Quantification of the fragmentation of rest-activity patterns in elderly individuals using a state transition analysis

Sleep trajectories across three cognitive-aging pathways in community older adults

INTRODUCTION

Comparing sleep and rest-activity rhythms across different cognitive aging pathways can identify novel risk factors and potential mechanisms. However, our current understanding is restricted by differences in sleep measurement, limited longitudinal data, and heterogeneous cognitive aging processes.

METHODS

We applied cubic splines to longitudinal self-reported sleep and actigraphy data from 1449 participants in the Rush Memory and Aging Project and quantified differences in the levels and trajectories of sleep amount, regularity, and timing within and between three cognitive aging pathways: normal, stable mild cognitive impairment, dementia.

RESULTS

Sleep amount was lowest in the dementia pathway prior to cognitive impairment but increased with age, most rapidly after dementia. Regularity declined across all pathways, most rapidly after cognitive diagnoses. Timing advanced across all pathways.

DISCUSSION

Shorter sleep amount in cognitively healthy older adults may be a risk factor or prodromal indicator of dementia, while longer sleep amounts and decreasing regularity may reflect neurodegeneration.

HIGHLIGHTS

We quantified longitudinal changes in sleep across three cognitive-aging pathways. We incorporated both subjective and objective measures of sleep health. Self-report duration increased noticeably from before to after cognitive diagnosis. Sleep irregularity increased most prominently after cognitive diagnosis. Advances in sleep timing occurred in both normal and pathological aging.

The Past and Future of Sleep Medicine

The past of sleep medicine is rich with seminal discoveries, from the recognition of clinical syndromes to measurement of sleep itself to classic and novel therapeutics. Advances in neurobiology have mapped a number of sleep circuits, described the central and peripheral circadian system, and identified the cause of narcolepsy with cataplexy. Sleep apnea endotypes and phenotypes now have established clinical relevance, though treatment implications are a work in progress. Artificial intelligence will continue to change sleep medicine in a number of domains from aiding scoring to health outcome predictions. There is a large gap between the known science and clinical translational.

The bright and dark side of blue-enriched light on sleep and activity in older adults

Low indoor light in urban housing can disrupt health and wellbeing, especially in older adults who experience reduced light sensitivity and sleep/circadian disruptions with natural aging. While controlled studies suggest that enhancing indoor lighting may alleviate the negative effects of reduced light sensitivity, evidence for this to be effective in the real world is lacking. This study investigates the effects of two light conditions on actigraphic rest-activity rhythms and subjective sleep in healthy older adults (≥ 60 years) living at home. Two photon-matched lights were compared; a control white light (4000 K) and a blue-enriched white light (17000 K) at two different intensities (300-450 lx and 1100-1200 lx respectively). Participants (n = 36, 25 female) completed an 11-week randomized, cross-over study, comprising 1 week of baseline, 3 weeks of self-administered light exposure (2 h in the morning and 2 h in the evening), and 2 weeks of washout for each light condition. Participants completed sleep diaries, wore a wrist actigraph and a light sensor necklace, and collected urine to measure 6-sulphatoxymelatonin. Longer duration of morning blue-enriched light significantly improved rest-activity rhythm stability and decreased sleep fragmentation. More time spent above 2500 lx increased actigraphy amplitude, daytime activity, and advanced bedtime. Evening light exposure, however, increased sleep latency and lowered sleep efficiency. Our findings show morning blue-enriched light is beneficial whereas evening light should be avoided. Optimal timing of self-administered light interventions thus may offer a promising strategy to improve sleep and rest-activity rhythms in older adults in real-world settings.

Behavioral patterns in elderly single-person households

The global rise in the aging population and the increase in older adults living alone have raised concerns about health-related behaviors, particularly sedentary lifestyles and reduced daily activities. These behaviors are linked to higher risks of physical and cognitive conditions. While many global studies have explored these patterns, research within the Chilean context remains limited. This work presents a analysis of behavioral patterns in elderly individuals living alone in Chile, offering valuable insights into this population. Using clustering techniques, we identified two distinct activity patterns among the participants. The first pattern is characterized by a gradual increase in activity during the day, peaking around midday and followed by a decline, likely associated with meal preparation and rest. The second pattern demonstrates a more dynamic lifestyle, with a rapid surge in activity after waking and sustained levels throughout the day, suggesting a potentially healthier approach to aging. These findings align with previous studies indicating high levels of sedentary behavior in older adults, reinforcing the need for interventions tailored to diversify daily routines and promote physical activity. This study is the first to explore these patterns in the Chilean context, contributing to a more comprehensive understanding of elderly care and informing future strategies for improving the well-being of older adults living alone.

Reliable measures of rest-activity rhythm fragmentation: how many days are needed?

BACKGROUND

A more fragmented, less stable rest-activity rhythm (RAR) is emerging as a risk factor for health. Accelerometer devices are increasingly used to measure RAR fragmentation using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probabilities (TP), self-similarity parameter (α), and activity balance index (ABI). These metrics were proposed in the context of long period of wear but, in real life, non-wear might introduce measurement bias. This study aims to determine the minimum number of valid days to obtain reliable fragmentation metrics.

METHODS

Wrist-worn accelerometer data were drawn from the Whitehall accelerometer sub-study (age: 60 to 83 years) to simulate different non-wear patterns. Pseudo-simulated data with different numbers of valid days (one to seven), defined as < 1/3 of non-wear during both day and night periods, and with omission or imputation of non-wear periods were compared against complete data using intraclass correlation coefficient (ICC) and mean absolute percent error (MAPE).

RESULTS

Five days with valid data (97.8% of participants) and omission of non-wear periods allowed an ICC ≥ 0.75 and MAPE ≤ 15%, acceptable cut points for reliability, for IS and ABI; this number was lower for TPs (two-three days), α and IV (four days). Overall, imputation of data did not provide better estimates. Findings were consistent across age and sex groups.

CONCLUSIONS

The number of days of wrist accelerometer data with at least 2/3 of wear time for both day and night periods varies from two (TPs) to five (IS, ABI) days for reliable RAR measures among older adults.

Measures of fragmentation of rest activity patterns: mathematical properties and interpretability based on accelerometer real life data

Accelerometers, devices that measure body movements, have become valuable tools for studying the fragmentation of rest-activity patterns, a core circadian rhythm dimension, using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probability (TP), and self-similarity parameter (named α ). However, their use remains mainly empirical. Therefore, we investigated the mathematical properties and interpretability of rest-activity fragmentation metrics by providing mathematical proofs for the ranges of IS and IV, proposing maximum likelihood and Bayesian estimators for TP, introducing the activity balance index (ABI) metric, a transformation of α , and describing distributions of these metrics in real-life setting. Analysis of accelerometer data from 2,859 individuals (age=60-83 years, 21.1% women) from the Whitehall II cohort (UK) shows modest correlations between the metrics, except for ABI and α . Sociodemographic (age, sex, education, employment status) and clinical (body mass index (BMI), and number of morbidities) factors were associated with these metrics, with differences observed according to metrics. For example, a difference of 5 units in BMI was associated with all metrics (differences ranging between -0.261 (95% CI -0.302, -0.220) to 0.228 (0.18, 0.268) for standardised TP rest to activity during the awake period and TP activity to rest during the awake period, respectively). These results reinforce the value of these rest-activity fragmentation metrics in epidemiological and clinical studies to examine their role for health. This paper expands on a set of methods that have previously demonstrated empirical value, improves the theoretical foundation for these methods, and evaluates their empirical use in a large dataset.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

INTERPRETATION

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

Altered Motor Activity Patterns within 10-Minute Timescale Predict Incident Clinical Alzheimer's Disease

Background

Fractal motor activity regulation (FMAR), characterized by self-similar temporal patterns in motor activity across timescales, is robust in healthy young humans but degrades with aging and in Alzheimer's disease (AD).

Objective

To determine the timescales where alterations of FMAR can best predict the clinical onset of AD.

Methods

FMAR was assessed from actigraphy at baseline in 1,077 participants who had annual follow-up clinical assessments for up to 15 years. Survival analysis combined with deep learning (DeepSurv) was used to examine how baseline FMAR at different timescales from 3 minutes up to 6 hours contributed differently to the risk for incident clinical AD.

Results

Clinical AD occurred in 270 participants during the follow-up. DeepSurv identified three potential regions of timescales in which FMAR alterations were significantly linked to the risk for clinical AD: <10, 20-40, and 100-200 minutes. Confirmed by the Cox and random survival forest models, the effect of FMAR alterations in the timescale of <10 minutes was the strongest, after adjusting for covariates.

Conclusions

Subtle changes in motor activity fluctuations predicted the clinical onset of AD, with the strongest association observed in activity fluctuations at timescales <10 minutes. These findings suggest that short actigraphy recordings may be used to assess the risk of AD.

Circadian disturbances and frailty risk in older adults

Frailty is characterized by diminished resilience to stressor events. It is associated with adverse future health outcomes and impedes healthy aging. The circadian system orchestrates ~24-h rhythms in bodily functions in synchrony with the day-night cycle, and disturbed circadian regulation plays an important role in many age-related health consequences. We investigated prospective associations of circadian disturbances with incident frailty in over 1000 older adults who had been followed annually for up to 16 years. We found that decreased rhythm strength, reduced stability, or increased variation were associated with a higher risk of incident frailty and faster progress of frailty over time. Perturbed circadian rest-activity rhythms may be an early sign or risk factor for frailty in older adults.

Measures of fragmentation of rest activity patterns: mathematical properties and interpretability based on accelerometer real life data

Accelerometers, devices that measure body movements, have become valuable tools for studying the fragmentation of rest-activity patterns, a core circadian rhythm dimension, using metrics such as inter-daily stability (IS), intradaily variability (IV), transition probability (TP), and self-similarity parameter (named α ). However, their use remains mainly empirical. Therefore, we investigated the mathematical properties and interpretability of rest-activity fragmentation metrics by providing mathematical proofs for the ranges of IS and IV, proposing maximum likelihood and Bayesian estimators for TP, introducing the activity balance index metric, an adaptation of α , and describing distributions of these metrics in real-life setting. Analysis of accelerometer data from 2,859 individuals (age=60-83 years, 21.1% women) from the Whitehall II cohort (UK) shows modest correlations between the metrics, except for ABI and α . Sociodemographic (age, sex, education, employment status) and clinical (body mass index (BMI), and number of morbidities) factors were associated with these metrics, with differences observed according to metrics. For example, a difference of 5 units in BMI was associated with all metrics (differences ranging between -0.261 (95% CI -0.302, -0.220) to 0.228 (0.18, 0.268) for standardised TP rest to activity during the awake period and TP activity to rest during the awake period, respectively). These results reinforce the value of these rest-activity fragmentation metrics in epidemiological and clinical studies to examine their role for health. This paper expands on a set of methods that have previously demonstrated empirical value, improves the theoretical foundation for these methods, and evaluates their empirical worth in a large dataset.

Personalized relapse prediction in patients with major depressive disorder using digital biomarkers

Major depressive disorder (MDD) is a chronic illness wherein relapses contribute to significant patient morbidity and mortality. Near-term prediction of relapses in MDD patients has the potential to improve outcomes by helping implement a 'predict and preempt' paradigm in clinical care. In this study, we developed a novel personalized (N-of-1) encoder-decoder anomaly detection-based framework of combining anomalies in multivariate actigraphy features (passive) as triggers to utilize an active concurrent self-reported symptomatology questionnaire (core symptoms of depression and anxiety) to predict near-term relapse in MDD. The framework was evaluated on two independent longitudinal observational trials, characterized by regular bimonthly (every other month) in-person clinical assessments, weekly self-reported symptom assessments, and continuous activity monitoring data with two different wearable sensors for ≥ 1 year or until the first relapse episode. This combined passive-active relapse prediction framework achieved a balanced accuracy of ≥ 71%, false alarm rate of ≤ 2.3 alarm/patient/year with a median relapse detection time of 2-3 weeks in advance of clinical onset in both studies. The study results suggest that the proposed personalized N-of-1 prediction framework is generalizable and can help predict a majority of MDD relapses in an actionable time frame with relatively low patient and provider burden.

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.

Correlates of Person-Specific Rates of Change in Sensor-Derived Physical Activity Metrics of Daily Living in the Rush Memory and Aging Project

This study characterized person-specific rates of change of total daily physical activity (TDPA) and identified correlates of this change. TDPA metrics were extracted from multiday wrist-sensor recordings from 1083 older adults (average age 81 years; 76% female). Thirty-two covariates were collected at baseline. A series of linear mixed-effect models were used to identify covariates independently associated with the level and annual rate of change of TDPA. Though, person-specific rates of change varied during a mean follow-up of 5 years, 1079 of 1083 showed declining TDPA. The average decline was 16%/year, with a 4% increased rate of decline for every 10 years of age older at baseline. Following variable selection using multivariate modeling with forward and then backward elimination, age, sex, education, and 3 of 27 non-demographic covariates including motor abilities, a fractal metric, and IADL disability remained significantly associated with declining TDPA accounting for 21% of its variance (9% non-demographic and 12% demographics covariates). These results show that declining TDPA occurs in many very old adults. Few covariates remained correlated with this decline and the majority of its variance remained unexplained. Further work is needed to elucidate the biology underlying TDPA and to identify other factors that account for its decline.

Circadian disturbances and frailty risk in older adults: a prospective cohort study

Frailty is characterized by diminished resilience to stressor events. It associates with adverse future health outcomes and impedes healthy aging. The circadian system orchestrates a ~24-h rhythm in bodily functions in synchrony with the day-night cycle, and disturbed circadian regulation plays an important role in many age-related health consequences. We investigated prospective associations of circadian disturbances with incident frailty in over 1,000 older adults who had been followed annually for up to 16 years. We found that decreased rhythm strength, reduced stability, or increased variation, were associated with a higher risk of incident frailty, and faster worsening of the overall frailty symptoms over time. Perturbed circadian rest-activity rhythms may be an early sign or risk factor for frailty in older adults.

Fragmentation, circadian amplitude, and fractal pattern of daily-living physical activity in people with multiple sclerosis: Is there relevant information beyond the total amount of physical activity?

BACKGROUND

Physical activity is lower in people with multiple sclerosis (pwMS) compared to healthy controls. Previous work focused on studying activity levels or activity volume, but studies of daily-living rest-activity fragmentation patterns, circadian rhythms, and fractal regulation in pwMS are limited. Based on findings in other cohorts, one could suggest that these aspects of daily-living physical activity will provide additional information about the health and well-being of pwMS. Therefore, here, we aimed to (1) identify which fragmentation, fractal, and circadian amplitude measures differ between pwMS and healthy controls, (2) evaluate the relationship between fragmentation, fractal, and circadian amplitude measures and disease severity, and (3) begin to evaluate the added value of those measures, as compared to more conventional measures of physical activity (e.g., mean signal vector magnitude (SVM). A global measure of the overall volume of physical activity).

METHODS

132 people with relapsing-remitting MS (47±11 yrs, 69.7% female, Expanded Disability Status Scale, EDSS, median (IQR): 3 (2-4)) and 90 healthy controls (46±11 yrs, 47.8% female) were asked to wear a 3D accelerometer on their lower back for 7 days. Rest-activity fragmentation, circadian amplitude, fractal regulation, and mean SVM metrics were extracted. PwMS and healthy controls were compared using independent samples t-tests and linear regression, including comparisons adjusted for mean SVM to control for the effect of physical activity volume. Spearman correlations between measures and logistic regressions were used to identify the clinical condition based on the measures that differed significantly after adjusting for SVM. All analyses included adjustments for demographic and clinical parameters (e.g., age, sex).

RESULTS

Multiple measures of activity fragmentation significantly differed between pwMS and healthy controls, reflecting a more fragmented active behavior in pwMS. PwMS had a lower circadian rhythm amplitude, indicating a smaller amplitude in the circadian changes of daily activity, and weaker temporal correlations as based on the fractal analysis. When taking into account physical activity volume, one circadian amplitude measure and one fractal measure remained significantly different in pwMS and controls. Fragmentation measures and circadian amplitude measures were significantly associated with disability level as measured by the EDSS; the association with circadian amplitude remained significant, even after adjusting for the mean SVM.

CONCLUSION

The physical activity patterns of pwMS differ from those of healthy individuals in rest-activity fragmentation, the amplitude of the circadian rhythm, and fractal regulation. Measures describing these aspects of activity provide information that is not captured in the total volume of physical activity and could, perhaps, augment the monitoring of disease progression and evaluation of the response to interventions.

Changes in the rest-activity rhythm in migraine patients are associated with anxiety symptoms

OBJECTIVE

To characterize rest-activity rhythm in chronic migraine (CM) and to investigate the relationship between this rhythm and depressive and anxiety symptoms in patients with CM.

METHODS

This was a study of adults aged 20 to 40 years. The rest-activity rhythm of patients with CM (n=23) and non-headache controls (NH, n=23) was assessed by actigraphy for 15 days, and they completed the following assessments: Visual Analogue Scale for pain intensity; Headache Diary; Headache Impact Test-6; Morningness-Eveningness Questionnaire; Pittsburgh Sleep Quality Index; Epworth Sleepiness Scale; Beck Depression Inventory; and State-Trait Anxiety Inventory.

RESULTS

Patients with CM showed less activity over 24 hours and more fragmented sleep. Reduced interdaily stability of the rest-activity rhythm was observed, with less robustness of this rhythm in the CM group. Multiple linear regressions revealed a significant association between the rest-activity rhythm and trait anxiety variables in patients with CM, specifically regarding the relative amplitude of the cycle, activity throughout 24 hours and during sleep, and robustness of the rest-activity rhythm.

CONCLUSIONS

Our findings provide evidence that the robustness of the rest-activity rhythm, activity throughout 24 hours, and sleep fragmentation are associated with trait anxiety in patients with CM.

Daytime rest: Association with 24-h rest-activity cycles, circadian timing and cognition in older adults

Growing epidemiological evidence points toward an association between fragmented 24-h rest-activity cycles and cognition in the aged. Alterations in the circadian timing system might at least partially account for these observations. Here, we tested whether daytime rest (DTR) is associated with changes in concomitant 24-h rest probability profiles, circadian timing and neurobehavioural outcomes in healthy older adults. Sixty-three individuals (59-82 years) underwent field actigraphy monitoring, in-lab dim light melatonin onset assessment and an extensive cognitive test battery. Actimetry recordings were used to measure DTR frequency, duration and timing and to extract 24-h rest probability profiles. As expected, increasing DTR frequency was associated not only with higher rest probabilities during the day, but also with lower rest probabilities during the night, suggesting more fragmented night-time rest. Higher DTR frequency was also associated with lower episodic memory performance. Moreover, later DTR timing went along with an advanced circadian phase as well as with an altered phase angle of entrainment between the rest-activity cycle and circadian phase. Our results suggest that different DTR characteristics, as reflective indices of wake fragmentation, are not only underlined by functional consequences on cognition, but also by circadian alteration in the aged.

The effects of napping on night‐time sleep in healthy young adults

The discrepancies in the effects of napping on sleep quality may be due to differences in methodologies, napping behaviours, and daytime activity levels across studies. We determined whether napping behaviours and daytime activity levels are associated with night-time sleep fragmentation and sleep quality in young adults. A total of 62 healthy adults (mean [SD] age 23.5 [4.2] years) completed screening questionnaires for sleep habits, physical activity, medical and psychological history. Actigraphy was used to record sleep including naps. The fragmentation algorithm (K_RA ) was applied to the actigraphic data to measure night-time sleep fragmentation. We classified participants' nap frequency as "non-nappers" (0 naps/8 days), "moderate nappers" (1-2 naps/8 days) or "frequent nappers" (≥3 naps/8 days) naps. Nap duration was defined as "short" (≤60 min) or "long" (>60 min). Naps' proximity to the night sleep episode was defined as "early" (≥7 h) and "late" (<7 h) naps. Outcome variables were night-time K_RA and actigraphic sleep variables. Frequent nappers had a significantly higher K_RA than moderate nappers (p < 0.01) and non-nappers (p < 0.02). Late naps were associated with poorer measures of night sleep quality versus early naps (all p ≤ 0.02). Nap duration and daytime activity were not associated with significant differences in the outcome variables (all p > 0.05). K_RA correlated with sleep duration, sleep efficiency, and awakenings (r = -0.32, -0.32, and 0.53, respectively; all p < 0.05). Frequent napping and late naps may be associated with increased sleep fragmentation and poorer sleep quality, reflected in longer sleep onsets and increased awakenings. These findings have implications for public health sleep hygiene recommendations.

ENIGMA-Sleep: Challenges, opportunities, and the road map

Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine.

Feasibility of a continuous, multi-sensor remote health monitoring approach in persons living with neurodegenerative disease

BACKGROUND

Remote health monitoring with wearable sensor technology may positively impact patient self-management and clinical care. In individuals with complex health conditions, multi-sensor wear may yield meaningful information about health-related behaviors. Despite available technology, feasibility of device-wearing in daily life has received little attention in persons with physical or cognitive limitations. This mixed methods study assessed the feasibility of continuous, multi-sensor wear in persons with cerebrovascular (CVD) or neurodegenerative disease (NDD).

METHODS

Thirty-nine participants with CVD, Alzheimer's disease/amnestic mild cognitive impairment, frontotemporal dementia, Parkinson's disease, or amyotrophic lateral sclerosis (median age 68 (45-83) years, 36% female) wore five devices (bilateral ankles and wrists, chest) continuously for a 7-day period. Adherence to device wearing was quantified by examining volume and pattern of device removal (non-wear). A thematic analysis of semi-structured de-brief interviews with participants and study partners was used to examine user acceptance.

RESULTS

Adherence to multi-sensor wear, defined as a minimum of three devices worn concurrently, was high (median 98.2% of the study period). Non-wear rates were low across all sensor locations (median 17-22 min/day), with significant differences between some locations (p = 0.006). Multi-sensor non-wear was higher for daytime versus nighttime wear (p < 0.001) and there was a small but significant increase in non-wear over the collection period (p = 0.04). Feedback from de-brief interviews suggested that multi-sensor wear was generally well accepted by both participants and study partners.

CONCLUSION

A continuous, multi-sensor remote health monitoring approach is feasible in a cohort of persons with CVD or NDD.

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.

Objective Assessment of Daytime Napping and Incident Heart Failure in 1140 Community-Dwelling Older Adults: A Prospective, Observational Cohort Study

Background Disrupted nighttime sleep has been associated with heart failure (HF). However, the relationship between daytime napping, an important aspect of sleep behavior commonly seen in older adults, and HF remains unclear. We sought to investigate the association of objectively assessed daytime napping and risk of incident HF during follow-up. Methods and Results We studied 1140 older adults (age, 80.7±7.4 [SD] years; female sex, 867 [76.1%]) in the Rush Memory and Aging Project who had no HF at baseline and were followed annually for up to 14 years. Motor activity (ie, actigraphy) was recorded for ≈10 days at baseline. We assessed daytime napping episodes between 9 am and 7 pm objectively from actigraphy using a previously published algorithm for sleep detection. Cox proportional hazards models examined associations of daily napping duration and frequency with incident HF. Eighty-six participants developed incident HF, and the mean onset time was 5.7 years (SD, 3.4; range, 1-14). Participants who napped longer than 44.4 minutes (ie, the median daily napping duration) showed a 1.73-fold higher risk of developing incident HF than participants who napped <44.4 minutes. Consistently, participants who napped >1.7 times/day (ie, the median daily napping frequency) showed a 2.20-fold increase compared with participants who napped <1.7 times/day. These associations persisted after adjustment for covariates, including nighttime sleep, comorbidities, and cardiovascular disease/risk factors. Conclusions Longer and more frequent objective napping predicted elevated future risk of developing incident HF. Future studies are needed to establish underlying mechanisms.

Is moderate depression associated with sleep stage architecture in adolescence? Testing the stage type associations using network and transition probability approaches

BACKGROUND

Depression even at the subclinical level is often accompanied by sleep disturbances, but little is known about the dynamics of the sleep stages in relation to depressive symptoms. We examined whether the amount, associations, and transition probabilities of various sleep stages were associated with depressive symptoms in a community sample of adolescents.

METHODS

The participants (N = 172, 59% girls, mean age 16.9 years) underwent overnight polysomnography and provided data on depressive symptoms (Beck Depression Inventory II). The association between depression status and total duration of each stage type was analyzed using ANOVA and survival analyses. The associations between the number of different sleep stage types were analyzed using graphical Gaussian models, mixed graphical models, and relative importance networks. A Markov chain algorithm was used to estimate the transition probabilities between each state and these probabilities were further compared between depression status groups.

RESULTS

The associations between N1 and N3 were significantly stronger in both directions of the association (p-values for interactions 0.012 and 0.006) in those with more depressive symptoms. Similarly, a stronger association was observed from N1 to wake stage in those with more depressive symptoms (p-value for interaction 0.002). In those with more depressive symptoms, it was more likely to transition from N2 to N3 and from REM to N2 compared to others.

CONCLUSIONS

These findings indicate that changes in sleep architecture are not limited to clinical depression and that the transitional dynamics of sleep stages are an important marker of subclinical depression.

Meta-analysis of differences in sleep quality based on actigraphs between day and night shift workers and the moderating effect of age

OBJECTIVES

This study was to conduct a meta-analysis of studies that used actigraphs to compare the influence of day and night shifts on the sleep quality of workers as well as examine the moderating effect of age.

METHODS

Databases including PubMed, CINAHL, the Cochrane Library, MEDLINE, and EBSCOhost were searched for relevant studies published in English between January 1st, 2000 and April 30st, 2021. Our main targets were studies that used actigraphs to assess the sleep quality of night shift workers. This meta-analysis included 12 papers and was performed using Comprehensive Meta-Analysis (CMA) Version 3.0. Effect sizes were displayed in a forest plot using standardized mean difference (SMD) and 95% confidence intervals (CI).

RESULTS

Among the sleep quality indices of the day and night shift workers, no significant difference existed in terms of sleep efficiency (SE) (SMD = 0.27, 95% CI: -0.03-0.57), whereas night shift workers presented longer sleep-onset latency (SOL) (SMD = 0.62, 95% CI: 0.15-1.08), greater wake after sleep onset (WASO) (SMD = 0.41, 95% CI: 0.12-0.70), and longer total sleep time (TST) (SMD = 0.85, 95% CI: 0.32-1.39) than did day shift workers. The differences between the day and night shift workers in SOL, WASO, and TST did not vary with age.

CONCLUSIONS

Among the sleep quality indices, night shift workers presented longer SOL and greater WASO than did day shift workers. However, night shift workers could regulate their rest time and had adequate TST; thus, their SE was not different from that of day shift workers.

Circadian disturbances in Alzheimer's disease progression: a prospective observational cohort study of community-based older adults

BACKGROUND

Circadian disturbances are commonly seen in people with Alzheimer's disease and have been reported in individuals without symptoms of dementia but with Alzheimer's pathology. We aimed to assess the temporal relationship between circadian disturbances and Alzheimer's progression.

METHODS

We did a prospective cohort study of 1401 healthy older adults (aged >59 years) enrolled in the Rush Memory and Aging Project (Rush University Medical Center, Chicago, IL, USA) who had been followed up for up to 15 years. Participants underwent annual assessments of cognition (with a battery of 21 cognitive performance tests) and motor activities (with actigraphy). Four measures were extracted from actigraphy to quantify daily and circadian rhythmicity, which were amplitude of 24-h activity rhythm, acrophase (representing peak activity time), interdaily stability of 24-h activity rhythm, and intradaily variability for hourly fragmentation of activity rhythm. We used Cox proportional hazards models and logistic regressions to assess whether circadian disturbances predict an increased risk of incident Alzheimer's dementia and conversion of mild cognitive impairment to Alzheimer's dementia. We used linear mixed-effects models to investigate how circadian rhythms changed longitudinally and how the change integrated to Alzheimer's progression.

FINDINGS

Participants had a median age of 81·8 (IQR 76·3-85·7) years. Risk of developing Alzheimer's dementia was increased with lower amplitude (1 SD decrease, hazard ratio [HR] 1·39, 95% CI 1·19-1·62) and higher intradaily variability (1 SD increase, 1·22, 1·04-1·43). In participants with mild cognitive impairment, increased risk of Alzheimer's dementia was predicted by lower amplitude (1 SD decrease, HR 1·46, 95% CI 1·24-1·72), higher intradaily variability (1 SD increase, 1·36, 1·15-1·60), and lower interdaily stability (1 SD decrease, 1·21, 1·02-1·44). A faster transition to Alzheimer's dementia in participants with mild cognitive impairment was predicted by lower amplitude (1 SD decrease, odds ratio [OR] 2·08, 95% CI 1·53-2·93), increased intradaily variability (1 SD increase, 1·97, 1·43-2·79), and decreased interdaily stability (1 SD decrease, 1·35, 1·01-1·84). Circadian amplitude, acrophase, and interdaily stability progressively decreased over time, and intradaily variability progressively increased over time. Alzheimer's progression accelerated these aging effects by doubling or more than doubling the annual changes in these measures after the diagnosis of mild cognitive impairment, and further doubled them after the diagnosis of Alzheimer's dementia. The longitudinal change of global cognition positively correlated with the longitudinal changes in amplitude and interdaily stability and negatively correlated with the longitudinal change in intradaily variability.

INTERPRETATION

Our results indicate a link between circadian dysregulation and Alzheimer's progression, implying either a bidirectional relation or shared common underlying pathophysiological mechanisms.

FUNDING

National Institutes of Health, and the BrightFocus Foundation.

More random motor activity fluctuations predict incident frailty, disability, and mortality

Mobile healthcare increasingly relies on analytical tools that can extract meaningful information from ambulatory physiological recordings. We tested whether a nonlinear tool of fractal physiology could predict long-term health consequences in a large, elderly cohort. Fractal physiology is an emerging field that aims to study how fractal temporal structures in physiological fluctuations generated by complex physiological networks can provide important information about system adaptability. We assessed fractal temporal correlations in the spontaneous fluctuations of ambulatory motor activity of 1275 older participants at baseline, with a follow-up period of up to 13 years. We found that people with reduced temporal correlations (more random activity fluctuations) at baseline had increased risk of frailty, disability, and all-cause death during follow-up. Specifically, for 1-SD decrease in the temporal activity correlations of this studied cohort, the risk of frailty increased by 31%, the risk of disability increased by 15 to 25%, and the risk of death increased by 26%. These incidences occurred on average 4.7 years (frailty), 3 to 4.2 years (disability), and 5.8 years (death) after baseline. These observations were independent of age, sex, education, chronic health conditions, depressive symptoms, cognition, motor function, and total daily activity. The temporal structures in daily motor activity fluctuations may contain unique prognostic information regarding wellness and health in the elderly population.

Sleep Fragmentation and Cognitive Trajectories After Critical Illness

BACKGROUND

ICU survivors can experience both cognitive dysfunction and persistent sleep disturbances after hospitalization. Sleep disturbances have been linked with cognitive impairment in various patient populations, and the apolipoprotein E (APOE) genotype has been linked to sleep-related impairments in cognition.

RESEARCH QUESTION

Is there an association between sleep, long-term cognition, and APOE status in ICU survivors?

STUDY DESIGN AND METHODS

We enrolled 150 patients from five centers who had been mechanically ventilated for at least 3 days; 102 patients survived to ICU discharge. Actigraphy and cognitive testing were undertaken at 7 days, 6 months, and 12 months after ICU discharge, and sleep duration, quality, and timing were estimated by actigraphy. APOE single nucleotide polymorphisms were assessed for each patient.

RESULTS

Actigraphy-estimated sleep fragmentation, but not total sleep time or interdaily stability (estimate of circadian rhythmicity), was associated with worse cognitive impairment at 7 days of ICU discharge. No actigraphy-estimated variable of sleep estimation at 7 days post-ICU discharge predicted cognitive impairment or persistent sleep abnormalities at 6 and 12 months of follow-up in subsequently assessed survivors. Possessing the APOE ε4 allele was not significantly associated with sleep disturbances and its presence did not modify the risk of sleep-related cognitive impairment at follow-up.

INTERPRETATION

Sleep fragmentation estimated by actigraphy was associated with worse cognitive performance in hospital, but not at later time intervals. Further research is needed to better delineate the relationship between persistent sleep disturbances and cognition in larger numbers of ICU survivors.

TRIAL REGISTRY

ClinicalTrials.gov; No.: NCT02086877; URL: www.clinicaltrials.gov.

Total daily physical activity, brain pathologies, and parkinsonism in older adults

Objective

We examined the association of physical activity, postmortem brain pathologies, and parkinsonism proximate to death in older adults.

Methods

We studied the brains of 447 older decedents participating in a clinical-autopsy cohort study. We deployed a wrist worn activity monitor to record total daily physical activity during everyday living in the community-setting. Parkinsonism was assessed with 26 items of a modified motor portion of Unified Parkinson’s Disease Rating Scale (UPDRS). We used linear regression models, controlling for age and sex, to examine the association of physical activity with parkinsonism with and without indices of Alzheimer’s disease and related disorders (ADRD) pathologies. In separate models, we added interaction terms to examine if physical activity modified the associations of brain pathologies with parkinsonism.

Results

Mean age at death was 90.9 (SD, 6.2), mean severity of parkinsonism was 14.1 (SD, 9.2, Range 0–59.4), and 350 (77%) had evidence of more than one ADRD pathologies. Higher total daily physical activity was associated with less severe parkinsonism (Estimate, -0.315, S.E., 0.052, p<0.001). The association of more physical activity with less severe parkinsonism persisted after adding terms for ten brain pathologies (Estimate, -0.283, S.E., 0.052, p<0.001). The associations of brain pathologies with more severe parkinsonism did not vary with the level of physical activity.

Conclusion

The association of higher physical activity with less severe parkinsonism may be independent of the presence of ADRD brain pathologies. Further work is needed to identify mechanisms through which physical activity may maintain motor function in older adults.

Fragmentation of Rest/Activity Patterns in Community-Based Elderly Individuals Predicts Incident Heart Failure

STUDY OBJECTIVES

Heart failure has previously been linked to sleep disorders that are often associated with frequent disturbances to human rest/activity patterns. We tested whether fragmentation of sustained rest/activity patterns derived from actigraphic recordings at baseline predicts incident heart failure in community-based elderly individuals.

METHODS

We studied 1099 community-based elderly adults participating in the Rush Memory and Aging Project who had baseline motor activity monitoring up to 11 days and were followed annually for up to 14 years. Fragmentation was assessed using previously validated indexes, derived from the probability of transitions once sustained rest or activity has been established. Heart failure was recorded via a clinical interview during the annual follow-up. Cox proportional hazards models were constructed to examine the relationship between rest fragmentation index and incident heart failure. Covariates grouped in terms of demographics, lifestyle factors and co-morbidities and cardiovascular risk factors/diseases were included.

RESULTS

Increased rest fragmentation (but not activity fragmentation) was associated with higher risk for incident heart failure. Specifically, a subject with a rest fragmentation at the 90th percentile showed a 57% increased risk of developing incident heart failure compared to a subject at the 10th percentile in this cohort. This effect was equivalent to that of being over a decade older. These observations were consistent after adjusting for all covariates.

CONCLUSION

Increased rest fragmentation, a potential surrogate for sleep fragmentation, is independently associated with a higher risk of developing heart failure in community-based elderly adults during up to 14 years of follow-up. Further work is required to examine the specific contributions from daytime napping versus nighttime sleep periods in the elderly, as well as the underlying autonomic and cardio-dynamic pathways that may explain the effects on heart function.

Sleep fragmentation, microglial aging, and cognitive impairment in adults with and without Alzheimer's dementia

Sleep disruption is associated with cognitive decline and dementia in older adults; however, the underlying mechanisms are unclear. In rodents, sleep disruption causes microglial activation, inhibition of which improves cognition. However, data from humans are lacking. We studied participants in two cohort studies of older persons-the Rush Memory and Aging Project and the Religious Orders Study. We assessed sleep fragmentation by actigraphy and related this to cognitive function, to neocortical microglial marker gene expression measured by RNA sequencing, and to the neocortical density of microglia assessed by immunohistochemistry. Greater sleep fragmentation was associated with higher neocortical expression of genes characteristic of aged microglia, and a higher proportion of morphologically activated microglia, independent of chronological age- and dementia-related neuropathologies. Furthermore, these were, in turn, associated with worse cognition. This suggests that sleep fragmentation is accompanied by accelerated microglial aging and activation, which may partially underlie its association with cognitive impairment.

Actigraphy Detects Greater Intra-Individual Variability During Gait in Non-Manifesting LRRK2 Mutation Carriers

BACKGROUND

With recent advances in the search for disease-modifying therapies for Parkinson's disease (PD) the importance of identifying prodromal markers becomes greater. Non-manifesting LRRK2 mutation carriers (NMC) are at risk for developing PD, and provide a population in which to identify possible markers.

OBJECTIVE

The aim of this study was to test the hypothesis that NMC have differences in daily activity, fragmentation of sleep, arm swing asymmetry, and movement variability during walking, detectable by actigraphy, as compared to matched control subjects.

METHODS

Eleven NMC, fourteen PD patients (4 LRRK2-PD, 10 idiopathic PD (iPD)), and twenty-nine controls wore wristbands containing an accelerometer for seven days, and performed a daily walking task. Outcome measures included daily activity, fragmentation of activity, fragmentation of sleep, arm swing asymmetry during walking, and intra-individual variability.

RESULTS

Compared to healthy controls, both NMC and LRRK2/iPD showed higher intra-individual variability in activity during walking compared to healthy controls. Individuals with LRRK2-PD/iPD, but not NMC, tend to have lower activity levels, more arm swing asymmetry and less increase of arm swing with transition from slow to faster walking speed compared to healthy controls.

CONCLUSION

Higher intra-individual variability of gait-associated movements might be a useful biomarker of prodromal PD. These results encourage replication in a larger sample and longitudinal analysis is warranted.

Evaluating the effects of general anesthesia on sleep in children undergoing elective surgery: an observational case-control study

Study Objectives

Previous research has suggested that general anesthetics can disturb postoperative sleep patterns by affecting the sleep-wake cycle. The objective was to identify the effects of general anesthetics on sleep quality and related behavioral changes in children.

Methods

This was a prospective, observational case-control study with children, aged 18 months to 8 years, undergoing general anesthesia for elective surgery. Participants wore an actigraph for 7 days on three occasions: prior to surgery, the immediate postoperative period, and 3 months after surgery. Data regarding behavior patterns were collected using behavioral assessments at baseline, the first postoperative week, and 3 months following surgery.

Results

Thirty-one participants (mean age 4.8 ± 2.0 years, 81% male) underwent urologic or otolaryngologic surgery. The median (interquartile range) anesthetic duration was 132.0 (80.0-184.0) min. No significant differences were found in sleep efficiency, total sleep time, wake time after sleep onset, or sleep onset latency between baseline, 7 day postoperative period, and the 3 month follow-up. No significant differences were found in sleep-related behavioral metrics including internalizing and externalizing behaviors, and executive functioning. Data were compared with a control group of 18 participants (mean age 5.3 ± 1.8 years, 61% male). No significant differences were found in sleep patterns and related behavioral metrics between both groups.

Conclusions

In this study, general anesthesia did not result in disturbed sleep or associated negative behavioral changes in otherwise healthy children undergoing elective surgeries of low complexity. Physicians can advise parents that a child's surgery and associated general anesthetic exposure may not result in significant changes in postoperative sleep patterns.

Actigraphy-Derived Daily Rest-Activity Patterns and Body Mass Index in Community-Dwelling Adults

Study Objectives

To examine associations between 24-hour rest-activity patterns and body mass index (BMI) among community-dwelling US adults. Rest-activity patterns provide a field method to study exposures related to circadian rhythms.

Methods

Adults (N = 578) wore an actigraph on their nondominant wrist for 7 days. Intradaily variability and interdaily stability (IS), M10 (most active 10-hours), L5 (least active 5-hours), and relative amplitude (RA) were derived using nonparametric rhythm analysis. Mesor, acrophase, and amplitude were calculated from log-transformed count data using the parametric cosinor approach.

Results

Participants were 80% female and mean (standard deviation) age was 52 (15) years. Participants with higher BMI had lower values for magnitude, RA, IS, total sleep time (TST), and sleep efficiency. In multivariable analyses, less robust 24-hour rest-activity patterns as represented by lower RA were consistently associated with higher BMI: comparing the bottom quintile (least robust) to the top quintile (most robust 24-hour rest-activity pattern) of RA, BMI was 3-kg/m2 higher (p = .02). Associations were similar in magnitude to an hour less of TST (1-kg/m2 higher BMI) or a 10% decrease in sleep efficiency (2-kg/m2 higher BMI), and independent of age, sex, race, education, and the duration of rest and/or activity.

Conclusions

Lower RA, reflecting both higher night activity and lower daytime activity, was associated with higher BMI. Independent of the duration of rest or activity during the day or night, 24-hour rest, and activity patterns from actigraphy provide aggregated measures of activity that associate with BMI in community-dwelling adults.

Sleep devices: wearables and nearables, informational and interventional, consumer and clinical

The field of sleep is in many ways ideally positioned to take full advantage of advancements in technology and analytics that is fueling the mobile health movement. Combining hardware and software advances with increasingly available big datasets that contain scored data obtained under gold standard sleep laboratory conditions completes the trifecta of this perfect storm. This review highlights recent developments in consumer and clinical devices for sleep, emphasizing the need for validation at multiple levels, with the ultimate goal of using personalized data and advanced algorithms to provide actionable information that will improve sleep health.

Statistical learning of mobility patterns from long-term monitoring of locomotor behaviour with body-worn sensors

Long term monitoring of locomotor behaviour in humans using body-worn sensors can provide insight into the dynamical structure of locomotion, which can be used for quantitative, predictive and classification analyses in a biomedical context. A frequently used approach to study daily life locomotor behaviour in different population groups involves categorisation of locomotion into various states as a basis for subsequent analyses of differences in locomotor behaviour. In this work, we use such a categorisation to develop two feature sets, namely state probability and transition rates between states, and use supervised classification techniques to demonstrate differences in locomotor behaviour. We use this to study the influence of various states in differentiating between older adults with and without dementia. We further assess the contribution of each state and transition and identify the states most influential in maximising the classification accuracy between the two groups. The methods developed here are general and can be applied to areas dealing with categorical time series.

Fractal regulation and incident Alzheimer's disease in elderly individuals

Introduction:

Healthy physiological systems exhibit fractal regulation (FR), generating similar fluctuation patterns in physiological outputs across different time scales. FR in motor activity is degraded in dementia, and the degradation correlates to cognitive decline. We tested whether degraded FR predicts Alzheimer’s dementia.

Methods:

FR in motor activity was assessed in 1097 nondemented older adults at baseline. Cognition was assessed annually for up to 11 years.

Results:

Participants with an FR metric at the 10th percentile in this cohort had a 1.8-fold Alzheimer’s disease risk (equivalent to the effect of being ~5.2 years older) and 1.3-fold risk for mild cognitive impairment (equivalent to the effect of being ~3.0 years older) than those at the 90th percentile. Consistently, degraded FR predicted faster cognitive decline. These associations were independent of physical activity, sleep fragmentation, and stability of daily activity rhythms.

Discussion:

FR may be a useful tool for predicting Alzheimer’s dementia.

Sleep Stage Transition Dynamics Reveal Specific Stage 2 Vulnerability in Insomnia

Study Objectives

Objective sleep impairments in insomnia disorder (ID) are insufficiently understood. The present study evaluated whether whole-night sleep stage dynamics derived from polysomnography (PSG) differ between people with ID and matched controls and whether sleep stage dynamic features discriminate them better than conventional sleep parameters.

Methods

Eighty-eight participants aged 21-70 years, including 46 with ID and 42 age- and sex-matched controls without sleep complaints, were recruited through www.sleepregistry.nl and completed two nights of laboratory PSG. Data of 100 people with ID and 100 age- and sex-matched controls from a previously reported study were used to validate the generalizability of findings. The second night was used to obtain, in addition to conventional sleep parameters, probabilities of transitions between stages and bout duration distributions of each stage. Group differences were evaluated with nonparametric tests.

Results

People with ID showed higher empirical probabilities to transition from stage N2 to the lighter sleep stage N1 or wakefulness and a faster decaying stage N2 bout survival function. The increased transition probability from stage N2 to stage N1 discriminated people with ID better than any of their deviations in conventional sleep parameters, including less total sleep time, less sleep efficiency, more stage N1, and more wake after sleep onset. Moreover, adding this transition probability significantly improved the discriminating power of a multiple logistic regression model based on conventional sleep parameters.

Conclusions

Quantification of sleep stage dynamics revealed a particular vulnerability of stage N2 in insomnia. The feature characterizes insomnia better than-and independently of-any conventional sleep parameter.

Religious Orders Study and Rush Memory and Aging Project

BACKGROUND

The Religious Orders Study and Rush Memory and Aging Project are both ongoing longitudinal clinical-pathologic cohort studies of aging and Alzheimer's disease (AD).

OBJECTIVES

To summarize progress over the past five years and its implications for understanding neurodegenerative diseases.

METHODS

Participants in both studies are older adults who enroll without dementia and agree to detailed longitudinal clinical evaluations and organ donation. The last review summarized findings through the end of 2011. Here we summarize progress and study findings over the past five years and discuss new directions for how these studies can inform on aging and AD in the future.

RESULTS

We summarize 1) findings on the relation of neurobiology to clinical AD; 2) neurobiologic pathways linking risk factors to clinical AD; 3) non-cognitive AD phenotypes including motor function and decision making; 4) the development of a novel drug discovery platform.

CONCLUSION

Complexity at multiple levels needs to be understood and overcome to develop effective treatments and preventions for cognitive decline and AD dementia.

Performance of the biological rhythms interview for assessment in neuropsychiatry: An item response theory and actigraphy analysis

BACKGROUND

Biological rhythm disturbances are widely associated with the pathophysiology of mood disorders. The Biological Rhythms Interview for Assessment in Neuropsychiatry (BRIAN) is a self-report that indexes rhythm disturbance in sleep, activity, social and eating patterns. The aim of this study was to perform an Item Response Theory (IRT) analysis of the BRIAN and investigate its associations with objective sleep and rhythm disturbance measures.

METHODS

103 subjects (31 bipolar, 32 major depression and 40 healthy volunteers) wore an actiwatch for fifteen days, and completed a first morning urine sample and the BRIAN on day 15. IRT analysis assessed individual BRIAN items and their relationship to total score. Individual actiwatch records were processed to produce a sequence of transitions between rest/activity, and a likelihood of transitioning between states was calculated to investigate sleep-wake dynamics. Cosinor analysis produced daily activity rhythms (DARs). Spearman correlations were used to assess the association between sleep/DAR variables and the BRIAN.

RESULTS

IRT analyses showed that 11 of 18 BRIAN items displayed a high level of discrimination between item options across a range of BRIAN total scores. Total BRIAN score correlated with wake after sleep onset, total activity count during sleep, and urinary 6-sulphatoxymelatonin. BRIAN Activity domain correlated with the daytime transition probability from rest to activity.

LIMITATIONS

The sample size may have been underpowered for the graded-response model employed in IRT. The study lacked an objective comparison for BRIAN eating and social domain.

CONCLUSION

The present study reveals the BRIAN displays promising external validity compared to objective parameters of circadian rhythmicity.

Sleep fragmentation and Parkinson's disease pathology in older adults without Parkinson's disease

INTRODUCTION

Patients with Parkinson's disease (PD) frequently experience disrupted sleep, and several sleep abnormalities are associated with an increased risk of incident PD. However, there are few data concerning the relationship between objectively quantified sleep disruption and the cardinal histopathological features of PD, especially in individuals without clinical PD.

METHODS

We studied 269 older adults without PD who had participated in the Rush Memory and Aging Project and undergone uniform structured neuropathologic evaluations upon death. Sleep fragmentation was measured using actigraphy. Logistic regression models examined the associations of sleep fragmentation proximate to death with the burden of Lewy body pathology and substantia nigra neuron loss.

RESULTS

Greater sleep fragmentation was associated with the presence of Lewy body pathology (odds ratio 1.40; 95% confidence interval 1.05-1.86; P = .02) and substantia nigra neuron loss (odds ratio 1.43; 95% confidence interval 1.10-1.88; P = .008) and a higher odds of a pathological diagnosis of PD (odds ratio 2.04; 95% confidence interval 1.34-3.16; P = .0009). These associations were independent of motor features of parkinsonism, demographic characteristics, and a wide range of medical co-morbidities.

CONCLUSIONS

Sleep fragmentation is associated with PD pathology in older adults without PD. These results suggest that sleep fragmentation may be a marker of or risk factor for PD pathology in older adults without PD. © 2017 International Parkinson and Movement Disorder Society.

A study protocol for an observational cohort investigating COGnitive outcomes and WELLness in survivors of critical illness: the COGWELL study

INTRODUCTION

Up to 9 out of 10 intensive care unit (ICU) survivors will suffer some degree of cognitive impairment at hospital discharge and approximately half will have decrements that persist for years. The mechanisms for this newly acquired brain injury are poorly understood. The purpose of this study is to describe the prevalence of sleep abnormalities and their association with cognitive impairment, examine a well-known genetic risk factor for dementia (Apolipoprotein E ε4) that may allow for genetic risk stratification of ICU survivors at greatest risk of cognitive impairment and determine if electroencephalography (EEG) is an independent predictor of long-term cognitive impairment and possibly a candidate intermediate end point for future clinical trials.

METHODS AND ANALYSIS

This is a multisite, prospective, observational cohort study. The setting for this trial will be medical and surgical ICUs of five large tertiary care referral centres. The participants will be adult patients admitted to a study ICU and invasively ventilated for ≥3 days . Participants will undergo follow-up within 7 days of ICU discharge, 6 months and 1 year. At each time point, patients will have an EEG, blood work (biomarkers; gene studies), sleep study (actigraphy), complete a number of questionnaires as well as undergo neuropsychological testing. The primary outcome of this study will be long-term cognitive function at 12 months follow-up as measured by the Repeatable Battery for the Assessment of Neuropsychological Status and Trails Making Test B.

ETHICS AND DISSEMINATION

The study has received the following approvals: University Health Network Research Ethics Committee (13-6425-BE), Sunnybrook Health Centre Research Ethics Committee (365-2013), Mount Sinai Research Ethics Committee (14-0194-E) and St. Michael's Hospital Research Ethics Committee (14-295). Results will be made available to critical care survivors, their caregivers, the funders, the critical care societies and other researchers.

TRIAL REGISTRATION NUMBER

NCT02086877; Pre-results.

Exponential state transition dynamics in the rest-activity architecture of patients with bipolar disorder

OBJECTIVE

Our goal was to model the temporal dynamics of sleep-wake transitions, represented by transitions between rest and activity obtained from actigraphic data, in patients with bipolar disorder using a probabilistic state transition approach.

METHODS

We collected actigraphic data for 14 days from 20 euthymic patients with bipolar disorder, who had been characterized clinically, demographically, and with respect to their circadian preferences (chronotype). We processed each activity record to generate a series of transitions in both directions between the states of rest (R) and activity (A) and plotted the estimated transition probabilities (pRA and pAR). Each 24-hour period was also divided into a rest phase consisting of the eight consecutive least active hours in each day and an active phase consisting of the 16 consecutive most active hours in each day. We then calculated separate transition probabilities for each of these phases for each participant. We subsequently modeled the rest phase data to find the best fit for rest-activity transitions using maximum likelihood estimation. We also examined the association of transition probabilities with clinical and demographic variables.

RESULTS

The best-fit model for rest-activity transitions during the rest phase was a mixture (bimodal) of exponential functions. Of those patients with rapid cycling, 75% had an evening-type chronotype. Patients with bipolar II disorder taking antidepressants had a lower probability of transitioning back to rest than those not on antidepressants [mean ± SD = 0.050 ± 0.006 versus 0.141 ± 0.058, F(1,15) = 3.40, p < 0.05].

CONCLUSIONS

The dynamics of transitions between rest and activity in bipolar disorder can be accounted for by a mixture (bimodal) of exponential functions. Patients taking antidepressants had a reduced probability of sustaining and returning to sleep.

Sleep Fragmentation, Cerebral Arteriolosclerosis, and Brain Infarct Pathology in Community-Dwelling Older People

BACKGROUND AND PURPOSE

Although several forms of sleep disruption are associated with stroke, few studies have examined the relationship between sleep and histopathologic measures of cerebrovascular disease. We tested the hypothesis that greater sleep fragmentation is associated with a higher burden of cerebral vessel and infarct pathology at autopsy.

METHODS

We used ordinal logistic regression models to relate sleep fragmentation measured by actigraphy to the severity of arteriolosclerosis, atherosclerosis, and cerebral amyloid angiopathy, and the number of macroscopic and microscopic infarcts assessed by structured brain autopsy in 315 participants from the Rush Memory and Aging Project.

RESULTS

Greater sleep fragmentation was associated with more severe arteriolosclerosis (odds ratio, 1.27; 95% confidence interval, 1.02-1.59; P=0.03 per 1 SD greater sleep fragmentation) and more subcortical macroscopic infarcts (odds ratio, 1.31; 95% confidence interval, 1.01-1.68; P=0.04). These associations were independent of established cardiovascular risk factors and diseases, and several medical comorbidities.

CONCLUSIONS

Sleep fragmentation is associated with arteriolosclerosis and subcortical infarcts in older adults.

Regional Neocortical Gray Matter Structure and Sleep Fragmentation in Older Adults

STUDY OBJECTIVES

To test the hypothesis that greater sleep fragmentation is associated with regionally decreased cortical gray matter volume in older community-dwelling adults without cognitive impairment.

METHODS

We studied 141 community-dwelling older adults (median age 82.9; 73% female) without cognitive impairment or stroke, and not using sedative/ hypnotic medications, participating in the Rush Memory and Aging Project. We quantified sleep fragmentation from 7 d of actigraphy using the metric kRA and related this to total cortical gray matter volume, and regional gray matter volume in 34 cortical regions quantified by automated segmentation of magnetic resonance imaging data. We determined statistical significance and accounted for multiple comparisons by empirically estimating the false discovery rate by permutation.

RESULTS

Lower total cortical gray matter volume was associated with higher sleep fragmentation (coefficient +0.23, standard error [SE] 0.11, P = 0.037). Lower gray matter volumes in four cortical regions were accompanied by higher sleep fragmentation with a false discovery rate < 0.05: the left (coefficient +0.36, SE 0.10, P = 2.7 × 10(-4)) and right (coefficient +0.31, SE 0.10, P = 4.0 × 10(-3)) lateral orbitofrontal cortices, and the adjacent left (coefficient +0.31, SE 0.10, 5.4 × 10(-4)) and right (coefficient +0.39, SE 0.10, P = 1.2 × 10(-4)) inferior frontal gyri pars orbitalis. These associations were unchanged after accounting for age, sex, education, depression, cognitive function, and a number of medical comorbidities.

CONCLUSIONS

Lower cortical gray matter volume in the lateral orbitofrontal cortex and inferior frontal gyrus pars orbitalis is associated with greater sleep fragmentation in older community-dwelling adults. Further work is needed to clarify whether this is a consequence of or contributor to sleep fragmentation.

COMMENTARY

A commentary on this article appears in this issue on page 15.

The effect of melatonin on sleep and quality of life in patients with advanced breast cancer

BACKGROUND

Fatigue and sleep problems are prevalent in cancer patients and can be associated with disruption of circadian rhythmicity. In this prospective phase II trial, we sought to assess the effect of melatonin on circadian biomarkers, sleep, and quality of life in breast cancer patients.

METHODS

Thirty-two patients with metastatic breast cancer, receiving hormonal or trastuzumab therapy, took 5 mg of melatonin at bedtime for 2 months. Before starting and after 2 months on melatonin therapy, sleep and circadian rhythmicity were assessed by actigraphy, diurnal patterns of serum cortisol, and the expression of the core clock genes PER2 and BMAL1 in peripheral blood mononuclear cells. The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 questionnaire was completed for subjective parameters.

RESULTS

Bedtime melatonin was associated with a significant improvement in a marker of objective sleep quality, sleep fragmentation and quantity, subjective sleep, fatigue severity, global quality of life, and social and cognitive functioning scales. Morning clock gene expression was increased following bedtime melatonin intake. Melatonin did not affect actigraphy measure of circadian rhythmicity, or the diurnal cortisol pattern.

CONCLUSION

These results invite further investigation of melatonin as a potentially useful therapeutic agent for improving sleep and quality of life in cancer patients.

Irregular 24-hour activity rhythms and the metabolic syndrome in older adults

Circadian rhythms - near 24 h intrinsic biological rhythms - modulate many aspects of human physiology and hence disruption of circadian rhythms may have an important impact on human health. Experimental work supports a potential link between irregular circadian rhythms and several key risk factors for cardiovascular disease including hypertension, obesity, diabetes and dyslipidemia, collectively termed the metabolic syndrome. While several epidemiological studies have demonstrated an association between shift-work and the components of the metabolic syndrome in working-age adults, there is a relative paucity of data concerning the impact of non-occupational circadian irregularity in older women and men. To address this question, we studied 7 days of actigraphic data from 1137 older woman and men participating in the Rush Memory and Aging Project, a community-based cohort study of the chronic conditions of aging. The regularity of activity rhythms was quantified using the nonparametric interdaily stability metric, and was related to the metabolic syndrome and its components obesity, hypertension, diabetes and dyslipidemia. More regular activity rhythms were associated with a lower odds of having the metabolic syndrome (OR = 0.69, 95% CI = 0.60-0.80, p = 5.8 × 10(-7)), being obese (OR = 0.73, 95% CI = 0.63-0.85, p = 2.5 × 10(-5)), diabetic (OR = 0.76, 95% CI = 0.65-0.90, p = 9.3 × 10(-4)), hypertensive (OR = 0.78, 95% CI = 0.66-0.91, p = 2.0 × 10(-3)) or dyslipidemic (OR = 0.82, 95% CI = 0.72-0.92, p = 1.2 × 10(-3)). These associations were independent of differences in objectively measured total daily physical activity or rest, and were not accounted for by prevalent coronary artery disease, stroke or peripheral artery disease. Moreover, more regular activity rhythms were associated with lower odds of having cardiovascular disease (OR = 0.83; 95% CI = 0.73-0.95, p = 5.7 × 10(-3)), an effect that was statistically mediated by the metabolic syndrome. We conclude that irregular activity rhythms are associated with several key components of the metabolic syndrome in older community-dwelling adults, and that the metabolic syndrome statistically partially mediates the association between activity rhythms and prevalent cardiovascular disease. Although additional longitudinal and experimental studies are needed to conclusively delineate the causal relationships underlying these associations, these findings are consistent with preclinical data, and add further support for investigations of the irregularity of activity rhythms as a potential therapeutic target to decrease the burden of cardiovascular disease in older adults.