythm maintains the sleep-wake cycle in biological systems. Various biological activities are regulated and modulated by the circadian rhythm, disruption of which can result in onset of diseases. Robust rhythms of phosphorylation profiles and abundances of PERIOD (PER) proteins are thought to be the master keys that drive circadian clock functions. The role of casein kinase 2 (CK2) in circadian rhythm via its direct interactions with the PER protein has been extensively studied; however, the exact mechanism by which it affects circadian rhythms at the molecular level is not known.

Methods

Here, we propose an extended circadian rhythm model in Drosophila that incorporates the crosstalk between the PER protein and CK2. We studied the regulatory role of CK2 in the dynamics of PER proteins involved in circadian rhythm using the stochastic simulation algorithm.

Results

We observed that variations in the concentration of CK2 in the circadian rhythm model modulates the PER protein dynamics at different cellular states, namely, active, weakly active, and rhythmic death. These oscillatory states may correspond to distinct pathological cellular states of the living system. We find molecular noise at the expression level of CK2 to switch normal circadian rhythm to any of the three above-mentioned circadian oscillatory states. Our results suggest that the concentration levels of CK2 in the system has a strong impact on its dynamics, which is reflected in the time evolution of PER protein.

Discussion

We believe that our findings can contribute towards understanding the molecular mechanisms of circadian dysregulation in pathways driven by the PER mutant genes and their pathological states, including cancer, obesity, diabetes, neurodegenerative disorders, and socio-psychological disease.

Are sleep disturbances a cause or consequence of autism spectrum disorder?

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by core symptoms such as atypical social communication, stereotyped behaviors, and restricted interests. One of the comorbid symptoms of individuals with ASD is sleep disturbance. There are two major hypotheses regarding the neural mechanism underlying ASD, i.e., the excitation/inhibition (E/I) imbalance and the altered neuroplasticity hypotheses. However, the pathology of ASD remains unclear due to inconsistent research results. This paper argues that sleep is a confounding factor, thus, must be considered when examining the pathology of ASD because sleep plays an important role in modulating the E/I balance and neuroplasticity in the human brain. Investigation of the E/I balance and neuroplasticity during sleep might enhance our understanding of the neural mechanisms of ASD. It may also lead to the development of neurobiologically informed interventions to supplement existing psychosocial therapies.

FABP7: a glial integrator of sleep, circadian rhythms, plasticity, and metabolic function

Sleep and circadian rhythms are observed broadly throughout animal phyla and influence neural plasticity and cognitive function. However, the few phylogenetically conserved cellular and molecular pathways that are implicated in these processes are largely focused on neuronal cells. Research on these topics has traditionally segregated sleep homeostatic behavior from circadian rest-activity rhythms. Here we posit an alternative perspective, whereby mechanisms underlying the integration of sleep and circadian rhythms that affect behavioral state, plasticity, and cognition reside within glial cells. The brain-type fatty acid binding protein, FABP7, is part of a larger family of lipid chaperone proteins that regulate the subcellular trafficking of fatty acids for a wide range of cellular functions, including gene expression, growth, survival, inflammation, and metabolism. FABP7 is enriched in glial cells of the central nervous system and has been shown to be a clock-controlled gene implicated in sleep/wake regulation and cognitive processing. FABP7 is known to affect gene transcription, cellular outgrowth, and its subcellular localization in the fine perisynaptic astrocytic processes (PAPs) varies based on time-of-day. Future studies determining the effects of FABP7 on behavioral state- and circadian-dependent plasticity and cognitive processes, in addition to functional consequences on cellular and molecular mechanisms related to neural-glial interactions, lipid storage, and blood brain barrier integrity will be important for our knowledge of basic sleep function. Given the comorbidity of sleep disturbance with neurological disorders, these studies will also be important for our understanding of the etiology and pathophysiology of how these diseases affect or are affected by sleep.

PSNSleep: a self-supervised learning method for sleep staging based on Siamese networks with only positive sample pairs

Traditional supervised learning methods require large quantities of labeled data. However, labeling sleep data according to polysomnography by well-trained sleep experts is a very tedious job. In the present day, the development of self-supervised learning methods is making significant progress in many fields. It is also possible to apply some of these methods to sleep staging. This is to remove the dependency on labeled data at the stage of representation extraction. Nevertheless, they often rely too much on negative samples for sample selection and construction. Therefore, we propose PSNSleep, a novel self-supervised learning method for sleep staging based on Siamese networks. The crucial step to the success of our method is to select appropriate data augmentations (the time shift block) to construct the positive sample pair. PSNSleep achieves satisfactory results without relying on any negative samples. We evaluate PSNSleep on Sleep-EDF and ISRUC-Sleep and achieve accuracy of 80.0% and 74.4%. The source code is publicly available at https://github.com/arthurxl/PSNSleep.

Dynamic modelling of chronotype and hypo/manic and depressive symptoms in young people with emerging mental disorders

There is significant interest in the possible influence of chronotype on clinical states in young people with emerging mental disorders. We apply a dynamic approach (bivariate latent change score modelling) to examine the possible prospective influence of chronotype on depressive and hypo/manic symptoms in a youth cohort with predominantly depressive, bipolar, and psychotic disorders (N = 118; 14-30-years), who completed a baseline and follow-up assessment of these constructs (mean interval = 1.8-years). Our primary hypotheses were that greater baseline eveningness would predict increases in depressive but not hypo/manic symptoms. We found moderate to strong autoregressive effects for chronotype (β = -0.447 to -0.448, p < 0.001), depressive (β = -0.650, p < 0.001) and hypo/manic symptoms (β = -0.819, p < 0.001). Against our predictions, baseline chronotypes did not predict change in depressive (β = -0.016, p = 0.810) or hypo/manic symptoms (β = 0.077, p = 0.104). Similarly, the change in chronotype did not correlate with the change in depressive symptoms (β = -0.096, p = 0.295) nor did the change in chronotype and the change in hypo/manic symptoms (β = -0.166, p = 0.070). These data suggest that chronotypes may have low utility for predicting future hypo/manic and depressive symptoms in the short term, or that more frequent assessments over longer periods are needed to observe these associations. Future studies should test whether other circadian phenotypes (e.g. sleep-wake variability) are better indicators of illness course.

An End-to-End Multi-Channel Convolutional Bi-LSTM Network for Automatic Sleep Stage Detection

Sleep stage detection from polysomnography (PSG) recordings is a widely used method of monitoring sleep quality. Despite significant progress in the development of machine-learning (ML)-based and deep-learning (DL)-based automatic sleep stage detection schemes focusing on single-channel PSG data, such as single-channel electroencephalogram (EEG), electrooculogram (EOG), and electromyogram (EMG), developing a standard model is still an active subject of research. Often, the use of a single source of information suffers from data inefficiency and data-skewed problems. Instead, a multi-channel input-based classifier can mitigate the aforementioned challenges and achieve better performance. However, it requires extensive computational resources to train the model, and, hence, a tradeoff between performance and computational resources cannot be ignored. In this article, we aim to introduce a multi-channel, more specifically a four-channel, convolutional bidirectional long short-term memory (Bi-LSTM) network that can effectively exploit spatiotemporal features of data collected from multiple channels of the PSG recording (e.g., EEG Fpz-Cz, EEG Pz-Oz, EOG, and EMG) for automatic sleep stage detection. First, a dual-channel convolutional Bi-LSTM network module has been designed and pre-trained utilizing data from every two distinct channels of the PSG recording. Subsequently, we have leveraged the concept of transfer learning circuitously and have fused two dual-channel convolutional Bi-LSTM network modules to detect sleep stages. In the dual-channel convolutional Bi-LSTM module, a two-layer convolutional neural network has been utilized to extract spatial features from two channels of the PSG recordings. These extracted spatial features are subsequently coupled and given as input at every level of the Bi-LSTM network to extract and learn rich temporal correlated features. Both Sleep EDF-20 and Sleep EDF-78 (expanded version of Sleep EDF-20) datasets are used in this study to evaluate the result. The model that includes an EEG Fpz-Cz + EOG module and an EEG Fpz-Cz + EMG module can classify sleep stage with the highest value of accuracy (ACC), Kappa (Kp), and F1 score (e.g., 91.44%, 0.89, and 88.69%, respectively) on the Sleep EDF-20 dataset. On the other hand, the model consisting of an EEG Fpz-Cz + EMG module and an EEG Pz-Oz + EOG module shows the best performance (e.g., the value of ACC, Kp, and F1 score are 90.21%, 0.86, and 87.02%, respectively) compared to other combinations for the Sleep EDF-78 dataset. In addition, a comparative study with respect to other existing literature has been provided and discussed in order to exhibit the efficacy of our proposed model.

Transdiagnostic association between subjective insomnia and depressive symptoms in major psychiatric disorders

In psychiatric disorders, comorbid depressive symptoms are associated with clinically important issues such as reduced quality of life, a poor prognosis, and increased suicide risk. Previous studies have found a close relationship between insomnia and depressive symptoms in major depressive disorder (MDD), and that actively improving insomnia heightens the improvement of depressive symptoms. This study aimed to investigate whether the association between insomnia and depressive symptoms is also found in other psychiatric disorders besides MDD. The subjects were 144 patients with MDD (n = 71), schizophrenia (n = 25), bipolar disorder (n = 22), or anxiety disorders (n = 26). Sleep status was assessed subjectively and objectively using the Athens Insomnia Scale (AIS) and sleep electroencephalography (EEG), respectively. Sleep EEG was performed using a portable EEG device. Depressive symptoms were assessed using the Beck Depression Inventory. Subjective insomnia, as defined by the AIS, was associated with depressive symptoms in all disorders. Moreover, in schizophrenia, a relation between depressive symptoms and insomnia was also found by objective sleep assessment methods using sleep EEG. Our findings suggest that the association between subjective insomnia and depressive symptoms is a transdiagnostic feature in major psychiatric disorders. Further studies are needed to clarify whether therapeutic interventions for comorbid insomnia can improve depressive symptoms in major psychiatric disorders, similar to MDD.

Relationship between nonrestorative sleep with short sleep duration and diabetes mellitus comorbid among a Japanese occupational population

Objective

Nonrestorative sleep (NRS) is one of the symptoms of insomnia and is clearly more associated with objective indices, such as sleep stability, sleep fragmentation, and inflammatory responses, than other insomnia symptoms. However, the link between NRS and diabetes mellitus is poorly understood. Therefore, the prevalence of NRS in workers and the relationships between NRS and diabetes were investigated.

Methods

The results of a single year's medical examinations were investigated for 26,144 Japanese active office workers who were 30 to 59 years old. NRS was investigated using a personal computer in a medical interview. Furthermore, the relationships between NRS and diabetes comorbidity in addition to sleep duration were also analyzed.

Results

The mean age of the subjects was 47.9 ± 7.3 years old, and the proportion of subjects with NRS was 26%. The presence of NRS together with a sleep duration ≤ 5 h or a sleep duration of 6 h was an independent comorbid factor for diabetes compared with the absence of NRS together with a sleep duration of 7 h (odds ratio [OR] 1.34; 95% confidence interval [CI] 1.14-1.58; P < 0.001; and OR 1.25; 95% CI 1.04-1.48; P = 0.015).

Conclusion

NRS in active workers may contribute to the development of diabetes even if the workers have the same short sleep durations as other workers without NRS.

How to deal with sleep problems during heatwaves: practical recommendations from the European Insomnia Network

Heatwaves are occurring more frequently and are known to affect particularly night-time temperatures. We review here literature on how night-time ambient temperature changes affect body temperature and sleep quality. We then discuss how these temperature effects impact particularly vulnerable populations such as older adults, children, pregnant women, and those with psychiatric conditions. Several ways of dealing with sleep problems in the context of heatwaves are then suggested, adapted from elements of cognitive behavioural therapy for insomnia, with more specific advice for vulnerable populations. By better dealing with sleep problems during heatwaves, general health effects of heatwaves may be more limited. However, given the sparse literature, many links addressed in this review on sleep problems affected by temperature changes should be the focus of future research.

Control of Emotion and Wakefulness by Neurotensinergic Neurons in the Parabrachial Nucleus

The parabrachial nucleus (PBN) integrates interoceptive and exteroceptive information to control various behavioral and physiological processes including breathing, emotion, and sleep/wake regulation through the neural circuits that connect to the forebrain and the brainstem. However, the precise identity and function of distinct PBN subpopulations are still largely unknown. Here, we leveraged molecular characterization, retrograde tracing, optogenetics, chemogenetics, and electrocortical recording approaches to identify a small subpopulation of neurotensin-expressing neurons in the PBN that largely project to the emotional control regions in the forebrain, rather than the medulla. Their activation induces freezing and anxiety-like behaviors, which in turn result in tachypnea. In addition, optogenetic and chemogenetic manipulations of these neurons revealed their function in promoting wakefulness and maintaining sleep architecture. We propose that these neurons comprise a PBN subpopulation with specific gene expression, connectivity, and function, which play essential roles in behavioral and physiological regulation.

Does the smartphone's eye protection mode work?

People spend about 5-8 hours per day on phones, causing circadian disruption and eye fatigue, thus raising a great need for comfort and health. Most phones have eye protection modes, claiming a potential eye protection effect. To examine the effectiveness, we investigated the color quality, namely gamut area and just noticeable color difference (JNCD), and circadian effect, namely equivalent melanopic lux (EML) and melanopic daylight efficacy ratio (MDER), characteristics of two smartphones: iPhone 13 and HUAWEI P30, in normal and eye protection mode. The results show that the circadian effect is inversely proportional to color quality when the iPhone 13 and HUAWEI P30 changed from normal to eye protection mode. The gamut area changed from 102.51% to 82.5% sRGB and 100.36% to 84.55% sRGB, respectively. The EML and MDER decreased by 13 and 15, and, 0.50 and 0.38, respectively, affected by the eye protection mode and screen luminance. The EML and JNCD results in different modes show that the eye protection mode benefits the nighttime circadian effect at the cost of the image quality. This study provides a way to precisely assess the image quality and circadian effect of displays and elucidates the tradeoff relationship between them.