The Neurobiological Basis of Sleep and Sleep Disorders

Association between circulating antioxidants and sleep disorders: comprehensive results from NHANES 2017-2018

Background: Oxidative stress plays an important role in the occurrence and pathological process of numerous human diseases. A bidirectional relationship was found between sleep disorders and oxidative stress. However, the association between circulating antioxidant levels and the risk of sleep disorders at the population-scale has yet to be determined. Methods: We used the dataset from the National Health and Nutrition Examination Survey (NHANES) 2017-2018 data release cycle and included 3062 adult participants aged 25-75 years. The circulating antioxidants levels in serum were measured, and the sleep status was assessed by self-reported sleep disorder questionnaire tests. We investigated the association and exposure-response relationship between the 12 main circulating antioxidants and sleep disorders using a generalized additive model (GAM), multiple linear, binary logistic, and restricted cubic spline (RCS) regression models. Multiple sensitivity analyses were conducted to validate the results of our study. Results: Significantly lower serum concentrations of ten antioxidants were observed in the group which had trouble sleeping symptoms compared to the control group. After adjusting for all the covariates, the binary logistic regression models indicated that six of the circulating antioxidants including alpha-carotene, alpha-cryptoxanthin, trans-beta-carotene, beta-cryptoxanthin, lutein and zeaxanthin, and vitamin C, showed a significant association with the risk of overall trouble sleeping symptoms, with odds ratios corresponding to 0.88 (95% CI: 0.80-0.96), 0.74 (95% CI: 0.62-0.87), 0.87 (95% CI: 0.79-0.97), 0.85 (95% CI: 0.75-0.95), 0.72 (95% CI: 0.61-0.84), and 0.83 (95% CI: 0.74-0.93), respectively. The GAM and multiple linear regression revealed similar associations whereas the RCS regression models further confirmed their significant negative exposure-response relationship. Conclusions: The circulating carotenoids and vitamin C levels were negatively correlated with the risk of sleep disorders. Higher circulating antioxidant levels were significantly associated with a lower risk of sleep disorders. The potential health risk of low circulating antioxidants levels was higher in the female population than in the male population.

The Role of Cannabis and The Endocannabinoid System in Sleep Regulation and Cognition: A Review of Human and Animal Studies

OBJECTIVES

Both sleep and cognition are partially modulated by the endocannabinoid (ECB) system. Cannabis has been reported to have effects on sleep and cognition. This review aims to summarize the recent literature on the ECB system, the role of cannabis and the ECB system on sleep regulation and cognition. Further, this review will identify existing gaps in knowledge and suggest potential targets for future research.

METHODS

We performed this review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Reports were identified by searching PubMed/MEDLINE, Embase, CINAHL, Web of Science, and PsycINFO for articles published through September 2021 for studies with data available on aspects of cognition, cannabis, or the ECB system, and sleep or circadian rhythms (CRs).

RESULTS

We identified 6 human and 6 animal studies to be eligible for inclusion in this review. Several human studies found that cannabis use is not associated with changes in sleep quality or cognitive function. However, individual cannabinoids appeared to have independent effects on cognition and sleep; THC alone decreased cognitive performance and increased daytime sleepiness, whereas CBD alone had no effect on sleep or cognition. Animal studies demonstrated that manipulation of the ECB system altered activity and cognitive function, some of which appeared to be dependent on the light/dark cycle.

CONCLUSION

The sleep-wake cycle and CRs are both likely modulated by the ECB system, potentially resulting in effects on cognition, however this area is critically understudied.

Sleep patterns according to genetically determined ethnicity in the population of São Paulo, Brazil

Sleep is a behavior expressed differently for each individual. However, studies have shown that some ethnic groups express common sleep patterns, which can be observed in different ethnic groups. Previous studies have shown the existence of sleep disparities in populations of different ethnicities. Most of these studies have considered self-reported ethnicity and assessed sleep subjectively. Therefore, the aim of this study was to evaluate sleep disparities in different ethnic groups based on an analysis of genetic ancestry and the use of objective sleep evaluation. To do this, we used data from the São Paulo Epidemiologic Sleep Study (EPISONO), which was undertaken in Brazil, a country that is known for its ethnic/racial diversity. All individuals completed a series of questionnaires, underwent full polysomnography and had their blood collected for DNA extraction. After genotyping and identifying samples with high-quality DNA suitable for genetic analysis, 31 ancestry-informative markers (AIMs) were selected. These markers exhibited substantial allelic frequency differences, enabling the characterization of the three primary founding populations of modern Brazil - Europeans, West-Africans, and Native Americans. Through this analysis, the genetic contribution of each of these ancestral groups was identified in respect of each participant. Based on this, a latent class cluster analysis (LCCA) was performed to define the three clusters that best classified the sample according to ethnic group: African (n = 255), Caucasian (n = 668) and Native American (n = 83). Applying the adjusted model for the confounding variables (age, socio-economic class and sex), statistically significant differences in sleep variables between ethnicities were found. Africans had higher sleep latency compared to the other groups (β = 4.46, CI = 1.18 to 7.74 and β = 7.83, CI = 3.50 to 12.15), while Caucasians had longer total sleep time (β = -16.47, CI = -29.94 to -2.99) and better sleep efficiency (β = -2.19, CI = -4.35 to -0.02) compared to Africans. Regarding the respiratory arousals index (β = -1.11, IC = -2.07 to -0.16) and periodic leg movements index (β = -7.48, CI = -12.08 to -2.88), both were higher among Caucasians compared to Africans. We were able to conclude that genetic ancestry might modulate sleep structure and the occurrence of sleep disorders.

Fatigue and fallibility: the perils of prolonged shifts for neonatologists

Sleep deprivation is a major challenge for neonatologists, who face increasing demands in the complex healthcare system. Current neonatal intensive care unit (NICU) schedule models often include extended shifts and overnight call, which can lead to sleep deprivation. This lack of sufficient sleep poses adverse health risks to neonatologists and can impair cognitive function, which increases the risk of medical errors and compromises patient safety. This paper proposes reducing shift durations and implementing policies and interventions to reduce fatigue among neonatologists and improve patient safety. The paper also offers policymakers, healthcare leaders, and NICU physicians valuable insights on potential ways to promote the health of the neonatologist workforce and safety in the NICU.

Re-examining the role of the dorsal fan-shaped body in promoting sleep in Drosophila

The needs fulfilled by sleep are unknown, though the effects of insufficient sleep are manifold. To better understand how the need to sleep is sensed and discharged, much effort has gone into identifying the neural circuits involved in regulating arousal, especially those that promote sleep. In prevailing models, the dorsal fan-shaped body (dFB) plays a central role in this process in the fly brain. In the present study we manipulated various properties of the dFB including its electrical activity, synaptic output, and endogenous gene expression. In each of these experimental contexts we were unable to identify any effect on sleep that could be unambiguously mapped to the dFB. Furthermore, we found evidence that sleep phenotypes previously attributed to the dFB were caused by genetic manipulations that inadvertently targeted the ventral nerve cord. We also examined expression of two genes whose purported effects have been attributed to functions within a specific subpopulation of dFB neurons. In both cases we found little to no expression in the expected cells. Collectively, our results cast doubt on the prevailing hypothesis that the dFB plays a central role in promoting sleep.

Pharmacological interventions targeting α-synuclein aggregation triggered REM sleep behavior disorder and early development of Parkinson's disease

Rapid eye movement (REM) sleep behavior disorder (RBD) is a parasomnia characterized by elevated motor behaviors and dream enactments in REM sleep, often preceding the diagnosis of Parkinson's disease (PD). As RBD could serve as a biomarker for early PD developments, pharmacological interventions targeting α-synuclein aggregation triggered RBD could be applied toward early PD progression. However, robust therapeutic guidelines toward PD-induced RBD are lacking, owing in part to a historical paucity of effective treatments and trials. We reviewed the bidirectional links between α-synuclein neurodegeneration, progressive sleep disorders, and RBD. We highlighted the correlation between RBD development, α-synuclein aggregation, and neuronal apoptosis in key brainstem regions involved in REM sleep atonia maintenance. The current pharmacological intervention strategies targeting RBD and their effects on progressive PD are discussed, as well as current treatments for progressive neurodegeneration and their effects on RBD. We also evaluated emerging and potential pharmacological solutions to sleep disorders and developing synucleinopathies. This review provides insights into the mechanisms and therapeutic targets underlying RBD and PD, and explores bidirectional treatment effects for both diseases, underscoring the need for further research in this area.

Gut microbiota: Candidates for a novel strategy for ameliorating sleep disorders

The aim of this review was to evaluate the feasibility of treating sleep disorders using novel gut microbiota intervention strategies. Multiple factors can cause sleep disorders, including an imbalance in the gut microbiota. Studies of the microbiome-gut-brain axis have revealed bidirectional communication between the central nervous system and gut microbes, providing a more comprehensive understanding of mood and behavioral regulatory patterns. Changes in the gut microbiota and its metabolites can stimulate the endocrine, nervous, and immune systems, which regulate the release of neurotransmitters and alter the activity of the central nervous system, ultimately leading to sleep disorders. Here, we review the main factors affecting sleep, discuss possible pathways and molecular mechanisms of the interaction between sleep and the gut microbiota, and compare common gut microbiota intervention strategies aimed at improving sleep physiology.

Dysregulated arousal as a pathway linking childhood neglect and clinical sleep disturbances in adulthood

BACKGROUND

A history of childhood maltreatment has a well-established association with clinical sleep disturbances in adulthood, which is a transdiagnostic contributor to many chronic diseases.

OBJECTIVE

Determine whether actigraphy-measured indices of dysregulated arousal during sleep explain associations between abuse or neglect in childhood and clinical sleep disturbances in adulthood.

PARTICIPANTS AND SETTING

Participants were 646 individuals, ages 25-83 (59.3% female) from the MIDUS II Biomarker, Refresher studies.

METHODS

Participants completed the Childhood Trauma Questionnaire, wore an actigraph for seven days, and rated sleep quality using the Pittsburgh Sleep Quality Index (PSQI).

RESULTS

Both neglect (b = 0.66, SE = 0.33, p = .04) and abuse (b = 1.09, SE = 0.32, p < .001) were associated with clinical sleep disturbance. Actigraphy-measured sleep efficiency mediated the link between neglect and clinical sleep disturbances (ab = 0.33, SE = 0.12, 95%CI [0.12, 0.57]). However, no such link between abuse and clinical sleep disturbances was mediated by actigraphy-measured indices. Sleep onset latency did not mediate the link between neglect or abuse and sleep disturbance. Models covaried for other maltreatment, gender, and age.

CONCLUSIONS

While the unique associations between abuse or neglect and clinical sleep disturbances were robust in this sample, only sleep efficiency emerged as a mediator linking maltreatment and clinical sleep disturbances. Critically, this mediation was specific to neglect. Abuse and neglect may lead to disease through distinct pathways. Moreover, potential dysregulation in arousal that leads to sleep inefficiency may be a specific pathway through which experiences of neglect in childhood contribute to chronic disease.

The translational neuroscience of sleep: A contextual framework

Sleep is entwined across many physiologic processes in the brain and periphery, thereby exerting tremendous influence on our well-being. Yet sleep exists in a social-environmental context. Contextualizing sleep health with respect to its determinants—from individual- to societal-level factors—would enable neuroscientists to more effectively translate sleep health into clinical practice. Key challenges and opportunities pertain to (i) recognizing and exploring sleep’s functional roles, (ii) clarifying causal mechanisms in relation to key outcomes, (iii) developing richer model systems, (iv) linking models to known contextual factors, and (v) leveraging advances in multisensory technology. Meeting these challenges and opportunities would help transcend disciplinary boundaries such that social-environmental considerations related to sleep would become an ever-greater presence in the clinic.

Microbiota and sleep: awakening the gut feeling

Various lifestyle and environmental factors are known to influence sleep. Increasingly, evidence points to a role for the microbiota in regulating brain and behaviour. This article explores how the microbiota-gut-brain axis affects sleep directly and indirectly. We summarize the possible molecular mechanisms underlying sleep-microbiome interactions and discuss how various factors interact with the gut microbiota to influence sleep. Furthermore, we present the current evidence of alterations of the microbiota-gut-brain axis in various sleep disorders and pathologies where comorbid sleep disturbances are common. Since manipulating the gut microbiota could potentially improve sleep, we outline ways in which this can be achieved.

Differential Co-Occurring Patterns Between Depressive Symptomatology and Sleep-Wake-Related Disturbances in Mood Disorders

PURPOSE

This study aimed to elucidate the various co-occurring patterns of depressive symptomatology and sleep-wake-related disturbances (SWRDs) in patients with mood disorders.

PATIENTS AND METHODS

Individuals in non-acute states of major depressive disorder or bipolar disorder were recruited. The Beck Depression Inventory II (BDI-II) was utilized to evaluate depressive symptoms. BDI-II items were classified into three domains: cognitive, affective, and somatic. Between-domain differences with various SWRDs were examined. Latent class analysis was used to empirically classify participants using BDI-II items as indicator variables. Co-occurring patterns between domains of BDI-II items and SWRDs were re-examined in each subgroup to elucidate inter-individual differences.

RESULTS

In total, 657 participants were enrolled. Of participants, 66.8% were female, and 52.4% were diagnosed with major depressive disorder. Each BDI-II domain exhibited different co-occurring patterns. The somatic domain was most likely to co-occur with various SWRDs. Three subgroups were derived from latent class analysis and were designated as poor sleep quality and high insomnia (n=150), poor sleep quality and moderate insomnia (n=248), and poor sleep quality and low insomnia (n=159). The group with more severe insomnia presented with more severe depressive and anxiety symptoms. The three subgroups further differed in co-occurring patterns. From the low insomnia to high insomnia group, the associations with various SWRDs appeared in the sequence of somatic, affective, and cognitive domains.

CONCLUSION

Co-occurring patterns between domains of depressive symptomatology with various SWRDs differ and may vary among individuals.

Sleep Quality in Autism from Adolescence to Old Age

Background

Sleep problems are common in autism from early childhood. Although research suggests that poor sleep continues at least into early middle age, the pattern of sleep problems has rarely been characterized beyond childhood. The aim of this study was to examine sleep quality from adolescence to old age in autistic individuals as compared with age-matched non-autistic comparison groups from the general population.

Methods

Participants ranged from 15 to 80 years; there were 297 participants in the autistic group (mean [M]_age = 34.36 years, standard deviation [SD] = 15.24), and the comparison group had 233 participants (M_age  = 33.01 years, SD = 15.53). Sleep quality, sleep onset latency (SoL), total night sleep, and sleep efficiency as measured by Pittsburgh Sleep Quality Index were compared between groups and across age groups (15-19, 20-39, 40-59, 60+ years). Five predictors of sleep quality (autistic traits, mental health condition, medication, employment, and sex) were also examined.

Results

Overall, problematic sleep was more common for the autistic participants (63.7%) than the comparison group (46.4%), and autistic participants had poorer sleep quality and longer SoL (all p < 0.001). In early adulthood and middle age, autistic adults had significantly poorer sleep quality and longer SoL than similar age comparison group adults; autistic and comparison group adolescents and the elderly did not differ. In the autistic group, predictors accounted for 21% of sleep quality variance. Sex (p < 0.001) was the strongest predictor, with all predictors except employment contributing unique variance. In the comparison group, predictors accounted for 25% of the variance in sleep quality. The strongest predictor was mental health condition (p < 0.001), with all predictors except sex contributing unique variance.

Conclusions

Autistic adolescents and adults, particularly females, remain vulnerable to sleep problems, with early and middle adulthood being at times of particular risk. Targeted sleep interventions are required.

Lay summary

Why was this study done?: Difficulty sleeping is a common occurrence among autistic individuals, but we know very little about sleep in autistic adults.What was the purpose of the study?: To compare self-reported sleep quality in autistic and non-autistic people aged 15 to 80 years.What did the researchers do?: Online surveys were completed by 297 autistic individuals (average age 34.36 years) and 233 non-autistic individuals (average age 33.01 years). Participants were asked questions about their sleep quality, the time it takes them to fall asleep (sleep latency), and the number of hours of sleep they usually get each night (total sleep). Using information about how long they slept and their responses to questions about their bedtime and wake time we calculated the percentage of time they spent in bed asleep (sleep efficiency [SE]). We compared these sleep measures between the autistic and non-autistic participants. We also split the participants into four age groups (15-19, 20-39, 40-59, and 60+ years) to look at any differences at specific age points. Finally, we looked to see whether autistic symptoms, having a mental health problem, being on medication, being unemployed, and/or sex (male/female) predicted sleep quality.What were the results of the study?: Poor sleep quality was more common for the autistic participants (63.7%) than non-autistic participants (46.4%). On average, autistic participants also had poorer sleep quality scores and it took them longer to fall asleep than non-autistic participants. Autistic participants in early adulthood (20-39) and middle age (40-59) had poorer sleep quality and took longer to fall asleep than non-autistic adults of the same age. There were no differences between autistic and non-autistic adolescents (15-19) or older adults (60+). For autistic participants, the best predictor of poor sleep quality was being female; other predictors of poor sleep quality were having a mental health problem, more autistic symptoms, and being on medication. Among non-autistic participants, the best predictor of poor sleep quality was having a mental health problem; other predictors were more autistic symptoms, being on medication, and being unemployed.What do these findings add to what is already known?: Similar to the findings in autistic children, autistic adults are more likely to have poor sleep quality compared with non-autistic adults. Autistic females are particularly at risk for poor sleep, and autistic adults aged 20 to 59 years are more at risk for poor sleep quality.What are potential weaknesses in the study?: Sleep was measured by using a self-report questionnaire, which is not as reliable as using a sleep diary or other objective measures of sleep (e.g., actigraphy). In addition, this study only looked at data collected at one point in time, and as such it is not possible to examine changes over time in sleep quality among autistic adults.How will these findings help autistic adults now or in the future?: The findings in this study identified that sleep difficulties persist across the lifespan for autistic adults. Therefore, there is a critical need for future research to focus on understanding the cause of poor sleep quality in autism and develop sleep interventions for autistic adults.

Insomnia in Patients Seeking Care at an Orofacial Pain Unit

Introduction: Orofacial pain and dysfunction include a broad range of disturbances among which pain and insomnia are some of the most common complaints. Sleep strengthens physiological and psychological resilience and is an absolute requirement for health. Insomnia is a common symptom or sleep disorder, yet data on its prevalence is sparse. Here we extracted data from the insomnia severity index which was part of the web-based interdisciplinary symptom evaluation (WISE) tool given to a large sample of patients seeking care at an orofacial pain unit for analyzing insomnia prevalence in this clinical population.

Material and methods: Anonymized data were available from 952 patients who consulted the Orofacial Pain Unit at the Center of Dental Medicine, University of Zurich, Zurich, Switzerland between January 2017 and December 2018. Prevalence data for insomnia stratified by gender and 10 age groups (decades) were calculated. The distribution of four insomnia severity grades was determined, also stratified by age and gender.

Results: 952 patients (290 men: 30.5%) with a mean age of 44.8 ± 17.4 years completed a WISE. Three hundred and fifty-two (37.0%) patients with a mean age of 45.8 ± 16.7 years positively responded to a screening question for insomnia and/or hypersomnia. Insomnia was severe in women from the 2nd to 8th decade, ranging from 4.3% (3rd decade) to 14.5% (6th decade), and moderately severe from the 2nd to 9th decade, ranging from 18.8% (6th decade) to 27.8% (2nd decade). In men, severe insomnia was present from the 3rd to 7th decade, ranging from 2.3% (7th decade) to 4.4% (4th decade) and moderately severe insomnia from the 3rd to 7th decade, ranging from 4.6% (7th decade) to 12.2% (5th decade).

Conclusions: This is the first study reporting on insomnia in a large sample of patients seeking care at an orofacial pain unit. One in three patients reported some form of sleep disturbances, which for almost half of them was moderate to severe insomnia. The gender ratio was almost equal throughout adulthood, yet younger and older women were more frequently affected and experienced higher insomnia severity than men.

Sleep disturbance at pre-deployment is a significant predictor of post-deployment re-experiencing symptoms

Background: Insomnia is common in service members and associated with many mental and physical health problems. Recently, longitudinal data have been used to assess the impact of disturbed sleep on mental health outcomes. These studies have consistently shown relationships between sleep disturbance and development of mental illness. Objective: The present study examined the longitudinal relationship between sleep disturbance and PTSD symptomatology in a cohort of Marines and Navy Corpsmen deployed to Iraq and Afghanistan (n = 2,404) assessed prior to deployment, as well as at -3 and 6 months post-deployment. Additionally, we aimed to investigate the extent to which these relationships are moderated by combat-stress severity, and to what extent these findings are replicated in a second, separate cohort of Marines and Navy corpsmen (n = 938) assessed with identical measures prior to deployment and within 3 months of return. Method: The present study employed latent variable path models to examine the relationships between pre-deployment sleep disturbance and post-deployment re-experiencing symptoms. Initial cross-lagged path models were conducted on discovery and replication samples to validate the hypothesized predictive relationships. Follow up moderation path models were then conducted to include the effect of combat-stress severity on these relationships. Results: Initial cross-lagged models supported a significant relationship between pre-deployment sleep disturbance and future re-experiencing PTSD symptoms at all time points. Initial moderation models showed a small moderator effect of combat-stress severity, though the main predictive relationship between pre-deployment sleep disturbance and PTSD symptoms remained significant. The moderator effect was not significant in the replication sample. Conclusions: The results of this study support pre-deployment sleep disturbance as a risk factor for development of post-deployment PTSD symptoms. Interventions aimed at normalizing sleep may be important in preventive measures for PTSD.