The role of depressive symptoms and symptom dimensions in actigraphy-assessed sleep, circadian rhythm, and physical activity

Actigraphic monitoring of sleep and circadian rest-activity rhythm in individuals with major depressive disorder or depressive symptoms: A meta-analysis

BACKGROUND

Disrupted sleep and rest-activity pattern are common clinical features in depressed individuals. This meta-analysis compared sleep and circadian rest-activity rhythms in people with major depressive disorder (MDD) or depressive symptoms and healthy controls.

METHODS

Eligible studies were identified in five databases up to December 2023. The search yielded 53 studies with a total of 11,115 participants, including 4000 depressed participants and 7115 healthy controls.

RESULTS

Pooled meta-analyses demonstrated that depressed individuals have significantly longer sleep latency (SMD = 0.23, 95 % CI: 0.12 to 0.33) and wake time after sleep onset (SMD = 0.37, 95 % CI: 0.22 to 0.52), lower sleep efficiency (SMD = -0.41, 95 % CI: -0.56 to -0.25), more nocturnal awakenings (SMD = 0.58, 95 % CI: 0.29 to 0.88), lower MESOR (SMD = -0.54, 95 % CI: -0.81 to -0.28), amplitude (SMD = -0.33, 95 % CI: -0.57 to -0.09), and interdaily stability (SMD = -0.17, 95 % CI: -0.28 to -0.05), less daytime (SMD = -0.79, 95 % CI: -1.08 to -0.49) and total activities (SMD = -0.89, 95 % CI: -1.28 to -0.50) when compared with healthy controls.

LIMITATIONS

Most of the included studies reported separate sleep and activity parameters instead of 24-hour rest-activity rhythms. The variabilities among actigraphy devices and the types of participants recruited also impede precise comparisons.

CONCLUSIONS

The findings emerging from this study offered a better understanding of sleep and rest-activity rhythm in individuals with MDD or depressive symptoms. Future studies could advocate for deriving objective, distinctive 24-hour rest-activity profiles contributing to the risk of depression.

PROSPERO REGISTRATION NUMBER

CRD42021259780.

Familial risk for depression is associated with reduced physical activity in young adults: evidence from a wrist-worn actigraphy study

Depression is characterized by reduced physical activity and sleep-wake cycle disturbances, often considered important features of the disease. While a few studies have suggested that self-reported reduced physical activity and sleep-wake cycle disturbances might both be linked to depression vulnerability, actigraphy-based measures in vulnerable samples remain largely unexplored. This study relied on actigraphy-based parameters to test whether these disturbances characterize depression vulnerability. Seven-day actigraphy data were collected from 20 (13 female) university students with a high vulnerability to depression, which was determined by the presence of a family history of the condition but no current symptoms, and 32 (21 female) controls with neither a family history of depression nor current depressive symptoms. Daily physical activity, namely gross motor activity, was quantified as average daily acceleration and time spent engaging in moderate-vigorous physical activity (MVPA). The sleep-wake cycle and circadian rhythms were assessed as total sleep duration per night (in hours), sleep within sleep period time (in hours), sleep efficiency (%), and relative amplitude (i.e., the difference between the activity during the day and the night, which reflects circadian rhythms amplitude). Results showed that individuals with a familial risk for depression exhibited reduced daily acceleration and time spent in MVPA relative to the control group, particularly on the weekend during their free time away from scheduled activities. On the other hand, the two groups were comparable in terms of sleep estimates. Taken together, reduced physical activity, but not sleep-wake disturbances, seem to be associated with vulnerability to depression and might be a viable target for identification and prevention efforts.

Subtypes of major depressive disorders and objectively measured physical activity and sedentary behaviors in the community

BACKGROUND

Lack of physical activity (PA) and high sedentary behavior (SB) may enhance mental health problems, including depression, and are associated with increased mortality. Aside from a large body of research on major depressive disorder (MDD) assessed as an entity and either PA or SB, few studies have examined associations among subtypes of MDD and both PA and SB simultaneously derived from wrist-worn accelerometers. Accordingly, our aim was to explore the associations among MDD subtypes (atypical, melancholic, combined atypical-melancholic and unspecified) and four actigraphy-derived behaviors combining the levels of PA and SB.

METHODS

The sample stemmed from CoLaus|PsyCoLaus, a population-based cohort study, consisting of 2375 participants (55.1% women; mean age: 62.4 years) who wore an accelorometer for 14 days after a physical exam and subsequently completed a semi-structured psychiatric interview. Activity behaviors were defined according to the combination of the levels of moderate-to-vigorous intensity PA and SB. Associations of remitted MDD subtypes, current MDD and physical inactivity behaviors were assessed using multinomial logistic regression, adjusted for socio-demographic characteristics, a history of anxiety, alcohol and drug use disorders and cardiovascular risk factors.

RESULTS

In the fully adjusted model, participants with the remitted combined atypical-melancholic subtype had a higher risk of being more physically inactive.

CONCLUSIONS

Our findings suggest that low PA and high SB are not restricted to the duration of depressive episodes in people with atypical and melancholic episodes. The lack of PA and high SB in this group of depressive patients exposes them to an additional long-term cardiovascular risk and measures to increase PA may be particularly fruitful in this MDD subgroup.

Association of circadian rhythms with brain disorder incidents: a prospective cohort study of 72242 participants

Circadian rhythm disruption (CRD) is a shared characteristic of various brain disorders, such as Alzheimer's disease (AD), Parkinson's disease (PD), and major depression disorder (MDD). Disruption of circadian rhythm might be a risk factor for brain disorder incidents. From 7-day accelerometry data of 72,242 participants in UK Biobank, we derived a circadian relative amplitude variable, which to some extent reflected the degree of circadian rhythm disruption. Records of brain disorder incidents were obtained from a wide range of health outcomes across self-report, primary care, hospital inpatient data, and death data. Using multivariate Cox proportional hazard ratio regression, we created two models adjusting for different covariates. Then, linear correlations between relative amplitude and several brain morphometric measures were examined in participants with brain MRI data. After a median follow-up of around 6.1 years, 72,242 participants were included in the current study (female 54.9%; mean age 62.1 years). Individuals with reduced relative amplitude had increasing risk of all-cause dementia (Hazard ratio 1.23 [95% CI 1.15 to 1.31]), PD (1.33 [1.25 to 1.41]), stroke (1.13 [1.06 to 1.22]), MDD (1.18 [1.13 to 1.23]), and anxiety disorder (1.14 [1.09 to 1.20]) in fully adjusted models. Additionally, significant correlations were found between several cortical regions and white matter tracts and relative amplitude that have been linked to dementia and psychiatric disorders. We confirm CRD to be a risk factor for various brain disorders. Interventions for regulating circadian rhythm may have clinical relevance to reducing the risk of various brain disorders.

Patterns of activity correlate with symptom severity in major depressive disorder patients

Objective measures, such as activity monitoring, can potentially complement clinical assessment for psychiatric patients. Alterations in rest-activity patterns are commonly encountered in patients with major depressive disorder. The aim of this study was to investigate whether features of activity patterns correlate with severity of depression symptoms (evaluated by Montgomery-Åsberg Rating Scale (MADRS) for depression). We used actigraphy recordings collected during ongoing major depressive episodes from patients not undergoing any antidepressant treatment. The recordings were acquired from two independent studies using different actigraphy systems. Data was quality-controlled and pre-processed for feature extraction following uniform procedures. We trained multiple regression models to predict MADRS score from features of activity patterns using brute-force and semi-supervised machine learning algorithms. The models were filtered based on the precision and the accuracy of fitting on training dataset before undergoing external validation on an independent dataset. The features enriched in the models surviving external validation point to high depressive symptom severity being associated with less complex activity patterns and stronger coupling to external circadian entrainers. Our results bring proof-of-concept evidence that activity patterns correlate with severity of depressive symptoms and suggest that actigraphy recordings may be a useful tool for individual evaluation of patients with major depressive disorder.

It's About Time: The Circadian Network as Time-Keeper for Cognitive Functioning, Locomotor Activity and Mental Health

A variety of organisms including mammals have evolved a 24h, self-sustained timekeeping machinery known as the circadian clock (biological clock), which enables to anticipate, respond, and adapt to environmental influences such as the daily light and dark cycles. Proper functioning of the clock plays a pivotal role in the temporal regulation of a wide range of cellular, physiological, and behavioural processes. The disruption of circadian rhythms was found to be associated with the onset and progression of several pathologies including sleep and mental disorders, cancer, and neurodegeneration. Thus, the role of the circadian clock in health and disease, and its clinical applications, have gained increasing attention, but the exact mechanisms underlying temporal regulation require further work and the integration of evidence from different research fields. In this review, we address the current knowledge regarding the functioning of molecular circuits as generators of circadian rhythms and the essential role of circadian synchrony in a healthy organism. In particular, we discuss the role of circadian regulation in the context of behaviour and cognitive functioning, delineating how the loss of this tight interplay is linked to pathological development with a focus on mental disorders and neurodegeneration. We further describe emerging new aspects on the link between the circadian clock and physical exercise-induced cognitive functioning, and its current usage as circadian activator with a positive impact in delaying the progression of certain pathologies including neurodegeneration and brain-related disorders. Finally, we discuss recent epidemiological evidence pointing to an important role of the circadian clock in mental health.

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.

Digital phenotype of mood disorders: A conceptual and critical review

BACKGROUND

Mood disorders are commonly diagnosed and staged using clinical features that rely merely on subjective data. The concept of digital phenotyping is based on the idea that collecting real-time markers of human behavior allows us to determine the digital signature of a pathology. This strategy assumes that behaviors are quantifiable from data extracted and analyzed through digital sensors, wearable devices, or smartphones. That concept could bring a shift in the diagnosis of mood disorders, introducing for the first time additional examinations on psychiatric routine care.

OBJECTIVE

The main objective of this review was to propose a conceptual and critical review of the literature regarding the theoretical and technical principles of the digital phenotypes applied to mood disorders.

METHODS

We conducted a review of the literature by updating a previous article and querying the PubMed database between February 2017 and November 2021 on titles with relevant keywords regarding digital phenotyping, mood disorders and artificial intelligence.

RESULTS

Out of 884 articles included for evaluation, 45 articles were taken into account and classified by data source (multimodal, actigraphy, ECG, smartphone use, voice analysis, or body temperature). For depressive episodes, the main finding is a decrease in terms of functional and biological parameters [decrease in activities and walking, decrease in the number of calls and SMS messages, decrease in temperature and heart rate variability (HRV)], while the manic phase produces the reverse phenomenon (increase in activities, number of calls and HRV).

CONCLUSION

The various studies presented support the potential interest in digital phenotyping to computerize the clinical characteristics of mood disorders.

Metabolomics Analysis of the Prefrontal Cortex in a Rat Chronic Unpredictable Mild Stress Model of Depression

BACKGROUND

Depressive disorder is the leading cause of disability and suicidality worldwide. Metabolites are considered indicators and regulators of depression. However, the pathophysiology of the prefrontal cortex (PFC) in depression remains unclear.

METHODS

A chronic unpredictable mild stress (CUMS) model and a maturation rodent model of depression was used to investigate metabolic changes in the PFC. Eighteen male Sprague-Dawley rats were randomly divided into CUMS and control groups. The sucrose preference test (SPT) and forced swimming test (FST) were employed to evaluate and record depression-associated behaviors and changes in body weight (BW). High-performance liquid chromatography-tandem mass spectrometry was applied to test metabolites in rat PFC. Furthermore, principal component analysis and orthogonal partial least-squares discriminant analysis were employed to identify differentially abundant metabolites. Metabolic pathways were analyzed using MetaboAnalyst. Finally, a metabolite-protein interaction network was established to illustrate the function of differential metabolites.

RESULTS

SPT and FST results confirmed successful establishment of the CUMS-induced depression-like behavior model in rats. Five metabolites, including 1-methylnicotinamide, 3-methylhistidine, acetylcholine, glycerophospho-N-palmitoyl ethanolamine, α-D-mannose 1-phosphate, were identified as potential biomarkers of depression. Four pathways changed in the CUMS group. Metabolite-protein interaction analysis revealed that 10 pathways play roles in the metabolism of depression.

CONCLUSION

Five potential biomarkers were identified in the PFC and metabolite-protein interactions associated with metabolic pathophysiological processes were explored using the CUMS model. The results of this study will assist physicians and scientists in discovering potential diagnostic markers and novel therapeutic targets for depression.