Sleep and its regulation: An emerging pathogenic and treatment frontier in Alzheimer's disease

Voltage Gated Ion Channels and Sleep

Ion channels are integral components of the nervous system, playing a pivotal role in shaping membrane potential, neuronal excitability, synaptic transmission and plasticity. Dysfunction in these channels, such as improper expression or localization, can lead to irregular neuronal excitability and synaptic communication, which may manifest as various behavioral abnormalities, including disrupted rest-activity cycles. Research has highlighted the significant impact of voltage gated ion channels on sleep parameters, influencing sleep latency, duration and waveforms. Furthermore, these ion channels have been implicated in the vulnerability to, and the pathogenesis of, several neurological and psychiatric disorders, including epilepsy, autism, schizophrenia, and Alzheimer's disease (AD). In this comprehensive review, we aim to provide a summary of the regulatory role of three predominant types of voltage-gated ion channels-calcium (Ca2+), sodium (Na+), and potassium (K+)-in sleep across species, from flies to mammals. We will also discuss the association of sleep disorders with various human diseases that may arise from the dysfunction of these ion channels, thereby underscoring the potential therapeutic benefits of targeting specific ion channel subtypes for sleep disturbance treatment.

Prevalence of cognitive impairment and its associated factors in middle-aged and elderly people in Anhui Province, China: An observational study

To understand the prevalence of cognitive impairment (CI) in middle-aged and elderly individuals in Anhui Province and to develop a CI risk prediction model. From May to June 2022, a multistage, stratified cluster-sampling method was used to select 3200 middle-aged and elderly people over 45 years old in Anhui Province for a questionnaire survey, and the Chinese version of the Mini-Mental State Examination (MMSE) was used to assess cognitive function. SPSS 25.0 was used for univariate and multivariate analyses, and R software was used to establish and validate the nomogram. A total of 3059 valid questionnaires were included, of which 384 were from participants who were diagnosed with CI, and the prevalence rate was 12.6%. Multivariate logistic analysis showed that female sex, advanced age, family history, etc., were closely related to the occurrence of CI. The area under curve (AUC) values in the modeling and validation groups were 0.845 (95% CI: 0.822-0.868) and 0.868 (95% CI: 0.835-0.902), respectively, indicating that the predictive ability of the model was good. The Hosmer-Lemeshow test suggested that the model had good goodness-of-fit, and the decision-curve evaluation nomogram had a high benefit within the threshold, which had a certain clinical importance. The prevalence rate of CI among middle-aged and elderly individuals in Anhui Province was 12.6%. Female sex, elderly age, family history, low educational status, current smoking status, sleep disorders, hypertension, stroke, and diabetes were shown to be risk factors for CI, while exercise was shown to be a protective factor.

Circadian rhythm disruption and retinal dysfunction: a bidirectional link in Alzheimer's disease?

Dysfunction in circadian rhythms is a common occurrence in patients with Alzheimer's disease. A predominant function of the retina is circadian synchronization, carrying information to the brain through the retinohypothalamic tract, which projects to the suprachiasmatic nucleus. Notably, Alzheimer's disease hallmarks, including amyloid-β, are present in the retinas of Alzheimer's disease patients, followed/associated by structural and functional disturbances. However, the mechanistic link between circadian dysfunction and the pathological changes affecting the retina in Alzheimer's disease is not fully understood, although some studies point to the possibility that retinal dysfunction could be considered an early pathological process that directly modulates the circadian rhythm.

Rescuing impaired hippocampal-cortical interactions and spatial reorientation learning and memory during sleep in a mouse model of Alzheimer's disease using hippocampal 40 Hz stimulation

In preclinical Alzheimer's disease (AD), spatial learning and memory is impaired. We reported similar impairments in 3xTg-AD mice on a virtual maze (VM) spatial-reorientation-task that requires using landmarks to navigate. Hippocampal (HPC)-cortical dysfunction during sleep (important for memory consolidation) is a potential mechanism for memory impairments in AD. We previously found deficits in HPC-cortical coordination during sleep coinciding with VM impairments the next day. Some forms of 40 Hz stimulation seem to clear AD pathology in mice, and improve functional connectivity in AD patients. Thus, we implanted a recording array targeting parietal cortex (PC) and HPC to assess HPC-PC coordination, and an optical fiber targeting HPC for 40 Hz or sham optogenetic stimulation in 3xTg/PV cre mice. We assessed PC delta waves (DW) and HPC sharp wave ripples (SWRs). In sham mice, SWR-DW cross-correlations were reduced, similar to 3xTg-AD mice. In 40 Hz mice, this phase-locking was rescued, as was performance on the VM. However, rescued HPC-PC coupling no longer predicted performance as in NonTg animals. Instead, DWs and SWRs independently predicted performance in 40 Hz mice. Thus, 40 Hz stimulation of HPC rescued functional interactions in the HPC-PC network, and rescued impairments in spatial navigation, but did not rescue the correlation between HPC-PC coordination during sleep and learning and memory. Together this pattern of results could inform AD treatment timing by suggesting that despite applying 40 Hz stimulation before significant tau and amyloid aggregation, pathophysiological processes led to brain changes that were not fully reversed even though cognition was recovered.

Significance Statement

One of the earliest symptoms of Alzheimer's disease (AD) is getting lost in space or experiencing deficits in spatial navigation, which involve navigation computations as well as learning and memory. We investigated cross brain region interactions supporting memory formation as a potential causative factor of impaired spatial learning and memory in AD. To assess this relationship between AD pathophysiology, brain changes, and behavioral alterations, we used a targeted approach for clearing amyloid beta and tau to rescue functional interactions in the brain. This research strongly connects brain activity patterns during sleep to tau and amyloid accumulation, and will aid in understanding the mechanisms underlying cognitive dysfunction in AD. Furthermore, the results offer insight for improving early identification and treatment strategies.

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.

Associations Between Repetitive Negative Thinking and Objective and Subjective Sleep Health in Cognitively Healthy Older Adults

Objective

Poor sleep and high levels of repetitive negative thinking (RNT), including future-directed (ie, worry) and past-directed (ie, brooding) negative thoughts, have been associated with markers of dementia risk. The relationship between RNT and sleep health in older adults is unknown. This study aimed to investigate this association and its specificities including multiple dimensions of objective and subjective sleep.

Methods

This study used a cross sectional quantitative design with baseline data from 127 cognitively healthy older adults (mean age 69.4 ± 3.8 years; 63% female) who took part in the Age-Well clinical trial, France. RNT (ie, worry and brooding) levels were measured using the Penn State Worry Questionnaire and the Rumination Response Scale (brooding subscale). Polysomnography was used to assess sleep objectively, and the Pittsburgh Sleep Quality Index and the St. Mary's Hospital Sleep Questionnaire were used to measure sleep subjectively. In primary analyses the associations between RNT and sleep (ie, objective sleep duration, fragmentation and efficiency and subjective sleep disturbance) were assessed via adjusted regressions.

Results

Higher levels of RNT were associated with poorer objective sleep efficiency (worry: β=-0.32, p<0.001; brooding: β=-0.26, p=0.002), but not objective sleep duration, fragmentation, or subjective sleep disturbance. Additional analyses, however, revealed differences in levels of worry between those with short, compared with typical and long objective sleep durations (p < 0.05).

Conclusion

In cognitively healthy older adults, RNT was associated with sleep characteristics that have been implicated in increased dementia risk. It will take additional research to ascertain the causal link between RNT and sleep characteristics and how they ultimately relate to the risk of developing dementia.

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

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

[Sleep and dementia]

Aging is associated with changes in sleep structure and cerebral deposition of amyloid beta and tau proteins. Sleep disturbances precede the onset of dementia by years. Comorbid sleep disorders, such as insomnia and sleep-disordered breathing, a family history of dementia and epigenetic factors can contribute to the development of dementia. This article explores the question of the interaction between sleep and dementia based on the existing literature. Alterations caused by slow wave sleep lead to changes in the glymphatic clearance of amyloid beta, tau proteins and other proteins. Transient and chronic sleep disorders cause disturbances in the brain areas responsible for cognition and behavior. Sleep-regulating brain areas are the first to be affected in the neurodegenerative process and accelerate the risk of dementia. Circadian age-related changes in amyloid beta and tau proteins affect the amount and depth of sleep and vice versa. Amyloid beta in cerebrospinal fluid shows an inverse correlation with sleep. Orexins modulate amyloid beta and sleep.

Bioelectronic Zeitgebers: targeted neuromodulation to re-establish circadian rhythms

Existing neurostimulation systems implanted for the treatment of neurodegenerative disorders generally deliver invariable therapy parameters, regardless of phase of the sleep/wake cycle. However, there is considerable evidence that brain activity in these conditions varies according to this cycle, with discrete patterns of dysfunction linked to loss of circadian rhythmicity, worse clinical outcomes and impaired patient quality of life. We present a targeted concept of circadian neuromodulation using a novel device platform. This system utilises stimulation of circuits important in sleep and wake regulation, delivering bioelectronic cues (Zeitgebers) aimed at entraining rhythms to more physiological patterns in a personalised and fully configurable manner. Preliminary evidence from its first use in a clinical trial setting, with brainstem arousal circuits as a surgical target, further supports its promising impact on sleep/wake pathology. Data included in this paper highlight its versatility and effectiveness on two different patient phenotypes. In addition to exploring acute and long-term electrophysiological and behavioural effects, we also discuss current caveats and future feature improvements of our proposed system, as well as its potential applicability in modifying disease progression in future therapies.

Resveratrol and Sir2 Reverse Sleep and Memory Defects Induced by Amyloid Precursor Protein

Resveratrol (RES), a natural polyphenolic phytochemical, has been suggested as a putative anti-aging molecule for the prevention and treatment of Alzheimer's disease (AD) by the activation of sirtuin 1 (Sirt1/Sir2). In this study, we tested the effects of RES and Sirt1/Sir2 on sleep and courtship memory in a Drosophila model by overexpression of amyloid precursor protein (APP), whose duplications and mutations cause familial AD. We found a mild but significant transcriptional increase of Drosophila Sir2 (dSir2) by RES supplementation for up to 17 days in APP flies, but not for 7 days. RES and dSir2 almost completely reversed the sleep and memory deficits in APP flies. We further demonstrated that dSir2 acts as a sleep promotor in Drosophila neurons. Interestingly, RES increased sleep in the absence of dSir2 in dSir2-null mutants, and RES further enhanced sleep when dSir2 was either overexpressed or knocked down in APP flies. Finally, we showed that Aβ aggregates in APP flies were reduced by RES and dSir2, probably via inhibiting Drosophila β-secretase (dBACE). Our data suggest that RES rescues the APP-induced behavioral deficits and Aβ burden largely, but not exclusively, via dSir2.

Night-to-night variability in sleep and amyloid beta burden in normal aging

INTRODUCTION

Alzheimer's disease is associated with sleep disturbances and accumulation of cerebral amyloid beta. The objective was to examine whether actigraphy-detected sleep parameters might be biomarkers for early amyloid burden.

METHODS

Participants underwent a week of actigraphy and an amyloid positron emission tomography (PET) scan. Sleep duration and continuity disruption (sleep fragmentation and nocturnal awakenings) were extracted and compared between amyloid-positive and amyloid-negative participants. Then multiple linear regressions were used between mean or night-to-night intra-individual variability (standard deviation) of sleep parameters and brain amyloid burden in a voxel-wise analysis.

RESULTS

Eighty-six subjects were included (80.3 ± 5.4 years; 48.8% of women). Amyloid-positive participants had a higher variability of sleep fragmentation compared to amyloid-negative participants. This parameter was associated with a higher amyloid burden in the frontal and parietal regions, and in the precuneus, in the whole sample.

DISCUSSION

This study highlights the relevance of using variability in sleep continuity as a potential biomarker of early amyloid pathogenesis.

Proteostasis failure exacerbates neuronal circuit dysfunction and sleep impairments in Alzheimer's disease

Failed proteostasis is a well-documented feature of Alzheimer's disease, particularly, reduced protein degradation and clearance. However, the contribution of failed proteostasis to neuronal circuit dysfunction is an emerging concept in neurodegenerative research and will prove critical in understanding cognitive decline. Our objective is to convey Alzheimer's disease progression with the growing evidence for a bidirectional relationship of sleep disruption and proteostasis failure. Proteostasis dysfunction and tauopathy in Alzheimer's disease disrupts neurons that regulate the sleep-wake cycle, which presents behavior as impaired slow wave and rapid eye movement sleep patterns. Subsequent sleep loss further impairs protein clearance. Sleep loss is a defined feature seen early in many neurodegenerative disorders and contributes to memory impairments in Alzheimer's disease. Canonical pathological hallmarks, β-amyloid, and tau, directly disrupt sleep, and neurodegeneration of locus coeruleus, hippocampal and hypothalamic neurons from tau proteinopathy causes disruption of the neuronal circuitry of sleep. Acting in a positive-feedback-loop, sleep loss and circadian rhythm disruption then increase spread of β-amyloid and tau, through impairments of proteasome, autophagy, unfolded protein response and glymphatic clearance. This phenomenon extends beyond β-amyloid and tau, with interactions of sleep impairment with the homeostasis of TDP-43, α-synuclein, FUS, and huntingtin proteins, implicating sleep loss as an important consideration in an array of neurodegenerative diseases and in cases of mixed neuropathology. Critically, the dynamics of this interaction in the neurodegenerative environment are not fully elucidated and are deserving of further discussion and research. Finally, we propose sleep-enhancing therapeutics as potential interventions for promoting healthy proteostasis, including β-amyloid and tau clearance, mechanistically linking these processes. With further clinical and preclinical research, we propose this dynamic interaction as a diagnostic and therapeutic framework, informing precise single- and combinatorial-treatments for Alzheimer's disease and other brain disorders.

The association of subjective sleep characteristics and plasma biomarkers of Alzheimer's disease pathology in older cognitively unimpaired adults with higher amyloid-β burden

We aimed to investigate the association of subjective sleep characteristics and plasma Alzheimer's disease (AD) biomarkers in older cognitively unimpaired adults with higher amyloid-β (Aβ) burden. Unimpaired cognition was determined by education-adjusted performance for the Mini-Mental State Examination and exclusion of dementia and mild cognitive impairment via standardized neuropsychological tests. We used Pittsburgh Sleep Quality Index (PSQI) to assess subjective sleep quality. The participants also underwent examination of plasma AD biomarkers and ¹⁸F-florbetapir PET scan. Correlation and multiple linear regression analyses were used to investigate the association between subjective sleep characteristics and AD biomarkers. A total of 335 participants were included and 114 were Aβ-PET positive. Multivariable regression analysis showed sleep duration > 8 h and sleep disturbance were associated with Aβ deposition in total participants. Two multiple linear regression models were applied and the results revealed in participants with Aβ-PET (+), falling asleep at ≥ 22:00 to ≤ 23:00 was associated with higher levels of Aβ42 and Aβ42/40. Other associations with higher Aβ42/40 and standard uptake value ratio contained sleep efficiency value, sleep efficiency ≥ 75%, no/mild daytime dysfunction and PSQI score ≤ 5. Higher p-Tau-181 level was associated with sleep latency > 30 min in Aβ-PET (+) group and moderate/severe sleep disturbance in Aβ-PET (-) group. Our data suggests sleep duration ≤ 8 h and no/mild sleep disturbance may be related to less Aβ burden. In participants with Aβ deposition, falling asleep at 22:00 to 23:00, higher sleep efficiency (at least ≥ 75%), no/mild daytime dysfunction, sleep latency ≤ 30 min, and good sleep quality may help improve AD pathology.

Dissociation of Arousal Index Between REM and NREM Sleep in Elderly Adults with Cognitive Impairment, No Dementia: A Pilot Study

BACKGROUND

Sleep disruption in elderly has been associated with an increased risk of cognitive impairment and its transition into Alzheimer's disease (AD). High arousal indices (AIs) during sleep may serve as an early-stage biomarker of cognitive impairment non-dementia (CIND).

OBJECTIVE

Using full-night polysomnography (PSG), we investigated whether CIND is related to different AIs between NREM and REM sleep stages.

METHODS

Fourteen older adults voluntarily participated in this population-based study that included Mini-Mental State Examination, Neuropsi battery, Katz Index of Independence in Activities of Daily Living, and single-night PSG. Subjects were divided into two groups (n = 7 each) according to their results in Neuropsi memory and attention subtests: cognitively unimpaired (CU), with normal results; and CIND, with -2.5 standard deviations in memory and/or attention subtests. AIs per hour of sleep during N1, N2, N3, and REM stages were obtained and correlated with Neuropsi total score (NTS).

RESULTS

AI (REM)  was significantly higher in CU group than in CIND group. For the total sample, a positive correlation between AI (REM)  and NTS was found (r = 0.68, p = 0.006), which remained significant when controlling for the effect of age and education. In CIND group, the AI (N2)  was significantly higher than the AI (REM) .

CONCLUSION

In CIND older adults, this attenuation of normal arousal mechanisms in REM sleep are dissociated from the relative excess of arousals observed in stage N2. We propose as probable etiology an early hypoactivity at the locus coeruleus noradrenergic system, associated to its early pathological damage, present in the AD continuum.

Comparison of polysomnography in people with Alzheimer's disease and insomnia versus non-demented elderly people with insomnia

BACKGROUND

We used baseline polysomnography (PSG) data obtained during the clinical program development for suvorexant to compare the PSG profiles of people with Alzheimer's disease and insomnia (ADI) versus age-matched elderly individuals with insomnia (EI).

METHODS

Sleep laboratory baseline PSG data from participants age 55-80 years from 2 trials in people with insomnia and a trial in people with ADI were included. ADI participants had dementia of mild-to-moderate severity. Diagnostic criteria for insomnia, exclusion for other sleep problems, PSG recording procedures, and endpoint derivations were similar across the trials. All participants underwent a night of in-laboratory PSG prior to the baseline night to allow for screening/adaptation. Participants in the EI and ADI groups were compared with regard to sleep architecture, sleep micro-structure, and quantitative EEG power spectral endpoints. The analysis was performed on a post hoc basis using propensity score matching to compare sleep parameters separately in women and men while accounting for age group and total sleep time.

RESULTS

A total of 837 EI and 239 ADI participants were included, with the majority in each population (∼65%) being women. Compared to EI, those with ADI had a lower percentage of time spent in slow wave sleep (and a corresponding higher percentage of time spent in the lighter N1 sleep), a lower number of spindles per minute of N2 sleep, and lower absolute EEG power during NREM sleep, particularly in the lower-frequency bands. Trends for lower REM sleep percentage in ADI did not reach statistical significance.

CONCLUSIONS

Our findings in this large data set, in which the influence of sleep problems was effectively subtracted out (since both groups had insomnia), provide strong confirmatory support of results from previous smaller studies in indicating that AD of mild-to-moderate severity is associated with less slow wave sleep, spindles, and lower-frequency EEG power.

TRIAL REGISTRATION

ClinicalTrials.gov, numbers NCT01097616, NCT01097629, NCT02750306.

EEG Entropy in REM Sleep as a Physiologic Biomarker in Early Clinical Stages of Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is associated with EEG changes across the sleep-wake cycle. As the brain is a non-linear system, non-linear EEG features across behavioral states may provide an informative physiologic biomarker of AD. Multiscale fluctuation dispersion entropy (MFDE) provides a sensitive non-linear measure of EEG information content across a range of biologically relevant time-scales.

OBJECTIVE

To evaluate MFDE in awake and sleep EEGs as a potential biomarker for AD.

METHODS

We analyzed overnight scalp EEGs from 35 cognitively normal healthy controls, 23 participants with mild cognitive impairment (MCI), and 19 participants with mild dementia due to AD. We examined measures of entropy in wake and sleep states, including a slow-to-fast-activity ratio of entropy (SFAR-entropy). We compared SFAR-entropy to linear EEG measures including a slow-to-fast-activity ratio of power spectral density (SFAR-PSD) and relative alpha power, as well as to cognitive function.

RESULTS

SFAR-entropy differentiated dementia from MCI and controls. This effect was greatest in REM sleep, a state associated with high cholinergic activity. Differentiation was evident in the whole brain EEG and was most prominent in temporal and occipital regions. Five minutes of REM sleep was sufficient to distinguish dementia from MCI and controls. Higher SFAR-entropy during REM sleep was associated with worse performance on the Montreal Cognitive Assessment. Classifiers based on REM sleep SFAR-entropy distinguished dementia from MCI and controls with high accuracy, and outperformed classifiers based on SFAR-PSD and relative alpha power.

CONCLUSION

SFAR-entropy measured in REM sleep robustly discriminates dementia in AD from MCI and healthy controls.

The prevalence of sleep loss and sleep disorders in young and old adults

The ability to sleep declines with age. The National Sleep Foundation, USA has recommended a minimum sleep amount for all ages. Individuals who experience sleep lesser than the recommended amount could be sleep-deprived. Several factors like stress, altered circadian cycle, medical conditions, etc. cause sleep deficiency. Almost 50-60 % of elderly population suffer from sleep disorders such as sleep apnea, restless legs syndrome, REM sleep behavior disorder, etc. Chronic sleep deprivation may further lead to the development of diseases such as Alzheimer's and Parkinson's. This paper reviews the prevalence of sleep disorders and consequences of sleep loss in young and old adults.

The relationship between Alzheimer's-related brain atrophy patterns and sleep macro-architecture

Introduction

Sleep is increasingly recognized as a major risk factor for neurodegenerative disorders such as Alzheimer's disease (AD).

Methods

Using an magnetic resonance imaging (MRI)-based AD score based on clinical data from the Alzheimer's Disease Neuroimaging Initiative 1 (ADNI1) case-control cohort, we investigated the associations between polysomnography-based sleep macro-architecture and AD-related brain atrophy patterns in 712 pre-symptomatic, healthy subjects from the population-based Study of Health in Pomerania.

Results

We identified a robust inverse association between slow-wave sleep and the AD marker (estimate: -0.019; 95% confidence interval: -0.03 to -0.0076; false discovery rate [FDR] = 0.0041), as well as with gray matter (GM) thicknesses in typical individual cortical AD-signature regions. No effects were identified regarding rapid eye movement or non-rapid eye movement (NREM) stage 2 sleep, and NREM stage 1 was positively associated with GM thickness, mainly in the prefrontal cortical regions.

Discussion

There is a cross-sectional relationship between AD-related neurodegenerative patterns and the proportion of sleep spent in slow-wave sleep.

Cross-sectional and longitudinal association of sleep and Alzheimer biomarkers in cognitively unimpaired adults

Sleep abnormalities are prevalent in Alzheimer’s disease, with sleep quality already impaired at its preclinical stage. Epidemiological and experimental data point to sleep abnormalities contributing to the risk of Alzheimer’s disease. However, previous studies are limited by either a lack of Alzheimer’s disease biomarkers, reduced sample size or cross-sectional design. Understanding if, when, and how poor sleep contributes to Alzheimer’s disease progression is important so that therapies can be targeted to the right phase of the disease. Using the largest cohort to date, the European Prevention of Alzheimer’s Dementia Longitudinal Cohort Study, we test the hypotheses that poor sleep is associated with core Alzheimer’s disease CSF biomarkers cross-sectionally and predicts future increments of Alzheimer’s disease pathology in people without identifiable symptoms of Alzheimer’s disease at baseline. This study included 1168 adults aged over 50 years with CSF core Alzheimer’s disease biomarkers (total tau, phosphorylated tau and amyloid-beta), cognitive performance, and sleep quality (Pittsburgh sleep quality index questionnaire) data. We used multivariate linear regressions to analyse associations between core Alzheimer’s disease biomarkers and the following Pittsburgh sleep quality index measures: total score of sleep quality, binarized score (poor sleep categorized as Pittsburgh sleep quality index > 5), sleep latency, duration, efficiency and disturbance. On a subsample of 332 participants with CSF taken at baseline and after an average period of 1.5 years, we assessed the effect of baseline sleep quality on change in Alzheimer’s disease biomarkers over time. Cross-sectional analyses revealed that poor sleep quality (Pittsburgh sleep quality index total > 5) was significantly associated with higher CSF t-tau; shorter sleep duration (<7 h) was associated with higher CSF p-tau and t-tau; and a higher degree of sleep disturbance (1–9 versus 0 and >9 versus 0) was associated with lower CSF amyloid-beta. Longitudinal analyses showed that greater sleep disturbances (1–9 versus 0 and >9 versus 0) were associated with a decrease in CSF Aβ42 over time. This study demonstrates that self-reported poor sleep quality is associated with greater Alzheimer’s disease-related pathology in cognitively unimpaired individuals, with longitudinal results further strengthening the hypothesis that disrupted sleep may represent a risk factor for Alzheimer’s disease. This highlights the need for future work to test the efficacy of preventive practices, designed to improve sleep at pre-symptomatic stages of disease, on reducing Alzheimer’s disease pathology.

Home EEG sleep assessment shows reduced slow-wave sleep in mild-moderate Alzheimer's disease

Introduction

Sleep disturbances are common in Alzheimer's disease (AD), with estimates of prevalence as high as 65%. Recent work suggests that specific sleep stages, such as slow-wave sleep (SWS) and rapid eye movement (REM), may directly impact AD pathophysiology. A major limitation to sleep staging is the requirement for clinical polysomnography (PSG), which is often not well tolerated in patients with dementia. We have recently developed a deep learning model to reliably analyze lower quality electroencephalogram (EEG) data obtained from a simple, two-lead EEG headband. Here we assessed whether this methodology would allow for home EEG sleep staging in patients with mild-moderate AD.

Methods

A total of 26 mild-moderate AD patients and 24 age-matched, healthy control participants underwent home EEG sleep recordings as well as actigraphy and subjective sleep measures through the Pittsburgh Sleep Quality Index (PSQI). Each participant wore the EEG headband for up to three nights. Sleep was staged using a deep learning model previously developed by our group, and sleep stages were correlated with actigraphy measures as well as PSQI scores.

Results

We show that home EEG with a headband is feasible and well tolerated in patients with AD. Patients with mild-moderate AD were found to spend less time in SWS compared to healthy control participants. Other sleep stages were not different between the two groups. Actigraphy or the PSQI were not found to predict home EEG sleep stages.

Discussion

Our data show that home EEG is well tolerated, and can ascertain reduced SWS in patients with mild-moderate AD. Similar findings have previously been reported, but using clinical PSG not suitable for the home environment. Home EEG will be particularly useful in future clinical trials assessing potential interventions that may target specific sleep stages to alter the pathogenesis of AD.

Highlights

Home electroencephalogram (EEG) sleep assessments are important for measuring sleep in patients with dementia because polysomnography is a limited resource not well tolerated in this patient population.Simplified at-home EEG for sleep assessment is feasible in patients with mild-moderate Alzheimer's disease (AD).Patients with mild-moderate AD exhibit less time spent in slow-wave sleep in the home environment, compared to healthy control participants.Compared to healthy control participants, patients with mild-moderate AD spend more time in bed, with decreased sleep efficiency, and more awakenings as measured by actigraphy, but these measures do not correlate with EEG sleep stages.

Ultra-high-resolution time-frequency analysis of EEG to characterise brain functional connectivity with the application in Alzheimer's disease

OBJECTIVE

This study aims to explore the potential of high-resolution brain functional connectivity based on electroencephalogram (EEG), a non-invasive low-cost technique, to be translated into a long-overdue biomarker and a diagnostic method for Alzheimer's disease (AD).

APPROACH

The paper proposes a novel ultra-high-resolution time-frequency nonlinear cross-spectrum method to construct a promising biomarker of AD pathophysiology. Specifically, using the peak frequency estimated from a Revised Hilbert-Huang Transformation cross-spectrum as a biomarker, the Support Vector Machine classifier is used to distinguish AD from healthy controls (HC).

MAIN RESULTS

With the combinations of the proposed biomarker and machine learning, we achieved a promising accuracy of 89%. The proposed method performs better than the wavelet cross-spectrum and other functional connectivity measures in the temporal or frequency domain, particularly in the Full, Delta and Alpha bands. Besides, a novel visualisation approach developed from topography is introduced to represent the brain functional connectivity, with which the difference between AD and HCs can be clearly displayed. The interconnections between posterior and other brain regions are obviously affected in AD.

SIGNIFICANCE

Those findings imply that the proposed RHHT approach could better track dynamic and nonlinear functional connectivity information, paving the way for the development of a novel diagnostic approach.

Alterations of sleep oscillations in Alzheimer's disease: A potential role for GABAergic neurons in the cortex, hippocampus, and thalamus

Sleep abnormalities are widely reported in patients with Alzheimer's disease (AD) and are linked to cognitive impairments. Sleep abnormalities could be potential biomarkers to detect AD since they are often observed at the preclinical stage. Moreover, sleep could be a target for early intervention to prevent or slow AD progression. Thus, here we review changes in brain oscillations observed during sleep, their connection to AD pathophysiology and the role of specific brain circuits. Slow oscillations (0.1-1 Hz), sleep spindles (8-15 Hz) and their coupling during non-REM sleep are consistently reduced in studies of patients and in AD mouse models although the timing and magnitude of these alterations depends on the pathophysiological changes and the animal model studied. Changes in delta (1-4 Hz) activity are more variable. Animal studies suggest that hippocampal sharp-wave ripples (100-250 Hz) are also affected. Reductions in REM sleep amount and slower oscillations during REM are seen in patients but less consistently in animal models. Thus, changes in a variety of sleep oscillations could impact sleep-dependent memory consolidation or restorative functions of sleep. Recent mechanistic studies suggest that alterations in the activity of GABAergic neurons in the cortex, hippocampus and thalamic reticular nucleus mediate sleep oscillatory changes in AD and represent a potential target for intervention. Longitudinal studies of the timing of AD-related sleep abnormalities with respect to pathology and dysfunction of specific neural networks are needed to identify translationally relevant biomarkers and guide early intervention strategies to prevent or delay AD progression.

Night‐to‐night variation in sleep associates with day‐to‐day variation in vigilance, cognition, memory, and behavioral problems in Alzheimer's disease

Introduction

Sleep disturbances are commonly reported in people living with Alzheimer's disease (AD), but it is currently unknown whether night‐to‐night variation in sleep predicts day‐to‐day variation in vigilance, cognition, mood, and behavior (daytime measures).

Methods

Subjective and objective sleep and daytime measures were collected daily for 2 weeks in 15 participants with mild AD, eight participants with mild cognitive impairment (MCI), and 22 participants with no cognitive impairment (NCI). Associations between daytime measures and four principal components of sleep (duration, quality, continuity, and latency) were quantified using mixed‐model regression.

Results

Sleepiness, alertness, contentedness, everyday memory errors, serial subtraction, and behavioral problems were predicted by at least one of the components of sleep, and in particular sleep duration and continuity. Associations between variations in sleep and daytime measures were linear or quadratic and often different between participants with AD and those with NCI.

Discussion

These findings imply that daytime functioning in people with AD may be improved by interventions that target sleep continuity.

The role of orexin in Alzheimer disease: From sleep-wake disturbance to therapeutic target

Accumulating evidence has shown that sleep disturbance is a common symptom in Alzheimer's disease (AD), which is regarded as a modifiable risk factor for AD. Orexin is a key modulator of the sleep-wake cycle and has been found to be dysregulated in AD patients. The increased orexin in cerebrospinal fluid (CSF) is associated with decreased sleep efficiency and REM sleep, as well as cognitive impairment in AD patients. The orexin system has profuse projections to brain regions that are implicated in arousal and cognition and has been found to participate in the progression of AD pathology. Conversely the orexin receptor antagonists are able to consolidate sleep and reduce AD pathology. Therefore, improved understanding of the mechanisms linking orexin system, sleep disturbance and AD could make orexin receptor antagonists a promising target for the prevention or treatment of AD.

Symptomatic, Genetic, and Mechanistic Overlaps between Autism and Alzheimer's Disease

Autism spectrum disorder (ASD) and Alzheimer's disease (AD) are neurodevelopmental and neurodegenerative disorders affecting two opposite ends of life span, i.e., childhood and old age. Both disorders pose a cumulative threat to human health, with the rate of incidences increasing considerably worldwide. In the context of recent developments, we aimed to review correlated symptoms and genetics, and overlapping aspects in the mechanisms of the pathogenesis of ASD and AD. Dementia, insomnia, and weak neuromuscular interaction, as well as communicative and cognitive impairments, are shared symptoms. A number of genes and proteins linked with both disorders have been tabulated, including MECP2, ADNP, SCN2A, NLGN, SHANK, PTEN, RELN, and FMR1. Theories about the role of neuron development, processing, connectivity, and levels of neurotransmitters in both disorders have been discussed. Based on the recent literature, the roles of FMRP (Fragile X mental retardation protein), hnRNPC (heterogeneous ribonucleoprotein-C), IRP (Iron regulatory proteins), miRNAs (MicroRNAs), and α-, β0, and γ-secretases in the posttranscriptional regulation of cellular synthesis and processing of APP (amyloid-β precursor protein) have been elaborated to describe the parallel and overlapping routes and mechanisms of ASD and AD pathogenesis. However, the interactive role of genetic and environmental factors, oxidative and metal ion stress, mutations in the associated genes, and alterations in the related cellular pathways in the development of ASD and AD needs further investigation.

Association between Sleep, Alzheimer's, and Parkinson's Disease

The majority of neurodegenerative diseases are pathologically associated with protein misfolding and aggregation. Alzheimer's disease (AD) is a type of dementia that slowly affects memory and cognitive function, and is characterized by the aggregation of the β-amyloid protein and tau neurofibrillary tangles in the brain. Parkinson's disease (PD) is a movement disorder typically resulting in rigidity and tremor, which is pathologically linked to the aggregation of α-synuclein, particularly in dopaminergic neurons in the midbrain. Sleep disorders commonly occur in AD and PD patients, and it can precede the onset of these diseases. For example, cognitively normal older individuals who have highly fragmented sleep had a 1.5-fold increased risk of subsequently developing AD. This suggests that sleep abnormalities may be a potential biomarker of these diseases. In this review, we describe the alterations of sleep in AD and PD, and discuss their potential in the early diagnosis of these diseases. We further discuss whether sleep disturbance could be a target for the treatment of these diseases.

The influence of probable rapid eye movement sleep behavior disorder and sleep insufficiency on fall risk in a community-dwelling elderly population

Background

The objective was to investigate the individual effect and potential interactions of probable rapid eye movement sleep behavior disorder (pRBD) and sleep insufficiency on fall risk among a Chinese elderly population.

Methods

Community-dwelling population aged 55 years or above were recruited from the Beijing Longitudinal Study on Aging II cohort from 2010 to 2011. Odds ratio (ORs) and 95% confidence intervals (CIs) were estimated using multivariate logistic regression models. Multiplicative and additive interactions between pRBD and sleep insufficiency were examined using likelihood ratio tests and relative excess risk due to interaction (RERI), respectively.

Results

Among 6891 included participants, 479 experienced at least once fall. pRBD and sleep insufficiency were both independently associated with elevated fall risk. Compared to the elderly without pRBD or sleep insufficiency, pRBD and sleep insufficiency was each associated with a 2.57-fold (OR = 2.57, 95%CI: 1.46–4.31) and 1.45-fold (OR = 1.45, 95%CI: 1.11–1.88) risk of falls individually, while their coexistence was associated with a less-than-additive 17% (OR = 1.17, 95%CI: 0.43–2.63) increased risk of falls. The combination of these two factors demonstrated evidence of a negative interaction on both multiplicative (ratio of ORs = 0.31, 95%CI: 0.10, 0.86) and additive (RERI = − 1.85, 95%CI: − 3.61, − 0.09) scale.

Conclusions

Our study has provided robust evidence for the adverse effect of pRBD and sleep insufficiency, as well as their negative interaction on increasing fall risk in a Chinese elderly population.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02513-2.

Mutual Interactions between Brain States and Alzheimer's Disease Pathology: A Focus on Gamma and Slow Oscillations

Brain state varies from moment to moment. While brain state can be defined by ongoing neuronal population activity, such as neuronal oscillations, this is tightly coupled with certain behavioural or vigilant states. In recent decades, abnormalities in brain state have been recognised as biomarkers of various brain diseases and disorders. Intriguingly, accumulating evidence also demonstrates mutual interactions between brain states and disease pathologies: while abnormalities in brain state arise during disease progression, manipulations of brain state can modify disease pathology, suggesting a therapeutic potential. In this review, by focusing on Alzheimer's disease (AD), the most common form of dementia, we provide an overview of how brain states change in AD patients and mouse models, and how controlling brain states can modify AD pathology. Specifically, we summarise the relationship between AD and changes in gamma and slow oscillations. As pathological changes in these oscillations correlate with AD pathology, manipulations of either gamma or slow oscillations can modify AD pathology in mouse models. We argue that neuromodulation approaches to target brain states are a promising non-pharmacological intervention for neurodegenerative diseases.

A Deep Learning Strategy for Automatic Sleep Staging Based on Two-Channel EEG Headband Data

Sleep disturbances are common in Alzheimer’s disease and other neurodegenerative disorders, and together represent a potential therapeutic target for disease modification. A major barrier for studying sleep in patients with dementia is the requirement for overnight polysomnography (PSG) to achieve formal sleep staging. This is not only costly, but also spending a night in a hospital setting is not always advisable in this patient group. As an alternative to PSG, portable electroencephalography (EEG) headbands (HB) have been developed, which reduce cost, increase patient comfort, and allow sleep recordings in a person’s home environment. However, naïve applications of current automated sleep staging systems tend to perform inadequately with HB data, due to their relatively lower quality. Here we present a deep learning (DL) model for automated sleep staging of HB EEG data to overcome these critical limitations. The solution includes a simple band-pass filtering, a data augmentation step, and a model using convolutional (CNN) and long short-term memory (LSTM) layers. With this model, we have achieved 74% (±10%) validation accuracy on low-quality two-channel EEG headband data and 77% (±10%) on gold-standard PSG. Our results suggest that DL approaches achieve robust sleep staging of both portable and in-hospital EEG recordings, and may allow for more widespread use of ambulatory sleep assessments across clinical conditions, including neurodegenerative disorders.

Association of sleep duration in middle and old age with incidence of dementia

Sleep dysregulation is a feature of dementia but it remains unclear whether sleep duration prior to old age is associated with dementia incidence. Using data from 7959 participants of the Whitehall II study, we examined the association between sleep duration and incidence of dementia (521 diagnosed cases) using a 25-year follow-up. Here we report higher dementia risk associated with a sleep duration of six hours or less at age 50 and 60, compared with a normal (7 h) sleep duration, although this was imprecisely estimated for sleep duration at age 70 (hazard ratios (HR) 1.22 (95% confidence interval 1.01-1.48), 1.37 (1.10-1.72), and 1.24 (0.98-1.57), respectively). Persistent short sleep duration at age 50, 60, and 70 compared to persistent normal sleep duration was also associated with a 30% increased dementia risk independently of sociodemographic, behavioural, cardiometabolic, and mental health factors. These findings suggest that short sleep duration in midlife is associated with an increased risk of late-onset dementia.