Medial temporal lobe atrophy relates more strongly to sleep-wake rhythm fragmentation than to age or any other known risk

Circadian rapid eye movement sleep expression is associated with brain microstructural integrity in older adults

Rapid eye movement sleep (REMS) is increasingly suggested as a discriminant sleep state for subtle signs of age-related neurodegeneration. While REMS expression is under strong circadian control and circadian dysregulation increases with age, the association between brain aging and circadian REMS regulation has not yet been assessed. Here, we measure the circadian amplitude of REMS through a 40-h in-lab multiple nap protocol in controlled laboratory conditions, and brain microstructural integrity with quantitative multi-parameter mapping (MPM) imaging in 86 older individuals. We show that reduced circadian REMS amplitude is related to lower magnetization transfer saturation (MTsat), longitudinal relaxation rate (R1) and effective transverse relaxation rate (R2*) values in several white matter regions mostly located around the lateral ventricles, and with lower R1 values in grey matter clusters encompassing the hippocampus, parahippocampus, thalamus and hypothalamus. Our results further highlight the importance of considering circadian regulation for understanding the association between sleep and brain structure in older individuals.

Evaluating a novel 24-hour rest/activity rhythm marker of preclinical β-amyloid deposition

STUDY OBJECTIVES

To compare sleep and 24-hour rest/activity rhythms (RARs) between cognitively normal older adults who are β-amyloid-positive (Aβ+) or Aβ- and replicate a novel time-of-day-specific difference between these groups identified in a previous exploratory study.

METHODS

We studied 82 cognitively normal participants from the Baltimore Longitudinal Study of Aging (aged 75.7 ± 8.5 years, 55% female, 76% white) with wrist actigraphy data and Aβ+ versus Aβ- status measured by [11C] Pittsburgh compound B positron emission tomography. RARs were calculated using epoch-level activity count data from actigraphy. We used novel, data-driven function-on-scalar regression analyses and standard RAR metrics to cross-sectionally compare RARs between 25 Aβ+ and 57 Aβ- participants.

RESULTS

Compared to Aβ- participants, Aβ+ participants had higher mean activity from 1:00 p.m. to 3:30 p.m. when using less conservative pointwise confidence intervals (CIs) and from 1:30 p.m. to 2:30 p.m. using more conservative, simultaneous CIs. Furthermore, Aβ+ participants had higher day-to-day variability in activity from 9:00 a.m. to 11:30 a.m. and lower variability from 1:30 p.m. to 4:00 p.m. and 7:30 p.m. to 10:30 p.m. according to pointwise CIs, and lower variability from 8:30 p.m. to 10:00 p.m. using simultaneous CIs. There were no Aβ-related differences in standard sleep or RAR metrics.

CONCLUSIONS

Findings suggest Aβ+ older adults have higher, more stable day-to-day afternoon/evening activity than Aβ- older adults, potentially reflecting circadian dysfunction. Studies are needed to replicate our findings and determine whether these or other time-of-day-specific RAR features have utility as markers of preclinical Aβ deposition and if they predict clinical dementia and agitation in the afternoon/evening (i.e. "sundowning").

Impact of Sleep Disorders and Disturbed Sleep on Brain Health: A Scientific Statement From the American Heart Association

Accumulating evidence supports a link between sleep disorders, disturbed sleep, and adverse brain health, ranging from stroke to subclinical cerebrovascular disease to cognitive outcomes, including the development of Alzheimer disease and Alzheimer disease-related dementias. Sleep disorders such as sleep-disordered breathing (eg, obstructive sleep apnea), and other sleep disturbances, as well, some of which are also considered sleep disorders (eg, insomnia, sleep fragmentation, circadian rhythm disorders, and extreme sleep duration), have been associated with adverse brain health. Understanding the causal role of sleep disorders and disturbances in the development of adverse brain health is complicated by the common development of sleep disorders among individuals with neurodegenerative disease. In addition to the role of sleep disorders in stroke and cerebrovascular injury, mechanistic hypotheses linking sleep with brain health and biomarker data (blood-based, cerebrospinal fluid-based, and imaging) suggest direct links to Alzheimer disease-specific pathology. These potential mechanisms and the increasing understanding of the "glymphatic system," and the recognition of the importance of sleep in poststroke recovery, as well, support a biological basis for the indirect (through the worsening of vascular disease) and direct (through specific effects on neuropathology) connections between sleep disorders and brain health. Given promising evidence for the benefits of treatment and prevention, sleep disorders and disturbances represent potential targets for early treatment that may improve brain health more broadly. In this scientific statement, we discuss the evidence supporting an association between sleep disorders and disturbances and poor brain health ranging from stroke to dementia and opportunities for prevention and early treatment.

The Interactive Role of Sleep and Circadian Rhythms in Episodic Memory in Older Adults

Adequate sleep is essential for healthy physical, emotional, and cognitive functioning, including memory. However, sleep ability worsens with increasing age. Older adults on average have shorter sleep durations and more disrupted sleep compared with younger adults. Age-related sleep changes are thought to contribute to age-related deficits in episodic memory. Nonetheless, the nature of the relationship between sleep and episodic memory deficits in older adults is still unclear. Further complicating this relationship are age-related changes in circadian rhythms such as the shift in chronotype toward morningness and decreased circadian stability, which may influence memory abilities as well. Most sleep and cognitive aging studies do not account for circadian factors, making it unclear whether age-related and sleep-related episodic memory deficits are partly driven by interactions with circadian rhythms. This review will focus on age-related changes in sleep and circadian rhythms and evidence that these factors interact to affect episodic memory, specifically encoding and retrieval. Open questions, methodological considerations, and clinical implications for diagnosis and monitoring of age-related memory impairments are discussed.

Association between circadian sleep regulation and cortical gyrification in young and older adults

The circadian system orchestrates sleep timing and structure and is altered with increasing age. Sleep propensity, and particularly REM sleep is under strong circadian control and has been suggested to play an important role in brain plasticity. In this exploratory study, we assessed whether surface-based brain morphometry indices are associated with circadian sleep regulation and whether this link changes with age. Twenty-nine healthy older (55-82 years; 16 men) and 28 young participants (20-32 years; 13 men) underwent both structural magnetic resonance imaging and a 40-h multiple nap protocol to extract sleep parameters over day and night time. Cortical thickness and gyrification indices were estimated from T1-weighted images acquired during a classical waking day. We observed that REM sleep was significantly modulated over the 24-h cycle in both age groups, with older adults exhibiting an overall reduction in REM sleep modulation compared to young individuals. Interestingly, when taking into account the observed overall age-related reduction in REM sleep throughout the circadian cycle, higher day-night differences in REM sleep were associated with increased cortical gyrification in the right inferior frontal and paracentral regions in older adults. Our results suggest that a more distinctive allocation of REM sleep over the 24-h cycle is associated with regional cortical gyrification in aging, and thereby point towards a protective role of circadian REM sleep regulation for age-related changes in brain organization.

Rest-Activity Rhythm Characteristics Associated With Depression Symptoms in Stroke Survivors

OBJECTIVE

To examine which 24-hour rest-activity rhythm (RAR) characteristics are associated with depression symptoms in stroke survivors.

DESIGN

Cross-sectional observational study examining associations of RAR characteristics with the presence of depression symptoms adjusting for age, sex, race, and medical comorbidity.

SETTING

Community setting.

PARTICIPANTS

Stroke survivors: (1) recruited locally (N women=35, N men=28) and (2) a nationally representative probability sample (the National Health and Nutrition Examination Survey [NHANES]; N women=156, N men=124).

INTERVENTIONS

None.

MEASUREMENTS

Objective RAR characteristics derived from accelerometer recordings including activity onset/offset times and non-parametric measures of RAR strength (relative amplitude), stability (interdaily stability), and fragmentation (intradaily variability). The presence of depression symptoms was categorized using Patient Health Questionnaire scores.

RESULTS

In both samples, the only RAR characteristic associated with depression symptoms was intradaily variability (fragmentation): local sample, odds ratio=1.96 [95% confidence interval=1.05-3.63]; NHANES sample, odds ratio=1.34, [95% confidence interval=1.01-1.78]). In the NHANES sample, which included both mild and moderate/severe depression, the association between 24-hour sleep-wake fragmentation and depression symptoms was driven by moderate-to-severe cases.

CONCLUSIONS

Stroke survivors with higher levels of RAR fragmentation were more likely to have depression symptoms in both samples. These findings have implications, given prior studies in general samples linking RAR fragmentation with future depression and dementia risk. Research is needed to establish the potential consequences, mechanisms, and modifiability of RAR fragmentation in stroke survivors.

Earlier chronotype in midlife as a predictor of accelerated brain aging: a population-based longitudinal cohort study

STUDY OBJECTIVES

Evidence suggests that sleep-wake cycle disruption could be an early manifestation of neurodegeneration and might even be a risk factor for developing diseases in healthy adults. We investigated the impact of circadian phase change on structural and functional brain deterioration in a late-adulthood population.

METHODS

We analyzed the data of 1874 participants (mean age 58.6 ± 6.3 years, 50.3% female) from the Korean Genome and Epidemiology Study, who were identified as cognitively unimpaired. The mid-sleep time on free days corrected for sleep debt on workdays (MSFsc) at baseline was adopted as an indicator of the chronotype and used to categorize the participants into three groups. The relationships between the chronotype and longitudinal changes in the gray matter volume (GMV) and cognitive function were investigated (mean interval: 4.2 ± 0.5 years).

RESULTS

The mean MSFsc of the participants was 2:45 am. The earlier MSFsc was linearly associated with smaller right entorhinal GMV (β [SE] = 0.02 [0.01]; p = .001) and lower visual memory function test scores at baseline. Longitudinally, the earlier MSFsc at baseline was only significantly associated with more rapid atrophy in the temporal lobe (β [SE] = 0.18 [0.07]; p = .018) and not with other brain lobes or subregions. Moreover, the earlier MSFsc was associated with more deteriorated verbal learning and visual memory function test scores.

CONCLUSIONS

An earlier chronotype in midlife, measured using a questionnaire, can be a valuable indicator for individuals who should be closely monitored for the development of neurodegenerative disorders.

Associations between neuropsychiatric symptoms of affective and vegetative domains and brain morphology in aging people with mild cognitive impairment and Alzheimer's disease

OBJECTIVE

Neuropsychiatric symptoms (NPS) are common in mild cognitive impairment (MCI) and even more in Alzheimer's disease (AD). The symptom-based cluster including nighttime disturbances, depression, appetite changes, anxiety, and apathy (affective and vegetative symptoms) was associated with an increased risk of dementia in MCI and has common neuroanatomical associations. Our objective was to investigate the differences in brain morphology associations with affective and vegetative symptoms between three groups: cognitively normal older adults (CN), MCI and AD.

MATERIAL AND METHODS

Alzheimer's Disease Neuroimaging Initiative data of 223 CN, 367 MCI and 175 AD, including cortical volumes, surface areas and thicknesses and severity scores of the five NPS were analyzed. A whole-brain vertex-wise general linear model was performed to test for intergroup differences (CN-MCI, CN-AD, AD-MCI) in brain morphology associations with five NPS. Multiple regressions were conducted to investigate cortical change as a function of NPS severity in the AD-MCI contrast.

RESULTS

We found (1) signature differences in nighttime disturbances associations with prefrontal regions in AD-MCI, (2) signature differences in NPS associations with temporal regions in AD-MCI for depression and in CN-AD for anxiety, (3) decreased temporal metrics in MCI as nighttime disturbances and depression severity increased, (4) decreased pars triangularis metrics in AD as nighttime disturbances and apathy severity increased.

CONCLUSION

Each NPS seems to have a signature on brain morphology. Affective and vegetative NPS were primarily associated with prefrontal and temporal regions. These signatures open the possibility of potential future assessments of links between brain morphology and NPS on an individual level.

Sleep Quality and Cognitive Decline Across the Adult Age Range: Findings from the Maastricht Aging Study (MAAS)

BACKGROUND

Sleep disturbances have been linked with cognitive decline and a higher risk of dementia. However, there is a lack of studies with sufficient follow-up duration, a detailed neuropsychological assessment and adequate control of main confounders.

OBJECTIVE

To investigate the relation between self-reported sleep quality and cognitive decline over 12 years in cognitively healthy individuals from the general population.

METHODS

We used data from the Maastricht Aging Study (MAAS), a Dutch population-based prospective cohort study of 1,823 community-dwelling adults aged 24 to 82 years at baseline. Cognitive performance was measured at baseline, 6 and 12 years on verbal memory, executive functions, and information processing speed. Sleep quality was assessed at baseline using the sleep subscale score of the 90-item Symptom Checklist (SCL-90). Additional modifiable dementia risk factors were summarized in the LIfestyle for BRAin health (LIBRA) risk score. Weighted linear mixed models tested the association between continuous scores and tertiles of subjective sleep quality and change in cognitive performances over time. Models were adjusted for age, gender, educational level, LIBRA, and use of hypnotic (sleep) medication.

RESULTS

Worse sleep quality was associated with faster decline in processing speed. At older age (≥65 years), it was also associated with faster decline in verbal memory. Association were independent of other modifiable dementia risk factors and use of hypnotic medication. Directionally similar but non-significant associations were found between worse sleep quality and executive functions.

CONCLUSIONS

In this population-based study across the adult age range, poor self-reported sleep was associated with accelerated cognitive decline.

Correlations between sleep disturbance and brain structures associated with neurodegeneration in the National Alzheimer's Coordinating Center Uniform Data Set

This study aimed to 1) determine the association between sleep disturbance and brain structure volumes, 2) the moderation effect of apolipoprotein ε4 genotype on sleep disturbance and brain structures, and 3) the moderation effect of sleep disturbance on cognitive status and regional brain volumes. Using the National Alzheimer's Coordinating Center Uniform Data Set (n = 1,533), multiple linear regressions were used to evaluate the association between sleep disturbance and brain volumes. Sleep disturbance was measured using one question from the NPI-Q. After controlling for intracranial volume, age, sex, years of education, race, ethnicity, and applying the FDR correction, total cerebrospinal fluid volume, left lateral ventricle volume, total lateral ventricle volume, and total third ventricle volume demonstrated significantly higher means for those with sleep disturbance. Total brain volume, total white and gray matter volume, total cerebrum brain volume (including gray but not white matter), left hippocampus volume, total hippocampal volume, the left, right, and total frontal lobe cortical gray matter volume, and the left, right, and total temporal lobe cortical gray matter volume demonstrated significantly lower mean volumes for those with sleep disturbance. Sleep disturbance moderated the association between cognitive status and lateral ventricular volumes. These findings suggest that disrupted sleep is associated with atrophy across multiple brain regions and ventricular hydrocephalus ex vacuo.

Association of 24-Hour Activity Pattern Phenotypes With Depression Symptoms and Cognitive Performance in Aging

Importance

Evidence regarding the nature and prevalence of 24-hour activity pattern phenotypes in older adults, especially those related to depression symptoms and cognition, is needed to guide the development of targeted mechanism research and behavioral interventions.

Objectives

To identify subgroups of older adults with similar 24-hour activity rhythm characteristics and characterize associated depression symptoms and cognitive performance.

Design, Setting, and Participants

From January to March 2022, a cross-sectional analysis of the 2011-2014 National Health and Nutrition Examination and Survey (NHANES) accelerometer study was conducted. The NHANES used a multistage probability sample that was designed to be representative of noninstitutionalized adults in the US. The main analysis included participants 65 years or older who had accelerometer and depression measures weighted to represent approximately 32 million older adults.

Exposures

Latent profile analysis identified subgroups with similar 24-hour activity pattern characteristics as measured using extended-cosine and nonparametric methods.

Main Outcomes and Measures

Covariate-adjusted sample-weighted regressions assessed associations of subgroup membership with (1) depression symptoms defined as 9-Item Patient Health Questionnaire (PHQ-9) scores of 10 or greater (PHQ-9) and (2) having at least psychometric mild cognitive impairment (p-MCI) defined as scoring less than 1 SD below the mean on a composite cognitive performance score.

Results

The actual clustering sample size was 1800 (weighted: mean [SD] age, 72.9 [7.3] years; 57% female participants). Clustering identified 4 subgroups: (1) 677 earlier rising/robust (37.6%), (2) 587 shorter active period/less modelable (32.6%), (3) 177 shorter active period/very weak (9.8%), and (4) 359 later settling/very weak (20.0%). The prevalence of a PHQ-9 score of 10 or greater differed significantly across groups (cluster 1, 3.5%; cluster 2, 4.7%; cluster 3, 7.5%; cluster 4, 9.0%; χ2 P = .004). The prevalence of having at least p-MCI differed significantly across groups (cluster 1, 7.2%; cluster 2, 12.0%; cluster 3, 21.0%; cluster 4, 18.0%; χ2 P < .001). Five of 9 depression symptoms differed significantly across subgroups.

Conclusions and Relevance

In this cross-sectional study, findings indicate that approximately 1 in 5 older adults in the US may be classified in a subgroup with weak activity patterns and later settling, and approximately 1 in 10 may be classified in a subgroup with weak patterns and shorter active duration. Future research is needed to investigate the biologic processes related to these behavioral phenotypes, including why earlier and robust activity patterns appear protective, and whether modifying disrupted patterns improves outcomes.

Associations of sleep timing and time in bed with dementia and cognitive decline among Chinese older adults: A cohort study

BACKGROUND

The longitudinal associations of sleep timing and time in bed (TIB) with dementia and cognitive decline in older adults are unclear.

METHODS

This population-based cohort study used data from 1982 participants who were aged ≥60 years, free of dementia, and living in rural communities in western Shandong, China. At the baseline (2014) and follow-up (2018) examinations, sleep parameters were assessed using standard questionnaires. Cognitive function was measured using the Mini-Mental State Examination (MMSE). Dementia was diagnosed following the DSM-IV criteria, and the NIA-AA criteria for Alzheimer disease (AD). Data were analyzed using restricted cubic splines, Cox proportional-hazards models, and general linear models.

RESULTS

During the mean follow-up of 3.7 years, dementia was diagnosed in 97 participants (68 with AD). Restricted cubic spline curves showed J-shaped associations of sleep duration, TIB, and rise time with dementia risk, and a reverse J-shaped association with mid-sleep time. When sleep parameters were categorized into tertiles, the multivariable-adjusted hazard ratio (HR) of incident dementia was 1.69 (95%CI 1.01-2.83) for baseline sleep duration >8 hours (vs. 7-8 h), 2.17 (1.22-3.87) for bedtime before 9 p.m. (vs. 10 p.m. or later), and 2.00 (1.23-3.24) for mid-sleep time before 1 a.m. (vs. 1-1.5 a.m.). Early bedtime and mid-sleep time were significantly associated with incident AD (HR range: 2.25-2.51; p < 0.05). Among individuals who were free of dementia at follow-up, baseline long TIB, early bedtime and mid-sleep time, early and late rise time, and prolonged TIB and advanced bedtime and mid-sleep time from baseline to follow-up were associated with a greater decline in MMSE score (p < 0.05). These associations with cognitive decline were statistically evident mainly among men or participants who were aged 60-74 years.

CONCLUSIONS

Long TIB and early sleep timing are associated with an increased risk of dementia, and the associations with greater cognitive decline are evident only among older people aged 60-74 years and men.

Associations of environmental and lifestyle factors with spatial navigation in younger and older adults

OBJECTIVE

Advanced age is associated with prominent impairment in allocentric navigation dependent on the hippocampus. This study examined whether age-related impairment in allocentric navigation and strategy selection was associated with sleep disruption or circadian rest-activity fragmentation. Further, we examined whether associations with navigation were moderated by perceived stress and physical activity.

METHOD

Sleep fragmentation and total sleep time over the course of 1 week were assayed in younger (n = 42) and older (n = 37) adults via wrist actigraphy. Subsequently, participants completed cognitive mapping and route learning tasks, as well a measure of spontaneous navigation strategy selection. Measurements of perceived stress and an actigraphy-based index of physical activity were also obtained. Circadian rest-activity fragmentation was estimated via actigraphy post-hoc.

RESULTS

Age was associated with reduced cognitive mapping, route learning, allocentric strategy use, and total sleep time (ps < .01), replicating prior findings. Novel findings included that sleep fragmentation increased with advancing age (p = .009) and was associated with lower cognitive mapping (p = .022) within the older adult cohort. Total sleep time was not linearly associated with the navigation tasks (ps > .087). Post-hoc analyses revealed that circadian rest-activity fragmentation increased with advancing age within the older adults (p = .026) and was associated with lower cognitive mapping across the lifespan (p = .001) and within older adults (p = .005). Neither stress nor physical activity were robust moderators of sleep fragmentation associations with the navigation tasks (ps > .113).

CONCLUSION

Sleep fragmentation and circadian rest-activity fragmentation are potential contributing factors to age effects on cognitive mapping within older adults.

The association of sleep and cortical thickness in mild cognitive impairment

We investigated whether device-measured sleep parameters are associated with cortical thickness in older adults with probable mild cognitive impairment (MCI). We performed a cross-sectional, exploratory analysis of sleep and structural MRI data. Sleep data were collected with MotionWatch8© actigraphy over 7 days. We computed average and variability for sleep duration, sleep efficiency, and fragmentation index. T1-weighted MRI scans were used to measure cortical thickness in FreeSurfer. We employed surface-based analysis to determine the association between sleep measures and cortical thickness, adjusting for age, sex, Montreal Cognitive Assessment (MoCA) score, and sleep medication use. Our sample included 113 participants (age = 73.1 [5.7], female = 72 [63.7 %]). Higher fragmentation index variability predicted lower cortical thickness in the left superior frontal gyrus (cluster size = 970.9 mm², cluster-wise p = 0.017, cortical thickness range = 2.1 mm² to 3.0 mm²), adjusting for age, sex, MoCA, and sleep medication. Our results suggest that higher variability in sleep fragmentation, an indicator of irregular sleep pattern, is linked to lower cortical thickness. Future longitudinal studies are needed to determine the directionality of these associations.

Sleep Loss Causes Dysfunction in Murine Extraorbital Lacrimal Glands

Purpose

Sleep loss markedly affects the structure and function of the lacrimal gland and may cause ocular surface disease as a common public health problem. This study aims to investigate the circadian disturbance caused by sleep loss leading to dysfunction of extraorbital lacrimal glands (ELGs).

Methods

A mouse sleep deprivation (SD) model for sleep loss studies was built in C57BL/6J male mice. After four weeks, the ELGs were collected at three-hour intervals during a 24-hour period. The Jonckheere-Terpstra-Kendall algorithm was used to determine the composition, phase, and rhythmicity of transcriptomic profiles in ELGs. Furthermore, we compared the non-sleep-deprived and SD-treated mouse ELG (i) reactive oxygen species (ROS) by fluorescein staining, (ii) DNA damage by immunostaining for γ-H2Ax, and (iii) circadian migration of immune cells by immunostaining for CD4, CD8, γδ-TCR, CD64, and CX3CR1. Finally, we also evaluated (i) the locomotor activity and core body temperature rhythm of mice and (ii) the mass, cell size, and tear secretion of the ELGs.

Results

SD dramatically altered the composition and phase-associated functional enrichment of the circadian transcriptome, immune cell trafficking, metabolism, cell differentiation, and neural secretory activities of mouse ELGs. Additionally, SD caused the ROS accumulation and consequent DNA damage in the ELGs, and the ELG dysfunction caused by SD was irreversible.

Conclusions

SD damages the structure, function, and diurnal oscillations of ELGs. These results highlight comprehensive characterization of insufficient sleep–affected ELG circadian transcriptome that may provide a new therapeutic approach to counteract the effects of SD on ELG function.

Rest-activity rhythms and tract specific white matter lesions in older adults at risk for cognitive decline

White matter lesions (WMLs) are common in older adults and represent an important predictor of negative long-term outcomes. Rest-activity rhythm disturbance is also common, however, few studies have investigated associations between these factors. We employed a novel AI-based automatic WML segmentation tool and diffusion-weighted tractography to investigate associations between tract specific WML volumes and non-parametric actigraphy measures in older adults at risk for cognitive decline. The primary non-parametric measures of interest were inter-daily stability (IS), intra-daily variability and relative amplitude, with the anterior thalamic radiation (ATR), superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILF) selected as tracts of interest. One hundred and eight participants at risk for cognitive decline (classified as experiencing subjective or objective cognitive decline) were included (mean age = 68.85 years, SD = 8.91). Of the primary non-parametric measures of interest, results showed that lower IS was associated with a greater likelihood of higher WML burden in the ATR (OR = 1.82, 95% CI [1.12,3.15]). Analysis of secondary non-parametric measures revealed later onset of the least active period to be associated with greater likelihood of high WML burden in the SLF (OR = 1.55, 95% CI [1.00,2.53]) and increased activity during the least active 5-h period to be associated with a greater likelihood of high whole-brain WML burden (OR = 1.83, 95% CI [1.06,3.47]). This study shows integrity of the ATR and SLF, and overall WML burden is linked to altered rest-activity rhythms in older adults at risk for cognitive decline, with those demonstrating altered rest-activity rhythms showing 50%-80% higher odds of having high WML burden.

pyActigraphy: Open-source python package for actigraphy data visualization and analysis

Over the past 40 years, actigraphy has been used to study rest-activity patterns in circadian rhythm and sleep research. Furthermore, considering its simplicity of use, there is a growing interest in the analysis of large population-based samples, using actigraphy. Here, we introduce pyActigraphy, a comprehensive toolbox for data visualization and analysis including multiple sleep detection algorithms and rest-activity rhythm variables. This open-source python package implements methods to read multiple data formats, quantify various properties of rest-activity rhythms, visualize sleep agendas, automatically detect rest periods and perform more advanced signal processing analyses. The development of this package aims to pave the way towards the establishment of a comprehensive open-source software suite, supported by a community of both developers and researchers, that would provide all the necessary tools for in-depth and large scale actigraphy data analyses.

The possibility to continuously record locomotor movements using accelerometers (actigraphy) has allowed field studies of sleep and rest-activity patterns. It has also enabled large-scale data collections, opening new avenues for research. However, each brand of actigraph devices encodes recordings in its own format and closed-source proprietary softwares are typically used to read and analyse actigraphy data. In order to provide an alternative to these softwares, we developed a comprehensive open-source toolbox for actigraphy data analysis, pyActigraphy. It allows researchers to read actigraphy data from 7 different file formats and gives access to a variety of rest-activity rhythm variables, automatic sleep detection algorithms and more advanced signal processing techniques. Besides, in order to empower researchers and clinicians with respect to their analyses, we created a series of interactive tutorials that illustrate how to implement the key steps of typical actigraphy data analyses. As an open-source project, all kind of user’s contributions to our toolbox are welcome. As increasing evidence points to the predicting value of rest-activity patterns derived from actigraphy for brain integrity, we believe that the development of the pyActigraphy package will not only benefit the sleep and chronobiology research, but also the neuroscientific community at large.

Rest-activity functioning is related to white matter microarchitecture and modifiable risk factors in older adults at-risk for dementia

STUDY OBJECTIVES

Growing evidence demonstrates pronounced alterations in rest-activity functioning in older adults at-risk for dementia. White matter degeneration, poor cardiometabolic functioning, and depression have also been linked to a greater risk of decline; however, limited studies have examined the white matter in relation to rest-activity functioning in at-risk older adults.

METHODS

We investigated associations between nonparametric actigraphy measures and white matter microarchitecture using whole-brain fixel-based analysis of diffusion-weighted imaging in older adults (aged 50 years or older) at-risk for cognitive decline and dementia. The fixel-based metrics assessed were fiber density, fiber cross-section, and combined fiber-density, and cross-section. Interactions between rest-activity functioning and known clinical risk factors, specifically body mass index (BMI), vascular risk factors, depressive symptoms and self-reported exercise, and their association with white matter properties were then investigated.

RESULTS

Sixty-seven older adults were included (mean = 65.78 years, SD = 7.89). Lower relative amplitude, poorer 24-h synchronization and earlier onset of the least active 5-h period were associated with reductions in markers of white matter atrophy in widespread regions, including cortico-subcortical and cortical association pathways. Preliminary evidence was also found indicating more pronounced white matter alterations in those with lower amplitude and higher BMI (β = 0.25, 95% CI [0.05, 0.46]), poorer 24-h synchronization and more vascular risk factors (β = 0.17, 95% CI [-0.02, 0.36]) and earlier onset of inactivity and greater depressive symptoms (β = 0.17, 95% CI [0.03, 0.30]).

CONCLUSIONS

These findings highlight the complex interplay between rest-activity rhythms, white matter, and clinical risk factors in individuals at-risk for dementia that should be considered in future studies.

Interrelations of Cerebral Hemodynamics with Parameters of Cardiac Function and Brain Tissue in Patients with Ischemic Stroke

We analyzed interrelations between the cerebral blood flow, cardiac output, and condition of the brain substance in 530 patients with ischemic stroke. Dependencies between the linear blood flow velocities in all arteries supplying the brain, as well as between the total volume blood flow through the internal carotid arteries and left ventricular stroke volume were revealed. The severity of atrophy was maximum in the parietal lobes (median 1.5 (1.0; 2.0)) and minimum in the occipital lobes (median 0.5 (0; 1.0)). Temporal lobes cortical atrophy significantly correlated with changes in the limbic system and in the periventricular and deep white matter; a significant weak inverse correlation of this parameter with blood flow in the middle cerebral artery was also found. Changes in the periventricular white matter (but not in deep white matter) demonstrated a significant inverse correlation with blood flow in the middle and anterior cerebral arteries.

Rest-activity rhythms and white matter microstructure across the lifespan

STUDY OBJECTIVES

The purpose of this study was to examine how rest-activity (RA) rhythm stability may be associated with white matter microstructure across the lifespan in healthy adults free of significant cardiovascular risk.

METHODS

We analyzed multi-shell diffusion tensor images from 103 healthy young and older adults using tract-based spatial statistics (TBSS) to examine relationships between white matter microstructure and RA rhythm stability. RA measures were computed using both cosinor and non-parametric methods derived from 7 days of actigraphy data. Fractional anisotropy (FA) and mean diffusivity (MD) were examined in this analysis. Because prior studies have suggested that the corpus callosum (CC) is sensitive to sleep physiology and RA rhythms, we also conducted a focused region of interest analysis on the CC.

RESULTS

Greater rest-activity rhythm stability was associated with greater FA across both young and older adults, primarily in the CC and anterior corona radiata. This effect was not moderated by age group. While RA measures were associated with sleep metrics, RA rhythm measures uniquely accounted for the variance in white matter integrity.

CONCLUSIONS

This study strengthens existing evidence for a relationship between brain white matter structure and RA rhythm stability in the absence of health risk factors. While there are differences in RA stability between age groups, the relationship with brain white matter was present across both young and older adults. RA rhythms may be a useful biomarker of brain health across both periods of adult development.

Altered insula-prefrontal functional connectivity correlates to decreased vigilant attention after total sleep deprivation

BACKGROUND

Sleep deprivation can robustly affect vigilant attention. The insula is a key hub of the salience network that mediates shifting attention between endogenous and exogenous states. However, little is known regarding the involvement of insular functional connectivity in impaired vigilant attention after total sleep deprivation (TSD). The purpose of this study is to explore the alterations in insular functional connectivity and its association with vigilant attention performance following TSD.

METHODS

Twenty-six adult men were enrolled in the study. Participants underwent two counterbalanced resting-state functional magnetic resonance imaging (rs-fMRI) scans, once in rested wakefulness (RW) and once after 36 h of TSD. Seed-based functional connectivity analysis was performed using rs-fMRI data for the left and right insula. The vigilant attention was measured using a psychomotor vigilance test (PVT). Furthermore, Pearson correlation analysis was conducted to investigate the relationship between altered insular functional connectivity and PVT performance.

RESULTS

Compared to RW, enhanced functional connectivity was observed between the insula and prefrontal cortex and anterior cingulate cortex, while reduced functional connectivity was observed between the insula and temporal, parietal, and occipital regions following TSD. Moreover, altered insular functional connectivity with the prefrontal cortex, ie superior frontal gyrus and middle frontal gyrus, and inferior temporal gyrus was correlated with PVT performance after TSD.

CONCLUSION

Our results suggest that insular coupling with the prefrontal cortex and inferior temporal gyrus may act as neural indicators for vigilant attention impairment, which further reveals the critical role of the salience network in cognitive decline following TSD.

Does circadian rhythm disruption during their early development have lasting effects on cognition of the elder rats?

OBJECTIVES

This study aimed to investigate the changes in learning and memory after chronic circadian disruption followed by a long period of circadian recovery.

MATERIALS AND METHODS

Eleven adult male spontaneously hypertensive rats were randomly divided into control group, 12-h light/12-h dark circadian disruption group (12L/12D) and 6-h light/6-h dark circadian disruption group (6L/6D). Rats in control group remained under the original 12-h light/12-h dark cycle throughout the experiment; rats in the 12L/12D group were exposed to 12-h light/12-h dark cycle with light-dark order changed every 3 days; rats in the 6L/6D group were exposed to 6-h light/6-h dark cycle. The disruption period continued for 18 weeks. Then after 8 weeks and 32 weeks of circadian re-entrainment, all animals were tested by Morris Water Maze (MWM), respectively, followed by an MRI examination.

RESULTS

Rats in the 12L/12D group demonstrated longer escape latency and swim distance in the MWM test than rats in the other two groups (P < 0.05). The MRI results showed volume% reduction and concentration% decrease of brain regions in the two circadian disruptive groups, while the changes were more significant and comprehensive in the 12L/12D group (P < 0.05).

CONCLUSIONS

Circadian disruption during early life accelerates cognition decline in later life in rats. Frequent light-dark order shift is more harmful.

A machine learning approach to unmask novel gene signatures and prediction of Alzheimer's disease within different brain regions

Alzheimer's disease (AD) is a progressive neurodegenerative disorder whose aetiology is currently unknown. Although numerous studies have attempted to identify the genetic risk factor(s) of AD, the interpretability and/or the prediction accuracies achieved by these studies remained unsatisfactory, reducing their clinical significance. Here, we employ the ensemble of random-forest and regularized regression model (LASSO) to the AD-associated microarray datasets from four brain regions - Prefrontal cortex, Middle temporal gyrus, Hippocampus, and Entorhinal cortex- to discover novel genetic biomarkers through a machine learning-based feature-selection classification scheme. The proposed scheme unraveled the most optimum and biologically significant classifiers within each brain region, which achieved by far the highest prediction accuracy of AD in 5-fold cross-validation (99% average). Interestingly, along with the novel and prominent biomarkers including CORO1C, SLC25A46, RAE1, ANKIB1, CRLF3, PDYN, numerous non-coding RNA genes were also observed as discriminator, of which AK057435 and BC037880 are uncharacterized long non-coding RNA genes.

A multi-level assessment of the bidirectional relationship between aging and the circadian clock

The daily temporal order of physiological processes and behavior contribute to the wellbeing of many organisms including humans. The central circadian clock, which coordinates the timing within our body, is located in the suprachiasmatic nucleus (SCN) of the hypothalamus. Like in other parts of the brain, aging impairs the SCN function, which in turn promotes the development and progression of aging-related diseases. We here review the impact of aging on the different levels of the circadian clock machinery-from molecules to organs-with a focus on the role of the SCN. We find that the molecular clock is less effected by aging compared to other cellular components of the clock. Proper rhythmic regulation of intracellular signaling, ion channels and neuronal excitability of SCN neurons are greatly disturbed in aging. This suggests a disconnection between the molecular clock and the electrophysiology of these cells. The neuronal network of the SCN is able to compensate for some of these cellular deficits. However, it still results in a clear reduction in the amplitude of the SCN electrical rhythm, suggesting a weakening of the output timing signal. Consequently, other brain areas and organs not only show aging-related deficits in their own local clocks, but also receive a weaker systemic timing signal. The negative spiral completes with the weakening of positive feedback from the periphery to the SCN. Consequently, chronotherapeutic interventions should aim at strengthening overall synchrony in the circadian system using life-style and/or pharmacological approaches.

Correlation of Frontal Atrophy and CSF Tau Levels With Neuropsychiatric Symptoms in Patients With Cognitive Impairment: A Memory Clinic Experience

Background: Behavioral and psychological symptoms of dementia (BPSD) are a distressful condition. We aimed to investigate the BPSD distribution in subjects with cognitive impairment, and the potential correlations between BPSD and neurodegeneration in terms of cerebrospinal fluid (CSF) tau and brain atrophy.

Methods: One-hundred patients with mild cognitive impairment (MCI) or dementia (Alzheimer’s disease, AD; Lewy-body disease, LBD; frontotemporal dementia, FTD; vascular dementia, VD) underwent a complete diagnostic workup, including 3T-MRI and/or CT and CSF. Cortical atrophy was assessed with medial temporal atrophy (MTA), posterior atrophy (PA), and global cortical atrophy-frontal lobe (GCA-F) scales. BPSD were rated using the Neuropsychiatric Inventory (NPI), and BPSD clusters were defined according to the European Alzheimer Disease Consortium.

Results: Delusions, hallucinations, and psychosis cluster were differently distributed among the diagnostic groups (p < 0.05, p < 0.001, and p < 0.05), with LBD patients showing higher scores for hallucinations (vs. MCI, p < 0.001, and AD, p < 0.05) and psychosis cluster (vs. MCI, p < 0.05). In primary dementias, we found a negative correlation between NPI total score and tau levels (p = 0.08), confirmed by beta regression (p < 0.01), while a positive non-significant relationship was observed in MCI. Higher GCA-F scores were associated with delusions and apathy (p < 0.05, on both hemispheres) and hallucinations (left: p < 0.01, right: p < 0.05). GCA-F scores were positively correlated with psychosis cluster (right: p < 0.05), and agitation/aggression (left: p < 0.05). Conversely, nighttime disturbances were positively correlated with both GCA-F and MTA scores (left: p < 0.01; right: p < 0.05).

Conclusion: Our results suggest that psychotic symptoms are significantly more represented in LBD patients and that CSF tau and frontal atrophy are associated with the occurrence and severity of BPSD in clinical practice. Longitudinal studies are however required to ascertain their actual predictive value.

Brain changes associated with sleep disruption in cognitively unimpaired older adults: A short review of neuroimaging studies

Ageing is characterized by a progressive decline of sleep quality. Sleep difficulties are increasingly recognized as a risk factor for Alzheimer's disease (AD), and have been associated with cognitive decline. However, the brain substrates underlying this association remain unclear. In this review, our objective was to provide a comprehensive overview of the relationships between sleep changes and brain structural, functional and molecular integrity, including amyloid and tau pathologies in cognitively unimpaired older adults. We especially discuss the topography and causality of these associations, as well as the potential underlying mechanisms. Taken together, current findings converge to a link between several sleep parameters, amyloid and tau levels in the CSF, and neurodegeneration in diffuse frontal, temporal and parietal areas. However, the existing literature remains heterogeneous, and the specific sleep changes associated with early AD pathological changes, in terms of topography and neuroimaging modality, is not clearly established yet. Notably, if slow wave sleep disruption seems to be related to frontal amyloid deposition, the brain correlates of sleep-disordered breathing and REM sleep disruption remain unclear. Moreover, sleep parameters associated with tau- and FDG-PET imaging are largely unexplored. Lastly, whether sleep disruption is a cause or a consequence of brain alterations remains an open question.

Using Fractal Dimension Analysis with the Desikan-Killiany Atlas to Assess the Effects of Normal Aging on Subregional Cortex Alterations in Adulthood

Normal aging is associated with functional and structural alterations in the human brain. The effects of normal aging and gender on morphological changes in specific regions of the brain are unknown. The fractal dimension (FD) can be a quantitative measure of cerebral folding. In this study, we used 3D-FD analysis with the Desikan–Killiany (DK) atlas to assess subregional morphological changes in adulthood. A total of 258 participants (112 women and 146 men) aged 30–85 years participated in this study. Participants in the middle-age group exhibited a decreased FD in the lateral frontal lobes, which then spread to the temporal and parietal lobes. Men exhibited an earlier and more significant decrease in FD values, mainly in the right frontal and left parietal lobes. Men exhibited more of a decrease in FD values in the subregions on the left than those in the right, whereas women exhibited more of a decrease in the lateral subregions. Older men were at a higher risk of developing mild cognitive impairment (MCI) and exhibited age-related memory decline earlier than women. Our FD analysis using the DK atlas-based prediagnosis may provide a suitable tool for assessing normal aging and neurodegeneration between groups or in individual patients.

Aberrant functional connectivity between the suprachiasmatic nucleus and the superior temporal gyrus: Bridging RORA gene polymorphism with diurnal mood variation in major depressive disorder

Diurnal mood variation (DMV), a common symptom of major depressive disorder (MDD), is associated with circadian related genes and dysregulation of the suprachiasmatic nucleus (SCN). Previous research confirmed that the RORA gene is involved in the regulation of circadian rhythms. In this study, we hypothesized that polymorphisms of RORA may affect DMV symptoms of MDD through functional changes in the SCN. A total of 208 patients diagnosed with depression and 120 control subjects were enrolled and underwent a resting-state functional magnetic resonance imaging (rs-fMRI). Blood samples were collected and genotyping of 9 RORA gene SNPs were performed using next-generation sequencing technology. Patients were categorized as an AA genotype or C allele carriers based on RORA rs72752802 polymorphism. SCN-seed functional connectivity (FC) was compared between the two groups and correlation with severity of DMV was analyzed. Finally, a mediation analysis was performed to further determine FC intermediary effects. We observed that rs72752802 was significantly associated with patients' DMV symptoms. C allele carriers of rs72752802 showed significantly decreased FC between the right SCN and right superior temporal gyrus (rSTG). This was also correlated with DMV symptoms. In addition, the rs72752802 SNP influenced DMV symptoms through intermediary effects of SCN-rSTG connectivity. The study presented here provides a neurological and genetic basis for understanding depressed patients experiencing DMV.

Light in the Senior Home: Effects of Dynamic and Individual Light Exposure on Sleep, Cognition, and Well-Being

Disrupted sleep is common among nursing home patients and is associated with cognitive decline and reduced well-being. Sleep disruptions may in part be a result of insufficient daytime light exposure. This pilot study examined the effects of dynamic “circadian” lighting and individual light exposure on sleep, cognitive performance, and well-being in a sample of 14 senior home residents. The study was conducted as a within-subject study design over five weeks of circadian lighting and five weeks of conventional lighting, in a counterbalanced order. Participants wore wrist accelerometers to track rest–activity and light profiles and completed cognitive batteries (National Institute of Health (NIH) toolbox) and questionnaires (depression, fatigue, sleep quality, lighting appraisal) in each condition. We found no significant differences in outcome variables between the two lighting conditions. Individual differences in overall (indoors and outdoors) light exposure levels varied greatly between participants but did not differ between lighting conditions, except at night (22:00–6:00), with maximum light exposure being greater in the conventional lighting condition. Pooled data from both conditions showed that participants with higher overall morning light exposure (6:00–12:00) had less fragmented and more stable rest–activity rhythms with higher relative amplitude. Rest–activity rhythm fragmentation and long sleep duration both uniquely predicted lower cognitive performance.

Nonparametric time series summary statistics for high-frequency accelerometry data from individuals with advanced dementia

Accelerometry data has been widely used to measure activity and the circadian rhythm of individuals across the health sciences, in particular with people with advanced dementia. Modern accelerometers can record continuous observations on a single individual for several days at a sampling frequency of the order of one hertz. Such rich and lengthy data sets provide new opportunities for statistical insight, but also pose challenges in selecting from a wide range of possible summary statistics, and how the calculation of such statistics should be optimally tuned and implemented. In this paper, we build on existing approaches, as well as propose new summary statistics, and detail how these should be implemented with high frequency accelerometry data. We test and validate our methods on an observed data set from 26 recordings from individuals with advanced dementia and 14 recordings from individuals without dementia. We study four metrics: Interdaily stability (IS), intradaily variability (IV), the scaling exponent from detrended fluctuation analysis (DFA), and a novel nonparametric estimator which we call the proportion of variance (PoV), which calculates the strength of the circadian rhythm using spectral density estimation. We perform a detailed analysis indicating how the time series should be optimally subsampled to calculate IV, and recommend a subsampling rate of approximately 5 minutes for the dataset that has been studied. In addition, we propose the use of the DFA scaling exponent separately for daytime and nighttime, to further separate effects between individuals. We compare the relationships between all these methods and show that they effectively capture different features of the time series.

REM sleep is associated with white matter integrity in cognitively healthy, older adults

There is increasing awareness that self-reported sleep abnormalities are negatively associated with brain structure and function in older adults. Less is known, however, about how objectively measured sleep associates with brain structure. We objectively measured at-home sleep to investigate how sleep architecture and sleep quality related to white matter microstructure in older adults. 43 cognitively normal, older adults underwent diffusion tensor imaging (DTI) and a sleep assessment within a six-month period. Participants completed the PSQI, a subjective measure of sleep quality, and used an at-home sleep recorder (Zeo, Inc.) to measure total sleep time (TST), sleep efficiency (SE), and percent time in light sleep (LS), deep sleep (DS), and REM sleep (RS). Multiple regressions predicted fractional anisotropy (FA) and mean diffusivity (MD) of the corpus callosum as a function of total PSQI score, TST, SE, and percent of time spent in each sleep stage, controlling for age and sex. Greater percent time spent in RS was significantly associated with higher FA (β = 0.41, p = 0.007) and lower MD (β = -0.30, p = 0.03). Total PSQI score, TST, SE, and time spent in LS or DS were not significantly associated with FA or MD (p>0.13). Percent time spent in REM sleep, but not quantity of light and deep sleep or subjective/objective measures of sleep quality, positively predicted white matter microstructure integrity. Our results highlight an important link between REM sleep and brain health that has the potential to improve sleep interventions in the elderly.

Sleep-wake regulation and the hallmarks of the pathogenesis of Alzheimer's disease

While efficient treatments for Alzheimer's disease (AD) remain elusive, a growing body of research has highlighted sleep-wake regulation as a potential modifiable factor to delay disease progression. Evidence accumulated in recent years is pointing toward a tight link between sleep-wake disruption and the three main hallmarks of the pathogenesis of AD, i.e. abnormal amyloid-beta (Aβ) and tau proteins accumulation, and neurodegeneration. However, all three hallmarks are rarely considered together in the same study. In this review, we gather and discuss findings in favor of an association between sleep-wake disruption and each AD hallmark in animal models and in humans, with a focus on the preclinical stages of the disease. We emphasize that these relationships are likely bidirectional for each of these hallmarks. Altogether, current findings provide strong support for considering sleep-wake disruption as a true risk factor in the early unfolding of AD, but more research integrating recent technical advances is needed, particularly with respect to tau protein and neurodegeneration. Interventional longitudinal studies among cognitively healthy older individuals should assess the practical use of improving sleep-wake regulation to slow down the progression of AD pathogenesis.

24-h Activity Rhythms and Health in Older Adults

Purpose of Review

Circadian rhythms, including 24-h activity rhythms, change with age. Disturbances in these 24-h activity rhythms at older age have also been implied in various diseases. This review evaluates recent findings on 24-h activity rhythms and disease in older adults.

Recent Findings

Growing evidence supports that 24-h activity rhythm disturbances at older age are related to the presence and/or progression of disease. Longitudinal and genetic work even suggests a potential causal contribution of disturbed 24-h activity rhythms to disease development. Interventional studies targeting circadian and 24-h activity rhythms demonstrate that 24-h rhythmicity can be improved, but the effect of improving 24-h rhythmicity on disease risk or progression remains to be shown.

Summary

Increasing evidence suggests that 24-h activity rhythms are involved in age-related diseases. Further studies are needed to assess causality, underlying mechanisms, and the effects of treating disturbed 24-h activity rhythms on age-related disease.

Preserved wake-dependent cortical excitability dynamics predict cognitive fitness beyond age-related brain alterations

Age-related cognitive decline arises from alterations in brain structure as well as in sleep-wake regulation. Here, we investigated whether preserved wake-dependent regulation of cortical function could represent a positive factor for cognitive fitness in aging. We quantified cortical excitability dynamics during prolonged wakefulness as a sensitive marker of age-related alteration in sleep-wake regulation in 60 healthy older individuals (50-69 y; 42 women). Brain structural integrity was assessed with amyloid-beta- and tau-PET, and with MRI. Participants' cognition was investigated using an extensive neuropsychological task battery. We show that individuals with preserved wake-dependent cortical excitability dynamics exhibit better cognitive performance, particularly in the executive domain which is essential to successful cognitive aging. Critically, this association remained significant after accounting for brain structural integrity measures. Preserved dynamics of basic brain function during wakefulness could therefore be essential to cognitive fitness in aging, independently from age-related brain structural modifications that can ultimately lead to dementia.

Relationships between objectives sleep parameters and brain amyloid load in subjects at risk for Alzheimer’s disease: the INSIGHT-preAD Study

Study Objectives

Sleep changes have been associated with increased risks of developing cognitive disturbances and Alzheimer’s disease (AD). A bidirectional relation is underlined between amyloid-beta (Aß) and sleep disruptions. The sleep profile in participants at risk to develop AD is not fully deciphered. We aim to investigate sleep–wake changes with objective sleep measurements in elderly participants without cognitive impairment depending on their brain amyloid status, positive (Aß+) or negative (Aß−) based on standard absorption ratios (SUVr) positron emission tomography-florbetapir imaging.

Methods

Sixty-eight participants without cognitive impairment who have accepted to be involved in the sleep ancillary study from the InveStIGation of Alzheimer’s Predictors in Subjective Memory Complainers (INSIGHT-pre AD) cohort, aiming to record sleep profile based on the analyses of an ambulatory accelerometer-based assessment (seven consecutive 24-hour periods). Neuropsychological tests were performed and sleep parameters have been individualized by actigraph. Participants also underwent a magnetic resonance imaging scan to assess their hippocampal volume. Based on SUVr PET-florbetapir imaging, two groups Aß+ and Aß− were compared.

Results

Participants were divided into two groups: Aß+ (n = 24) and Aß− (n = 44). Except for the SUVr, the two subgroups were comparable. When looking to sleep parameters, increased sleep latency, sleep fragmentation (wake after sleep onset [WASO] score and awakenings) and worst sleep efficiency were associated with cortical brain amyloid load.

Conclusion

Actigraphic sleep parameters were associated with cortical brain amyloid load in participants at risk to develop AD. The detection of sleep abnormalities in those participants may be of interest to propose some preventive strategies.

Association between circadian rhythms and neurodegenerative diseases

Dysfunction in 24-h circadian rhythms is a common occurrence in ageing adults; however, circadian rhythm disruptions are more severe in people with age-related neurodegenerative diseases, including Alzheimer's disease and related dementias, and Parkinson's disease. Manifestations of circadian rhythm disruptions differ according to the type and severity of neurodegenerative disease and, for some patients, occur before the onset of typical clinical symptoms of neurodegeneration. Evidence from preliminary studies suggest that circadian rhythm disruptions, in addition to being a symptom of neurodegeneration, might also be a potential risk factor for developing Alzheimer's disease and related dementias, and Parkinson's disease, although large, longitudinal studies are needed to confirm this relationship. The mechanistic link between circadian rhythms and neurodegeneration is still not fully understood, although proposed underlying pathways include alterations of protein homoeostasis and immune and inflammatory function. While preliminary clinical studies are promising, more studies of circadian rhythm disruptions and its mechanisms are required. Furthermore, clinical trials are needed to determine whether circadian interventions could prevent or delay the onset of neurodegenerative diseases.

A Systematic Review of Evidence for a Role of Rest-Activity Rhythms in Dementia

Background: Rest-activity rhythm (RAR) disruption may be a risk factor for dementia that can be objectively measured with wearable accelerometers. It is possible that risk monitoring and preventive interventions could be developed targeting RARs. To evaluate whether current evidence supports these applications, we systematically reviewed published studies linking RARs with dementia, its course, and mechanisms. Methods: Entering pre-defined search terms in PsycINFO, MEDLINE, and PubMed databases returned 192 unique titles. We identified 32 articles that met our primary inclusion criteria, namely, that they examined objective RAR measures in the context of dementia, cognition, or brain biomarkers. Results: Cross-sectional studies consistently found that people with dementia had less stable (5/6 studies), more fragmented (4/6 studies), lower amplitude rhythms (5/5 studies), that had a worse fit to 24-h models (3/3 studies). Findings from studies relating RARs to cognitive test performance (rather than diagnostic status) were more nuanced. RAR fragmentation was associated with neurodegeneration biomarkers in 2/2 studies; and 1/1 study found 24-h model fit related to hippocampal hyperactivation. Although 2/2 studies found RARs related to markers of cerebrovascular disease, the specific RARs and cerebrovascular disease measures were not consistent. Longitudinal studies (3/3 articles) reported that lower amplitude and worse 24-h rhythm fit predicted future cognitive impairment and executive function. However, interventions aimed at modifying RARs had mixed effects (e.g., 0/4 studies demonstrated effects of morning light on 24-h model fit; evening light was associated with improved 24-h fit in 2/2 studies reporting); these effects may be more evident in subgroups. Conclusions: Consistent evidence shows that dementia is associated with disrupted RARs. Importantly, recent studies have shown that RAR disruption is associated with dementia biomarkers and, prospectively, with the risk of cognitive impairment. Interventions mostly tried using bright light to modify RARs in people who already have dementia; these studies produced modest effects on RARs and did not show modification of dementia's course. Altogether, these findings suggest studies are needed to understand how RARs relate to changes in brain health earlier in the disease process. Better understanding of the biopsychosocial mechanisms linking RARs with future dementia risk can help further target intervention development.

Poor Sleep Quality Associates With Decreased Functional and Structural Brain Connectivity in Normative Aging: A MRI Multimodal Approach

Sleep is a ubiquitous phenomenon, essential to the organism homeostasis. Notwithstanding, there has been an increasing concern with its disruption, not only within the context of pathological conditions, such as neurologic and psychiatric diseases, but also in health. In fact, sleep complaints are becoming particularly common, especially in middle-aged and older adults, which may suggest an underlying susceptibility to sleep quality loss and/or its consequences. Thus, a whole-brain modeling approach to study the shifts in the system can cast broader light on sleep quality mechanisms and its associated morbidities. Following this line, we sought to determine the association between the standard self-reported measure of sleep quality, the Pittsburgh Sleep Quality Index (PSQI) and brain correlates in a normative aging cohort. To this purpose, 86 participants (age range 52–87 years) provided information regarding sociodemographic parameters, subjective sleep quality and associated psychological variables. A multimodal magnetic resonance imaging (MRI) approach was used, with whole-brain functional and structural connectomes being derived from resting-state functional connectivity (FC) and probabilistic white matter tractography (structural connectivity, SC). Brain regional volumes and white matter properties associations were also explored. Results show that poor sleep quality was associated with a decrease in FC and SC of distinct networks, overlapping in right superior temporal pole, left middle temporal and left inferior occipital regions. Age displayed important associations with volumetric changes in the cerebellum cortex and white matter, thalamus, hippocampus, right putamen, left supramarginal and left lingual regions. Overall, results suggest that not only the PSQI global score may act as a proxy of changes in FC/SC in middle-aged and older individuals, but also that the age-related regional volumetric changes may be associated to an adjustment of brain connectivity. These findings may also represent a step further in the comprehension of the role of sleep disturbance in disease, since the networks found share regions that have been shown to be affected in pathologies, such as depression and Alzheimer's disease.