Association between circadian activity rhythms and mood episode relapse in bipolar disorder: a 12-month prospective cohort study

Longitudinal Assessment of Seasonal Impacts and Depression Associations on Circadian Rhythm Using Multimodal Wearable Sensing: Retrospective Analysis

BACKGROUND

Previous mobile health (mHealth) studies have revealed significant links between depression and circadian rhythm features measured via wearables. However, the comprehensive impact of seasonal variations was not fully considered in these studies, potentially biasing interpretations in real-world settings.

OBJECTIVE

This study aims to explore the associations between depression severity and wearable-measured circadian rhythms while accounting for seasonal impacts.

METHODS

Data were sourced from a large longitudinal mHealth study, wherein participants' depression severity was assessed biweekly using the 8-item Patient Health Questionnaire (PHQ-8), and participants' behaviors, including sleep, step count, and heart rate (HR), were tracked via Fitbit devices for up to 2 years. We extracted 12 circadian rhythm features from the 14-day Fitbit data preceding each PHQ-8 assessment, including cosinor variables, such as HR peak timing (HR acrophase), and nonparametric features, such as the onset of the most active continuous 10-hour period (M10 onset). To investigate the association between depression severity and circadian rhythms while also assessing the seasonal impacts, we used three nested linear mixed-effects models for each circadian rhythm feature: (1) incorporating the PHQ-8 score as an independent variable, (2) adding seasonality, and (3) adding an interaction term between season and the PHQ-8 score.

RESULTS

Analyzing 10,018 PHQ-8 records alongside Fitbit data from 543 participants (n=414, 76.2% female; median age 48, IQR 32-58 years), we found that after adjusting for seasonal effects, higher PHQ-8 scores were associated with reduced daily steps (β=-93.61, P<.001), increased sleep variability (β=0.96, P<.001), and delayed circadian rhythms (ie, sleep onset: β=0.55, P=.001; sleep offset: β=1.12, P<.001; M10 onset: β=0.73, P=.003; HR acrophase: β=0.71, P=.001). Notably, the negative association with daily steps was more pronounced in spring (β of PHQ-8 × spring = -31.51, P=.002) and summer (β of PHQ-8 × summer = -42.61, P<.001) compared with winter. Additionally, the significant correlation with delayed M10 onset was observed solely in summer (β of PHQ-8 × summer = 1.06, P=.008). Moreover, compared with winter, participants experienced a shorter sleep duration by 16.6 minutes, an increase in daily steps by 394.5, a delay in M10 onset by 20.5 minutes, and a delay in HR peak time by 67.9 minutes during summer.

CONCLUSIONS

Our findings highlight significant seasonal influences on human circadian rhythms and their associations with depression, underscoring the importance of considering seasonal variations in mHealth research for real-world applications. This study also indicates the potential of wearable-measured circadian rhythms as digital biomarkers for depression.

Bipolar Disorder, Circadian Rhythm and Clock Genes

Sleep disturbance and abnormal circadian rhythm might be closely related to bipolar disorder. Several studies involving disturbed sleep/wake cycle, changes in rhythms such as melatonin and cortisol, clock genes, and circadian preference have shown the relationship between bipolar disorder and circadian rhythm. The results differed across different studies. In some studies, a delay in the circadian rhythm was observed in the depressive episode and advanced circadian rhythm was observed during the manic episode. In other studies, a delay in circadian rhythm was observed independent of mood episodes. Accordingly, circadian rhythm disorder was proposed as a trait marker for bipolar disorder. The altered circadian rhythm may represent a pathological mechanism that contributes to the mood episodes. However, a prospective cohort study is needed for further clarification.

Causal dynamics of sleep, circadian rhythm, and mood symptoms in patients with major depression and bipolar disorder: insights from longitudinal wearable device data

BACKGROUND

Sleep and circadian rhythm disruptions are common in patients with mood disorders. The intricate relationship between these disruptions and mood has been investigated, but their causal dynamics remain unknown.

METHODS

We analysed data from 139 patients (76 female, mean age = 23.5 ± 3.64 years) with mood disorders who participated in a prospective observational study in South Korea. The patients wore wearable devices to monitor sleep and engaged in smartphone-delivered ecological momentary assessment of mood symptoms. Using a mathematical model, we estimated their daily circadian phase based on sleep data. Subsequently, we obtained daily time series for sleep/circadian phase estimates and mood symptoms spanning >40,000 days. We analysed the causal relationship between the time series using transfer entropy, a non-linear causal inference method.

FINDINGS

The transfer entropy analysis suggested causality from circadian phase disturbance to mood symptoms in both patients with MDD (n = 45) and BD type I (n = 35), as 66.7% and 85.7% of the patients with a large dataset (>600 days) showed causality, but not in patients with BD type II (n = 59). Surprisingly, no causal relationship was suggested between sleep phase disturbances and mood symptoms.

INTERPRETATION

Our findings suggest that in patients with mood disorders, circadian phase disturbances directly precede mood symptoms. This underscores the potential of targeting circadian rhythms in digital medicine, such as sleep or light exposure interventions, to restore circadian phase and thereby manage mood disorders effectively.

FUNDING

Institute for Basic Science, the Human Frontiers Science Program Organization, the National Research Foundation of Korea, and the Ministry of Health & Welfare of South Korea.

Investigating Rhythmicity in App Usage to Predict Depressive Symptoms: Protocol for Personalized Framework Development and Validation Through a Countrywide Study

BACKGROUND

Understanding a student's depressive symptoms could facilitate significantly more precise diagnosis and treatment. However, few studies have focused on depressive symptom prediction through unobtrusive systems, and these studies are limited by small sample sizes, low performance, and the requirement for higher resources. In addition, research has not explored whether statistically significant rhythms based on different app usage behavioral markers (eg, app usage sessions) exist that could be useful in finding subtle differences to predict with higher accuracy like the models based on rhythms of physiological data.

OBJECTIVE

The main objective of this study is to explore whether there exist statistically significant rhythms in resource-insensitive app usage behavioral markers and predict depressive symptoms through these marker-based rhythmic features. Another objective of this study is to understand whether there is a potential link between rhythmic features and depressive symptoms.

METHODS

Through a countrywide study, we collected 2952 students' raw app usage behavioral data and responses to the 9 depressive symptoms in the 9-item Patient Health Questionnaire (PHQ-9). The behavioral data were retrieved through our developed app, which was previously used in our pilot studies in Bangladesh on different research problems. To explore whether there is a rhythm based on app usage data, we will conduct a zero-amplitude test. In addition, we will develop a cosinor model for each participant to extract rhythmic parameters (eg, acrophase). In addition, to obtain a comprehensive picture of the rhythms, we will explore nonparametric rhythmic features (eg, interdaily stability). Furthermore, we will conduct regression analysis to understand the association of rhythmic features with depressive symptoms. Finally, we will develop a personalized multitask learning (MTL) framework to predict symptoms through rhythmic features.

RESULTS

After applying inclusion criteria (eg, having app usage data of at least 2 days to explore rhythmicity), we kept the data of 2902 (98.31%) students for analysis, with 24.48 million app usage events, and 7 days' app usage of 2849 (98.17%) students. The students are from all 8 divisions of Bangladesh, both public and private universities (19 different universities and 52 different departments). We are analyzing the data and will publish the findings in a peer-reviewed publication.

CONCLUSIONS

Having an in-depth understanding of app usage rhythms and their connection with depressive symptoms through a countrywide study can significantly help health care professionals and researchers better understand depressed students and may create possibilities for using app usage-based rhythms for intervention. In addition, the MTL framework based on app usage rhythmic features may more accurately predict depressive symptoms due to the rhythms' capability to find subtle differences.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/51540.

Patient-reported outcomes on sleep quality and circadian rhythm during treatment with intravenous ketamine for treatment-resistant depression

Background

Intravenous (IV) ketamine is a rapid acting antidepressant used primarily for treatment-resistant depression (TRD). It has been suggested that IV ketamine's rapid antidepressant effects may be partially mediated via improved sleep and changes to the circadian rhythm.

Objectives

This study explores IV ketamine's association with changes in patient-reported sleep quality and circadian rhythm in an adult population with TRD.

Methods

Adult patients (18-64 years) with TRD scheduled for IV ketamine treatment were recruited to complete patient rated outcomes measures on sleep quality using the Pittsburgh Sleep Quality Index (PSQI) and circadian rhythm using the Morningness-Eveningness Questionnaire (MEQ). Over a 4-week course of eight ketamine infusions, reports were obtained at baseline (T0), prior to second treatment (T1), prior to fifth treatment (T2), and 1 week after eighth treatment (T3).

Results

Forty participants with TRD (mean age = 42.8, 45% male) were enrolled. Twenty-nine (72.5%) had complete follow-up data. Paired t tests revealed statistically significant improvements at the end of treatment in sleep quality (PSQI) (p = 0.003) and depressive symptoms (Clinically Useful Depression Outcome Scale-Depression, p < 0.001) while circadian rhythm (MEQ) shifted earlier (p = 0.007). The PSQI subscale components of sleep duration (p = 0.008) and daytime dysfunction (p = 0.001) also improved. In an exploratory post hoc analysis, ketamine's impact on sleep quality was more prominent in patients with mixed features, while its chronobiotic effect was prominent in those without mixed features.

Conclusion

IV ketamine may improve sleep quality and advance circadian rhythm in individuals with TRD. Effects may differ in individuals with mixed features of depression as compared to those without. Since this was a small uncontrolled study, future research is warranted.

Associations between actigraphy estimates of sleep and circadian rhythmicity and psychotropic medications in bipolar disorders: An exploratory study

INTRODUCTION

Disturbances in sleep and circadian rhythmicity (CR) are frequent in individuals with bipolar disorders (BD). Very few studies explored the associations between psychotropic medications and these disturbances in euthymic BD. Therefore, we aimed at exploring the associations between several classes of medications (lithium, sedative/non-sedative Atypical Antipsychotics (AAP), anticonvulsants, antidepressants, benzodiazepines) and sleep disturbances and CR dimensions in a sample of euthymic individuals with BD.

METHODS

We included euthymic adults with BD type 1 or 2 assessed with 21 days of actimetry. We used a Principal Component Analysis (PCA) of sleep and CR estimates to generate dimensions to be studied in association with the current use of psychotropic medications, with adjustments for potential confounding factors.

RESULTS

We included individuals with BD-1 (n = 116) or BD-2 (n = 37). The PCA led to four dimensions of sleep and CR estimates. Benzodiazepines were associated with better sleep quality (pcorrected = 0.032). Aripiprazole was associated with less robust CR (pcorrected = 0.016), but with earlier peak of activity patterns (pcorrected = 0.020). Sedative AAPs were associated with better sleep quality, which was no longer significant after correction. We found no association between lithium or anticonvulsants and CR.

LIMITATIONS

The cross-sectional design and the possible non-representativeness of the sample were limitations of our study.

CONCLUSIONS

In euthymic individuals with BD, benzodiazepines may have a positive effect on sleep quality, while aripiprazole may have mixed effects on CR (less robust but with earlier peak of activity patterns). No association with lithium or anticonvulsants observed. Further studies are warranted to replicate and extend these results.

Sleep and Postpartum Psychosis: A Narrative Review of the Existing Literature

Sleep problems are extremely common during the postpartum period. The role of sleep in the development of postpartum psychosis (PP) is, however, still under-researched. This narrative review aims to (1) provide a summary of the existing evidence for the associations between sleep problems and PP, (2) discuss the relevant risk factors associated with sleep problems and PP, and (3) suggest future lines of research in this area. Some of the existing literature suggests an association between sleep problems, specifically insomnia, sleep loss and sleep disruption during pregnancy and postpartum, and PP, with the most relevant risk factors including history of bipolar disorder and time of delivery. However, it is still unclear whether the previously mentioned sleep problems are a symptom of, or a trigger for PP. Thus, further research is needed to identify the specific role of sleep problems in PP, using longitudinal designs and more objective measures of sleep. This will allow appropriate detection, intervention and support for women experiencing and/or at risk for PP.

Circadian variability of objective sleep measures predicts the relapse of a mood episode in bipolar disorder: findings from the APPLE cohort

AIM

Sleep disturbance, a core feature of bipolar disorder, is closely associated with mood symptoms. We examined the association between actigraphy sleep parameters and mood episode relapses in patients with bipolar disorder.

METHODS

This prospective cohort study analyzed 193 outpatients with bipolar disorder who participated in the Association between the Pathology of Bipolar Disorder and Light Exposure in Daily Life (APPLE) cohort study. The participants' sleep was objectively evaluated via actigraphy over seven consecutive days for the baseline assessment and then at the 2-year follow-up appointment for mood episode relapses. The actigraphy sleep parameters were presented using the mean and variability (standard deviation) of each sleep parameter for 7 days.

RESULTS

Of the 193 participants, 110 (57%) experienced mood episodes during follow-up. The participants with higher variability in total sleep time had a significantly shorter mean estimated time to mood episode relapses than those with lower variability (12.5 vs. 16.8 months; P < 0.001). The Cox proportional hazards model, when adjusted for potential confounders, demonstrated that variability in total sleep time was significantly associated with an increase in the mood episode relapses (per hour; hazard ratio [HR], 1.407; 95% confidence interval (CI), 1.057-1.873), mainly in the depressive episodes (per hour; HR, 1.477; 95% CI, 1.088-2.006).

CONCLUSIONS

Our findings suggest that consistency in sleep time might be useful, as an adjunct therapy, in preventing the recurrence or relapse of mood episodes in bipolar disorder.

Profile of sleep disturbances in patients with recurrent depressive disorder or bipolar affective disorder in a tertiary sleep disorders service

Bidirectional relationship between sleep disturbances and affective disorders is increasingly recognised, but its underlying mechanisms are far from clear, and there is a scarcity of studies that report on sleep disturbances in recurrent depressive disorder (RDD) and bipolar affective disorder (BPAD). To address this, we conducted a retrospective study of polysomnographic and clinical records of patients presenting to a tertiary sleep disorders clinic with affective disorders. Sixty-three BPAD patients (32 female; mean age ± S.D.: 41.8 ± 12.4 years) and 126 age- and gender-matched RDD patients (62 female; 41.5 ± 12.8) were studied. Whilst no significant differences were observed in sleep macrostructure parameters between BPAD and RDD patients, major differences were observed in comorbid sleep and physical disorders, both of which were higher in BPAD patients. Two most prevalent sleep disorders, namely obstructive sleep apnoea (OSA) (BPAD 50.8.0% vs RDD 29.3%, P = 0.006) and insomnia (BPAD 34.9% vs RDD 15.0%, P = 0.005) were found to be strongly linked with BPAD. In summary, in our tertiary sleep clinic cohort, no overt differences in the sleep macrostructure between BPAD and RDD patients were demonstrated. However, OSA and insomnia, two most prevalent sleep disorders, were found significantly more prevalent in patients with BPAD, by comparison to RDD patients. Also, BPAD patients presented with significantly more severe OSA, and with higher overall physical co-morbidity. Thus, our findings suggest an unmet/hidden need for earlier diagnosis of those with BPAD.

Current role and future perspectives of electroacupuncture in circadian rhythm regulation

In recent years, in-depth research on chronobiology has been conducted, and the circadian rhythm has become a new target for the treatment of diseases. Circadian rhythms are closely related to the normal physiological functions of organisms. Increasing evidence indicates that circadian rhythm disorders are the pathological basis of diseases such as sleep disorders, depression, cardiovascular diseases, and cancer. As an economical, safe, and effective treatment method, electroacupuncture has been widely used in clinical practice. In this paper, we summarize the current literature on electroacupuncture's regulation of circadian rhythm disorders and circadian clock genes. In addition, we briefly explore the optimization of electroacupuncture intervention programmes and the feasibility of implementing electroacupuncture intervention programmes at selected times in clinical practice. We conclude that electroacupuncture may have good application prospects in circadian rhythm regulation, but this conclusion needs to be confirmed by clinical trials.

Does circadian dysrhythmia drive the switch into high- or low-activation states in bipolar I disorder?

OBJECTIVES

Emerging evidence suggests a role of circadian dysrhythmia in the switch between "activation" states (i.e., objective motor activity and subjective energy) in bipolar I disorder.

METHODS

We examined the evidence with respect to four relevant questions: (1) Are natural or environmental exposures that can disrupt circadian rhythms also related to the switch into high-/low-activation states? (2) Are circadian dysrhythmias (e.g., altered rest/activity rhythms) associated with the switch into activation states in bipolar disorder? (3) Do interventions that affect the circadian system also affect activation states? (4) Are associations between circadian dysrhythmias and activation states influenced by other "third" factors?

RESULTS

Factors that naturally or experimentally alter circadian rhythms (e.g., light exposure) have been shown to relate to activation states; however future studies need to measure circadian rhythms contemporaneously with these natural/experimental factors. Actigraphic measures of circadian dysrhythmias are associated prospectively with the switch into high- or low-activation states, and more studies are needed to establish the most relevant prognostic actigraphy metrics in bipolar disorder. Interventions that can affect the circadian system (e.g., light therapy, lithium) can also reduce the switch into high-/low-activation states. Whether circadian rhythms mediate these clinical effects is an unknown but valuable question. The influence of age, sex, and other confounders on these associations needs to be better characterised.

CONCLUSION

Based on the reviewed evidence, our view is that circadian dysrhythmia is a plausible driver of transitions into high- and low-activation states and deserves prioritisation in research in bipolar disorders.

Habitual light exposure and circadian activity rhythms in bipolar disorder: A cross-sectional analysis of the APPLE cohort

BACKGROUND

Circadian activity rhythm disruption is a core feature in bipolar disorder. We investigated whether light exposure in daily life is associated with circadian activity rhythms in patients with bipolar disorder.

METHODS

In a cross-sectional study, we enrolled 194 outpatients with bipolar disorder who were participants of the Association between Pathology of Bipolar Disorder and Light Exposure in Daily Life (APPLE) cohort study. The participants' physical activity and daytime illuminance were measured using an actigraph over 7 consecutive days. Nighttime illuminance in the bedroom was measured using a portable photometer. Circadian activity rhythm parameters were calculated using cosinor analysis and a nonparametric circadian rhythm analysis.

RESULTS

The median daytime illuminance and nighttime illuminance were 224.5 lx (interquartile range, 154.5-307.5 lx) and 2.3 lx (0.3-9.4 lx), respectively. Multivariable linear regression analysis, adjusted for potential confounding factors, showed that higher daytime illuminance was significantly associated with higher amplitude and most active continuous 10-hour period, advanced acrophase, higher interdaily stability, and lower intradaily variability. Higher nighttime illuminance was significantly associated with lower relative amplitude, delayed onset of the least active continuous 5-hour period, and higher intradaily variability.

LIMITATIONS

As this was a cross-sectional study, the results do not necessarily imply that light exposure alters circadian activity rhythms.

CONCLUSIONS

Daytime light exposure was associated with a positive effect and nighttime light exposure with a negative effect on circadian activity rhythms in bipolar disorder.

Can circadian rhythm predict changes in neurocognitive functioning in bipolar disorder: protocol of a 12-month longitudinal cohort study based on research domain criteria

Introduction: Bipolar disorder (BD) is a prevalent and disabling mental disorder characterized by disrupted circadian rhythms and impaired neurocognitive features, both of which fall under the major domains of Research Domain Criteria (RDoC). However, there is limited evidence regarding the interaction between circadian rhythms and long-term neurocognitive functioning. Therefore, this longitudinal cohort study protocol aims to explore whether circadian rhythm can predict changes in neurocognitive functioning over time in patients with BD.Methods: This study adopts a longitudinal cohort design, aiming to recruit 100 BD patients in either depressive or remitted states. Participants will undergo evaluations from clinical, circadian rhythm, and neurocognitive perspectives at baseline, 6-month, and 12-month follow-ups, involving questionnaires, actigraphy, and computed neurocognitive tests. We will examine both cross-sectional and longitudinal associations between participants' circadian rhythm patterns and neurocognitive functioning. Statistical analyses will employ Spearman correlation and mixed regression models.Discussion: We anticipate that circadian rhythms may serve as predictors of neurocognitive functioning changes. The findings of this study could offer supplementary insights into BD pathophysiology, potential treatment targets, and prediction.Trial Registration: This study has been registered with the Chinese Clinical Trial Registry under the registration code ChiCTR2200064922 on 21st October 2022.

Effect of nighttime bedroom light exposure on mood episode relapses in bipolar disorder

OBJECTIVE

A previous cross-sectional study reported that nighttime light is associated with increased occurrence of manic symptoms in bipolar disorder; however, the longitudinal association between nighttime light and subsequent mood episode relapses remains unclear. We determined whether bedroom nighttime light was associated with mood episode relapses in patients with bipolar disorder.

METHODS

This prospective cohort study included 172 outpatients with bipolar disorder who participated in an Association between the Pathology of Bipolar Disorder and Light Exposure in Daily Life (APPLE) cohort study. A portable photometer was used to measure illuminance in the bedroom from bedtime to rising time during 7 consecutive nights for baseline assessment. Then, the participants were assessed at a 2-year follow-up for mood episode relapses.

RESULTS

Of the 172 participants, 157 (91%) completed the 2-year follow-up, and 39 (22%) experienced manic or hypomanic episodes (with or without mixed features), during that time. In the Cox proportional-hazards model, the hazard ratio (HR) for manic/hypomanic episode relapses was significantly higher when the average nighttime illuminance was ≥3 lux (n = 71) than when it was <3 lux (n = 101; HR, 2.54; 95% confidence interval (CI), 1.33-4.84). In the multivariable model adjusted for a propensity score in relation to nighttime light, the relationship remained significant (HR, 2.17; 95% CI, 1.04-4.52). The association between nighttime light and depressive episode relapses was not significantly different.

CONCLUSIONS

Keeping the bedroom dark at night may prevent hypomanic and manic episodes.

Which Actigraphy Dimensions Predict Longitudinal Outcomes in Bipolar Disorders?

Bipolar disorder (BD) is characterized by recurrent mood episodes. It is increasingly suggested that disturbances in sleep–wake cycles and/or circadian rhythms could represent valuable predictors of recurrence, but few studies have addressed this question. Euthymic individuals with BD (n = 69) undertook 3 weeks of actigraphy recording and were then followed up for a median duration of 3.5 years. Principal component analyses were used to identify core dimensions of sleep quantity/variability and circadian rhythmicity. Associations between clinical variables and actigraphy dimensions and time to first recurrence were explored using survival analyses, and then using area under the curve (AUC) analyses (early vs. late recurrence). Most participants (64%) experienced a recurrence during follow-up (median survival time: 18 months). After adjusting for potential confounding factors, an actigraphy dimension comprising amplitude and variability/stability of circadian rhythms was a significant predictor of time to recurrence (p = 0.009). The AUC for correct classification of early vs. late recurrence subgroups was only 0.64 for clinical predictors, but combining these variables with objectively measured intra-day variability improved the AUC to 0.82 (p = 0.04). Actigraphy estimates of circadian rhythms, particularly variability/stability and amplitude, may represent valid predictive markers of future BD recurrences and could be putative targets for future psychosocial interventions.

Altered distribution of resting periods of daily locomotor activity in patients with delayed sleep phase disorder

Delayed sleep phase disorder (DSPD) and mood disorders have a close relationship. However, the shared mechanisms by DSPD and mood disorders have not been well-elucidated. We previously found that micro-fluctuations in human behaviors are organized by robust statistical laws (behavioral organization), where the cumulative distributions of resting and active period durations take a power-law distribution form and a stretched exponential functional form, respectively. Further, we found that the scaling exponents of resting period distributions significantly decreased in major depressive disorder (MDD). In this study, we hypothesized that DSPD had similar characteristics of the altered behavioral organization to that of MDD. Locomotor activity data were acquired for more than 1 week from 17 patients with DSPD and 17 age- and gender-matched healthy participants using actigraphy. We analyzed the cumulative distributions of resting and active period durations in locomotor activity data and subsequently derived fitting parameters of those distributions. Similar to patients with MDD, we found that resting period distributions took a power-law form over the range of 2-100 min, with significantly lower values of scaling exponents γ in patients with DSPD compared with healthy participants. The shared alteration in γ suggests the existence of similar pathophysiology between DSPD and MDD.