Comparison of single-channel EEG, actigraphy, and sleep diary in cognitively normal and mildly impaired older adults

A Protocol for Evaluating Digital Technology for Monitoring Sleep and Circadian Rhythms in Older People and People Living with Dementia in the Community

Sleep and circadian rhythm disturbance are predictors of poor physical and mental health, including dementia. Long-term digital technology-enabled monitoring of sleep and circadian rhythms in the community has great potential for early diagnosis, monitoring of disease progression, and assessing the effectiveness of interventions. Before novel digital technology-based monitoring can be implemented at scale, its performance and acceptability need to be evaluated and compared to gold-standard methodology in relevant populations. Here, we describe our protocol for the evaluation of novel sleep and circadian technology which we have applied in cognitively intact older adults and are currently using in people living with dementia (PLWD). In this protocol, we test a range of technologies simultaneously at home (7-14 days) and subsequently in a clinical research facility in which gold standard methodology for assessing sleep and circadian physiology is implemented. We emphasize the importance of assessing both nocturnal and diurnal sleep (naps), valid markers of circadian physiology, and that evaluation of technology is best achieved in protocols in which sleep is mildly disturbed and in populations that are relevant to the intended use-case. We provide details on the design, implementation, challenges, and advantages of this protocol, along with examples of datasets.

Fragmentation of rest periods, astrocyte activation, and cognitive decline in older adults with and without Alzheimer's disease

INTRODUCTION

Sleep disruption is associated with astrocyte activation and impaired cognition in model organisms. However, the relationship among sleep, astrocyte activation, and cognition in humans is uncertain.

METHODS

We used RNA-seq to quantify the prefrontal cortex expression of a panel of human activated astrocyte marker genes in 1076 older adults in the Religious Orders Study and Rush Memory and Aging Project, 411 of whom had multi-day actigraphy prior to death. We related this to rest fragmentation, a proxy for sleep fragmentation, and to longitudinal cognitive function.

RESULTS

Fragmentation of rest periods was associated with higher expression of activated astrocyte marker genes, which was associated with a lower level and faster decline of cognitive function.

DISCUSSION

Astrocyte activation and fragmented rest are associated with each other and with accelerated cognitive decline. If experimental studies confirm a causal relationship, targeting sleep fragmentation and astrocyte activation may benefit cognition in older adults.

HIGHLIGHTS

Greater fragmentation of rest periods, a proxy for sleep fragmentation, is associated with higher composite expression of a panel of genes characteristic of activated astrocytes. Increased expression of genes characteristic of activated astrocytes was associated with a lower level and more rapid decline of cognitive function, beyond that accounted for by the burden of amyloid and neurofibrillary tangle pathology. Longitudinal and experimental studies are needed to delineate the causal relationships among sleep, astrocyte activation, and cognition.

Age differences in the association between sleep and Alzheimer's disease biomarkers in the EPAD cohort

Introduction

We aimed to determine the independent association between sleep quality and Alzheimer's disease (AD) biomarkers, and whether the associations differ with age.

Methods

We included 1240 individuals aged ≥50, without dementia from the European Prevention of Alzheimer's Disease v1500.0 dataset. Linear regression was used to examine Pittsburgh Sleep Quality Index (PSQI) scores against cerebrospinal fluid (CSF) phosphorylated tau/β-amyloid ratio (p-tau/Aβ42) for the entire sample and via age tertiles. Models controlled for demographic, clinical, genetic, vascular, and neuroimaging variables.

Results

For the youngest age tertile, shorter sleep duration and higher sleep efficiency were associated with greater p-tau/Aβ42 ratio. For the oldest tertile, longer sleep latency was associated with greater p-tau/Aβ42.

Discussion

Differential relationships between sleep and AD pathology depend on age. Short sleep duration and sleep efficiency are relevant in middle age whereas time taken to fall asleep is more closely linked to AD biomarkers in later life.

Highlights

This study shows age differences in the link between sleep and AD biomarkers.Shorter sleep was associated with greater p-tau/Aβ42 ratio in middle age.The association was independent of genetic, vascular, and neuroimaging markers of AD.

Prospective association between sleep duration and cognitive impairment: Findings from the China Health and Retirement Longitudinal Study (CHARLS)

Objective

The association between sleep duration and cognition are inconclusive. Our study aimed to comprehensively investigate the effects of sleep duration on the risk of cognitive impairment in the middle-aged and older Chinese population.

Methods

We used the longitudinal cohort data from waves 1-4 (2011-2018) of the China Health and Retirement Longitudinal Study (CHARLS). Self-reported exposures included total sleep duration, nocturnal sleep duration, post-lunch napping, and changes in sleep duration over time according to face-to-face interviews. Cognitive function was assessed by a Chinese version of the Modified Mini-Mental State Examination (MMSE).

Results

A total of 7,342 eligible participants were included. The mean age was 61.5 ± 6.5 years, and 48.9% (3,588/7,342) were male. We identified a U-shaped association of total sleep duration as well as nocturnal sleep duration with the risk of cognitive impairment. People with 7-8 h of total sleep duration and 6-7 h of nocturnal sleep had the lowest risk of cognitive impairment. Further results showed that post-lunch napping within 2 h was beneficial to cognition and 60 min was optimal. Moreover, analyses of changes in sleep duration further supported that sleeping less or more was harmful to cognition. Notably, those "excessive-change" sleepers (from ≤6 to ≥9 h, or from ≥9 to ≤6 h) had more risks.

Conclusions

Keeping 7-8 h per day was related to the lowest risk of cognitive impairment in midlife and late life, and an optimal post-lunch napping was 60 min for these stable sleepers. Especially, excessive changes in sleep duration over time led to poorer cognition. Our work highlights the importance of optimal sleep habits to cognitive function. The self-reported sleep measures limited our findings, and further studies are needed for verification.

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.

Sleep and longitudinal cognitive performance in preclinical and early symptomatic Alzheimer's disease

Sleep monitoring may provide markers for future Alzheimer's disease; however, the relationship between sleep and cognitive function in preclinical and early symptomatic Alzheimer's disease is not well understood. Multiple studies have associated short and long sleep times with future cognitive impairment. Since sleep and the risk of Alzheimer's disease change with age, a greater understanding of how the relationship between sleep and cognition changes over time is needed. In this study, we hypothesized that longitudinal changes in cognitive function will have a non-linear relationship with total sleep time, time spent in non-REM and REM sleep, sleep efficiency and non-REM slow wave activity. To test this hypothesis, we monitored sleep-wake activity over 4-6 nights in 100 participants who underwent standardized cognitive testing longitudinally, APOE genotyping, and measurement of Alzheimer's disease biomarkers, total tau and amyloid-β42 in the CSF. To assess cognitive function, individuals completed a neuropsychological testing battery at each clinical visit that included the Free and Cued Selective Reminding test, the Logical Memory Delayed Recall assessment, the Digit Symbol Substitution test and the Mini-Mental State Examination. Performance on each of these four tests was Z-scored within the cohort and averaged to calculate a preclinical Alzheimer cognitive composite score. We estimated the effect of cross-sectional sleep parameters on longitudinal cognitive performance using generalized additive mixed effects models. Generalized additive models allow for non-parametric and non-linear model fitting and are simply generalized linear mixed effects models; however, the linear predictors are not constant values but rather a sum of spline fits. We found that longitudinal changes in cognitive function measured by the cognitive composite decreased at low and high values of total sleep time (P < 0.001), time in non-REM (P < 0.001) and REM sleep (P < 0.001), sleep efficiency (P < 0.01) and <1 Hz and 1-4.5 Hz non-REM slow wave activity (P < 0.001) even after adjusting for age, CSF total tau/amyloid-β42 ratio, APOE ε4 carrier status, years of education and sex. Cognitive function was stable over time within a middle range of total sleep time, time in non-REM and REM sleep and <1 Hz slow wave activity, suggesting that certain levels of sleep are important for maintaining cognitive function. Although longitudinal and interventional studies are needed, diagnosing and treating sleep disturbances to optimize sleep time and slow wave activity may have a stabilizing effect on cognition in preclinical or early symptomatic Alzheimer's disease.