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

BACKGROUND: Considering the heterogeneity of depression, distinct depressive symptom dimensions may be differentially associated with more objective actigraphy-based estimates of physical activity (PA), sleep and circadian rhythm (CR). We examined the association between PA, sleep, and CR assessed with actigraphy and symptom dimensions (i.e. mood/cognition, somatic/vegetative, sleep). METHODS: Fourteen-day actigraphy data of 359 participants were obtained from the Netherlands Study of Depression and Anxiety. PA, sleep, and CR estimates included gross motor activity (GMA), sleep duration (SD), sleep efficiency (SE), relative amplitude between daytime and night-time activity (RA) and sleep midpoint. The 30-item Inventory of Depressive Symptomatology was used to assess depressive symptoms, which were categorised in three depression dimensions: mood/cognition, somatic/vegetative, and sleep. RESULTS: GMA and RA were negatively associated with higher score on all three symptom dimensions: mood/cognition (GMA: ß = -0.155, p < 0.001; RA: ß = -0.116, p = 0.002), somatic/vegetative (GMA: ß = -0.165, p < 0.001; RA: ß = -0.133, p < 0.001), sleep (GMA: ß = -0.169, p < 0.001; RA: ß = -0.190, p < 0.001). The association with sleep was more pronounced for two depression dimensions: longer SD was linked to somatic/vegetative (ß = 0.115, p = 0.015) dimension and lower SE was linked to sleep (ß = -0.101, p = 0.011) dimension. CONCLUSION: As three symptom dimensions were associated with actigraphy-based low PA and dampened CR, these seem to be general indicators of depression. Sleep disturbances appeared more linked to the somatic/vegetative and sleep dimensions; the effectiveness of sleep interventions in patients reporting somatic/vegetative symptoms may be explored, as well as the potential of actigraphy to monitor treatment response to such interventions.

Within-day bidirectional associations between physical activity and affect: A real-time ambulatory study in persons with and without depressive and anxiety disorders.

BACKGROUND: Ambulatory assessments offer opportunities to study physical activity level (PAL) and affect at the group and person-level. We examined bidirectional associations between PAL and affect in a 3-h timeframe and evaluated whether associations differ between people with and without current or remitted depression/anxiety. METHODS: Two-week ecological momentary assessment (EMA) and actigraphy data of 359 participants with current (n = 93), remitted (n = 176), or no (n = 90) Composite International Diagnostic Interview depression/anxiety diagnoses were obtained from the Netherlands Study of Depression and Anxiety. Positive affect (PA) and negative affect (NA) were assessed by EMA 5 times per day. Average PAL between EMA assessments were calculated from actigraphy data. RESULTS: At the group-level, higher PAL was associated with subsequent higher PA (b = 0.109, p < .001) and lower NA (b = -0.043, p < .001), while higher PA (b = 0.066, p < .001) and lower NA (b = -0.053, p < .001) were associated with subsequent higher PAL. The association between higher PAL and subsequent lower NA was stronger for current depression/anxiety patients than controls (p = .01). At the person-level, analyses revealed heterogeneity in bidirectional associations. CONCLUSIONS: Higher PAL may improve affect, especially among depression/anxiety patients. As the relationships vary at the person-level, ambulatory assessments may help identify who would benefit from behavioral interventions.

Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD): recruitment, retention, and data availability in a longitudinal remote measurement study.

BACKGROUND: Major Depressive Disorder (MDD) is prevalent, often chronic, and requires ongoing monitoring of symptoms to track response to treatment and identify early indicators of relapse. Remote Measurement Technologies (RMT) provide an opportunity to transform the measurement and management of MDD, via data collected from inbuilt smartphone sensors and wearable devices alongside app-based questionnaires and tasks. A key question for the field is the extent to which participants can adhere to research protocols and the completeness of data collected. We aimed to describe drop out and data completeness in a naturalistic multimodal longitudinal RMT study, in people with a history of recurrent MDD. We further aimed to determine whether those experiencing a depressive relapse at baseline contributed less complete data. METHODS: Remote Assessment of Disease and Relapse - Major Depressive Disorder (RADAR-MDD) is a multi-centre, prospective observational cohort study conducted as part of the Remote Assessment of Disease and Relapse - Central Nervous System (RADAR-CNS) program. People with a history of MDD were provided with a wrist-worn wearable device, and smartphone apps designed to: a) collect data from smartphone sensors; and b) deliver questionnaires, speech tasks, and cognitive assessments. Participants were followed-up for a minimum of 11 months and maximum of 24 months. RESULTS: Individuals with a history of MDD (n = 623) were enrolled in the study,. We report 80% completion rates for primary outcome assessments across all follow-up timepoints. 79.8% of people participated for the maximum amount of time available and 20.2% withdrew prematurely. We found no evidence of an association between the severity of depression symptoms at baseline and the availability of data. In total, 110 participants had > 50% data available across all data types. CONCLUSIONS: RADAR-MDD is the largest multimodal RMT study in the field of mental health. Here, we have shown that collecting RMT data from a clinical population is feasible. We found comparable levels of data availability in active and passive forms of data collection, demonstrating that both are feasible in this patient group.

Sociodemographic, Health and Lifestyle, Sampling, and Mental Health Determinants of 24-Hour Motor Activity Patterns: Observational Study.

BACKGROUND: Analyzing actigraphy data using standard circadian parametric models and aggregated nonparametric indices may obscure temporal information that may be a hallmark of the circadian impairment in psychiatric disorders. Functional data analysis (FDA) may overcome such limitations by fully exploiting the richness of actigraphy data and revealing important relationships with mental health outcomes. To our knowledge, no studies have extensively used FDA to study the relationship between sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics and daily motor activity patterns assessed with actigraphy in a sample of individuals with and without depression/anxiety. OBJECTIVE: We aimed to study the association between daily motor activity patterns assessed via actigraphy and (1) sociodemographic, health and lifestyle, and sampling factors, and (2) psychiatric clinical characteristics (ie, presence and severity of depression/anxiety disorders). METHODS: We obtained 14-day continuous actigraphy data from 359 participants from the Netherlands Study of Depression and Anxiety with current (n=93), remitted (n=176), or no (n=90) depression/anxiety diagnosis, based on the criteria of the Diagnostic and Statistical Manual of Mental Disorders, fourth edition. Associations between patterns of daily motor activity, quantified via functional principal component analysis (fPCA), and sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics were assessed using generalized estimating equation regressions. For exploratory purposes, function-on-scalar regression (FoSR) was applied to quantify the time-varying association of sociodemographic, health and lifestyle, sampling, and psychiatric clinical characteristics on daily motor activity. RESULTS: Four components of daily activity patterns captured 77.4% of the variability in the data: overall daily activity level (fPCA1, 34.3% variability), early versus late morning activity (fPCA2, 16.5% variability), biphasic versus monophasic activity (fPCA3, 14.8% variability), and early versus late biphasic activity (fPCA4, 11.8% variability). A low overall daily activity level was associated with a number of sociodemographic, health and lifestyle, and psychopathology variables: older age (P<.001), higher education level (P=.005), higher BMI (P=.009), greater number of chronic diseases (P=.02), greater number of cigarettes smoked per day (P=.02), current depressive and/or anxiety disorders (P=.05), and greater severity of depressive symptoms (P<.001). A high overall daily activity level was associated with work/school days (P=.02) and summer (reference: winter; P=.03). Earlier morning activity was associated with older age (P=.02), having a partner (P=.009), work/school days (P<.001), and autumn and spring (reference: winter; P=.02 and P<.001, respectively). Monophasic activity was associated with older age (P=.005). Biphasic activity was associated with work/school days (P<.001) and summer (reference: winter; P<.001). Earlier biphasic activity was associated with older age (P=.005), work/school days (P<.001), and spring and summer (reference: winter; P<.001 and P=.005, respectively). In FoSR analyses, age, work/school days, and season were the main determinants having a time-varying association with daily motor activity (all P<.05). CONCLUSIONS: Features of daily motor activity extracted with fPCA reflect commonly studied factors such as the intensity of daily activity and preference for morningness/eveningness. The presence and severity of depression/anxiety disorders were found to be associated mainly with a lower overall activity pattern but not with the time of the activity. Age, work/school days, and season were the variables most strongly associated with patterns and time of activity, and thus future epidemiological studies on motor activity in depression/anxiety should take these variables into account.

Sleep, circadian rhythm, and physical activity patterns in depressive and anxiety disorders: A 2-week ambulatory assessment study.

BACKGROUND: Actigraphy may provide a more valid assessment of sleep, circadian rhythm (CR), and physical activity (PA) than self-reported questionnaires, but has not been used widely to study the association with depression/anxiety and their clinical characteristics. METHODS: Fourteen-day actigraphy data of 359 participants with current (n = 93), remitted (n = 176), or no (n = 90) composite international diagnostic interview depression/anxiety diagnoses were obtained from the Netherlands Study of Depression and Anxiety. Objective estimates included sleep duration (SD), sleep efficiency, relative amplitude (RA) between day-time and night-time activity, mid sleep on free days (MSF), gross motor activity (GMA), and moderate-to-vigorous PA (MVPA). Self-reported measures included insomnia rating scale, SD, MSF, metabolic equivalent total, and MVPA. RESULTS: Compared to controls, individuals with current depression/anxiety had a significantly different objective, but not self-reported, PA and CR: lower GMA (23.83 vs. 27.4 milli-gravity/day, p = .022), lower MVPA (35.32 vs. 47.64 min/day, p = .023), lower RA (0.82 vs. 0.83, p = .033). In contrast, self-reported, but not objective, sleep differed between people with current depression/anxiety compared to those without current disorders; people with current depression/anxiety reported both shorter and longer SD and more insomnia. More depressive/anxiety symptoms and number of depressive/anxiety diagnoses were associated with larger disturbances of the actigraphy measures. CONCLUSION: Actigraphy provides ecologically valid information on sleep, CR, and PA that enhances data from self-reported questionnaires. As those with more severe or comorbid forms showed the lowest PA and most CR disruptions, the potential for adjunctive behavioral and chronotherapy interventions should be explored, as well as the potential of actigraphy to monitor treatment response to such interventions.

Development of a novel non-invasive biomarker panel for hepatic fibrosis in MASLD.

Accurate non-invasive biomarkers to diagnose metabolic dysfunction-associated steatotic liver disease (MASLD)-related fibrosis are urgently needed. This study applies a translational approach to develop a blood-based biomarker panel for fibrosis detection in MASLD. A molecular gene expression signature identified from a diet-induced MASLD mouse model (LDLr-/-.Leiden) is translated into human blood-based biomarkers based on liver biopsy transcriptomic profiles and protein levels in MASLD patient serum samples. The resulting biomarker panel consists of IGFBP7, SSc5D and Sema4D. LightGBM modeling using this panel demonstrates high accuracy in predicting MASLD fibrosis stage (F0/F1: AUC = 0.82; F2: AUC = 0.89; F3/F4: AUC = 0.87), which is replicated in an independent validation cohort. The overall accuracy of the model outperforms predictions by the existing markers Fib-4, APRI and FibroScan. In conclusion, here we show a disease mechanism-related blood-based biomarker panel with three biomarkers which is able to identify MASLD patients with mild or advanced hepatic fibrosis with high accuracy.

Biopsychosocial Response to the COVID-19 Lockdown in People with Major Depressive Disorder and Multiple Sclerosis.

BACKGROUND: Changes in lifestyle, finances and work status during COVID-19 lockdowns may have led to biopsychosocial changes in people with pre-existing vulnerabilities such as Major Depressive Disorders (MDDs) and Multiple Sclerosis (MS). METHODS: Data were collected as a part of the RADAR-CNS (Remote Assessment of Disease and Relapse-Central Nervous System) program. We analyzed the following data from long-term participants in a decentralized multinational study: symptoms of depression, heart rate (HR) during the day and night; social activity; sedentary state, steps and physical activity of varying intensity. Linear mixed-effects regression analyses with repeated measures were fitted to assess the changes among three time periods (pre, during and post-lockdown) across the groups, adjusting for depression severity before the pandemic and gender. RESULTS: Participants with MDDs (N = 255) and MS (N = 214) were included in the analyses. Overall, depressive symptoms remained stable across the three periods in both groups. A lower mean HR and HR variation were observed between pre and during lockdown during the day for MDDs and during the night for MS. HR variation during rest periods also decreased between pre- and post-lockdown in both clinical conditions. We observed a reduction in physical activity for MDDs and MS upon the introduction of lockdowns. The group with MDDs exhibited a net increase in social interaction via social network apps over the three periods. CONCLUSIONS: Behavioral responses to the lockdown measured by social activity, physical activity and HR may reflect changes in stress in people with MDDs and MS. Remote technology monitoring might promptly activate an early warning of physical and social alterations in these stressful situations. Future studies must explore how stress does or does not impact depression severity.

The day-to-day bidirectional longitudinal association between objective and self-reported sleep and affect: An ambulatory assessment study.

BACKGROUND: Ambulatory assessments offer opportunities to evaluate daily dynamics of sleep and momentary affect using mobile technologies. This study examines day-to-day bidirectional associations between sleep and affect using mobile monitoring, and evaluates whether these associations differ between people without and with current or remitted depression/anxiety. METHODS: Two-week ecological momentary assessment (EMA) and actigraphy data of 359 participants with current (n = 93), remitted (n = 176) or no (n = 90) CIDI depression/anxiety diagnoses were obtained from the Netherlands Study of Depression and Anxiety. Objective sleep duration (SD) and efficiency were obtained from actigraphy data. Self-reported SD, sleep quality (SQ), positive affect (PA) and negative affect (NA) were assessed by electronic diaries through EMA. RESULTS: A bidirectional longitudinal association was found between self-reported SQ and affect, while no association was found for self-reported SD and objective SD and efficiency. Better SQ predicted affect the same day (higher PA: b = 0.035, p < 0.001; lower NA: b = -0.022, p < 0.001), while lower NA on the preceding day predicted better SQ (b = -0.102, p = 0.001). The presence of current depression/anxiety disorders moderated the association between better SQ and subsequent lower NA; it was stronger for patients compared to controls (p = 0.003). LIMITATIONS: Observational study design can only point to areas of interest for interventions. CONCLUSIONS: This 2-week ambulatory monitoring study shows that, especially among depression/anxiety patients, better self-reported SQ predicts higher PA and lower NA the same day, while lower NA predicts better self-reported SQ. The value of mobile technologies to monitor and potentially intervene in patients to improve their affect should be explored.