Sleep, Cognitive impairment, and Alzheimer's disease: A Systematic Review and Meta-Analysis

Prolonged sleep duration as a predictor of cognitive decline: A meta-analysis encompassing 49 cohort studies

Despite numerous studies have explored the association between sleep duration and cognition, the link between sleep duration trajectories and cognition remains underexplored. This systematic review aims to elucidate this correlation. We analyzed 55 studies from 14 countries, comprising 36 studies focusing on sleep duration, 20 on insomnia, and 13 on hypersomnia. A total of 10,767,085 participants were included in 49 cohort studies with a mean follow-up duration of 9.1 years. A non-linear association between sleep duration and cognitive decline was identified. Both long (risk ratio (RR):1.35, 95 % confidence intervals (CIs):1.23-1.48) and short sleep durations (RR: 1.12, 95 % CIs:1.03-1.22) were associated with an elevated risk of cognitive decline compared to moderate sleep duration. Additionally, hypersomnia (RR:1.26, 95 % CIs: 1.15-1.39) and insomnia (RR: 1.16, 95 % CIs: 1.002-1.34) were also linked to an increased risk. Moreover, prolonged sleep duration posed a higher risk of cognitive decline than stable sleep duration (RR:1.42, 95 % CIs:1.27-1.59). Importantly, transitioning from short or moderate to long sleep duration, as well as persistent long sleep duration, exhibited higher RRs for cognitive decline (RRs: 1.94, 1.40, and 1.28, respectively) compared to persistent moderate sleep duration. Our findings underscore the significance of prolonged sleep duration, alongside short and long sleep durations, with an elevated risk of cognitive decline. The association is tied to the degree of sleep duration changes. Our study highlights the importance of considering changes in sleep patterns over time, not just static sleep durations.

Prevalence of sleep disturbances in people with mild cognitive impairment: A systematic review and meta-analysis

This review was performed to determine sleep disturbance prevalence in individuals with mild cognitive impairment (MCI). The MEDLINE, Embase, Cochrane Library, CINAHL, PsycINFO, and Web of Science databases were systematically searched from inception to January 20, 2024. Fifty-two studies fulfilling the eligibility criteria were included. However, six of these studies were excluded from data synthesis due to poor methodological quality. The subjective sleep disturbance prevalence among all individuals with MCI was 35.8 % (95 % CI: 31.9-39.7) across 44 studies, and the objective sleep disturbance prevalence was 46.3 % (95 % CI: 36.3-56.3) across 6 studies. Five studies examined TST and WASO, while three assessed SE. Among all potential objective assessments of sleep disturbance prevalence, only TST, WASO, and SE could be meta-analyzed in MCI because of the limited number of studies available. The estimated sleep disturbance prevalence differed significantly according to measurement method, geographical region, and research design. However, the data source did not significantly influence prevalence estimates. In meta-regression analysis, publication year, participant age, percentage of females, and study quality did not predict prevalence. As subjective and objective sleep disturbances are common in people with MCI, effective intervention strategies should be developed to alleviate them.

[Prevention of cognitive decline in old age : Selected primary preventive approaches]

There are currently 1.8 million people in Germany affected by dementia. Despite advances in research and new treatments, there is no cure for most cases of dementia. The evidence regarding the prevention of cognitive decline in old age is unclear. In addition to the optimized adjustment of drug treatment (e.g., arterial hypertension and diabetes mellitus), preventive measures that can be influenced by individuals themselves play an important role. These include areas such as physical and cognitive activity, remedying hearing loss, sleep, social contacts, abstaining from alcohol as well as tobacco consumption and nutrition. Multimodal concepts and digital approaches appear to be promising and an increase in evidence is expected in the coming years.

The Glymphatic System and its Relationship to Migraine

PURPOSE OF REVIEW

We aim to critically review animal and human studies of the glymphatic system in migraine and propose a model for how the glymphatic system may function in migraine, based on the available evidence.

RECENT FINDINGS

Early studies in animal models report migraine attacks temporarily disrupt glymphatic flow. Human imaging studies suggest chronic migraine may be associated with alterations in glymphatic system function, albeit with conflicting results. Presently, it remains unknown whether repetitive migraine attacks or frequent nights of insomnia impair glymphatic system function over time in those with migraine, and whether alterations in glymphatic function could contribute to worsening migraine disability or risk for cognitive disease. Longitudinal studies of glymphatic function in patients with migraine and insomnia, with inclusion of cognitive assessments, may be informative.

Biomarkers of sleep-wake disturbance as predictors of cognitive decline and accelerated disease progression

INTRODUCTION

In older adults, where sleep disturbances and cognitive impairment are common, mounting evidence suggests a potential connection between sleep and cognitive function, highlighting the significance of utilizing sleep as a biomarker for early detection of cognitive impairment to improve clinical outcomes in a noninvasive, cost-effective manner.

AREAS COVERED

This review describes the relationship between sleep and cognitive function in older adults, encompassing both subjective and objective measures of sleep quality, duration, architecture, and sleep-disordered breathing. The authors consider the directionality of the associations observed in prospective and cross-sectional studies, exploring whether sleep disturbances precede cognitive decline or vice versa. Furthermore, they discuss the potential bidirectional relationships between sleep and Alzheimer's disease (AD) risks in older adults while also examining the neurodegenerative pathways of this relationship.

EXPERT OPINION

Routine sleep monitoring in primary care settings has the potential to bolster early detection and treatment of sleep disturbance, and by extension, reduce the risk of dementia. Improving sleep assessment tools, such as wearables, provide scalable alternatives to traditional methods like polysomnography, potentially enabling widespread monitoring of sleep characteristics. Standardized measurement and inclusive participant recruitment are needed to enhance generalizability, while longitudinal studies are essential to understand the interaction between sleep and AD pathology.

Conceptualization and characterization of "primary" and "secondary" cognitive impairment in schizophrenia

Cognitive impairment represents one of the core features of schizophrenia, involves both neurocognition and social cognition domains, and has a significant negative impact on real-world functioning. The present review provides a framework for the conceptualization and characterization of "primary" and "secondary" cognitive impairment in schizophrenia. In this conceptualization, primary cognitive impairment can be defined as a consequence of the neurobiological alterations that underlie psychopathological manifestations of the disorder, while secondary cognitive impairment can be defined as the results of a source issue that has a negative impact on cognitive performance. Sources of secondary cognitive impairment are frequent in people with schizophrenia and include several different factors, such as positive and negative symptoms, depressive symptoms, autistic symptoms, pharmacotherapy, substance abuse, metabolic syndrome, social deprivation, and sleep disorders. It can be hypothesized that secondary cognitive impairment may be improved by effectively resolving the source issue, while primary cognitive impairment may benefit from dedicated treatment. Further research is required to confirm this hypothesis, to better characterize the distinction between primary and secondary cognitive impairment in a clinical and in a neurobiological perspective, and to evaluate the impact of systematically assessing and treating secondary cognitive impairment.

Poor sleep and decreased cortical thickness in veterans with mild traumatic brain injury and post-traumatic stress disorder

BACKGROUND

Poor sleep quality has been associated with changes in brain volume among veterans, particularly those who have experienced mild traumatic brain injury (mTBI) and post-traumatic stress disorder (PTSD). This study sought to investigate (1) whether poor sleep quality is associated with decreased cortical thickness in Iraq and Afghanistan war veterans, and (2) whether these associations differ topographically depending on the presence or absence of mTBI and PTSD.

METHODS

A sample of 440 post-9/11 era U.S. veterans enrolled in the Translational Research Center for Traumatic Brain Injury and Stress Disorders study at VA Boston, MA from 2010 to 2022 was included in the study. We examined the relationship between sleep quality, as measured by the Pittsburgh Sleep Quality Index (PSQI), and cortical thickness in veterans with mTBI (n = 57), PTSD (n = 110), comorbid mTBI and PTSD (n = 129), and neither PTSD nor mTBI (n = 144). To determine the topographical relationship between subjective sleep quality and cortical thickness in each diagnostic group, we employed a General Linear Model (GLM) at each vertex on the cortical mantle. The extent of topographical overlap between the resulting statistical maps was assessed using Dice coefficients.

RESULTS

There were no significant associations between PSQI and cortical thickness in the group without PTSD or mTBI (n = 144) or in the PTSD-only group (n = 110). In the mTBI-only group (n = 57), lower sleep quality was significantly associated with reduced thickness bilaterally in frontal, cingulate, and precuneus regions, as well as in the right parietal and temporal regions (β = -0.0137, P < 0.0005). In the comorbid mTBI and PTSD group (n = 129), significant associations were observed bilaterally in frontal, precentral, and precuneus regions, in the left cingulate and the right parietal regions (β = -0.0094, P < 0.0005). Interaction analysis revealed that there was a stronger relationship between poor sleep quality and decreased cortical thickness in individuals with mTBI (n = 186) compared to those without mTBI (n = 254) specifically in the frontal and cingulate regions (β = -0.0077, P < 0.0005).

CONCLUSIONS

This study demonstrates a significant relationship between poor sleep quality and lower cortical thickness primarily within frontal regions among individuals with both isolated mTBI or comorbid diagnoses of mTBI and PTSD. Thus, if directionality is established in longitudinal and interventional studies, it may be crucial to consider addressing sleep in the treatment of veterans who have sustained mTBI.

Memory performance mediates subjective sleep quality associations with cerebrospinal fluid Alzheimer's disease biomarker levels and hippocampal volume among individuals with mild cognitive symptoms

Sleep disturbances are prevalent in Alzheimer's disease (AD), affecting individuals during its early stages. We investigated associations between subjective sleep measures and cerebrospinal fluid (CSF) biomarkers of AD in adults with mild cognitive symptoms from the European Prevention of Alzheimer's Dementia Longitudinal Cohort Study, considering the influence of memory performance. A total of 442 participants aged >50 years with a Clinical Dementia Rating (CDR) score of 0.5 completed the Pittsburgh Sleep Quality Index questionnaire and underwent neuropsychological assessment, magnetic resonance imaging acquisition, and CSF sampling. We analysed the relationship of sleep quality with CSF AD biomarkers and cognitive performance in separated multivariate linear regression models, adjusting for covariates. Poorer cross-sectional sleep quality was associated with lower CSF levels of phosphorylated tau and total tau alongside better immediate and delayed memory performance. After adjustment for delayed memory scores, associations between CSF biomarkers and sleep quality became non-significant, and further analysis revealed that memory performance mediated this relationship. In post hoc analyses, poorer subjective sleep quality was associated with lesser hippocampal atrophy, with memory performance also mediating this association. In conclusion, worse subjective sleep quality is associated with less altered AD biomarkers in adults with mild cognitive symptoms (CDR score 0.5). These results could be explained by a systematic recall bias affecting subjective sleep assessment in individuals with incipient memory impairment. Caution should therefore be exercised when interpreting subjective sleep quality measures in memory-impaired populations, emphasising the importance of complementing subjective measures with objective assessments.

Causal relationship between sleep disorders and the risk of Alzheimer's disease: A Mendelian randomization study

BACKGROUND AND OBJECTIVE

Epidemiological studies have shown that sleep disorders are risk factors for Alzheimer's disease (AD), but the causal relationship between sleep disorders and AD risk is unknown. We aim to assess the potential genetic causal association between sleep characteristics and AD, which may contribute to early identification and prediction of risk factors for AD.

METHODS

Seven sleep-related traits and the outcome phenotype AD were selected from published genome-wide association studies (GWASs). These sleep-related characteristics and instrumental variables (IVs) for AD were extracted. Two-sample and multivariate Mendelian randomization (MR) analyses were performed to assess the causal relationships between sleep characteristics and AD. The inverse variance weighted (IVW), weighted median (WME), weighted mode (WM), MR-Egger regression (MR-Egger) and simple mode (SM) models were used to evaluate causality. The existence of pleiotropy was detected and corrected by MR-Egger regression, MR pleiotropy residuals and outliers.

RESULTS

A two-sample MR study revealed a positive causal association between sleep duration and the onset of AD (OR = 1.002, 95 % CI: 1.000-1.004), and the risk of AD increased with increasing sleep duration. The MR-Egger regression method and MR-PRESSO were used to identify and correct pleiotropy, indicating that there was no horizontal pleiotropy. Heterogeneity was evaluated by Cochran's Q, which indicated no heterogeneity. In a multivariate MR study with seven sleep characteristics corrected for each other, we found that sleep duration remained causally associated with AD (OR = 1.004, 95 % CI: 1.000-1.007). Moreover, we found that after mutual correction, daytime napping had a causal relationship with the onset of AD, and daytime napping may reduce the risk of AD (OR = 0.995, 95 % CI: 0.991-1.000).

CONCLUSION

This study is helpful for the early identification and prediction of risk factors for AD, long sleep durations are a risk factor for AD, and daytime napping can reduce the risk of AD.

The impacts of sex and the 5xFAD model of Alzheimer's disease on the sleep and spatial learning responses to feeding time

Introduction

The relationships between the feeding rhythm, sleep and cognition in Alzheimer's disease (AD) are incompletely understood, but meal time could provide an easy-to-implement method of curtailing disease-associated disruptions in sleep and cognition. Furthermore, known sex differences in AD incidence could relate to sex differences in circadian rhythm/sleep/cognition interactions.

Methods

The 5xFAD transgenic mouse model of AD and non-transgenic wild-type controls were studied. Both female and male mice were used. Food access was restricted each day to either the 12-h light phase (light-fed groups) or the 12-h dark phase (dark-fed groups). Sleep (electroencephalographic/electromyographic) recording and cognitive behavior measures were collected.

Results

The 5xFAD genotype reduces NREM and REM as well as the number of sleep spindles. In wild-type mice, light-fed groups had disrupted vigilance state amounts, characteristics, and rhythms relative to dark-fed groups. These feeding time differences were reduced in 5xFAD mice. Sex modulates these effects. 5xFAD mice display poorer spatial memory that, in female mice, is curtailed by dark phase feeding. Similarly, female 5xFAD mice have decreased anxiety-associated behavior. These emotional and cognitive measures are correlated with REM amount.

Discussion

Our study demonstrates that the timing of feeding can alter many aspects of wake, NREM and REM. Unexpectedly, 5xFAD mice are less sensitive to these feeding time effects. 5xFAD mice demonstrate deficits in cognition which are correlated with REM, suggesting that this circadian-timed aspect of sleep may link feeding time and cognition. Sex plays an important role in regulating the impact of feeding time on sleep and cognition in both wild-type and 5xFAD mice, with females showing a greater cognitive response to feeding time than males.

Sleep-wake behavior and responses to sleep deprivation and immune challenge of protein kinase RNA-activated knockout mice

Protein Kinase RNA-activated (PKR) is an enzyme that plays a role in many systemic processes, including modulation of inflammation, and is implicated in neurodegenerative diseases, such as Alzheimer's disease (AD). PKR phosphorylation results in the production of several cytokines involved in the regulation / modulation of sleep, including interleukin-1β, tumor necrosis factor-α and interferon-γ. We hypothesized targeting PKR would alter spontaneous sleep of mice, attenuate responses to sleep deprivation, and inhibit responses to immune challenge. To test these hypotheses, we determined the sleep-wake phenotype of mice lacking PKR (knockout; PKR-/-) during undisturbed baseline conditions; in responses to six hours of sleep deprivation; and after immune challenge with lipopolysaccharide (LPS). Adult male mice (C57BL/6J, n = 7; PKR-/-, n = 7) were surgically instrumented with EEG recording electrodes and an intraperitoneal microchip to record core body temperature. During undisturbed baseline conditions, PKR -/- mice spent more time in non-rapid eye movement sleep (NREMS) and rapid-eye movement sleep (REMS), and less time awake at the beginning of the dark period of the light:dark cycle. Delta power during NREMS, a measure of sleep depth, was less in PKR-/- mice during the dark period, and core body temperatures were lower during the light period. Both mouse strains responded to sleep deprivation with increased NREMS and REMS, although these changes did not differ substantively between strains. The initial increase in delta power during NREMS after sleep deprivation was greater in PKR-/- mice, suggesting a faster buildup of sleep pressure with prolonged waking. Immune challenge with LPS increased NREMS and inhibited REMS to the same extent in both mouse strains, whereas the initial LPS-induced suppression of delta power during NREMS was greater in PKR-/- mice. Because sleep regulatory and immune responsive systems in brain are redundant and overlapping, other mediators and signaling pathways in addition to PKR are involved in the responses to acute sleep deprivation and LPS immune challenge.

Prediction of Mild Cognitive Impairment Status: Pilot Study of Machine Learning Models Based on Longitudinal Data From Fitness Trackers

BACKGROUND

Early signs of Alzheimer disease (AD) are difficult to detect, causing diagnoses to be significantly delayed to time points when brain damage has already occurred and current experimental treatments have little effect on slowing disease progression. Tracking cognitive decline at early stages is critical for patients to make lifestyle changes and consider new and experimental therapies. Frequently studied biomarkers are invasive and costly and are limited for predicting conversion from normal to mild cognitive impairment (MCI).

OBJECTIVE

This study aimed to use data collected from fitness trackers to predict MCI status.

METHODS

In this pilot study, fitness trackers were worn by 20 participants: 12 patients with MCI and 8 age-matched controls. We collected physical activity, heart rate, and sleep data from each participant for up to 1 month and further developed a machine learning model to predict MCI status.

RESULTS

Our machine learning model was able to perfectly separate between MCI and controls (area under the curve=1.0). The top predictive features from the model included peak, cardio, and fat burn heart rate zones; resting heart rate; average deep sleep time; and total light activity time.

CONCLUSIONS

Our results suggest that a longitudinal digital biomarker differentiates between controls and patients with MCI in a very cost-effective and noninvasive way and hence may be very useful for identifying patients with very early AD who can benefit from clinical trials and new, disease-modifying therapies.

Herbal medicines in Alzheimer's disease and the involvement of gut microbiota

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory loss and cognitive impairment. It severely affects the quality of life of victims. The prevalence of AD has been increasing in recent years. Therefore, it is of great importance to elucidate the pathogenic mechanism of AD and search for effective therapeutic approaches. Gut microbiota dysbiosis, an altered state of gut microbiota, has been well known for its involvement in the pathogenesis of AD. Much effort has been made in searching for approaches capable of modulating the composition of gut microbiota in recent years. Herbal medicines have attracted extensive attention in recent decades for the prevention and treatment of AD. Here, we gave an overview of the recent research progress on the modulatory effects of herbal medicines and herbal formulae on gut microbiota as well as the possible beneficial effects on AD, which may provide new insights into the discovery of anti-AD agents and their therapeutic potential for AD through modulating the composition of gut microbiota.

Charting Alzheimer's Disease and Dementia: Epidemiological Insights, Risk Factors and Prevention Pathways

Alzheimer's disease (AD), the most common cause of dementia, is a complex and multifactorial condition without cure at present. The latest treatments, based on anti-amyloid monoclonal antibodies, have only a modest effect in reducing the progression of cognitive decline in AD, whereas the possibility of preventing AD has become a crucial area of research. In fact, recent studies have observed a decrease in dementia incidence in developed regions such as the US and Europe. However, these trends have not been mirrored in non-Western countries (Japan or China), and the contributing factors of this reduction remain unclear. The Lancet Commission has delineated a constrained classification of 12 risk factors across different life stages. Nevertheless, the scientific literature has pointed to over 200 factors-including sociodemographic, medical, psychological, and sociocultural conditions-related to the development of dementia/AD. This narrative review aims to synthesize the risk/protective factors of dementia/AD. Essentially, we found that risk/protective factors vary between individuals and populations, complicating the creation of a unified prevention strategy. Moreover, dementia/AD explanatory mechanisms involve a diverse array of genetic and environmental factors that interact from the early stages of life. In the future, studies across different population-based cohorts are essential to validate risk/protective factors of dementia. This evidence would help develop public health policies to decrease the incidence of dementia.

Sleep characteristics and risk of Alzheimer's disease: a systematic review and meta-analysis of longitudinal studies

BACKGROUND

Alzheimer's disease (AD) is on the rise in our aging society, making it crucial to identify additional risk factors to mitigate its increasing incidence. This systematic review and meta-analysis aimed to provide updated evidence regarding the association between sleep and AD.

METHODS

We conducted a comprehensive search of MEDLINE, EMBASE, and Web of Science databases from inception to July 2023 to identify longitudinal studies. Adjusted relative risks were pooled for each sleep characteristic, and a dose-response analysis was performed specifically for sleep duration.

RESULTS

A total of 15,278 records were initially retrieved, and after screening, 35 records were ultimately included in the final analysis. The results showed that insomnia (RR, 1.43; 95%CI, 1.17-1.74), sleep-disordered breathing (RR, 1.22; 95%CI, 1.07-1.39), as well as other sleep problems, including sleep fragmentation and sleep-related movement disorders, were associated with a higher risk of developing AD, while daytime napping or excessive daytime sleepiness (RR, 1.18; 95%CI, 1.00-1.40) only exhibited a trend toward a higher risk of AD development. Furthermore, our analysis revealed a significant association between self-reported sleep problems (RR, 1.34; 95%CI, 1.26-1.42) and the incidence of AD, whereas this association was not observed with sleep problems detected by objective measurements (RR, 1.14; 95%CI, 0.99-1.31). Moreover, both quite short sleep duration (< 4 h) and long duration (> 8 h) were identified as potential risk factors for AD.

CONCLUSIONS

Our study found the association between various types of sleep problems and an increased risk of AD development. However, these findings should be further validated through additional objective device-based assessments. Additional investigation is required to establish a definitive causal connection between sleep problems and AD.

The interplay between insomnia symptoms and Alzheimer's Disease across three main brain networks

STUDY OBJECTIVES

Insomnia symptoms are prevalent along the trajectory of Alzheimer's disease (AD), but the neurobiological underpinning of their interaction is poorly understood. Here, we assessed structural and functional brain measures within and between the default mode network (DMN), salience network (SN), and central executive network (CEN).

METHODS

We selected 320 subjects from the ADNI database and divided by their diagnosis: cognitively normal (CN), Mild Cognitive Impairment (MCI), and AD, with and without self-reported insomnia symptoms. We measured the gray matter volume (GMV), structural covariance (SC), degrees centrality (DC), and functional connectivity (FC), testing the effect and interaction of insomnia symptoms and diagnosis on each index. Subsequently, we performed a within-group linear regression across each network and ROI. Finally, we correlated observed abnormalities with changes in cognitive and affective scores.

RESULTS

Insomnia symptoms were associated with FC alterations across all groups. The AD group also demonstrated an interaction between insomnia and diagnosis. Within-group analyses revealed that in CN and MCI, insomnia symptoms were characterised by within-network hyperconnectivity, while in AD, within- and between-network hypoconnectivity was ubiquitous. SC and GMV alterations were non-significant in the presence of insomnia symptoms, and DC indices only showed network-level alterations in the CEN of AD individuals. Abnormal FC within and between DMN and CEN hubs was additionally associated with reduced cognitive function across all groups, and increased depressive symptoms in AD.

CONCLUSIONS

We conclude that patients with clinical AD present with a unique pattern of insomnia-related functional alterations, highlighting the profound interaction between both conditions.

The Complex Relationship between Sleep and Cognitive Reserve: A Narrative Review Based on Human Studies

Sleep and brain/cognitive/neural reserve significantly impact well-being and cognition throughout life. This review aims to explore the intricate relationship between such factors, with reference to their effects on human cognitive functions. The specific goal is to understand the bidirectional influence that sleep and reserve exert on each other. Up to 6 February 2024, a methodical search of the literature was conducted using the PubMed database with terms related to brain, cognitive or neural reserve, and healthy or disturbed sleep. Based on the inclusion criteria, 11 articles were selected and analyzed for this review. The articles focus almost exclusively on cognitive reserve, with no explicit connection between sleep and brain or neural reserve. The results evidence sleep's role as a builder of cognitive reserve and cognitive reserve's role as a moderator in the effects of physiological and pathological sleep on cognitive functions. In conclusion, the findings of the present review support the notion that both sleep and cognitive reserve are critical factors in cognitive functioning. Deepening comprehension of the interactions between them is essential for devising strategies to enhance brain health and resilience against age- and pathology-related conditions.

Predicting Alzheimer's disease CSF core biomarkers: a multimodal Machine Learning approach

Introduction

Alzheimer's disease (AD) is a progressive neurodegenerative disorder. Current core cerebrospinal fluid (CSF) AD biomarkers, widely employed for diagnosis, require a lumbar puncture to be performed, making them impractical as screening tools. Considering the role of sleep disturbances in AD, recent research suggests quantitative sleep electroencephalography features as potential non-invasive biomarkers of AD pathology. However, quantitative analysis of comprehensive polysomnography (PSG) signals remains relatively understudied. PSG is a non-invasive test enabling qualitative and quantitative analysis of a wide range of parameters, offering additional insights alongside other biomarkers. Machine Learning (ML) gained interest for its ability to discern intricate patterns within complex datasets, offering promise in AD neuropathology detection. Therefore, this study aims to evaluate the effectiveness of a multimodal ML approach in predicting core AD CSF biomarkers.

Methods

Mild-moderate AD patients were prospectively recruited for PSG, followed by testing of CSF and blood samples for biomarkers. PSG signals underwent preprocessing to extract non-linear, time domain and frequency domain statistics quantitative features. Multiple ML algorithms were trained using four subsets of input features: clinical variables (CLINVAR), conventional PSG parameters (SLEEPVAR), quantitative PSG signal features (PSGVAR) and a combination of all subsets (ALL). Cross-validation techniques were employed to evaluate model performance and ensure generalizability. Regression models were developed to determine the most effective variable combinations for explaining variance in the biomarkers.

Results

On 49 subjects, Gradient Boosting Regressors achieved the best results in estimating biomarkers levels, using different loss functions for each biomarker: least absolute deviation (LAD) for the Aβ42, least squares (LS) for p-tau and Huber for t-tau. The ALL subset demonstrated the lowest training errors for all three biomarkers, albeit with varying test performance. Specifically, the SLEEPVAR subset yielded the best test performance in predicting Aβ42, while the ALL subset most accurately predicted p-tau and t-tau due to the lowest test errors.

Conclusions

Multimodal ML can help predict the outcome of CSF biomarkers in early AD by utilizing non-invasive and economically feasible variables. The integration of computational models into medical practice offers a promising tool for the screening of patients at risk of AD, potentially guiding clinical decisions.

Sleep Disorders and Dementia Risk in Older Patients with Kidney Failure: A Retrospective Cohort Study

Key Points

Background

Community-dwelling older adults with sleep disorders are at higher risk of developing dementia. Greater than 50% of older patients with kidney failure experience sleep disorders, which may explain their high burden of dementia.

Methods

Among 216,158 patients (aged 66 years and older) with kidney failure (United States Renal Data System; 2008–2019), we estimated the risk of dementia (including subtypes) associated with sleep disorders using Cox proportional hazards models with propensity score weighting. We tested whether positive airway pressure (PAP) therapy was associated with reduced dementia risk among patients with obstructive sleep apnea (OSA).

Results

26.3% of patients were diagnosed with sleep disorders; these patients had a higher 5-year unadjusted cumulative incidence for any type of dementia (36.2% versus 32.3%; P < 0.001), vascular dementia (4.4% versus 3.7%; P < 0.001), and other/mixed dementia (29.3% versus 25.8%; P < 0.001). Higher risk of any type of dementia was identified in patients with insomnia (adjusted hazard ratio [aHR], 1.42; 95% confidence interval [CI], 1.34 to 1.51), sleep-related breathing disorders (SRBDs) (aHR, 1.20, 95% CI, 1.17 to 1.23), and other sleep disorders (aHR, 1.24; 95% CI, 1.11 to 1.39). Higher vascular dementia risk was observed in patients with insomnia (aHR, 1.43; 95% CI, 1.19 to 1.73) and SRBDs (aHR, 1.15; 95% CI, 1.07 to 1.24). Patients with SRBDs (aHR, 1.07; 95% CI, 1.00 to 1.15) were at higher risk of Alzheimer disease. Among patients with OSA, PAP therapy was associated with lower risk of any type of dementia (aHR, 0.82; 95% CI, 0.76 to 0.90) and vascular dementia (aHR, 0.65; 95% CI, 0.50 to 0.85).

Conclusions

Older patients with kidney failure and sleep disorders are at a higher risk of dementia. Sleep is an important modifiable factor that should be considered for targeted interventions to mitigate dementia risk in patients with kidney failure. For patients with OSA, PAP therapy is associated with lower dementia risk.

Longer sleep duration and neuroinflammation in at-risk elderly with a parental history of Alzheimer's disease

STUDY OBJECTIVES

Although short sleep could promote neurodegeneration, long sleep may be a marker of ongoing neurodegeneration, potentially as a result of neuroinflammation. The objective was to evaluate sleep patterns with age of expected Alzheimer's disease (AD) onset and neuroinflammation.

METHODS

We tested 203 dementia-free participants (68.5 ± 5.4 years old, 78M). The PREVENT-AD cohort includes older persons with a parental history of AD whose age was nearing their expected AD onset. We estimated expected years to AD onset by subtracting the participants' age from their parent's at AD dementia onset. We extracted actigraphy sleep variables of interest (times of sleep onset and morning awakening, time in bed, sleep efficiency, and sleep duration) and general profiles (sleep fragmentation, phase delay, and hypersomnia). Cerebrospinal fluid (CSF) inflammatory biomarkers were assessed with OLINK multiplex technology.

RESULTS

Proximity to, or exceeding, expected age of onset was associated with a sleep profile suggestive of hypersomnia (longer sleep and later morning awakening time). This hypersomnia sleep profile was associated with higher CSF neuroinflammatory biomarkers (IL-6, MCP-1, and global score). Interaction analyses revealed that some of these sleep-neuroinflammation associations were present mostly in those closer/exceeding the age of expected AD onset, APOE4 carriers, and those with better memory performance.

CONCLUSIONS

Proximity to, or exceeding, parental AD dementia onset was associated with a longer sleep pattern, which was related to elevated proinflammatory CSF biomarkers. We speculate that longer sleep may serve a compensatory purpose potentially triggered by neuroinflammation as individuals are approaching AD onset. Further studies should investigate whether neuroinflammatory-triggered long sleep duration could mitigate cognitive deficits.

Just-in-Time Adaptive Intervention for Stabilizing Sleep Hours of Japanese Workers: Microrandomized Trial

BACKGROUND

Sleep disturbance is a major contributor to future health and occupational issues. Mobile health can provide interventions that address adverse health behaviors for individuals in a vulnerable health state in real-world settings (just-in-time adaptive intervention).

OBJECTIVE

This study aims to identify a subpopulation with vulnerable sleep state in daily life (study 1) and, immediately afterward, to test whether providing mobile health intervention improved habitual sleep behaviors and psychological wellness in real-world settings by conducting a microrandomized trial (study 2).

METHODS

Japanese workers (n=182) were instructed to collect data on their habitual sleep behaviors and momentary symptoms (including depressive mood, anxiety, and subjective sleep quality) using digital devices in a real-world setting. In study 1, we calculated intraindividual mean and variability of sleep hours, midpoint of sleep, and sleep efficiency to characterize their habitual sleep behaviors. In study 2, we designed and conducted a sleep just-in-time adaptive intervention, which delivered objective push-type sleep feedback messages to improve their sleep hours for a subset of participants in study 1 (n=81). The feedback messages were generated based on their sleep data measured on previous nights and were randomly sent to participants with a 50% chance for each day (microrandomization).

RESULTS

In study 1, we applied hierarchical clustering to dichotomize the population into 2 clusters (group A and group B) and found that group B was characterized by unstable habitual sleep behaviors (large intraindividual variabilities). In addition, linear mixed-effect models showed that the interindividual variability of sleep hours was significantly associated with depressive mood (β=3.83; P=.004), anxiety (β=5.70; P=.03), and subjective sleep quality (β=-3.37; P=.03). In study 2, we found that providing sleep feedback prolonged subsequent sleep hours (increasing up to 40 min; P=.01), and this effect lasted for up to 7 days. Overall, the stability of sleep hours in study 2 was significantly improved among participants in group B compared with the participants in study 1 (P=.001).

CONCLUSIONS

This is the first study to demonstrate that providing sleep feedback can benefit the modification of habitual sleep behaviors in a microrandomized trial. The findings of this study encourage the use of digitalized health intervention that uses real-time health monitoring and personalized feedback.

Population attributable fractions of modifiable risk factors for dementia: a systematic review and meta-analysis

BACKGROUND

More than 57 million people have dementia worldwide. Evidence indicates a change in dementia prevalence and incidence in high-income countries, which is likely to be due to improved life-course population health. Identifying key modifiable risk factors for dementia is essential for informing risk reduction and prevention strategies. We therefore aimed to estimate the population attributable fraction (PAF) for dementia associated with modifiable risk factors.

METHODS

In this systematic review and meta-analysis, we searched Embase, MEDLINE, and PsycINFO, via Ovid, from database inception up to June 29, 2023, for population-derived or community-based studies and reviews reporting a PAF value for one or more modifiable risk factor for later-life dementia (prevalent or incident dementia in people aged ≥60 years), with no restrictions on dementia subtype, the sex or baseline age of participants, or the period of study. Articles were independently screened for inclusion by four authors, with disagreements resolved through consensus. Data including unweighted and weighted PAF values (weighted to account for communality or overlap in risk) were independently extracted into a predefined template by two authors and checked by two other authors. When five or more unique studies investigated a given risk factor or combination of the same factors, random-effects meta-analyses were used to calculate a pooled PAF percentage estimate for the factor or combination of factors. The review protocol was registered on PROSPERO, CRD42022323429.

FINDINGS

4024 articles were identified, and 74 were included in our narrative synthesis. Overall, PAFs were reported for 61 modifiable risk factors, with sufficient data available for meta-analysis of 12 factors (n=48 studies). In meta-analyses, the highest pooled unweighted PAF values were estimated for low education (17·2% [95% CI 14·4-20·0], p<0·0001), hypertension (15·8% [14·7-17·1], p<0·0001), hearing loss (15·6% [10·3-20·9], p<0·0001), physical inactivity (15·2% [12·8-17·7], p<0·0001), and obesity (9·4% [7·3-11·7], p<0·0001). According to weighted PAF values, low education (9·3% [6·9-11·7], p<0·0001), physical inactivity (7·3% [3·9-11·2], p=0·0021), hearing loss (7·2% [5·2-9·7], p<0·0001), hypertension (7·1% [5·4-8·8], p<0·0001), and obesity (5·3% [3·2-7·4], p=0·0001) had the highest pooled estimates. When low education, midlife hypertension, midlife obesity, smoking, physical inactivity, depression, and diabetes were combined (Barnes and Yaffe seven-factor model; n=9 studies), the pooled unweighted and weighted PAF values were 55·0% (46·5-63·5; p<0·0001) and 32·0% (26·6-37·5; p<0·0001), respectively. The pooled PAF values for most individual risk factors were higher in low-income and middle-income countries (LMICs) versus high-income countries.

INTERPRETATION

Governments need to invest in a life-course approach to dementia prevention, including policies that enable quality education, health-promoting environments, and improved health. This investment is particularly important in LMICs, where the potential for prevention is high, but resources, infrastructure, budgets, and research focused on ageing and dementia are limited.

FUNDING

UK Research and Innovation (Medical Research Council).

Poor sleep quality is an important modifiable risk factor for dementia: Population attributable fraction of poor sleep in a Brazilian population-based study

OBJECTIVES

The populational impact of poor sleep quality and the risk of dementia is unclear. We analyzed the Population Attributable Fraction (PAF) of poor sleep quality for dementia, and its association with other two sleep parameters through self-reported and single questions collected in a large-scale Brazilian cohort (ELSI-Brazil).

METHODS

A subset of the ELSI-Brazil with complete responses to sleep quality was retrieved for this study. This is a large representative sample of the Brazilian elderly population with an extensive assessment of sociodemographic and health risk variables. Prevalence of poor sleep quality was estimated according to the complex sample design, and its PAF was measured using a meta-analytic relative risk. A total of 6024 (56.3% women, mean 62.8 ± 9.5 years of age) individuals had complete responses.

RESULTS

The prevalence of poor sleep quality was 24.9% (95%CI 23%-26%), and the PAF of poor sleep quality including other 10 modifiable risk factors of dementia was 52.5% in Brazil. Secondary analyses identified that sleep quality, restorative sleep and sleep drug usage varied considerably according to age ranges, race, and gender.

CONCLUSIONS

Poor sleep quality is an important populational modifiable risk factor for dementia in Brazil. Targeted interventions may provide an important impact in preventing dementia in low- and middle-income countries.

How Do Modifiable Risk Factors Affect Alzheimer's Disease Pathology or Mitigate Its Effect on Clinical Symptom Expression?

Epidemiological studies show that modifiable risk factors account for approximately 40% of the population variability in risk of developing dementia, including sporadic Alzheimer's disease (AD). Recent findings suggest that these factors may also modify disease trajectories of people with autosomal-dominant AD. With positron emission tomography imaging, it is now possible to study the disease many years before its clinical onset. Such studies can provide key knowledge regarding pathways for either the prevention of pathology or the postponement of its clinical expression. The former "resistance pathway" suggests that modifiable risk factors could affect amyloid and tau burden decades before the appearance of cognitive impairment. Alternatively, the resilience pathway suggests that modifiable risk factors may mitigate the symptomatic expression of AD pathology on cognition. These pathways are not mutually exclusive and may appear at different disease stages. Here, in a narrative review, we present neuroimaging evidence that supports both pathways in sporadic AD and autosomal-dominant AD. We then propose mechanisms for their protective effect. Among possible mechanisms, we examine neural and vascular mechanisms for the resistance pathway. We also describe brain maintenance and functional compensation as bases for the resilience pathway. Improved mechanistic understanding of both pathways may suggest new interventions.

Prediction of Cognitive Impairment Risk among Older Adults: A Machine Learning-Based Comparative Study and Model Development

INTRODUCTION

The prevalence of cognitive impairment and dementia in the older population is increasing, and thereby, early detection of cognitive decline is essential for effective intervention.

METHODS

This study included 2,288 participants with normal cognitive function from the Ma'anshan Healthy Aging Cohort Study. Forty-two potential predictors, including demographic characteristics, chronic diseases, lifestyle factors, anthropometric indices, physical function, and baseline cognitive function, were selected based on clinical importance and previous research. The dataset was partitioned into training, validation, and test sets in a proportion of 60% for training, 20% for validation, and 20% for testing, respectively. Recursive feature elimination was used for feature selection, followed by six machine learning algorithms that were employed for model development. The performance of the models was evaluated using area under the curve (AUC), specificity, sensitivity, and accuracy. Moreover, SHapley Additive exPlanations (SHAP) was conducted to access the interpretability of the final selected model and to gain insights into the impact of features on the prediction outcomes. SHAP force plots were established to vividly show the application of the prediction model at the individual level.

RESULTS

The final predictive model based on the Naive Bayes algorithm achieved an AUC of 0.820 (95% CI, 0.773-0.887) on the test set, outperforming other algorithms. The top ten influential features in the model included baseline Mini-Mental State Examination (MMSE), education, self-reported economic status, collective or social activities, Pittsburgh sleep quality index (PSQI), body mass index, systolic blood pressure, diastolic blood pressure, instrumental activities of daily living, and age. The model demonstrated the potential to identify individuals at a higher risk of cognitive impairment within 3 years from older adults.

CONCLUSION

The predictive model developed in this study contributes to the early detection of cognitive impairment in older adults by primary healthcare staff in community settings.

Associations between Physical Activity Frequency in Leisure Time and Subjective Cognitive Limitations in Middle-Aged Spanish Adults: A Cross-Sectional Study

There is a global ageing of the world's population. Ageing is associated with multiple pathologies, reductions in physical activity, and losses in cognitive function. This study aimed to analyse the associations between the frequency of leisure-time physical activity (PAF) in middle-aged Spaniards and subjective cognitive limitations (SCLs): self-reported problems for remembering or concentrating (data extracted from the 2017 National Health Survey and the 2020 European Health Survey in Spain). Furthermore, the study aimed to evaluate risk factors that could be related to a higher probability of developing SCLs. This was a cross-sectional study with 15,866 middle-aged Spaniards. The associations between FAP and SCLs were analysed using chi-square. Also, the risk factors for SCLs were evaluated using binary multiple logistic regression. The median age of participants was 55 years, with 49% men and 51% women. Associations were found between PAF and SCLs (p < 0.001). The highest prevalence of SCLs was found in physically inactive people and the lowest in very active people (13.7% vs. 5.8%, p < 0.05), and people with SCLs had a higher prevalence of inactivity than those without SCLs (47.2% vs. 33.8%, p < 0.05). Physical inactivity, low educational level, low social class, and being female were the main risk factors for SCLs. Among the actions to prevent cognitive limitations, as well as interventions in people with cognitive limitations, it would be advisable to include physical activity programmes, both as a preventive measure to delay cognitive limitations and to reduce the risk of other pathologies in people who already have them.

Instrumental activities of daily living function and cognitive status among Chinese older adults: a serial multiple mediation model

Objective

This study aimed to develop and validate a serial multiple mediation model to investigate the association between instrumental activities of daily living (IADL) function and cognitive status among older adults while exploring the underlying mechanisms.

Methods

This cross-sectional study involved 3,665 individuals aged 60 years and older who participated in the China Health and Retirement Longitudinal Survey (CHARLS). A serial multiple mediation model was utilized to explore the direct and indirect relationship between IADL function and cognitive status and whether sleep duration, social engagement, and depressive symptoms mediated this relationship.

Results

Decreased IADL function was associated with worse cognitive status [effect = -0.620, 95% CI: (-0.692, -0.540)]. Sleep duration, social participation (SP), and depressive symptoms all acted as mediators in the relationship between IADL function and cognitive status.

Conclusion

This study found both direct and indirect associations between IADL function and cognitive status, providing new insights into the effective prevention and intervention of cognitive decline among older adults.

Association of obstructive sleep apnea and sleep quality with cognitive function: a study of middle-aged and elderly persons in India

INTRODUCTION

Symptoms of obstructive sleep apnea (OSA) and poor sleep quality affect around one in ten people in India. We aimed to determine if OSA symptoms and poor sleep quality are independently associated with cognition in middle-aged and elderly urban Indian populations.

METHODS

We studied the cross-sectional association between OSA symptoms (by Berlin Questionnaire), poor sleep quality (by Pittsburgh Sleep Quality Index), and cognitive function in adults ≥ 50 years. Using a standard neuropsychological battery for cognitive function, a G-factor was derived as the first rotated principal component assessing domains of information processing, memory, and executive function. The associations of exposures with cognitive measures were modeled using linear regression, adjusted for metabolic risk factors, lifestyle factors, and psychosocial problems, followed by stratified analysis by decadal age group.

RESULTS

A total of 7505 adults were enrolled. Excluding those with MMSE < 26 (n 710), of 6795 individuals (49.2% women), mean (SD) age 64.2 (9.0) years, 38.3% had high risk of OSA symptoms, and 15.9% had poor sleep quality. OSA symptoms were negatively associated with cognitive domains of information processing (adjusted beta coefficient of z-score - 0.02, p-value 0.006), memory (- 0.03, 0.014), and G-factor (- 0.11, 0.014) in full-model. Stratified analysis by age group showed significant adverse effects of OSA symptoms on cognition for middle-aged people (50-60 years) (- 0.26, 0.001), but not in later age groups. Poor sleep quality was also associated with lower cognitive scores for G-factor (- 0.48, < 0.001), memory (- 0.08, 0.005), and executive domains (- 0.12, < 0.001), but not with information domain.

CONCLUSION

The findings suggest that both symptoms of OSA and poor sleep quality have a direct adverse impact on cognition in an Indian setting. A modest effect of age on the relationship of OSA and cognition was also observed.

Sleep architecture and the incidence of depressive symptoms in middle-aged and older adults: A community-based study

BACKGROUND

Rapid eye movement (REM) sleep and three stages of non-REM (NREM) sleep comprise the full sleep cycle. The changes in sleep have been linked to depression risk. This study aimed to explore the association between sleep architecture and depressive symptoms.

METHODS

A total of 3247 participants from the Sleep Heart Health Study (SHHS) were included in this cohort study. REM and NREM sleep were monitored by in-home polysomnography at SHHS visit 1. Depressive symptoms was reported as the first occurrence between SHHS visits 1 and 2 (mean follow-up of 5.3 years). Multivariable logistic regression was used to investigate the relationship between sleep stages and depressive symptoms.

RESULTS

In total, 225 cases of depressive symptoms (6.9 %) were observed between SHHS visits 1 and 2. A significant linear association between NREM Stage 1 and depressive symptoms was found after adjusting for potential covariates. Multivariable logistic regression analysis showed that percentage in NREM Stage 1 was associated with the incidence of depressive symptoms (odds ratio [OR], 1.06; 95 % confidence interval [CI], 1.02-1.10; P = 0.001), as were time in NREM Stage 1 and depressive symptoms (OR, 1.02; 95 % CI, 1.01-1.03; P = 0.001). However, no significant association with depressive symptoms was found for other sleep stage.

LIMITATIONS

The specific follow-up time for depressive symptoms diagnosis was missing.

CONCLUSIONS

Increased time or percentage in NREM Stage 1 was associated with a higher risk of developing depressive symptoms. The early change in sleep architecture were important for incidence of depressive symptoms and warrants constant concerns.

Vitamin D Deficiency Exacerbates Poor Sleep Outcomes with Endocrine-Disrupting Chemicals Exposure: A Large American Population Study

Phthalates and bisphenol A are recognized as the predominant endocrine-disrupting substances (EDCs) in the environment, but their impact on sleep health remains unclear. Vitamin D has often been reported to play a role in sleep health and may be affected by endocrine-disrupting compounds. The study utilized data from 5476 individuals in the NHANES project to investigate the correlation between combined exposure to environmental EDCs and sleep duration through modeling various exposures. Furthermore, it emphasizes the importance of vitamin D in the present scenario. Preliminary analyses suggested that vitamin D-deficient individuals generally slept shorter than individuals with normal vitamin D (p < 0.05). Exposure to Mono-ethyl phthalate (MEP), triclosan (TRS), and Mono-benzyl phthalate (MZP), either alone or in combination, was associated with reduced sleep duration and a greater risk of vitamin D deficiency. Individuals with low vitamin D levels exposed to TRS experienced shorter sleep duration than those with normal vitamin D levels (p < 0.05). TRS and MZP were identified as crucial factors in patient outcomes when evaluating mixed exposures (p < 0.05). The results provide new data supporting a link between exposure to EDCs and insufficient sleep length. Additionally, they imply that a vitamin D shortage may worsen the sleep problems induced by EDCs.

Association of objective sleep duration with cognition and brain aging biomarkers in older adults

The neuropathological mechanisms underlying the association between sleep duration and mild cognitive impairment remain poorly understood. This population-based study included 2032 dementia-free people (age ≥ 60 years; 55.1% women) derived from participants in the Multimodal Interventions to Delay Dementia and Disability in Rural China; of these, data were available in 841 participants for Alzheimer's plasma biomarkers (e.g. amyloid-β, total tau and neurofilament light chain), 1044 for serum microvascular biomarkers (e.g. soluble adhesion molecules) and 834 for brain MRI biomarkers (e.g. whiter matter, grey matter, hippocampus, lacunes, enlarged perivascular spaces and white matter hyperintensity WMH). We used electrocardiogram-based cardiopulmonary coupling analysis to measure sleep duration, a neuropsychological test battery to assess cognitive function and the Petersen's criteria to define mild cognitive impairment. Data were analysed with multivariable logistic and general linear models. In the total sample (n = 2032), 510 participants were defined with mild cognitive impairment, including 438 with amnestic mild cognitive impairment and 72 with non-amnestic mild cognitive impairment. Long sleep duration (>8 versus 6-8 h) was significantly associated with increased likelihoods of mild cognitive impairment and non-amnestic mild cognitive impairment and lower scores in global cognition, verbal fluency, attention and executive function (Bonferroni-corrected P < 0.05). In the subsamples, long sleep duration was associated with higher plasma amyloid-β40 and total tau, a lower amyloid-β42/amyloid-β40 ratio and smaller grey matter volume (Bonferroni-corrected P < 0.05). Sleep duration was not significantly associated with serum-soluble adhesion molecules, white matter hyperintensity volume, global enlarged perivascular spaces and lacunes (P > 0.05). Alzheimer's and neurodegenerative pathologies may represent common pathways linking long sleep duration with mild cognitive impairment and low cognition in older adults.

Noradrenaline enhances Na-K ATPase subunit expression by HuR-induced mRNA stabilization and their transportation to the cell surface through PLC and PKC mediated pathway: Implications with REMS-loss associated disorders

Rapid eye movement sleep (REMS) maintains brain excitability at least by regulating Na-K ATPase activity. Although REMS deprivation (REMSD)-associated elevated noradrenaline (NA) increases Na-K ATPase protein expression, its mRNA transcription did not increase. We hypothesized and confirmed both in vivo as well as in vitro that elevated mRNA stability explains the apparent puzzle. The mRNA stability was measured in control and REMSD rat brain with or without in vivo treatment with α1-adrenoceptor (AR) antagonist, prazosin (PRZ). Upon REMSD, Na-K ATPase α1-, and α2-mRNA stability increased significantly, which was prevented by PRZ. To decipher the molecular mechanism of action, we estimated NA-induced Na-K ATPase mRNA stability in Neuro-2a cells under controlled conditions and by transcription blockage using Actinomycin D (Act-D). NA increased Na-K ATPase mRNA stability, which was prevented by PRZ and propranolol (PRP, β-AR antagonist). The knockdown assay confirmed that the increased mRNA stabilization was induced by elevated cytoplasmic abundance of Human antigen R (HuR) and involving (Phospholipase C) PLC-mediated activation of Protein Kinase C (PKC). Additionally, using cell-impermeable Enz-link sulfo NHS-SS-Biotin, we observed that NA increased Na-K ATPase α1-subunits on the Neuro-2a cell surface. We conclude that REMSD-associated elevated NA, acting on α1- and β-AR, increases nucleocytoplasmic translocation of HuR and increases Na-K ATPase mRNA stability, resulting in increased Na-K ATPase protein expression. The latter then gets translocated to the neuronal membrane surface involving both PKC and (Protein Kinase A) PKA-mediated pathways. These findings may be exploited for the amelioration of REMSD-associated chronic disorders and symptoms.

Chronic sleep fragmentation impairs brain interstitial clearance in young wildtype mice

Accumulating evidence shows that most chronic neurological diseases have a link with sleep disturbances, and that patients with chronically poor sleep undergo an accelerated cognitive decline. Indeed, a single-night of sleep deprivation may increase metabolic waste levels in cerebrospinal fluid. However, it remains unknown how chronic sleep disturbances in isolation from an underlying neurological disease may affect the glymphatic system. Clearance of brain interstitial waste by the glymphatic system occurs primarily during sleep, driven by multiple oscillators including arterial pulsatility, and vasomotion. Herein, we induced sleep fragmentation in young wildtype mice and assessed the effects on glymphatic activity and cognitive functions. Chronic sleep fragmentation reduced glymphatic function and impaired cognitive functions in healthy mice. A mechanistic analysis showed that the chronic sleep fragmentation suppressed slow vasomotion, without altering cardiac-driven pulsations. Taken together, results of this study document that chronic sleep fragmentation suppresses brain metabolite clearance and impairs cognition, even in the absence of disease.

Investigation of the shared biological mechanisms and common biomarker APTAF1 of sleep deprivation and mild cognitive impairment using integrated bioinformatics analysis

Introduction: The relationship between sleep loss and cognitive impairment has long been widely recognized, but there is still a lack of complete understanding of the underlying mechanisms and potential biomarkers. The purpose of this study is to further explore the shared biological mechanisms and common biomarkers between sleep loss and cognitive impairment. Methods: The mitochondria-related genes and gene expression data were downloaded from the MitoCarta3.0 and Gene Expression Omnibus (GEO) databases. We identified the differentially expressed mitochondrial-related genes by combing the differentially expressed genes (DEGs) in sleep deprivation (SD) and mild cognitive impairment (MCI) datasets with mitochondria-related gene lists. Shared DEGs were then further analyzed for enrichment analysis. Next, the common biomarker was identified using two machine learning techniques and further validated using two independent GEO datasets. Then GSEA and GSVA were conducted to analyze the functional categories and pathways enriched for the common biomarker. Finally, immune infiltration analysis was used to investigate the correlation of immune cell infiltration with the common biomarker in SD and MCI. Results: A total of 32 mitochondrial-related differentially expressed genes were identified in SD and MCI. GO analysis indicated that these genes were significantly enriched for mitochondrial transport, and KEGG analysis showed they were mainly involved in pathways of neurodegenerative diseases. In addition, ATPAF1, which was significantly down-regulated in both SD and MCI, was identified through machine learning algorithms as the common biomarker with favorable diagnostic performance. GSEA and GSVA revealed that ATPAF1 was mainly involved in metabolic pathways, such as oxidative phosphorylation, acetylcholine metabolic process, valine, leucine and isoleucine degradation. Immune infiltration analysis showed that the expression of ATPAF1 was correlated with changes in immune cells, especially those key immune cell types associated with SD and MCI. Discussion: This study firstly revealed that mitochondrial dysfunction may be the common pathogenesis of sleep loss and mild cognitive impairment and identified ATPAF1 as a possible biomarker and therapeutic target involved in SD and MCI.

Socially-supported sleep in older adults aged 50 and older: a concept analysis

Introduction

The population of older adults is growing disproportionately, constituting 13% of the global population in 2022, and is expected to double by 2050. One of public health's priorities is healthy aging, the maintenance of functional ability aligned with well-being. As many as 50% of older adults report poor sleep quality, leading to an increased risk of morbidity and mortality. The quality and quantity of social relationships may broadly benefit sleep in older adults. However, the concept of socially-supported sleep is underdeveloped as a basis for intervention.

Methods

Existing literature was searched without time restriction in PubMed, CINAHL, PsycINFO, and Scopus ending in August 2022. Thematic analysis was used to determine the defining attributes, antecedents, and consequences of socially-supported sleep guided by Rodgers' evolutionary concept analysis.

Results

Twenty-nine articles written in English, peer-reviewed, and examined social support and sleep in participants aged ≥50 were included. The defining attributes reflect dimensions of sleep quality. The antecedents are safe and secure, belonging and connection, and warmth and comfort. The consequences of socially-supported sleep include improved regulatory capabilities, physical and emotional well-being, and quality of life.

Conclusion

Socially-supported sleep has the potential to inform interventions that promote sleep in older adults. Ongoing research is needed to address the antecedents and mechanisms through which socially-supported sleep may promote sleep quality for healthy aging.

Social and Behavior Factors of Alzheimer's Disease and Related Dementias: A National Study in the U.S

INTRODUCTION

Considerable research has linked many risk factors to Alzheimer's Disease and Related Dementias (ADRD). Without a clear etiology of ADRD, it is advantageous to rank the known risk factors by their importance and determine if disparities exist. Statistical-based ranking can provide insight into which risk factors should be further evaluated.

METHODS

This observational, population-based study assessed 50 county-level measures and estimates related to ADRD in 3,155 counties in the U.S. using data from 2010 to 2021. Statistical analysis was performed in 2022-2023. The machine learning method, eXtreme Gradient Boosting, was utilized to rank the importance of these variables by their relative contribution to the model performance. Stratified ranking was also performed based on a county's level of disadvantage. Shapley Additive exPlanations (SHAP) provided marginal contributions for each variable.

RESULTS

The top three ranked predictors at the county level were insufficient sleep, consuming less than one serving of fruits/vegetables per day among adults, and having less than a high school diploma. In both disadvantaged and non-disadvantaged counties, demographic variables such as sex and race were important in predicting ADRD. Lifestyle factors ranked highly in non-disadvantaged counties compared to more environmental factors in disadvantaged counties.

CONCLUSIONS

This ranked list of factors can provide a guided approach to ADRD primary prevention strategies in the U.S., as the effects of sleep, diet, and education on ADRD can be further developed. While sleep, diet, and education are important nationally, differing prevention strategies could be employed based on a county's level of disadvantage.

Associations of 24-Hour Rest-Activity Rhythm Fragmentation, Cognitive Decline, and Postmortem Locus Coeruleus Hypopigmentation in Alzheimer's Disease

OBJECTIVE

While studies suggested that locus coeruleus (LC) neurodegeneration contributes to sleep-wake dysregulation in Alzheimer's disease (AD), the association between LC integrity and circadian rest-activity patterns remains unknown. Here, we investigated the relationships between 24-hour rest-activity rhythms, cognitive trajectories, and autopsy-derived LC integrity in older adults with and without cortical AD neuropathology.

METHODS

This retrospective study leveraged multi-modal data from participants of the longitudinal clinical-pathological Rush Memory and Aging Project. Indices of 24-hour rest-activity rhythm fragmentation (intradaily variability) and stability (interdaily stability) were extracted from annual actigraphic recordings, and cognitive trajectories were computed from annual cognitive evaluations. At autopsy, LC neurodegeneration was determined by the presence of hypopigmentation, and cortical AD neuropathology was assessed. Contributions of comorbid pathologies (Lewy bodies, cerebrovascular pathology) were evaluated.

RESULTS

Among the 388 cases included in the study sample (age at death = 92.1 ± 5.9 years; 273 women), 98 (25.3%) displayed LC hypopigmentation, and 251 (64.7%) exhibited cortical AD neuropathology. Logistic regression models showed that higher rest-activity rhythm fragmentation, measured up to ~7.1 years before death, was associated with increased risk to display LC neurodegeneration at autopsy (odds ratio [OR] = 1.46, 95% confidence interval [CI95%]: 1.16-1.84, pBONF = 0.004), particularly in individuals with cortical AD neuropathology (OR = 1.56, CI95%: 1.15-2.15, pBONF = 0.03) and independently of comorbid pathologies. In addition, longitudinal increases in rest-activity rhythm fragmentation partially mediated the association between LC neurodegeneration and cognitive decline (estimate = -0.011, CI95%: -0.023--0.002, pBONF = 0.03).

INTERPRETATION

These findings highlight the LC as a neurobiological correlate of sleep-wake dysregulation in AD, and further underscore the clinical relevance of monitoring rest-activity patterns for improved detection of at-risk individuals. ANN NEUROL 2024;95:653-664.

Associations of sleep disorders with all-cause MCI/dementia and different types of dementia - clinical evidence, potential pathomechanisms and treatment options: A narrative review

Due to worldwide demographic change, the number of older persons in the population is increasing. Aging is accompanied by changes of sleep structure, deposition of beta-amyloid (Aß) and tau proteins and vascular changes and can turn into mild cognitive impairment (MCI) as well as dementia. Sleep disorders are discussed both as a risk factor for and as a consequence of MCI/dementia. Cross-sectional and longitudinal population-based as well as case-control studies revealed sleep disorders, especially sleep-disorderded breathing (SDB) and excessive or insufficient sleep durations, as risk factors for all-cause MCI/dementia. Regarding different dementia types, SDB was especially associated with vascular dementia while insomnia/insufficient sleep was related to an increased risk of Alzheimer's disease (AD). Scarce and still inconsistent evidence suggests that therapy of sleep disorders, especially continuous positive airway pressure (CPAP) in SDB, can improve cognition in patients with sleep disorders with and without comorbid dementia and delay onset of MCI/dementia in patients with sleep disorders without previous cognitive impairment. Regarding potential pathomechanisms via which sleep disorders lead to MCI/dementia, disturbed sleep, chronic sleep deficit and SDB can impair glymphatic clearance of beta-amyloid (Aß) and tau which lead to amyloid deposition and tau aggregation resulting in changes of brain structures responsible for cognition. Orexins are discussed to modulate sleep and Aß pathology. Their diurnal fluctuation is suppressed by sleep fragmentation and the expression suppressed at the point of hippocampal atrophy, contributing to the progression of dementia. Additionally, sleep disorders can lead to an increased vascular risk profile and vascular changes such as inflammation, endothelial dysfunction and atherosclerosis which can foster neurodegenerative pathology. There is ample evidence indicating that changes of sleep structure in aging persons can lead to dementia and also evidence that therapy of sleep disorder can improve cognition. Therefore, sleep disorders should be identified and treated early.

Sleep disturbances and change in multiple cognitive domains among older adults: a multicenter study of five Nordic cohorts

STUDY OBJECTIVES

We examined and compared cross-sectional and longitudinal associations between self-reported sleep disturbances and various cognitive domains in five separate Nordic European longitudinal aging studies (baseline N = 5631, mean age = 77.7, mean follow-up = 4.16 years).

METHODS

Comparable sleep parameters across studies included reduced sleep duration/quality, insomnia symptoms (sleep latency, waking up at night, and early awakenings), short and long sleep duration, and daytime napping. The cognitive domains were episodic memory, verbal fluency, perceptual speed, executive functioning, and global cognition (aggregated measure). A series of mixed linear models were run separately in each study and then compared to assess the level and rate of change in cognitive functioning across each sleep disturbance parameter. Models were adjusted for age, sex, education, hypnotic usage, depressive symptoms, lifestyle factors, cardiovascular, and metabolic conditions. By using a coordinated analytic approach, comparable construct-level measurements were generated, and results from identical statistical models were qualitatively compared across studies.

RESULTS

While the pattern of statistically significant results varied across studies, subjective sleep disturbances were consistently associated with worse cognition and steeper cognitive decline. Insomnia symptoms were associated with poorer episodic memory and participants sleeping less or more than 7-8 hours had a steeper decline in perceptual speed. In addition, daytime napping (>2 hours) was cross-sectionally and longitudinally associated with all examined cognitive domains. Most observed associations were study-specific (except for daytime napping), and a majority of association estimates remained significant after adjusting for covariates.

CONCLUSION

This rigorous multicenter investigation further supports the importance of sleep disturbance, including insomnia, long and short sleep duration, and daytime napping on baseline cognitive functioning and rate of change among older adults. These sleep factors may be targeted in future lifestyle interventions to reduce cognitive decline.

The effects of physical activity on sleep architecture and mood in naturalistic environments

Physical activity has been found to alter sleep architecture, but these effects have been studied predominantly in the laboratory and the generalizability of these findings to naturalistic environments and longer time intervals, as well as their psychological effects, have not been evaluated. Recent technological advancements in wearable devices have made it possible to capture detailed measures of sleep outside the lab, including timing of specific sleep stages. In the current study, we utilized photoplethysmography coupled with accelerometers and smartphone ambulatory assessment to collect daily measurements of sleep, physical activity and mood in a sample of N = 82 over multi-month data collection intervals. We found a robust inverse relationship between sedentary behavior and physical activity and sleep architecture: both low-intensity and moderate-to-vigorous physical activity were associated with increased NREM sleep and decreased REM sleep, as well as a longer REM latency, while higher levels of sedentary behavior showed the opposite pattern. A decreased REM/NREM ratio and increased REM latency were in turn associated with improved wellbeing, including increased energy, reduced stress and enhanced perceived restfulness of sleep. Our results suggest that physical activity and sleep account for unique variance in a person's mood, suggesting that these effects are at least partially independent.

Global prevalence of poor sleep quality in cancer patients: A systematic review and meta-analysis

OBJECTIVE

Poor sleep quality is common in patients with cancer, but the prevalence rates varied widely across studies. This systematic review and meta-analysis examined the pooled prevalence of poor sleep quality among patients with cancer.

METHODS

Systematic literature searches were independently conducted in the major databases (Web of Science, PubMed, EMBASE and PsycINFO). Studies that reported the prevalence of poor sleep quality in patients with cancer were analyzed using a random effects model. Funnel plots and Egger's tests were used to assess publication bias. Statistical analyses were performed using R software.

RESULTS

A total of 59 epidemiological studies involving 16,223 patients were included. The pooled prevalence of poor sleep quality in patients with cancer was 57.4% [95% confidence interval (CI): 53.3% - 61.6%]. Additionally, three comparative studies with 372 patients and 412 healthy controls were included. Compared to healthy controls, patients with cancer had a significantly higher risk for poor sleep quality [odd ratio (OR) = 3.0; 95%CI: 1.2-7.2; P < 0.05]. Subgroup analyses of the studies revealed that studies from Middle East & North Africa region and low income countries, and on gynecological cancer as well as those with a lower cut-off value of sleep quality (all P < 0.01) reported a higher prevalence of poor sleep quality. Meta-regression analyses showed that higher prevalence of poor sleep quality was associated with higher prevalence of comorbid depression (P < 0.05) and anxiety (P < 0.01), but was associated with a lower education level (P < 0.05) and alcohol use ratio (P < 0.05).

CONCLUSION

Poor sleep quality is common among patients with cancer. Considering the overall high prevalence rate and negative impact of poor sleep quality, appropriate measures to identify and improve poor sleep quality are needed to enhance the clinical outcomes in this group.

Individual sleep need is flexible and dynamically related to cognitive function

Given that sleep deprivation studies consistently show that short sleep causes neurocognitive deficits, the effects of insufficient sleep on brain health and cognition are of great interest and concern. Here we argue that experimentally restricted sleep is not a good model for understanding the normal functions of sleep in naturalistic settings. Cross-disciplinary research suggests that human sleep is remarkably dependent on environmental conditions and social norms, thus escaping universally applicable rules. Sleep need varies over time and differs between individuals, showing a complex relationship with neurocognitive function. This aspect of sleep is rarely addressed in experimental work and is not reflected in expert recommendations about sleep duration. We recommend focusing on the role of individual and environmental factors to improve our understanding of the relationship between human sleep and cognition.

Impact of sleep duration and sleep disturbances on the incidence of dementia and Alzheimer's disease: A 10-year follow-up study

The nature of the relationship between sleep problems and dementia remains unclear. This study investigated the relationship between sleep measures and dementia in older adults (≥ 65) using data from the English Longitudinal Study of Ageing (ELSA) and further investigated the causal association in Mendelian randomization (MR) analysis. In total of 7,223 individuals, 5.7 % developed dementia (1.7 % Alzheimer's disease (AD)) within an average of 8 (± 2.9) years. Cox regression models and MR were employed. Long sleep duration (>8 h) was associated with 64 % increased risk of incident dementia and 2-fold high risk of AD compared to ideal sleep duration (7-8 h). This association was particularly evident in older-older adults (≥70 years) and those who consumed alcohol. Short sleep duration (<7 h) was associated with lower risk of incident dementia among older-older but higher risk among younger-older adults. Sleep disturbances and perceived sleep quality were not associated with dementia or AD. The MR study did not reveal causal associations between sleep duration and dementia. These findings suggest that self-reported short sleep in younger-older and long sleep in older-older adults and those with frequent alcohol consumption are associated with dementia. Early detection of these sleep patterns may help identify individuals at higher dementia risk.

Nonlinear association between self-reported sleep duration and cognitive function among middle-aged and older adults in China: The moderating effect of informal care

BACKGROUND

Cognitive impairment is a major public health problem urgently to be solved. This study aims to examine the association between sleep duration and cognitive function and its two subdimensions: episodic memory and mental status, and to explore the moderating effects of informal care on these associations among middle-aged and older adults in China.

METHODS

Data was drawn from China Health and Retirement Longitudinal Study (CHARLS) 2011, 2013, 2015 and 2018 datasets. Sleep duration and informal care were self-reported. Cognitive function was measured using CHARLS Harmonized Cognitive Assessment Protocol. Effects of informal care on sleep duration-cognitive function were assessed using Generalized Estimating Equations models.

RESULTS

The relationships between sleep duration and cognitive function, episodic memory, and mental status were all found to follow an inverted U-shaped pattern. Spouse care weakened the adverse effects of extreme sleep duration on cognitive function while the children care amplified them. Further, we only observed the moderating effects of spouse and children care on the association between sleep duration and episodic memory, but not mental status.

CONCLUSIONS

The relationships between sleep duration and cognitive function, along with its different dimensions, are nonlinear in nature. The impacts of sleep duration on cognitive function and its dimensions are contingent upon the levels of informal care received and the sources of that care. We provide valuable insights into the complex interplay between sleep duration, informal care, and cognitive function.

Potentially Modifiable Risk Factors for Dementia and Mild Cognitive Impairment: An Umbrella Review and Meta-Analysis

INTRODUCTION

The prevalence of mild and major neurocognitive disorders (NCDs), also referred to as mild cognitive impairment and dementia, is rising globally. The prevention of NCDs is a major global public health interest. We sought to synthesize the literature on potentially modifiable risk factors for NCDs.

METHODS

We conducted an umbrella review using a systematic search across multiple databases to identify relevant systematic reviews and meta-analyses. Eligible reviews examined potentially modifiable risk factors for mild or major NCDs. We used a random-effects multi-level meta-analytic approach to synthesize risk ratios for each risk factor while accounting for overlap in the reviews. We further examined risk factors for major NCD due to two common etiologies: Alzheimer's disease and vascular dementia.

RESULTS

A total of 45 reviews with 212 meta-analyses were synthesized. We identified fourteen broadly defined modifiable risk factors that were significantly associated with these disorders: alcohol consumption, body weight, depression, diabetes mellitus, diet, hypertension, less education, physical inactivity, sensory loss, sleep disturbance, smoking, social isolation, traumatic brain injury, and vitamin D deficiency. All 14 factors were associated with the risk of major NCD, and five were associated with mild NCD. We found considerably less research for vascular dementia and mild NCD.

CONCLUSION

Our review quantifies the risk associated with 14 potentially modifiable risk factors for mild and major NCDs, including several factors infrequently included in dementia action plans. Prevention strategies should consider approaches that reduce the incidence and severity of these risk factors through health promotion, identification, and early management.

Comparative study of machine learning methods for modeling associations between risk factors and future dementia cases

A substantial portion of dementia risk can be attributed to modifiable risk factors that can be affected by lifestyle changes. Identifying the contributors to dementia risk could prove valuable. Recently, machine learning methods have been increasingly applied to healthcare data. Several studies have attempted to predict dementia progression by using such techniques. This study aimed to compare the performance of different machine-learning methods in modeling associations between known cognitive risk factors and future dementia cases. A subset of the AGES-Reykjavik Study dataset was analyzed using three machine-learning methods: logistic regression, random forest, and neural networks. Data were collected twice, approximately five years apart. The dataset included information from 1,491 older adults who underwent a cognitive screening process and were considered to have healthy cognition at baseline. Cognitive risk factors included in the models were based on demographics, MRI data, and other health-related data. At follow-up, participants were re-evaluated for dementia using the same cognitive screening process. Various performance metrics for all three machine learning algorithms were assessed. The study results indicate that a random forest algorithm performed better than neural networks and logistic regression in predicting the association between cognitive risk factors and dementia. Compared to more traditional statistical analyses, machine-learning methods have the potential to provide more accurate predictions about which individuals are more likely to develop dementia than others.

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

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

Poor sleep quality in schizophrenia patients: A systematic review and meta-analyses of epidemiological and case-control studies

OBJECTIVE

Poor sleep quality is common in patients with schizophrenia but estimated prevalence rates in this population have been mixed. This systematic review and meta-analysis examined the prevalence of poor sleep quality in schizophrenia samples and moderators of prevalence from epidemiological studies as well as the risk of poor sleep quality in schizophrenia patients based on case-control studies.

METHODS

Both international (PubMed, Web of Science, PsycINFO, EMBASE) and Chinese databases [Chinese Nation knowledge Infrastructure (CNKI) and WANFANG] were systematically searched. Studies that estimated the prevalence of poor sleep quality in schizophrenia were analyzed using a random effects model. Funnel plots and Egger's tests were used to assess publication bias. Statistical analyses were performed using R software.

RESULTS

In total, 23 epidemiological studies and nine case-control studies were included. Based on the epidemiological studies, the pooled overall prevalence of poor sleep quality was 63.4 % [95 % confidence interval (CI): 57.0 %-69.9 %]. Additionally, based on the nine case-control studies, schizophrenia patients had a significantly higher risk for poor sleep quality compared to healthy controls [odd ratio (OR) = 4.5; 95%CI: 2.4-8.3; P < 0.0001].

CONCLUSION

Poor sleep quality is common among schizophrenia patients. Considering negative outcomes caused by poor sleep quality, regular screening on poor sleep quality should be conducted and effective interventions should be provided to those in need.

Sleep in Healthy and Pathological Aging

Human sleep physiology is strongly affected by age [...].

Orexin Receptor Antagonism: Normalizing Sleep Architecture in Old Age and Disease

Sleep is essential for human well-being, yet the quality and quantity of sleep reduce as age advances. Older persons (>65 years old) are more at risk of disorders accompanied and/or exacerbated by poor sleep. Furthermore, evidence supports a bidirectional relationship between disrupted sleep and Alzheimer's disease (AD) or related dementias. Orexin/hypocretin neuropeptides stabilize wakefulness, and several orexin receptor antagonists (ORAs) are approved for the treatment of insomnia in adults. Dysregulation of the orexin system occurs in aging and AD, positioning ORAs as advantageous for these populations. Indeed, several clinical studies indicate that ORAs are efficacious hypnotics in older persons and dementia patients and, as in adults, are generally well tolerated. ORAs are likely to be more effective when administered early in sleep/wake dysregulation to reestablish good sleep/wake-related behaviors and reduce the accumulation of dementia-associated proteinopathic substrates. Improving sleep in aging and dementia represents a tremendous opportunity to benefit patients, caregivers, and health systems.