Circadian Rest-activity Rhythm Research Articles

Circadian rest-activity rhythm and longitudinal brain changes underlying late-life cognitive decline.

The neurobiological substrates underlying the relationship of circadian rest-activity rhythm (RAR) alteration with accelerated late-life cognitive decline are not clearly understood. In the present study, the longitudinal relationship of objectively measured circadian RAR with in vivo Alzheimer disease (AD) pathologies and cerebrovascular injury was investigated in older adults without dementia. The present study included 129 participants without dementia who participated in the KBASE (Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease) cohort. All participants underwent actigraphy at baseline and two consecutive [11 C] Pittsburgh compound-B positron emission tomography (PET), [18 F] fluorodeoxyglucose-PET, magnetic resonance imaging, and Mini-Mental State Examination (MMSE) at baseline and at a 2-year follow-up assessment. The associations of circadian RAR with annualized change in neuroimaging measures including global amyloid-beta retention, AD-signature region cerebral glucose metabolism (AD-CM), and white matter hyperintensity volume were examined. Delayed acrophase at baseline was significantly associated with greater annualized decline of AD-CM over a 2-year period, but not with that of other neuroimaging measures. In contrast, other circadian RAR parameters at baseline had no association with annualized change of any neuroimaging measures. Annualized decline of AD-CM was also significantly positively associated with the annual change in MMSE scores. Furthermore, a mediation analysis showed that greater reduction in AD-CM mediated the effect of delayed acrophase at baseline on faster decline of MMSE score. The findings indicate that delayed acrophase in late life may cause or predict hypometabolism at AD-signature brain regions, which underlies cognitive decline in the near future.

CovidRhythm: A Deep Learning Model for Passive Prediction of Covid-19 Using Biobehavioral Rhythms Derived From Wearable Physiological Data

Goal: To investigate whether a deep learning model can detect Covid-19 from disruptions in the human body's physiological (heart rate) and rest-activity rhythms (rhythmic dysregulation) caused by the SARS-CoV-2 virus. Methods: We propose CovidRhythm, a novel Gated Recurrent Unit (GRU) Network with Multi-Head Self-Attention (MHSA) that combines sensor and rhythmic features extracted from heart rate and activity (steps) data gathered passively using consumer-grade smart wearable to predict Covid-19. A total of 39 features were extracted (standard deviation, mean, min/max/avg length of sedentary and active bouts) from wearable sensor data. Biobehavioral rhythms were modeled using nine parameters (mesor, amplitude, acrophase, and intra-daily variability). These features were then input to CovidRhythm for predicting Covid-19 in the incubation phase (one day before biological symptoms manifest). Results: A combination of sensor and biobehavioral rhythm features achieved the highest AUC-ROC of 0.79 [Sensitivity = 0.69, Specificity = 0.89, F[Formula: see text] = 0.76], outperforming prior approaches in discriminating Covid-positive patients from healthy controls using 24 hours of historical wearable physiological. Rhythmic features were the most predictive of Covid-19 infection when utilized either alone or in conjunction with sensor features. Sensor features predicted healthy subjects best. Circadian rest-activity rhythms that combine 24 h activity and sleep information were the most disrupted. Conclusions: CovidRhythm demonstrates that biobehavioral rhythms derived from consumer-grade wearable data can facilitate timely Covid-19 detection. To the best of our knowledge, our work is the first to detect Covid-19 using deep learning and biobehavioral rhythms features derived from consumer-grade wearable data.

Sleep and Rest-Activity Rhythms in Recovering Patients with Severe Concurrent Mental and Substance Use Disorder: A Pilot Study

Objective: Mental health and substance use disorders are commonly associated with disrupted sleep and circadian rest-activity rhythms. How these disorders in combination relate to sleep and circadian organization is not well studied. We provide here the first quantitative assessment of sleep and rest-activity rhythms in inpatients with complex concurrent disorders, taking into account categories of substance use (stimulant vs. stimulant and opioid use) and psychiatric diagnosis (psychotic disorder and mood disorder). We also explore how sleep and rest-activity rhythms relate to psychiatric functioning. Methods: A total of 44 participants (10 female) between the age of 20–60 years (median = 29 years) wore wrist accelerometers over 5–70 days and completed standardized questionnaires assessing chronotype and psychiatric functioning (fatigue, psychiatric symptom severity, and impulsiveness). To examine potential influences from treatment, we computed (1) length of stay; (2) days of abstinence from stimulants and opioids as a measure of withdrawal; and (3) a sedative load based on prescribed medications. Results: Participants exhibited a sustained excessive sleep duration, frequent nighttime awakenings, and advanced rest-activity phase related to sedative load. Sleep disruptions were elevated in participants with a history of opioid use. Patients with a psychotic disorder showed the longest sleep and most fragmented and irregular rest-activity patterns. Non-parametric circadian rhythm analysis revealed a high rhythm amplitude by comparison with population norms, and this was associated with greater psychiatric symptom severity. Psychiatric symptom severity was also associated with greater fatigue and later MCTQ chronotype. Conclusions: This pilot study provides initial information on the prevalence and severity of sleep and circadian rhythm disturbances in individuals with severe concurrent disorders. The results underline the need for further studies to start to understand the role of sleep in the disease and recovery process in this understudied population.

PainRhythms: Machine learning prediction of chronic pain from circadian dysregulation using actigraph data — a preliminary study

Chronic pain is currently diagnosed using verbal self-reports, which present a challenge for patients with cognitive or physiological disorders. Prior work has explored machine learning prediction of pain from clinical data, which requires active user involvement and does not capture their behavior in natural settings. Passive objective assessment is desirable. Circadian Rhythms, including sleep-wake cycles, are biological processes that reoccur every 24 h and can be derived from physiological data such as heart rate, activity, and sleep, gathered using widely-owned smart wearables. This study investigated the feasibility of using machine learning and rest-activity circadian rhythm features to predict patients’ pain, including pain intensity, its interference with the patient’s life (dysregulation), and their difficulty in performing physical functions using passively gathered actigraphy data. To predict pain on day N , actigraphy data collected over that day were analyzed. Three sets of feature were extracted: (1) Activity (total sedentary bouts/time/breaks, % in sedentary/light/ moderate activity), (2) Sleep (sleep efficiency/latency, wake after sleep onset), and (3) Rest Activity Rhythm (mesor, acrophase, Intradaily Variability (IV)). These features were then classified using various machine learning algorithms. Our proposed PainRhythms approach achieved an average AUC-ROC of 0.97 with a stacking machine learning classifier for predicting pain, 0.67 and 0.62 with logistic regression for pain intensity and interference, and 0.56 with gradient boosting for physical function. We found that chronic pain predictions were more accurate using rest-activity rhythm features than sleep or activity features. Of all the rhythmic features, Intradaily Variability (IV) was the most predictive feature, with elevated values in pain associated with disturbed sleep. PainRhythms provides preliminary evidence that rest-activity rhythms can effectively detect subjects with chronic pain. In future work, we aim to gather more data and confirm our preliminary findings on a large, class-balanced and diverse dataset. • PainRhythms provides preliminary evidence that rest-activity rhythms can effectively detect subjects with chronic pain. • Chronic pain predictions were more accurate using rest-activity rhythms than sleep or activity. • Intradaily Variability (IV) was the most predictive feature, with elevated values in pain associated with disturbed sleep. • Sleep disturbance was more associated with pain and pain intensity. • Besides sleep disturbance, features encompassing the subject’s physical activity and sleep quality also influenced pain interference and physical function.

Blunted rest-activity circadian rhythm increases the risk of all-cause, cardiovascular disease and cancer mortality in US adults

To examine whether rest-activity circadian rhythm parameters can predict all-cause, cardiovascular disease and cancer mortality in a general adult population of the US. We further compared the mortality predictive performance of these parameters with that of traditional risk factors. This study included 7,252 adults from US National Health and Nutrition Examination Surveys (NHANES) 2011–2014, who had wrist accelerometer data obtained at baseline and follow-up status linked to the National Death Index records (2011–2019). During a median of 81 months (interquartile range, 69–94 months) of follow-up, 674 (9.3%) deaths occurred. There were inverse associations between relative amplitude (RA) and all-cause mortality, cardiovascular disease and cancer mortality with increased quartiles RA associated with lower mortality risk (all P < 0.05). The Hazard Ratios ranged from 0.61 to 0.79. Furthermore, RA outperformed all the tested traditional predictors of all-cause mortality with the exception of age. This study suggests that participants with blunted rest-activity circadian rhythms had a higher risk of all-cause, cardiovascular disease and cancer mortality. Future studies will be needed to test whether interventions that regulate rest-activity circadian activity rhythms will improve health outcomes.

Associations of circadian rest/activity rhythms with cognition in middle-aged and older adults: Demographic and genetic interactions.

ObjectivesWrist actigraphs (accelerometers) can record motor activity over multiple days and nights. The resulting data can be used to quantify 24-h activity profiles, known as circadian rest-activity rhythms (CRARs). Actigraphic CRARs have been tied to cognitive performance and decline in older adults; however, little is known about links between CRARs and performance or change in specific cognitive domains, or how individual differences may influence these associations. We investigated associations of actigraphic CRARs with cognitive performance and change in middle-aged and older adults, and explored whether age, sex/gender, race, and apolipoprotein E (APOE) e4 carrier status moderated these associations.Materials and methodsParticipants (N = 422; 47% male) were cognitively healthy adults (i.e., without mild cognitive impairment or dementia) at baseline aged ≥ 50 years from the Baltimore Longitudinal Study of Aging who completed 5.6 ± 0.89 nights of wrist actigraphy and tests of memory, executive function, attention, language, and visuospatial ability at the same visit the actigraph was issued; 292 participants had repeat cognitive testing 3.12 (1.58) years later. Predictors included indices of rhythm strength [i.e., amplitude; relative amplitude (RA); interdaily stability (IS); mesor], delayed timing of the rhythm peak [i.e., later acrophase; midpoint of an individual’s least active 5 h (L5 time); midpoint of an individual’s most active 10 h (M10 time)], and fragmentation [i.e., intradaily variability (IV)].ResultsIn main effects, later L5 time was cross sectionally associated with poorer memory, and greater IS predicted slower longitudinal memory decline. Associations of CRARs with cognition differed as a function of age, sex/gender, race, and APOE e4 carrier status.ConclusionAmong middle-aged and older adults, delayed circadian phase is associated with poorer memory performance, and greater day-to-day rhythm stability is associated with slower declines in memory. Significant interactions suggest that CRARs are generally more strongly associated with cognitive performance and rate of cognitive decline among women, Black adults, older individuals, and APOE e4 carriers. Replication in independent samples is needed.

Rest-Activity Rhythm Fragmentation and Weaker Circadian Strength Are Associated With Cognitive Impairment in Survivors of Acute Respiratory Failure.

Background: Survivors of acute respiratory failure (ARF) experience long-term cognitive impairment and circadian rhythm disturbance after hospital discharge. Although prior studies in aging and neurodegenerative diseases indicate actigraphy-estimated rest-activity circadian rhythm disturbances are risk factors for cognitive impairment, it is unclear if this applies to ARF survivors. This study explored the relationships of actigraphy-estimated rest-activity circadian rhythms with cognitive functioning in ARF survivors at 3months after discharge. Methods: 13 ARF survivors (mean age 51years and 69% males) completed actigraphy and sleep diaries for 9days, followed by at-home neuropsychological assessment. Principal component factor analysis created global cognition and circadian rhythm variables, and these first components were used to examine the global relationships between circadian rhythm and cognitive measure scores. Results: Global circadian function was associated with global cognition function in ARF survivors (r = .70, p = .024) after adjusting for age, education, and premorbid cognition. Also, greater fragmented rest-activity circadian rhythm (estimated by intradaily variability, r = .85, p = .002), and weaker circadian strength (estimated by amplitude, r = .66, p = .039; relative strength, r = .70, p = .024; 24-h lag serial autocorrelation, r = .67, p = .035), were associated with global cognition and individual cognitive tests. Conclusions: These results suggest circadian rhythm disturbance is associated with poorer global cognition in ARF survivors. Future prospective research with larger samples is needed to confirm these results and increase understanding of the relationship between disrupted circadian rhythms and cognitive impairment among ARF survivors.

Individual-specific changes in circadian rest-activity rhythm and sleep in symptom-free patients tapering their antidepressant medication

IntroductionGroup-level studies showed cross-sectional and prospective between-person associations between circadian rest-activity rhythms (RAR), physical activity (PA), sleep, and depressive symptoms. However, whether these associations replicate at the within-person level remains unclear. Therefore, it is clinically relevant to investigate these associations within persons and study whether changes in depressive symptoms are related to changes in circadian rhythm and sleep variables.ObjectivesTo identify changes in circadian rhythm elements in proximity to a transition in depressive symptoms, whether changes are less frequent in individuals without compared to those with transitions, and whether there are individual differences in the direction of change of circadian rhythm variables.MethodsData of remitted individuals tapering antidepressants were used: 12 with and 14 without a transition in depressive symptoms. RAR, PA, and sleep variables were calculated as predictors from four months of actigraphy data. Transitions in depressive symptoms were based on weekly SCL-90 scores and evaluation interviews. Kernel Change Point analyses were used to detect change points (CPs) and CP timing in circadian rhythm variables for each individual separately.ResultsIn 67% of individuals with depressive symptoms transitions, CPs were identified in proximity to symptom transitions. CPs were detected less frequently in the no-transition group with 7 CPs in 14 individuals, compared to transition groups with 10 CPs in 12 individuals. For several RAR and sleep variables, consistent changes were detected in expected directions.ConclusionsCircadian rhythm variables provide potentially clinically relevant information although their patterns around transitions are highly person-specific. Future research is needed to disentangle which variables are predictive for which patients.DisclosureNo significant relationships.

A multicenter telemonitoring-telecare study with automatic assessment of physiological parameters and patient-reported outcomes in remote pancreatic cancer patients on mFOLFIRINOX: Interim technology report.

e13617 Background: There is an unmet need for improved treatment outcomes along with safer care of patients (pts) at home, at risk of severe adverse events from chemotherapy. Methods: MultiDom (NCT04263948; Ramsay Santé Research GCS) aims to reduce emergency hospitalisations of pancreatic adenocarcinoma pts on mFOLFIRINOX with a novel telemonitoring-telecare platform (Clinikali). Accelerometry and body temperature are measured q1-min using a continuously-worn telecommunicating chest surface sensor, daily body weight is self-measured with a telecommunicating balance, and 23 electronic pt-reported outcomes (ePROs) are self-rated using a tablet for 1 week before (baseline) and 6 weeks after the first course. Hidden Markov, spectrum and other algorithms automatically compute physical activity, sleep, temperature, body weight change, ePROs severity, and dichotomy index I&lt;O of the circadian rest-activity rhythm (% activity In-bed below median activity Out-of-bed), one to four times daily. Alerts are automatically generated and sent to a coordination platform of health professionals, with trackable follow-up. Results: From 6/2021 to 2/2022, 16 of 42 planned pts (38%) from 4 centers have been included (females/males, 10/6 pts; aged 64-79 years; PS 0/1, 8/8 pts; 2 borderline/locally-advanced, and 14 metastatic (liver, 9; lymph nodes, 8; lung, 4). This technology report involves 9 pts on study for a median duration of 57 days (d) (range, 49-70d), whilst receiving 3 mFOLFIRINOX courses, with tumor control in 8 pts. Nearly 1.2x107 data were teletransmitted. At baseline, rest-activity rhythm was robust for 7 pts (I&lt;O &gt;97.5%) and disrupted for 2 pts (I&lt;O &lt;96%). Median compliance rates per pt (range) were 81% (67-92%) for rest-activity and body temperature, 96% (53-100%) for body weight, and 89% (78-100%) for self-rated e-PROMs. The median number of alerts generated for each pt (range) was 3 (0-10) for disrupted rest-activity rhythm (I&lt;O &lt;96%) or high temperature (2.5oC above median), and 2 (0-9) for body weight loss &gt;5%, A median of 6 alerts per pt was generated for one or more severe ePROs (pain, 7 pts; fatigue, 6 pts; impact on activity, 5 pts; anorexia, 4 pts). Supportive treatment was mostly initiated at home, avoiding undue hospitalization. Pts rated the median global evaluation factor as 5 (4-5), i.e. the highest score, in the 23-items research participation questionnaire. Conclusions: Continuous multidimensional telemonitoring of physiology and e-PROs met excellent patient compliance, thus supporting exploration of biological mechanisms linking e-PROs to circadian rhythms and treatment activity. Study is ongoing to assess whether such telemonitoring-telecare platform may drive practice-changes in patient pathways and digitized clinical trials in the current era of precision medicine. Clinical trial information: NCT04263948.

Optimization of Analysis of Circadian Rest-Activity Rhythm Using Cosinor Analysis in Mice.

Objective Data processing in analysis of circadian rhythm was performed in various ways. However, there was a lack of evidence for the optimal analysis of circadian rest-activity rhythm. Therefore, we aimed to perform mathematical simulations of data processing to investigate proper evidence for the optimal analysis of circadian rest-activity rhythm. Methods Locomotor activities of 20 ICR male mice were measured by infrared motion detectors. The data of locomotor activities was processed using data summation, data average, and data moving average methods for cosinor analysis. Circadian indices were estimated according to time block, respectively. Also, statistical F and p-values were calculated by zero-amplitude test. Results The data moving average result showed well-fitted cosine curves independent of data processing time. Meanwhile, the amplitude, MESOR, and acrophase were properly estimated within 800 seconds in data summation and data average methods. Conclusion These findings suggest that data moving average would be an optimal method for data processing in a cosinor analysis and data average within 800-second data processing time might be adaptable. The results of this study can be helpful to analyze circadian restactivity rhythms and integrate the results of the studies using different data processing methods.

Effects of dynamic bedroom lighting on measures of sleep and circadian rest-activity rhythm in inpatients with major depressive disorder

Bright light therapy is an effective treatment option for seasonal and non-seasonal affective disorders. However up to now, no study has investigated effects of dynamic bedroom lighting in hospitalized patients with major depression. A bedroom lighting system, which automatically delivered artificial dawn and dusk and blue-depleted nighttime lighting (DD-N lighting) was installed in a psychiatric ward. Patients with moderate to severe depression were randomly assigned to stay in bedrooms with the new lighting or standard lighting system. Patients wore wrist actimeters during the first two treatment weeks. Additionally, hospitalization duration and daily psychotropic medication were retrieved from patients’ medical charts. Data from thirty patients, recorded over a period of two weeks, were analyzed. Patients under DD-N lighting generally woke up earlier (+ 20 min), slept longer (week 1: + 11 min; week 2: + 27 min) and showed higher sleep efficiency (+ 2.4%) and shorter periods of nighttime awakenings (− 15 min). In the second treatment week, patients started sleep and the most active 10-h period earlier (− 33 min and − 64 min, respectively). This pilot study gives first evidence that depressed patients’ sleep and circadian rest/activity system may benefit from bedroom lighting when starting inpatient treatment.

Rest-Activity Circadian Rhythm and Light Exposure Using Wrist Actigraphy in ICU Patients

Actigraphy (ACTG) is easy to use and has proved reliable in non-critical populations of patients. It has been used to track circadian rest-activity cycles and to identify states of wakefulness and sleep [1]. A more recent study has found that ACTG have a moderate level of agreement with PSG in distinguishing between sleep and wakeful states which is more profound in non-ventilated patients [2].

Circadian rest-activity misalignment in critically ill medical intensive care unit patients.

Circadian alignment of rest-activity rhythms is an essential biological process that may be vulnerable to misalignment in critically ill patients. We evaluated circadian rest-activity rhythms in critically ill patients and their association with baseline (e.g. age) and clinical (e.g. mechanical ventilation status) variables, along with intensive care unit light-dark cycles. Using wrist actigraphy, we collected 48-hr activity and light exposure data from critically ill patients in a tertiary care medical intensive care unit. We evaluated circadian rest-activity rhythms using COSINOR and non-parametric circadian rhythm analysis models, and stratified these data across baseline and clinical variables. We used linear regression to evaluate the association of circadian rest-activity and light-dark exposure rhythms. In COSINOR and non-parametric circadian rhythm analysis analyses, the 34 medical intensive care unit patients completing 48-hr actigraphy recordings exhibited mean MESOR (mean activity levels of a fitted curve) and amplitudes of 0.50 ± 0.32 and 0.20 ± 0.19 movements per 30-s epoch, with high interdaily variability. Patients who were older, mechanically ventilated, sedated, restrained and with higher organ failure scores tended to exhibit greater circadian rest-activity misalignment, with three of 34 (9%) patients exhibiting no circadian rhythmicity. Circadian light-dark exposure misalignment was observed as well and was associated with rest-activity misalignment (p=0.03). Critically ill patients in our MICU experienced profound circadian rest-activity misalignment, with mostly weak or absent rhythms, along with circadian light-dark exposure misalignment. Potentially modifiable factors contributing to rest-activity misalignment (i.e. mechanical ventilation, restraints, low daytime light levels) highlight possible targets for future improvement efforts.

Development of circadian rest-activity rhythms during the first year of life in a racially diverse cohort.

To describe the development of circadian rest-activity rhythms (CRARs) during infancy in a racially diverse cohort. We studied 414 infants from the Nurture birth cohort (51.2% female, 65.2% Black) who wore actigraphs on their left ankles for 4 days and nights at 3, 6, 9, and 12 months. We quantified CRARs using cosinor and non-parametric circadian rhythm analysis, and investigated change in CRARs over time, comparing 6, 9, and 12 months to CRARs at 3 months. We adjusted for baseline and time-varying covariates and used function-on-scalar regression (FOSR) to identify the specific times of day at which activity changes occurred. Across the first year, daily mean and peak activity levels and day-to-day activity level regularity increased, and activity level fragmentation and nighttime activity decreased. Only at 9 months, compared to at 3 months, did timing of peak activity levels and the most active periods shift later, while timing of least active periods shifted earlier. FOSR analyses showed that mean activity levels decreased during nighttime hours and increased during daytime hours, with the most pronounced changes at 9 months. Among racially diverse infants, CRARs became more robust, stable, and less fragmented over time. Findings suggest the greatest change from 3-month CRARs occurs at 9 months, which may be a key period of CRAR development. This and future research will contribute to our understanding of normative infant CRAR development in diverse populations and enable us to identify infants who may benefit from intervention.

Blunted rest-activity rhythm is associated with increased white blood-cell-based inflammatory markers in adults: an analysis from NHANES 2011-2014

ABSTRACT Circadian rhythm disruption is associated with immune system disturbance and has been observed in many health problems where chronic-inflammation acts as a major contributor. We aim to examine whether rest-activity circadian rhythm is associated with chronic inflammation using white blood-cell-based inflammatory indices including white blood cell (WBC) count, neutrophil count, neutrophil-to-lymphocyte ratio (NLR) and systemic immune-inflammation index (SII). We analyzed the data from 8089 adults (age≥20) with at least 4 days of validated accelerometer recordings and a valid WBC count from the National Health and Nutrition Examination Survey (NHANES) 2011–2014. Non-parametric rest-activity circadian rhythm parameters were derived from the accelerometer recordings. In the models adjusting multiple covariates, a one-quantile increase in relative amplitude (i.e. more robust circadian rhythm) was associated with 1 × 108 cells/L decrease in WBC number (95% CI: 5 × 107 to 1.5 × 108, P < .001), 7 × 107 cells/L decrease in neutrophils (95% CI: 3 × 107 to 1.1 × 108, P = .003) and 15.2 × 109 /L decrease in SII (95% CI: 6 × 109 /L to 20 × 109/L, P = .019). Consistent results were also observed for the association of M10 value and L5 value with these inflammatory indices. Our results indicated that blunted rest-activity circadian rhythm is associated with increased white blood-cell-based inflammatory indices in adults, suggesting interventions aiming at enhancing circadian rhythm by lifestyle programs may be a novel approach to improve the general health.

Rest-activity circadian rhythm and impaired glucose tolerance in adults: an analysis of NHANES 2011-2014.

IntroductionCircadian rhythm disturbance occurs in type 2 diabetes, yet it is unknown whether it also exists in the prediagnostic phase of the disease. Thus, we examined the association of rest-activity circadian rhythm with 2-hour glucose levels and the risk of impaired glucose tolerance (IGT) in a nationally representative sample of adults without diabetes using a cross-sectional design.Research design and methodsWe analyzed data from 2760 adults without diabetes (age ≥20) with at least 4 days of validated accelerometer recordings and a valid oral glucose tolerance test from the National Health and Nutrition Examination Survey 2011–2014. Non-parametric rest-activity circadian rhythm parameters were derived from the accelerometer recordings.ResultsIn the models adjusting for multiple covariates, a one-quantile increase in relative amplitude (ie, increased circadian rhythmicity) was associated with 2.66 mg/dL decrease in 2-hour glucose level (95% CI −3.94 to −1.38, p<0.001) and a decreased odds of IGT (OR 0.75, 95% CI 0.63 to 0.89, p=0.002). A one-quantile increase in intradaily variability (ie, increased rhythm fragmentation) was associated with 3.01 mg/dL increase in 2-hour glucose level (95% CI 1.52 to 4.49, p=0.001) and an increased odds of IGT (OR 1.37, 95% CI 1.19 to 1.58, p<0.001).ConclusionsCircadian disruption is significantly associated with impaired glucose homeostasis in a general population of adults without diabetes. The association of circadian rhythm abnormalities with indicators of the pre-diabetic state suggests that circadian dysfunction may contribute to early disease pathogenesis.

Cross-sectional study of intraocular cataract lens replacement, circadian rest-activity rhythms, and sleep quality in older adults.

Age-related cataract decreases light transmission at the most sensitive spectrum for circadian photoentrainment, with negative ramifications for human health. Here, we assessed whether intraocular lens replacement (IOL) in older patients with previous cataract was associated with increased stability and amplitude of circadian rest-activity rhythms, and improved sleep quality. Our cross-sectional study included sixteen healthy older individuals without ocular diseases (controls; 55-80 years; 63.6 ± 5.6y; 8 women) and 13 patients with previous cataract and bilateral IOL (eight with blue-blocking [BB] lens and five with ultraviolet-only [UV] blocking lens; 55-80 years; 69.9 ± 5.2y; 9 women). The study comprised three weeks of at home rest-activity assessments using wrist-worn actigraphs, and each week preceded a laboratory protocol. Primary outcomes were actigraphy-derived interdaily stability, intradaily variability, and relative amplitude of circadian rest-activity rhythms. Secondary outcomes were actigraphy-assessed sleep quality (i.e. time in bed, sleep duration, sleep efficiency, mean wake bout time and fragmentation index). Patients with IOL had significantly higher interdaily stability ("Group" effect: pFDR =.001), but not intradaily variability ("Group" effect: pFDR = n.s.), and significantly higher relative amplitude of rest-activity rhythms ("Group" effect: pFDR < .001). Moreover, patients with IOL had significantly higher activity levels during the day and lower levels during the evening, as compared to healthy older controls ("Group" effect: pFDR = .03). Analyses of actigraphy-derived sleep parameters yielded no significant differences across groups ("Group" effect: all pFDR > .1). Our cross-sectional study suggests that enhancing spectral lens transmission in patients with cataract may benefit their circadian health.

The differential effects of dopamine d2, d3 agonist, quinpirole on circadian rest-activity rhythm according to dosing time

The differential effects of dopamine d2, d3 agonist, quinpirole on circadian rest-activity rhythm according to dosing time

Chronotypes and circadian rest-activity rhythms in bipolar disorders: a meta-analysis of self- and observer rating scales.

Chronobiological models postulate that abnormalities in circadian rest/activity rhythms (CRAR) are core phenomena of bipolar disorders (BDs). We undertook a meta-analysis of published studies to determine whether self- or observer ratings of CRAR differentiate BD cases from comparators (typically healthy controls [HCs]). We undertook systematic searches of four databases to identify studies for inclusion in random effects meta-analyses and meta-regression analyses. Effect sizes (ES) for pooled analyses of self- and observer ratings were expressed as standardized mean differences with 95% confidence intervals (CIs). The 30studies meeting eligibility criteria included 2840 cases and 3573 controls. Compared with HC, BD cases showed greater eveningness (ES: 0.33; 95% CI: 0.12-0.54), lower flexibility of rhythms (ES: 0.36; 95% CI: 0.06-0.67), lower amplitude of rhythms (ES: 0.55; 95% CI: 0.39-0.70) and more disturbances across a range of CRAR (ES of 0.78-1.12 for general and social activities, sleep and eating patterns). Between study heterogeneity was high (I2 >70%) and evidence indicated a potential publication bias for studies using the Biological Rhythms Interview of Assessment in Neuropsychiatry. Meta-regression analyses suggested significantly larger ES were observed in studies using observer ratings or including BD cases with higher levels of depressive symptoms. This meta-analysis demonstrates that BD is associated with higher levels of self- or observer-rated CRAR disturbances compared with controls. However, further studies should examine the respective performance of individual instruments when used alone or in combination, to clarify their applicability and utility in clinical practice.

Demographic characteristics associated with circadian rest-activity rhythm patterns: a cross-sectional study

BackgroundRest-activity rhythm (RAR), a manifestation of circadian rhythms, has been associated with morbidity and mortality risk. However, RAR patterns in the general population and specifically the role of demographic characteristics in RAR pattern have not been comprehensively assessed. Therefore, we aimed to describe RAR patterns among non-institutionalized US adults and age, sex, and race/ethnicity variation using accelerometry data from a nationally representative population.MethodsThis cross-sectional study was conducted using the US National Health and Nutrition Examination Survey (NHANES) 2011–2014. Participants aged ≥20 years who were enrolled in the physical activity monitoring examination and had at least four 24-h periods of valid wrist accelerometer data were included in the present analysis. 24-h RAR metrics were generated using both extended cosinor model (amplitude, mesor, acrophase and pseudo-F statistic) and nonparametric methods (interdaily stability [IS] and intradaily variability [IV]). Multivariable linear regression was used to assess the association between RAR and age, sex, and race/ethnicity.ResultsEight thousand two hundred participants (mean [SE] age, 49.1 [0.5] years) were included, of whom 52.2% were women and 67.3% Whites. Women had higher RAR amplitude and mesor, and also more robust (pseudo-F statistic), more stable (higher IS) and less fragmented (lower IV) RAR (all Ptrend < 0.001) than men. Compared with younger adults (20–39 years), older adults (≥ 60 years) exhibited reduced RAR amplitude and mesor, but more stable and less fragmented RAR, and also reached their peak activity earlier (advanced acrophase) (all Ptrend < 0.001). Relative to other racial/ethnic groups, Hispanics had the highest amplitude and mesor level, and most stable (highest IS) and least fragmented (lowest IV) RAR pattern (Ptrend < 0.001). Conversely, non-Hispanic blacks had the lowest peak activity level (lowest amplitude) and least stable (lowest IS) RAR pattern (all Ptrend < 0.001).ConclusionsIn the general adult population, RAR patterns vary significantly according to sex, age and race/ethnicity. These results may reflect demographic-dependent differences in intrinsic circadian rhythms and may have important implications for understanding racial, ethnic, sex and other disparities in morbidity and mortality risk.