Circadian Rhythm Dysregulation in Bipolar Spectrum Disorders

Moderating effect of shift work on sleep and depression in individuals at high risk of bipolar disorder

BACKGROUND

Social Zeitgeber Theory posits that disruptions in social rhythms can increase susceptibility to bipolar disorder (BD). Shift work (SW) is one of the external factors that cause instability in social rhythms and the sleep-wake cycle. This study evaluated the moderating influences of SW on the risks of BD and sleep-related parameters and depressive symptoms. Furthermore, we evaluated the specific work schedules including daytime, nighttime, and regular and irregular rotating SW.

METHODS

An online survey was administered to 6665 participants, with 3379 (50.7 %) classified as individuals with high scores of Mood Disorder Questionnaire (MDQ). The survey included the Pittsburgh Sleep Quality Index (PSQI), Insomnia Severity Scale (ISI), Epworth Sleepiness Scale (ESS), and Center for Epidemiologic Studies Depression Scale (CES-D).

RESULTS

A multivariate regression model revealed significant interactive effects of MDQ positivity and SW on PSQI, ISI, and CES-D scores, but not ESS scores. In a secondary analysis of the high MDQ screen group, daytime workers had lower scores in sleep disturbances and depressive symptoms compared to those engaged in other forms of SW.

LIMITATIONS

Online surveys were accessible voluntarily, leading to potential selection bias. Cross-sectional data identified associations, not causal relationships. Only a self-reported questionnaire was used.

CONCLUSIONS

Our findings emphasize the advantages of a daytime work schedule for individuals at high risk of BD. In accordance with the principles of social rhythm interpersonal therapy, sleep interventions for individuals at high risk of BD should include the maintenance of a consistent daytime schedule.

The relationship between anxiety symptoms and disturbances in biological rhythms in patients with depression

BACKGROUND

Biological rhythms denote the cyclical patterns of life activities anchored to a 24-hour cycle. Research shows that depression exhibits disturbances in biological rhythms. Yet, the relationship between these biological rhythms and concomitant anxiety symptoms is insufficiently investigated in structured clinical assessments.

METHODS

This multicenter study, carried out in four Chinese hospitals, comprehensively examined the relationship between anxiety and disruptions in biological rhythms among patients with depression. The study encompassed 218 patients diagnosed with depression and 205 matched healthy controls. The Chinese version of the Biological Rhythms Interview of Assessment in Neuropsychiatry was utilized to evaluate the participants' biological rhythms, focusing on four dimensions: sleep, activity, social, and diet.

RESULTS

In patients with depression, there is a significant positive correlation between the severity of anxiety symptoms and the disturbances in biological rhythms. The severity of anxiety and depression, along with the quality of life, are independently associated with disruptions in biological rhythms. The mediation model reveals that anxiety symptoms mediate the relationship between depressive symptoms and biological rhythms.

CONCLUSION

This research highlights the role of anxiety within the spectrum of depressive disorders and the associated disturbances in biological rhythms. Our findings shed light on potential pathways towards more targeted preventive strategies and therapeutic interventions for individuals battling depression and anxiety.

Social zeitgeber and sleep loss as risk factors for suicide in American Indian adolescents

American Indians / Alaska Natives (AI/AN) bear a high burden of suicide, the reasons for which are not completely understood, and rates can vary by tribal group and location. This article aims to identify circumstances reported by a community group of American Indian adolescent participants to be associated with their depression and/or suicide. American Indian adolescents (n  =  360) were recruited from contiguous reservations and were assessed with a semi-structured diagnostic interview. Twenty percent of the adolescents reported suicidal thoughts (ideation, plans), an additional 8% reported a history of suicide attempts, and three deaths due to suicide were reported. Suicidal behaviors and major depressive disorder (MDD) co-occurred and were more common among female adolescents. The distressing events that adolescents most often reported were: death in the family, family disruption, peer relationship problems, and school problems. All of these events were significantly associated with suicidal behaviors, however those with suicidal acts were more likely to report death in the family. Those with MDD but no suicidal behaviors were more likely to report disruptions in the family. Disruptions in falling asleep were also associated with suicidal behaviors and having experienced a death in the family. Disruptions in important relationships, particularly through death or divorce, may be interpreted as a loss or disruption in "social zeitgebers" that may in turn disturb biological rhythms, such as sleep, thus potentially increase the risk for MDD and/or suicide. Prevention programs aimed at ameliorating the impact of disruptions in important relationships may potentially reduce suicidal behaviors in AI/AN adolescents.

Social and circadian rhythm dysregulation and suicide: A systematic review and meta-analysis

This systematic review of 52 studies provides a quantitative synthesis of the empirical literature on social and circadian rhythm correlates of suicidal thoughts and behaviors (STB). Small-to-medium pooled effect sizes were observed for associations between evening chronotype and STB and suicidal ideation (SI), although the pooled effect size diminished when accounting for publication bias. Three studies employed longitudinal designs and suggested eveningness was predictive of future STB, with a small-to-medium effect size. Social rhythm irregularity was also a significant correlate of STB with pooled effect sizes in the medium range. Overall circadian rhythm disruption was not associated with STB, although certain circadian rhythm metrics, including mean daytime activity, circadian rhythm sleep-wake disorder diagnosis, and actigraphy-assessed amplitude were associated with STB. Pooled effect sizes for these indices were in the medium to large range. There is a need for additional longitudinal research on actigraphy-based circadian parameters and objective markers of circadian phase (i.e., dim-light melatonin onset) to gain a clearer understanding of associations of endogenous circadian function and STB beyond that which can be captured via self-report.

Impact of biological rhythms on perception of illness and cognitive flexibility in bipolar patients in remission

Our study aims to examine the possible mediating effects of biological rhythms on the relationship between illness perception, cognitive flexibility, and functionality in bipolar patients in remission. A total of 150 patients with bipolar disorder (BD) were enrolled. The sociodemographic data form, Biological Rhythm Interview of Assessment in Neuropsychiatry (BRIAN), Brief Illness Perception Questionnaire (BIPQ), Cognitive Flexibility Scale (CFS), Young Mania Rating Scale, Montgomery and Asberg Depression Scale, Beck Anxiety Inventory, and Short Functionality Assessment Scale were applied to the patients in the study. The mean age of the patients was 42.10 ± 12.92 (SD). The participants were 48.7% (n = 73) female and 66.6% (n = 100) BD-I. There was a negative correlation between the total BRIAN score and favorable BIPQ scores and a positive correlation between the total BRIAN score and unfavorable BIPQ scores (except timeline). Additionally, multiple regression analyses revealed that the total BRIAN score could predict favorable BIPQ (except treatment control) and unfavorable BIPQ (except timeline) scores (p < 0.05). The total CFS score also could predict favorable BIPQ (treatment control) and unfavorable BIPQ scores (except timeline). The second step mediation analysis showed that biological rhythm mediated the relationship between illness perception and cognitive flexibility. Our study found that biological rhythms played a full mediating role in the relationship between the perception of illness and cognitive flexibility. In addition, worsening in biological rhythms in bipolar patients could cause negative beliefs and attitudes towards their diseases with an unfavorable clinical course. Therefore, regularity in biological rhythms should be highly recommended for bipolar patients.

Reward sensitivity and social rhythms during goal-striving: An ecological momentary assessment investigation of bipolar spectrum disorders

BACKGROUND

The reward/circadian rhythm model of bipolar spectrum disorders (BSDs) posits that when individuals with hypersensitive reward systems encounter reward-relevant events, they experience social and circadian rhythm disruption, leading to mood symptoms. The aim of the current study is to test an element of this theoretical model by investigating changes in social rhythms during and after an ecologically-valid reward-relevant event and evaluating whether the strength of these associations differ by trait reward sensitivity and BSD diagnostic group.

METHODS

Young adults from three groups (low BSD risk with moderate reward sensitivity [MRew], high BSD risk with high reward sensitivity [HRew], and high reward sensitivity with BSD [HRew+BSD]) completed a reward responsiveness task and 20-day ecological momentary assessment study structured around a participant-specific goal occurring on day 15. Social rhythm disruption (SRD) and social rhythm regularity (SRR) were assessed daily. Multilevel models examined whether reward sensitivity and group moderated associations between study phase (baseline [days 1-5], goal-striving [days 16-20], or outcome [days 16-20]) and social rhythms.

RESULTS

Participants experienced greater SRD after the goal-striving event during the outcome phase, compared to the baseline phase. The HRew+BSD group had significant decreases in SRR during the outcome phase, and this pattern differed significantly from the low-risk and high-risk groups. Greater task reward responsiveness also was associated with significant decreases in SRR during the outcome phase.

LIMITATIONS

This study did not test whether social rhythm irregularity was associated with subsequent mood change.

CONCLUSIONS

Participants exhibited social rhythm changes over the course of this ecologically valid goal-striving period, providing evidence for the interplay between reward-activating events and social rhythms. The HRew+BSD group showed a distinct pattern in which their social rhythms were more irregular after completing reward-relevant goal-striving that was not observed for the low-BSD risk or high-BSD risk groups. These findings provide additional support for Interpersonal and Social Rhythms Therapy.

Evening Chronotype and Suicide: Exploring Neuroinflammation and Psychopathological Dimensions as Possible Bridging Factors-A Narrative Review

A chronotype is generally defined as the variability of the phase angle of entrainment, while the latter reflects the relationship between the timing of a certain rhythm (e.g., the sleep-wake cycle) and the timing of an external temporal cue. Individuals can be placed on a spectrum from "morning types" (M types) to "evening types" (E types). E-chronotype has been proposed as a transdiagnostic risk factor for psychiatric conditions, and it has been associated with psychopathological dimensions. Eveningness seems to be correlated with both suicidal ideation (SI) and suicidal behavior (SB) through several possible mediating factors. Immunological alterations have also been linked to later chronotypes and SI/SB. This narrative review aims to summarize the evidence supporting the possible association between chronotypes and suicide and the eventual mediating role of neuroinflammation and several psychopathological dimensions. A search of the literature (2003-2023) was conducted using various databases: PUBMED, EMBASE, Scopus, UpToDate, PsycINFO, and Cochrane Library. English-language articles were collected and screened for eligibility. Despite the apparent absence of a direct correlation between E-chronotype and suicidality, E-chronotype promotes a chain of effects that could be involved in an increased risk of SB, in which with neuroinflammation possibly plays an intriguing role and some psychopathological dimensions may stand out.

The concept of "metabolic jet lag" in the pathophysiology of bipolar disorder: implications for research and clinical care

Bipolar disorder (BD) is a potentially chronic mental disorder marked by recurrent depressive and manic episodes, circadian rhythm disruption, and changes in energetic metabolism. "Metabolic jet lag" refers to a state of shift in circadian patterns of energy homeostasis, affecting neuroendocrine, immune, and adipose tissue function, expressed through behavioral changes such as irregularities in sleep and appetite. Risk factors include genetic variation, mitochondrial dysfunction, lifestyle factors, poor gut microbiome health and abnormalities in hunger, satiety, and hedonistic function. Evidence suggests metabolic jet lag is a core component of BD pathophysiology, as individuals with BD frequently exhibit irregular eating rhythms and circadian desynchronization of their energetic metabolism, which is associated with unfavorable clinical outcomes. Although current diagnostic criteria lack any assessment of eating rhythms, technological advancements including mobile phone applications and ecological momentary assessment allow for the reliable tracking of biological rhythms. Overall, methodological refinement of metabolic jet lag assessment will increase knowledge in this field and stimulate the development of interventions targeting metabolic rhythms, such as time-restricted eating.

Mobile phone addiction and mental health: the roles of sleep quality and perceived social support

As a global phenomenon, mobile phone addiction has become an increasingly common issue among Chinese university students. Although previous research explored the link between mobile phone addiction and mental health, the possible mechanism underlying the above association is unclear. We administered a cross-sectional survey to 585 participants from two universities in Kunming, southwest China, from October 2021 to January 2022. Our results suggested that mobile phone addiction was negatively associated with mental health, and sleep quality partially mediated the relationship between mobile phone addiction and mental health. Furthermore, perceived social support positively moderated the direct effect of sleep quality on mental health, as well as the indirect effect of mobile phone addiction on mental health. These findings provide a new insight into the underlying mechanism by which mobile phone addiction affects university students' mental health. The results emphasize a necessary task for administrators, health workers, and family members to attach importance to the overuse of mobile phones among university students.

Opportunities for digital health technology: identifying unmet needs for bipolar misdiagnosis and depression care management

Introduction

Digital health technologies (DHTs) driven by artificial intelligence applications, particularly those including predictive models derived with machine learning methods, have garnered substantial attention and financial investment in recent years. Yet, there is little evidence of widespread adoption and scant proof of gains in patient health outcomes. One factor of this paradox is the disconnect between DHT developers and digital health ecosystem stakeholders, which can result in developing technologies that are highly sophisticated but clinically irrelevant. Here, we aimed to uncover challenges faced by psychiatrists treating patients with major depressive disorder (MDD). Specifically, we focused on challenges psychiatrists raised about bipolar disorder (BD) misdiagnosis.

Methods

We conducted semi-structured interviews with 10 United States-based psychiatrists. We applied text and thematic analysis to the resulting interview transcripts.

Results

Three main themes emerged: (1) BD is often misdiagnosed, (2) information crucial to evaluating BD is often occluded from clinical observation, and (3) BD misdiagnosis has important treatment implications.

Discussion

Using upstream stakeholder engagement methods, we were able to identify a narrow, unforeseen, and clinically relevant problem. We propose an organizing framework for development of digital tools based upon clinician-identified unmet need.

Sleep disorders in veterans with serious mental illnesses: prevalence in Veterans Affairs health record data

STUDY OBJECTIVES

This study aimed to estimate the 12-month prevalence of diagnosed sleep disorders among veterans with and without serious mental illnesses (SMI) in Veterans Affairs health record data in 2019. We also examined diagnosed sleep disorders across a 9-year period and explored associations with demographic and health factors.

METHODS

This study used health record data from VISN 4 of the Veterans Health Administration from 2011 to 2019. SMI diagnoses included schizophrenia and bipolar spectrum diagnoses as well as major depression with psychosis. Sleep diagnoses included insomnias, hypersomnias, sleep-related breathing disorders, circadian rhythm sleep-wake disorders, and sleep-related movement disorders. Demographic and health-related factors were also collected from the record.

RESULTS

In 2019, 21.8% of veterans with SMI were diagnosed with a sleep disorder. This is a significantly higher proportion than for veterans without SMI, 15.1% of whom were diagnosed with a sleep disorder. Sleep disorder rates were highest in veterans with a chart diagnosis of major depression with psychosis. From 2011 to 2019, the overall prevalence of sleep disorders in veterans with SMI more than doubled (10.2%-21.8%), suggesting improvements in the detection and diagnosis of sleep concerns for this group.

CONCLUSIONS

Our findings suggest that identification and diagnosis of sleep disorders for veterans with SMI has improved over the past decade, though diagnoses still likely underrepresent actual prevalence of clinically relevant sleep concerns. Sleep concerns may be at particularly high risk of going untreated in veterans with schizophrenia-spectrum disorders.

CITATION

Bonfils KA, Longenecker JM, Soreca I, et al. Sleep disorders in veterans with serious mental illnesses: prevalence in Veterans Affairs health record data. J Clin Sleep Med. 2023;19(9):1651-1660.

Circadian, Reward, and Emotion Systems in Teens prospective longitudinal study: protocol overview of an integrative reward-circadian rhythm model of first onset of bipolar spectrum disorder in adolescence

BACKGROUND

Bipolar spectrum disorders (BSDs) are associated with a heightened sensitivity to rewards and elevated reward-related brain function in cortico-striatal circuitry. A separate literature documents social and circadian rhythm disruption in BSDs. Recently, integrated reward-circadian models of BSDs have been proposed. These models draw on work indicating that the two systems influence each other and interact to affect mood functioning. When dysregulated, reward and circadian system signaling may combine to form a positive feedback loop, whereby dysregulation in one system exacerbates dysregulation in the other. Project CREST (Circadian, Reward, and Emotion Systems in Teens) provides a first systematic test of reward-circadian dysregulation as a synergistic and dynamic vulnerability for first onset of BSD and increases in bipolar symptoms during adolescence.

METHODS

This NIMH-funded R01 study is a 3-year prospective, longitudinal investigation of approximately 320 community adolescents from the broader Philadelphia area, United States of America. Eligible participants must be 13-16 years old, fluent in English, and without a prior BSD or hypomanic episode. They are being selected along the entire dimension of self-reported reward responsiveness, with oversampling at the high tail of the dimension in order to increase the likelihood of BSD onsets. At Times 1-6, every 6 months, participants will complete assessments of reward-relevant and social rhythm disruption life events and self-report and diagnostic assessments of bipolar symptoms and episodes. Yearly, at Times 1, 3, and 5, participants also will complete self-report measures of circadian chronotype (morningness-eveningness) and social rhythm regularity, a salivary dim light melatonin onset (DLMO) procedure to assess circadian phase, self-report, behavioral, and neural (fMRI) assessments of monetary and social reward responsiveness, and a 7-day ecological momentary assessment (EMA) period. During each EMA period, participants will complete continuous measures of sleep/wake and activity (actigraphy), a daily sleep diary, and three within-day (morning, afternoon, evening) measures of life events coded for reward-relevance and social rhythm disruption, monetary and social reward responsiveness, positive and negative affect, and hypo/manic and depressive symptoms. The fMRI scan will occur on the day before and the DLMO procedure will occur on the first evening of the 7-day EMA period.

DISCUSSION

This study is an innovative integration of research on multi-organ systems involved in reward and circadian signaling in understanding first onset of BSD in adolescence. It has the potential to facilitate novel pharmacological, neural, and behavioral interventions to treat, and ideally prevent, bipolar conditions.

Unipolar and Bipolar Depression Detection and Classification Based on Actigraphic Registration of Motor Activity Using Machine Learning and Uniform Manifold Approximation and Projection Methods

Modern technology frequently uses wearable sensors to monitor many aspects of human behavior. Since continuous records of heart rate and activity levels are typically gathered, the data generated by these devices have a lot of promise beyond counting the number of daily steps or calories expended. Due to the patient's inability to obtain the necessary information to understand their conditions and detect illness, such as depression, objectively, methods for evaluating various mental disorders, such as the Montgomery-Asberg depression rating scale (MADRS) and observations, currently require a significant amount of effort on the part of specialists. In this study, a novel dataset was provided, comprising sensor data gathered from depressed patients. The dataset included 32 healthy controls and 23 unipolar and bipolar depressive patients with motor activity recordings. Along with the sensor data collected over several days of continuous measurement for each patient, some demographic information was also offered. The result of the experiment showed that less than 70 of the 100 epochs of the model's training were completed. The Cohen Kappa score did not even pass 0.1 in the validation set, due to an imbalance in the class distribution, whereas in the second experiment, the majority of scores peaked in about 20 epochs, but because training continued during each epoch, it took much longer for the loss to decline before it fell below 0.1. In the second experiment, the model soon reached an accuracy of 0.991, which is as expected given the outcome of the UMAP dimensionality reduction. In the last experiment, UMAP and neural networks worked together to produce the best outcomes. They used a variety of machine learning classification algorithms, including the nearest neighbors, linear kernel SVM, Gaussian process, and random forest. This paper used the UMAP unsupervised machine learning dimensionality reduction without the neural network and showed a slightly lower score (QDA). By considering the ratings of the patient's depressive symptoms that were completed by medical specialists, it is possible to better understand the relationship between depression and motor activity.

Mapping anorexia nervosa genes to clinical phenotypes

BACKGROUND

Anorexia nervosa (AN) is a psychiatric disorder with complex etiology, with a significant portion of disease risk imparted by genetics. Traditional genome-wide association studies (GWAS) produce principal evidence for the association of genetic variants with disease. Transcriptomic imputation (TI) allows for the translation of those variants into regulatory mechanisms, which can then be used to assess the functional outcome of genetically regulated gene expression (GReX) in a broader setting through the use of phenome-wide association studies (pheWASs) in large and diverse clinical biobank populations with electronic health record phenotypes.

METHODS

Here, we applied TI using S-PrediXcan to translate the most recent PGC-ED AN GWAS findings into AN-GReX. For significant genes, we imputed AN-GReX in the Mount Sinai BioMe™ Biobank and performed pheWASs on over 2000 outcomes to test the clinical consequences of aberrant expression of these genes. We performed a secondary analysis to assess the impact of body mass index (BMI) and sex on AN-GReX clinical associations.

RESULTS

Our S-PrediXcan analysis identified 53 genes associated with AN, including what is, to our knowledge, the first-genetic association of AN with the major histocompatibility complex. AN-GReX was associated with autoimmune, metabolic, and gastrointestinal diagnoses in our biobank cohort, as well as measures of cholesterol, medications, substance use, and pain. Additionally, our analyses showed moderation of AN-GReX associations with measures of cholesterol and substance use by BMI, and moderation of AN-GReX associations with celiac disease by sex.

CONCLUSIONS

Our BMI-stratified results provide potential avenues of functional mechanism for AN-genes to investigate further.

Circadian dysregulation and Alzheimer’s disease: A comprehensive review

Alzheimer’s disease (AD), the foremost variant of dementia, has been associated with a menagerie of risk factors, many of which are considered to be modifiable. Among these modifiable risk factors is circadian rhythm, the chronobiological system that regulates sleep‐wake cycles, food consumption timing, hydration timing, and immune responses amongst many other necessary physiological processes. Circadian rhythm at the level of the suprachiasmatic nucleus (SCN), is tightly regulated in the human body by a host of biomolecular substances, principally the hormones melatonin, cortisol, and serotonin. In addition, photic information projected along afferent pathways to the SCN and peripheral oscillators regulates the synthesis of these hormones and mediates the manner in which they act on the SCN and its substructures. Dysregulation of this cycle, whether induced by environmental changes involving irregular exposure to light, or through endogenous pathology, will have a negative impact on immune system optimization and will heighten the deposition of Aβ and the hyperphosphorylation of the tau protein. Given these correlations, it appears that there is a physiologic association between circadian rhythm dysregulation and AD. This review will explore the physiology of circadian dysregulation in the AD brain, and will propose a basic model for its role in AD‐typical pathology, derived from the literature compiled and referenced throughout.

Machine Learning Models for Predicting Breast Cancer Risk in Women Exposed to Blue Light from Digital Screens

BACKGROUND

Nowadays, there is a growing global concern over rapidly increasing screen time (smartphones, tablets, and computers). An accumulating body of evidence indicates that prolonged exposure to short-wavelength visible light (blue component) emitted from digital screens may cause cancer. The application of machine learning (ML) methods has significantly improved the accuracy of predictions in fields such as cancer susceptibility, recurrence, and survival.

OBJECTIVE

To develop an ML model for predicting the risk of breast cancer in women via several parameters related to exposure to ionizing and non-ionizing radiation.

MATERIAL AND METHODS

In this analytical study, three ML models Random Forest (RF), Support Vector Machine (SVM), and Multi-Layer Perceptron Neural Network (MLPNN) were used to analyze data collected from 603 cases, including 309 breast cancer cases and 294 gender and age-matched controls. Standard face-to-face interviews were performed using a standard questionnaire for data collection.

RESULTS

The examined models RF, SVM, and MLPNN performed well for correctly classifying cases with breast cancer and the healthy ones (mean sensitivity> 97.2%, mean specificity >96.4%, and average accuracy >97.1%).

CONCLUSION

Machine learning models can be used to effectively predict the risk of breast cancer via the history of exposure to ionizing and non-ionizing radiation (including blue light and screen time issues) parameters. The performance of the developed methods is encouraging; nevertheless, further investigation is required to confirm that machine learning techniques can diagnose breast cancer with relatively high accuracies automatically.

The nosological status of unipolar mania and hypomania within UK Biobank according to objective and subjective measures of diurnal rest and activity

BACKGROUND

There is uncertainty whether unipolar mania is a discrete sub-type of bipolar disorder. Disrupted rest/activity rhythms are a key feature of bipolar disorder (BD) but have not been well characterised in unipolar mania/hypomania (UM). We compared subjective and objective rest/activity patterns, demographic and mental health outcomes across BD, UM and control groups.

METHODS

UK residents aged 37-73 years were recruited into UK Biobank from 2006 to 2010. BD, UM and control groups were identified via a mental health questionnaire. Demographic, mental health and subjective sleep outcomes were self-reported. Accelerometery data were available for a subset of participants, and objective measures of sleep and activity were derived.

RESULTS

A greater proportion of males met UM criteria, and more females were in the BD group. Both BD and UM groups had poor mental health outcomes vs. controls. Objectively measured activity differed between all three groups: UM had highest levels of activity and BD lowest. The UM group had shorter sleep duration compared to controls. Subjective rest/activity measures showed that both mood disorder groups (compared to controls) had later chronotype preference, more disturbed sleep and increased difficulty getting up in the morning. However, the UM group were more likely to report an early chronotype compared to BD and control groups.

CONCLUSIONS

BD and UM share features in common, but key differences support the proposition that UM may be a distinct and more clinically homogenous disorder. UM was characterised by a higher proportion of males, early chronotype, increased activity and shorter sleep duration.

Dim light melatonin patterns in unaffected offspring of parents with bipolar disorder: A case-control high-risk study

BACKGROUND

Circadian dysregulation has long been thought to be a key component in the pathophysiology of bipolar disorder (BD). However, it remains unclear whether this dysregulation constitutes a risk factor, manifestation, or consequence of BD. This study aimed to compare dim light melatonin secretion patterns between unaffected offspring of parents with BD (OBD) and offspring of control parents (OCP).

METHODS

This case-control study included unaffected OBD (mean age 14.0 years; male 50.0 %) and age- and sex-matched OCP (mean age 13.0 years; male: 43.5 %). Seventeen saliva samples were collected in dim light conditions. Dim light melatonin onset (DLMO), phase angles, and area under the curve (AUC) were calculated.

RESULTS

185 saliva samples from 12 OBD (n = 12) and 741 from OCP (n = 46) were collected. Unaffected OBD had a significant lower nocturnal melatonin level (14.8 ± 4.6 vs. 20.3 ± 11.7 pg/mL) and a smaller melatonin AUC within two hours after DLMO (35.5 ± 11.3 vs. 44.6 ± 18.1 pg/mL) but a significant larger phase angle between DLMO and sleep onset (2.2 ± 1.0 vs. 1.4 ± 1.2 h) than OCP. There was no significant between-group difference in DLMO. The graphic illustrations showed a considerably flattened melatonin secretion in unaffected OBD.

LIMITATIONS

The main limitations include lack of 24-h dim melatonin secretion measurement, large age range of participants, and small sample size.

CONCLUSIONS

These findings suggest that unaffected OBD already presented with circadian rhythm dysregulations. Future investigations are needed to clarify the role of abnormal melatonin secretion in the onset of BD.

Two-Dimensional Convolutional Neural Network for Depression Episodes Detection in Real Time Using Motor Activity Time Series of Depresjon Dataset

Depression is a common illness worldwide, affecting an estimated 3.8% of the population, including 5% of all adults, in particular, 5.7% of adults over 60 years of age. Unfortunately, at present, the ways to evaluate different mental disorders, like the Montgomery–Åsberg depression rating scale (MADRS) and observations, need a great effort, on part of specialists due to the lack of availability of patients to obtain the necessary information to know their conditions and to detect illness such as depression in an objective way. Based on data analysis and artificial intelligence techniques, like Convolutional Neural Network (CNN), it is possible to classify a person, from the mental status examination, into two classes. Moreover, it is beneficial to observe how the data of these two classes are similar in different time intervals. In this study, a motor activity database was used, from which the readings of 55 subjects of study (32 healthy and 23 with some degree of depression) were recorded with a small wrist-worn accelerometer to detect the peak amplitude of movement acceleration and generate a transient voltage signal proportional to the rate of acceleration. Motor activity data were selected per patient in time-lapses of one day for seven days (one week) in one-minute intervals. The data were pre-processed to be given to a two-dimensional convolutional network (2D-CNN), where each record of motor activity per minute was represented as a pixel of an image. The proposed model is capable of detecting depression in real-time (if this is implemented in a mobile device such as a smartwatch) with low computational cost and accuracy of 76.72% In summary, the model shows promising abilities to detect possible cases of depression, providing a helpful resource to identify the condition and be able to take the appropriate follow-up for the patient.

Mathematical Model of Interaction of Therapist and Patients with Bipolar Disorder: A Systematic Literature Review

Mood swings in patients with bipolar disorder (BD) are difficult to control and can lead to self-harm and suicide. The interaction between the therapist and BD will determine the success of therapy. The interaction model between the therapist and BD begins by reviewing the models that were previously developed using the Systematic Literature Review and Bibliometric methods. The limit of articles used was sourced from the Science Direct, Google Scholar, and Dimensions databases from 2009 to 2022. The results obtained were 67 articles out of a total of 382 articles, which were then re-selected. The results of the selection of the last articles reviewed were 52 articles. Using VOSviewer version 1.6.16, a visualization of the relationship between the quotes “model”, “therapy”, “emotions”, and “bipolar disorder” can be seen. This study also discusses the types of therapy that can be used by BD, as well as treatment innovations and the mathematical model of the therapy itself. The results of this study are expected to help further researchers to develop an interaction model between therapists and BD to improve the quality of life of BD.

Insulin signaling as a therapeutic mechanism of lithium in bipolar disorder

In this paper, we propose that lithium may exert its therapeutic effect in bipolar disorder by acting on insulin signaling pathways. Specifically, we assess the importance of the phosphatidylinositol 3-kinase/Protein Kinase B (PI3K/Akt) insulin signaling pathway and we assess how the action of lithium on both glycogen synthase kinase-3 (GSK3) and the phosphatidylinositol cycle may lead to mood stabilization mediated by PI3K/Akt insulin signaling. We also highlight evidence that several other actions of lithium (including effects on Akt, Protein kinase C (PKC), and sodium myo-inositol transporters) are putative mediators of insulin signaling. This novel mode of action of lithium is consistent with an emerging consensus that energy dysregulation represents a core deficit in bipolar disorder. It may also provide context for the significant co-morbidity between bipolar disorder, type 2 diabetes, and other forms of metabolic illness characterized by impaired glucose metabolism. It is suggested that developments in assessing neuronal insulin signaling using extracellular vesicles would allow for this hypothesis to be tested in bipolar disorder patients.

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

OBJECTIVE

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]).

METHOD

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).

RESULTS

The 30 studies 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.

CONCLUSION

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.

Hypnotic and Melatonin/Melatonin-Receptor Agonist Treatment in Bipolar Disorder: A Systematic Review and Meta-Analysis

BACKGROUND

Bipolar disorder (BD) is a chronic relapsing-remitting psychiatric disorder. Sleep and circadian rhythm disturbances persist during acute mood episodes of the disorder and during euthymia. However, the treatment potential of hypnotic agents that might be used to manage sleep disturbance in BD is not well understood. Similarly, melatonin and medications with a melatonin-receptor agonist mechanism of action may have chronotherapeutic potential for treating people with the disorder, but the impact of these substances on sleep and circadian rhythms and core symptoms in BD is unclear.

OBJECTIVE

Our aim was to conduct a systematic review and meta-analysis evaluating the current evidence for hypnotic and melatonin/melatonin-receptor agonist pharmacotherapy for symptoms of sleep disturbance, mania, and depression in patients with BD.

METHODS

AMED, Embase, MEDLINE and PsychINFO databases were searched for studies published in English from the date of inception to 31 October 2021. Studies included in this review were randomised controlled trials (RCTs) and non-controlled/non-randomised studies for BD that examined hypnotic medications selected based on a common pattern of usage for treating insomnia (i.e. chloral, clomethiazole, diphenhydramine, doxepin, doxylamine, promethazine, suvorexant, zaleplon, zolpidem, zopiclone, and eszopiclone) and melatonin and the melatonin-receptor agonist drugs ramelteon and agomelatine. Risk of bias was assessed using the RoB2 and AXIS tools. Pooled effect sizes for RCT outcomes were estimated using random-effects models.

RESULTS

A total of eleven studies (six RCTs and five experimental feasibility studies) involving 1279 participants were included. Each study examined melatonin or melatonin-receptor agonists. No studies of hypnotics were found that fulfilled the review inclusion criteria. Pilot feasibility studies suggested beneficial treatment effects for symptoms of sleep disturbance, depression, and mania. However, the pooled effect of the two available RCT studies assessing sleep quality via Pittsburgh Sleep Quality Index scores was not statistically significant (g = - 0.04 [95% CI - 0.81 to 0.73]) and neither was the pooled effect for depressive symptoms (four studies; g = - 0.10 [95% CI - 0.27 to 0.08]). Some RCT evidence suggests ramelteon might prevent relapse into depression in BD. The largest efficacy signal detected was for manic symptoms (four studies; g = - 0.44 [95% CI - 1.03 to 0.14]) but there was substantial heterogeneity between studies and patient characteristics. In the two RCTs assessing manic symptoms during acute mania, adjunctive melatonin demonstrated superior treatment effects versus placebo.

CONCLUSIONS

There is a paucity of studies examining pharmacological interventions for sleep and circadian rhythm disturbance in BD. Few studies assessed sleep-related symptoms, and none quantitatively examined endogenous melatonin patterns or other circadian rhythms. Melatonin may be a promising candidate for the adjunctive treatment of bipolar mania. However, dose-finding studies and studies with larger sample sizes are needed to confirm its efficacy. We recommend parallel monitoring of sleep and circadian rhythms in future trials. Chronobiology-informed trial designs are needed to improve the quality of future studies.

PROTOCOL REGISTRATION

PROSPERO (CRD42020167528).

Contribution of Age, Brain Region, Mood Disorder Pathology, and Interindividual Factors on the Methylome of Human Microglia

BACKGROUND

Transcriptome studies have revealed age-, disease-, and region-associated microglial phenotypes reflecting changes in microglial function during development, aging, central nervous system homeostasis, and pathology. The molecular mechanisms that contribute to these transcriptomic changes are largely unknown. The aim of this study was to characterize the DNA methylation landscape of human microglia and the factors that contribute to variations in the microglia methylome. We hypothesized that both age and brain region would have a large impact on DNA methylation in microglia.

METHODS

Microglia from postmortem brain tissue of four different brain regions of 22 donors, encompassing 1 patient with schizophrenia, 13 patients with mood disorder pathology, and 8 control subjects, were isolated and assayed using a genome-wide methylation array.

RESULTS

We found that human microglial cells have a methylation profile distinct from bulk brain tissue and neurons, and age explained a considerable part of the variation. Additionally, we showed that interindividual factors had a much larger effect on the methylation landscape of microglia than brain region, which was also seen at the transcriptome level. In our exploratory analysis, we found various differentially methylated regions that were related to disease status (mood disorder vs. control). This included differentially methylated regions that are linked to gene expression in microglia, as well as to myeloid cell function or neuropsychiatric disorders.

CONCLUSIONS

Although based on relatively small samples, these findings suggest that the methylation profile of microglia is responsive to interindividual variations and thereby plays an important role in the heterogeneity of microglia observed at the transcriptome level.

A systematic review and meta-analysis of sleep and circadian rhythms disturbances in individuals at high-risk of developing or with early onset of bipolar disorders

Sleep and circadian rhythms disturbances (SCRD) in young people at high risk or with early onset of bipolar disorders (BD) are poorly understood. We systematically searched for studies of self, observer or objective estimates of SCRD in asymptomatic or symptomatic offspring of parents with BD (OSBD), individuals with presentations meeting recognized BD-at-risk criteria (BAR) and youth with recent onset of full-threshold BD (FT-BD). Of 76 studies eligible for systematic review, 35 (46%) were included in random effects meta-analyses. Pooled analyses of self-ratings related to circadian rhythms demonstrated greater preference for eveningness and more dysregulation of social rhythms in BAR and FT-BD groups; analyses of actigraphy provided some support for these findings. Meta-analysis of prospective studies showed that pre-existing SCRD were associated with a 40% increased risk of onset of BD, but heterogeneity in assessments was a significant concern. Overall, we identified longer total sleep time (Hedges g: 0.34; 95% confidence intervals:.1,.57), especially in OSBD and FT-BD and meta-regression analysis indicated the effect sizes was moderated by the proportion of any sample manifesting psychopathology or receiving psychotropic medications. This evolving field of research would benefit from greater attention to circadian rhythm as well as sleep quality measures.

Motor activity patterns can distinguish between interepisode bipolar disorder patients and healthy controls

BACKGROUND

Bipolar disorder (BD) is linked to circadian rhythm disruptions resulting in aberrant motor activity patterns. We aimed to explore whether motor activity alone, as assessed by longitudinal actigraphy, can be used to classify accurately BD patients and healthy controls (HCs) into their respective groups.

METHODS

Ninety-day actigraphy records from 25 interepisode BD patients (ie, Montgomery-Asberg Depression Rating Scale (MADRS) and Young Mania Rating Scale (YMRS) < 15) and 25 sex- and age-matched HCs were used in order to identify latent actigraphic biomarkers capable of discriminating between BD patients and HCs. Mean values and time variations of a set of standard actigraphy features were analyzed and further validated using the random forest classifier.

RESULTS

Using all actigraphy features, this method correctly assigned 88% (sensitivity = 85%, specificity = 91%) of BD patients and HCs to their respective group. The classification success may be confounded by differences in employment between BD patients and HCs. When motor activity features resistant to the employment status were used (the strongest feature being time variation of intradaily variability, Cohen's d = 1.33), 79% of the subjects (sensitivity = 76%, specificity = 81%) were correctly classified.

CONCLUSION

A machine-learning actigraphy-based model was capable of distinguishing between interepisode BD patients and HCs solely on the basis of motor activity. The classification remained valid even when features influenced by employment status were omitted. The findings suggest that temporal variability of actigraphic parameters may provide discriminative power for differentiating between BD patients and HCs while being less affected by employment status.

Complexity and variability analyses of motor activity distinguish mood states in bipolar disorder

Changes in motor activity are core symptoms of mood episodes in bipolar disorder. The manic state is characterized by increased variance, augmented complexity and irregular circadian rhythmicity when compared to healthy controls. No previous studies have compared mania to euthymia intra-individually in motor activity. The aim of this study was to characterize differences in motor activity when comparing manic patients to their euthymic selves. Motor activity was collected from 16 bipolar inpatients in mania and remission. 24-h recordings and 2-h time series in the morning and evening were analyzed for mean activity, variability and complexity. Lastly, the recordings were analyzed with the similarity graph algorithm and graph theory concepts such as edges, bridges, connected components and cliques. The similarity graph measures fluctuations in activity reasonably comparable to both variability and complexity measures. However, direct comparisons are difficult as most graph measures reveal variability in constricted time windows. Compared to sample entropy, the similarity graph is less sensitive to outliers. The little-understood estimate Bridges is possibly revealing underlying dynamics in the time series. When compared to euthymia, over the duration of approximately one circadian cycle, the manic state presented reduced variability, displayed by decreased standard deviation (p = 0.013) and augmented complexity shown by increased sample entropy (p = 0.025). During mania there were also fewer edges (p = 0.039) and more bridges (p = 0.026). Similar significant changes in variability and complexity were observed in the 2-h morning and evening sequences, mainly in the estimates of the similarity graph algorithm. Finally, augmented complexity was present in morning samples during mania, displayed by increased sample entropy (p = 0.015). In conclusion, the motor activity of mania is characterized by altered complexity and variability when compared within-subject to euthymia.

Circadian rhythm disruptions: A possible link of bipolar disorder and endocrine comorbidities

Epidemiological studies have demonstrated an association between bipolar disorder (BP) and endocrine diseases. Further, circadian rhythm disruptions may be a potential common pathophysiological mechanism of both disorders. This review provides a brief overview of the molecular mechanisms of circadian rhythms, as well as roles circadian rhythms play in BP and common endocrine comorbidities such as diabetes and thyroid disease. Treatments targeting the circadian system, both pharmacological and non-pharmacological, are also discussed. The hope is to elicit new interest to the importance of circadian system in BP and offer new entry points and impetus to the development of medicine.

Impulsivity and sleep and circadian rhythm disturbance predict next-day mood symptoms in a sample at high risk for or with recent-onset bipolar spectrum disorder: An ecological momentary assessment study

BACKGROUND

Impulsivity and sleep and circadian rhythm disturbance are core features of bipolar spectrum disorders (BSDs) that are antecedents to onset and persist even between mood episodes; their pervasive presence in BSD suggests that they may be particularly relevant to understanding BSD onset and course. Considerable research demonstrates bidirectional associations between impulsivity and sleep disturbance in healthy individuals; thus, it is important to examine how these features interact to impact BSD symptomatology.

METHODS

Young adults (N = 107, 55% female, M age = 21.82 years) at high risk for developing BSD (based on high self-reported reward sensitivity) or with recent-onset BSD participated in ecological momentary assessment (EMA) to examine relationships between impulsivity, sleep and circadian rhythm alterations, and mood symptoms in everyday life. Impulsivity was measured via self-report/behavioral task, sleep was measured via actigraphy, circadian rhythms were measured via dim light melatonin onset (DLMO) time, and mood symptoms were measured three times daily via self-report.

RESULTS

Multi-level modeling revealed that less total sleep time predicted increased next-day mood symptoms. Moreover, DLMO, total sleep time, and sleep onset latency moderated the relationship between impulsivity and EMA-assessed mood symptoms. Fewer minutes of sleep and later DLMO strengthened the positive relationship between impulsivity and mood symptoms.

LIMITATIONS

Mood symptoms in our sample were mild; future studies should replicate findings in populations with more severe mood symptoms.

CONCLUSIONS

This multi-method assessment of dynamic relationships revealed novel associations between impulsivity, sleep and circadian rhythm disturbance, and symptoms within individuals at high-risk for or with recent-onset BSD.

Fullerene-Filtered Light Spectrum and Fullerenes Modulate Emotional and Pain Processing in Mice

The most symmetric molecule, Buckminster fullerene C60, due to its unique properties, has been intensively studied for various medical and technological advances. Minimally invasive and minimally toxic treatments hold great promise for future applications. With this in mind, this research exploited the physical properties of fullerene molecules for potential therapeutic effects. Pristine fullerenes have peak absorbance in the 380–500 nm range, making them an attractive violet-blue light filter. Since spectral quality of light can affect behavior, this research used resting state functional magnetic resonance imaging (rs fMRI) and behavioral testing to directly evaluate the effects of fullerene-filtered light on brain processing and behavior in mice. The same method was used to study if hydroxyl fullerene water complexes (3HFWC), with or without fullerene-filtered light, modulated brain processing. A month-long, daily exposure to fullerene-filtered light led to decreased activation of the brain area involved in emotional processing (amygdala). Water supplemented with 3HFWC resulted in an activation of brain areas involved in pain modulation and processing (periaqueductal gray), and decreased latency to first reaction when tested with a hot plate. The combination of fullerene-filtered light with 3HFWC in drinking water led to restored sensitivity to a hot plate and activation of brain areas involved in cognitive functions (prelimbic, anterior cingulate and retrosplenial cortex). These results uncovered the potential of fullerene-filtered light to impact emotional processing and modulate pain perception, indicating its further use in stress and pain management.

Adrift in time: the subjective experience of circadian challenge during COVID-19 amongst people with mood disorders

Social distancing/lockdown policies during the coronavirus (COVID-19) pandemic may alter social rhythms of people through imposition of restrictions on normal daily activities. This may in turn challenge circadian function, particularly in people with mood disorders. Although objective data describing the relationship between circadian disturbances and mood disorders exist, data regarding the subjective experience of circadian challenge is sparse, and its association with mood symptoms is unclear. The present qualitative study was one component of a mixed-methods multi-national project, which took advantage of widespread disruption to daily routines due to Government COVID-related lockdowns during 2020. The Behavior Emotion and Timing during COVID-19 (BEATCOVID) survey study included three open questions generating qualitative data on participants' subjective experience of social disruption due to social distancing/lockdown policies, two of which asked about the barriers and opportunities for stabilizing routines. Responses were coded and analyzed using Thematic Analysis. A total of N = 997 participants responded to at least one of the free-text questions. Four themes were identified: 1) loss of daily timed activities, 2) role of social interaction, 3) altered time perception and 4) disruption to motivation and associated psychological effects. Themes were organized into a provisional heuristic map, generating hypotheses for future research centered on the new concept of 'psychological drift.'

For whom the circadian clock ticks? Investigation of PERIOD and CLOCK gene variants in bipolar disorder

Clock genes play significant roles in the regulation of circadian rhythms, which are thought to be involved in the pathophysiology of neurodegenerative and psychiatric diseases. We aimed to investigate the association of five gene polymorphisms (PER3 VNTR (rs57875989), PER2 rs2304672, CLOCK rs1801260, CLOCK rs10462028, CLOCK rs11932595) with PCR-based methods as potential risk factors in bipolar disorder (BD). We used a multiple testing methodology in BD patients (n = 121) and healthy control individuals (n = 121) of Turkish descent to analyze the effects of these gene variants both as risk factors for the disorder and for the evaluation of these variants in the patient group with multiple subscales. We evaluated the circadian rhythm disturbances and seasonal variations in mood and behavior in BD patients using the Biological Rhythms Interview of Assessment in Neuropsychiatry (BRIAN) and Seasonal Pattern Assessment Questionnaire (SPAQ) to enlighten the possible links between these scores and the studied circadian gene variants. The results of our study revealed significant associations: PER3 VNTR (rs57875989) 5/5 repeat genotype displayed a protective effect against BD when compared with 4/4 repeat genotype. Moreover, patients with PER3 VNTR 5/5 repeat genotype displayed a higher ratio of hypomania. PER2 rs2304672 G allele frequency increased the risk for BD. There was no association in terms of genotype/allele frequency comparisons between patients and controls for CLOCK gene variants. However, significant associations were found in patients in terms of clinical and behavioral patterns such as mean age at disease onset and BRIAN total scores enabling some risk stratifications for patients. Our results indicate the significance of circadian gene variants in BD, which need to be confirmed in different studies with larger samples. Thus, the possible endophenotypes of BD can be enlightened and advanced chronotherapeutics approaches can be manipulated in the future for clinical benefit.

Evaluation of salivary melatonin concentrations as a circadian phase maker of morning awakening and their association with depressive mood in postpartum mothers

The disruption of circadian rhythm is closely related to mood disorders in night-shift workers, and a similar situation may occur in postpartum mothers. However, the situations of postpartum mothers remain largely unknown because of a lack of an appropriate circadian phase marker in the clinical setting. This study aimed to evaluate whether salivary melatonin concentration at awakening can identify misalignment between awakening time and the biological clock system, which might be associated with depressive mood in some mothers. Ninety-eight healthy mothers who were currently the primary parental caregivers were recruited at 1 month after delivery. All mothers completed the Edinburgh Postnatal Depression Scale (EPDS) and wore an actigraphy watch at home for 3 consecutive days to determine nocturnal sleep variables. While wearing the actigraphy watch, they also collected saliva samples during the awakening period for a melatonin concentration assay. The results indicated that daily salivary melatonin levels after 30 min of awakening (hereafter, melatonin levels) were positively correlated with sleep onset time and negatively correlated with sleep offset time and total sleep time. Six mothers with an EPDS score of ≥9 (the cutoff value for Japanese women at high risk for postnatal depression) had an average melatonin level of either <4 pg/ml or >16 pg/ml for 3 d. Mothers with melatonin levels <4 pg/ml or >16 pg/ml tended to have elevated EPDS scores (4.93 ± 2.95 or 4.20 ± 2.93, mean ± standard deviation) compared with mothers with melatonin levels between 4 and 16 pg/ml (3.00 ± 2.12, p = .053). Mothers whose melatonin levels were >16 pg/ml had relatively later sleep onset time and shorter nocturnal sleep duration. Backward stepwise regression demonstrated that such high/low levels of melatonin were a significant predictor of EPDS scores. These results suggest that elevated melatonin levels after 30 min of awakening could identify a phase-delayed circadian rhythm in postpartum mothers, and that relatively higher or lower melatonin levels could be associated with increased depressive mood.

Efficacy of early warning signals and spectral periodicity for predicting transitions in bipolar patients: An actigraphy study

Early-warning signals (EWS) have been successfully employed to predict transitions in research fields such as biology, ecology, and psychiatry. The predictive properties of EWS might aid in foreseeing transitions in mood episodes (i.e. recurrent episodes of mania and depression) in bipolar disorder (BD) patients. We analyzed actigraphy data assessed during normal daily life to investigate the feasibility of using EWS to predict mood transitions in bipolar patients. Actigraphy data of 15 patients diagnosed with BD Type I collected continuously for 180 days were used. Our final sample included eight patients that experienced a mood episode, three manic episodes and five depressed episodes. Actigraphy data derived generic EWS (variance and kurtosis) and context-driven EWS (autocorrelation at lag-720) were used to determine if these were associated to upcoming bipolar episodes. Spectral analysis was used to predict changes in the periodicity of the sleep/wake cycle. The study procedures were pre-registered. Results indicated that in seven out of eight patients at least one of the EWS did show a significant change-up till four weeks before episode onset. For the generic EWS the direction of change was always in the expected direction, whereas for the context-driven EWS the observed effect was often in the direction opposite of what was expected. The actigraphy data derived EWS and spectral analysis showed promise for the prediction of upcoming transitions in mood episodes in bipolar patients. Further studies into false positive rates are suggested to improve effectiveness for EWS to identify upcoming bipolar episode onsets.

Reciprocal Relationship Between Calcium Signaling and Circadian Clocks: Implications for Calcium Homeostasis, Clock Function, and Therapeutics

In animals, circadian clocks impose a daily rhythmicity to many behaviors and physiological processes. At the molecular level, circadian rhythms are driven by intracellular transcriptional/translational feedback loops (TTFL). Interestingly, emerging evidence indicates that they can also be modulated by multiple signaling pathways. Among these, Ca²⁺ signaling plays a key role in regulating the molecular rhythms of clock genes and of the resulting circadian behavior. In addition, the application of in vivo imaging approaches has revealed that Ca²⁺ is fundamental to the synchronization of the neuronal networks that make up circadian pacemakers. Conversely, the activity of circadian clocks may influence Ca²⁺ signaling. For instance, several genes that encode Ca²⁺ channels and Ca²⁺-binding proteins display a rhythmic expression, and a disruption of this cycling affects circadian function, underscoring their reciprocal relationship. Here, we review recent advances in our understanding of how Ca²⁺ signaling both modulates and is modulated by circadian clocks, focusing on the regulatory mechanisms described in Drosophila and mice. In particular, we examine findings related to the oscillations in intracellular Ca²⁺ levels in circadian pacemakers and how they are regulated by canonical clock genes, neuropeptides, and light stimuli. In addition, we discuss how Ca²⁺ rhythms and their associated signaling pathways modulate clock gene expression at the transcriptional and post-translational levels. We also review evidence based on transcriptomic analyzes that suggests that mammalian Ca²⁺ channels and transporters (e.g., ryanodine receptor, ip3r, serca, L- and T-type Ca²⁺ channels) as well as Ca²⁺-binding proteins (e.g., camk, cask, and calcineurin) show rhythmic expression in the central brain clock and in peripheral tissues such as the heart and skeletal muscles. Finally, we discuss how the discovery that Ca²⁺ signaling is regulated by the circadian clock could influence the efficacy of pharmacotherapy and the outcomes of clinical interventions.

The Emerging Circadian Phenotype of Borderline Personality Disorder: Mechanisms, Opportunities and Future Directions

PURPOSE OF REVIEW

We review the recent evidence suggesting that circadian rhythm disturbance is a common unaddressed feature of borderline personality disorder (BPD); amelioration of which may confer substantial clinical benefit. We assess chronobiological BPD studies from a mechanistic and translational perspective and highlight opportunities for the future development of this hypothesis.

RECENT FINDINGS

The emerging circadian phenotype of BPD is characterised by a preponderance of comorbid circadian rhythm sleep-wake disorders, phase delayed and misaligned rest-activity patterns and attenuated amplitudes of usually well-characterised circadian rhythms. Such disturbances may exacerbate symptom severity, and specific maladaptive personality dimensions may produce a liability towards extremes in chronotype. Pilot studies suggest intervention may be beneficial, but development is limited. Endogenous and exogenous circadian rhythm disturbances appear to be common in BPD. The interface between psychiatry and chronobiology has led previously to novel efficacious strategies for the treatment of psychiatric disorders. We believe that better characterisation of the circadian phenotype in BPD will lead to a directed biological target for treatment in a condition where there is a regrettable paucity of accessible therapies.

Circadian depression: A mood disorder phenotype

Major mood syndromes are among the most common and disabling mental disorders. However, a lack of clear delineation of their underlying pathophysiological mechanisms is a major barrier to prevention and optimised treatments. Dysfunction of the 24-h circadian system is a candidate mechanism that has genetic, behavioural, and neurobiological links to mood syndromes. Here, we outline evidence for a new clinical phenotype, which we have called 'circadian depression'. We propose that key clinical characteristics of circadian depression include disrupted 24-h sleep-wake cycles, reduced motor activity, low subjective energy, and weight gain. The illness course includes early age-of-onset, phenomena suggestive of bipolarity (defined by bidirectional associations between objective motor and subjective energy/mood states), poor response to conventional antidepressant medications, and concurrent cardiometabolic and inflammatory disturbances. Identifying this phenotype could be clinically valuable, as circadian-targeted strategies show promise for reducing depressive symptoms and stabilising illness course. Further investigation of underlying circadian disturbances in mood syndromes is needed to evaluate the clinical utility of this phenotype and guide the optimal use of circadian-targeted interventions.

Mood symptoms and impairment due to substance use: A network perspective on comorbidity

BACKGROUND

Mood disorders and problematic substance use co-occur and confer reciprocal risk for each other. Few studies use analytic approaches appropriate for testing whether specific features of one disorder confer risk for the other.

METHODS

445 participants (59.8% female, Mean age = 20.3 years) completed measures of depression and hypo/mania symptoms and substance use-related impairment; 330 had complete data at follow-up. Of these, 28% reported a history of depression, 4% of bipolar spectrum disorder, 11% of substance use disorder, and 55% reported substance-related impairment. Symptoms and domains of substance-related impairment were modeled in cross-sectional and cross-lagged panel network models.

RESULTS

Impulsive and interpersonal impairment were most highly comorbid with mood symptoms. Suicidal ideation, sadness, decreased need for sleep, and guilt were the symptoms most highly comorbid with impairment. Interpersonal impairment due to substance use was the strongest cross-construct predictor of mood symptoms and suicidal ideation was most predictive of impairment. Social, intrapersonal, and physical impairment due to substance use were most predicted by previous mood symptoms and decreased need for sleep, guilt, and euphoria were most strongly predicted by past impairment.

LIMITATIONS

Measures do not assess all mood symptoms, participants with low reward sensitivity were excluded, only self-report measures were used, and some variables were single-items.

CONCLUSIONS

Components of these syndromes that confer cross-construct risk might not be the same components that are predicted by the other construct. The bidirectional relationship between mood symptoms and problematic substance use might be better conceptualized at the element, rather than diagnostic, level.

Light therapy for mood disorders

In this chapter, light therapy for mood disorders is discussed, including mood disorders during and after pregnancy. In the introduction, we discuss the symptomatology, etiology, and treatment of a specific type of mood disorder, seasonal affective disorder, since it kick-started the first clinical trials with light therapy. Second, we elaborate on the pathophysiology of mood disorders, in particular in the peripartum period. Next, we present an overview of the proposed working mechanisms of light therapy, followed by a discussion of the clinical trials that have followed after the initial research in seasonal affective disorder. Finally, we also focus on the limitations of these trials, such as considerable heterogeneity among studies and many methodological shortcomings. This is complemented by a number of suggestions for future research. Further studies are needed, which stems from the fact that the results have not always been consistent. Despite this, light therapy may be a promising treatment option for various types of mood disorders, since it shows a significant reduction in symptoms in many patients with few adverse effects.

Functional and Mood Outcomes in Bipolar Disorder Patients With and Without Substance Use Disorders Undergoing Psychotherapy

Objectives: Research suggests that patients with co-morbid bipolar disorder (BD) and substance use disorder (SUD) have a poorer illness course and clinical outcome. The evidence is limited as SUD patients are often excluded from BD studies. In particular, evidence regarding long term outcomes from studies using psychotherapies as an adjunctive treatment is limited. We therefore examined data from two studies of Interpersonal Social Rhythm Therapy (IPSRT) for BD to determine whether lifetime or current SUD affected outcomes. Methods: Data were analyzed from two previous clinical trials of IPSRT for BD patients. Change in scores on the Social Adjustment Scale (SAS) from 0 to 78 weeks and cumulative mood scores from 0 to 78 weeks, measured using the Life Interval Follow-Up Evaluation (LIFE), were analyzed. Results: Of 122 patients (non-SUD n = 67, lifetime SUD but no current n = 43, current SUD n = 12), 79 received IPSRT and 43 received a comparison therapy-specialist supportive care-over 18 months. Lifetime SUD had a significant negative effect on change in SAS score but not LIFE score. There was no effect of current SUD on either change in score. Secondary analysis showed no correlation between symptom count and change in SAS total score or LIFE score. Conclusion: Current SUD has no impact on mood or functional outcomes, however, current SUD numbers were small, limiting conclusions. Lifetime SUD appears to be associated with impaired functional outcomes from psychotherapy. There is limited research on co-morbid BD and SUD patients undergoing psychotherapy.

Inactograms and objective sleep measures as means to capture subjective sleep problems in patients with a bipolar disorder

BACKGROUND

Sleep problems are common in bipolar disorders (BDs). To objectively characterize these problems in BDs, further methodological development is needed to capture subjective insomnia.

AIM

To test psychometric properties of the Athens Insomnia Scale (AIS), and associations with actigraphy-derived measures, applying modifications in actigraphy data processing to capture features of perturbed sleep in patients with a BD.

METHODS

Seventy-four patients completed the AIS and the Quick Inventory of Depressive Symptomatology, self-report (QIDS-SR-16). Locomotor activity was continuously recorded by wrist actigraphy for ≥10 consecutive days. We computed the sleep onset/offset, the center of daily inactivity (CenDI), as a proxy for chronotype, and the degree of consolidation of daily inactivity (ConDI), as a proxy for sleep-wake rhythm strength.

RESULTS

AIS showed good psychometric properties (Cronbach's alpha = 0.84; test-retest correlation = 0.84, P<.001). Subjective sleep problems correlated moderately with a later sleep phase (CenDI with AIS rho = 0.34, P = .003), lower consolidation (ConDI with AIS rho = -0.22, P = .05; with QIDS-SR-16 rho = -0.27, P = .019), later timing of sleep offset (with AIS rho = 0.49, P = ≤.001, with QIDS-SR-16 rho = 0.36, P = .002), and longer total sleep (with AIS rho = 0.29, P = .012, with QIDS-SR-16 rho = 0.41, P = ≤.001). While AIS was psychometrically more solid, correlations with objective sleep were more consistent across time for QIDS-SR-16.

CONCLUSIONS

AIS and QIDS-SR-16 are suitable for clinical screening of sleep problems among patients with a BD. Subjective insomnia associated with objective measures. For clinical and research purposes, actigraphy and data visualization on inactograms are useful for accurate longitudinal characterization of sleep patterns.

Classification of Actigraphy Records from Bipolar Disorder Patients Using Slope Entropy: A Feasibility Study

Bipolar Disorder (BD) is an illness with high prevalence and a huge social and economic impact. It is recurrent, with a long-term evolution in most cases. Early treatment and continuous monitoring have proven to be very effective in mitigating the causes and consequences of BD. However, no tools are currently available for a massive and semi-automatic BD patient monitoring and control. Taking advantage of recent technological developments in the field of wearables, this paper studies the feasibility of a BD episodes classification analysis while using entropy measures, an approach successfully applied in a myriad of other physiological frameworks. This is a very difficult task, since actigraphy records are highly non-stationary and corrupted with artifacts (no activity). The method devised uses a preprocessing stage to extract epochs of activity, and then applies a quantification measure, Slope Entropy, recently proposed, which outperforms the most common entropy measures used in biomedical time series. The results confirm the feasibility of the approach proposed, since the three states that are involved in BD, depression, mania, and remission, can be significantly distinguished.

Applying machine learning in motor activity time series of depressed bipolar and unipolar patients compared to healthy controls

Current practice of assessing mood episodes in affective disorders largely depends on subjective observations combined with semi-structured clinical rating scales. Motor activity is an objective observation of the inner physiological state expressed in behavior patterns. Alterations of motor activity are essential features of bipolar and unipolar depression. The aim was to investigate if objective measures of motor activity can aid existing diagnostic practice, by applying machine-learning techniques to analyze activity patterns in depressed patients and healthy controls. Random Forrest, Deep Neural Network and Convolutional Neural Network algorithms were used to analyze 14 days of actigraph recorded motor activity from 23 depressed patients and 32 healthy controls. Statistical features analyzed in the dataset were mean activity, standard deviation of mean activity and proportion of zero activity. Various techniques to handle data imbalance were applied, and to ensure generalizability and avoid overfitting a Leave-One-User-Out validation strategy was utilized. All outcomes reports as measures of accuracy for binary tests. A Deep Neural Network combined with SMOTE class balancing technique performed a cut above the rest with a true positive rate of 0.82 (sensitivity) and a true negative rate of 0.84 (specificity). Accuracy was 0.84 and the Matthews Correlation Coefficient 0.65. Misclassifications appear related to data overlapping among the classes, so an appropriate future approach will be to compare mood states intra-individualistically. In summary, machine-learning techniques present promising abilities in discriminating between depressed patients and healthy controls in motor activity time series.

Sex and race influence objective and self-report sleep and circadian measures in emerging adults independently of risk for bipolar spectrum disorder

There is a need to better understand key factors that impact sleep and circadian function for young adults of differing races and sexes. Sex and race are common factors contributing to disparities in health outcomes; however, the influence of these variables on sleep and circadian patterns for young adults are not well known. Multiple objective and self-report facets of sleep and circadian function were assessed (melatonin onset, actigraphy, and sleep diaries) in an ecological momentary assessment study of 150 emerging adults (M_age = 21.8 years; 58.7% female; 56% White, 22.7% Black, 21.3% Other ethnicity) at high or low risk for bipolar spectrum disorder (BSD). Controlling for BSD risk status, sex and race were significant predictors of objective and self-reported sleep and circadian rhythm measures. Males self-reported better sleep efficiency and exhibited later dim light melatonin onset phase than females, whereas females exhibited more actigraphy-measured sleep periods. White participants exhibited more actigraphy-measured total sleep time (TST), better sleep efficiency, and fewer sleep periods, and more self-reported TST and better sleep efficiency than Black participants. Our findings enhance the literature by utilizing robust measurement of sleep and circadian parameters to extend previous findings to a young adult sample at high or low risk for BSD.

The associations between illness perceptions and social rhythm stability on mood symptoms among patients with bipolar disorder

BACKGROUND

The association between illness perceptions and the effectiveness of patients' illness-management strategies has been supported across a range of medical and psychiatric disorders. Few studies have examined these variables or their association in bipolar disorder (BD). This study examined the main and interactive associations between illness perceptions and one important illness management strategy - social rhythms stability on mood symptom severity in adults with BD.

METHODS

A cross-sectional study with 131 patients with BD in Taiwan was conducted using clinician- and patient-rated mood symptoms, self-reported illness perceptions, and a measure of daily and nightly social rhythms.

RESULTS

Illness perceptions were associated with mood symptom severity, but social rhythms were not. Unfavorable illness perceptions (e.g., beliefs of experiencing more BD symptoms, having stronger emotional responses to the illness) were associated with more severe mood symptoms. Favorable illness perceptions (e.g., beliefs of being able to understand and control the illness) were associated with less severe mood symptoms, with personal control as the strongest correlate of mood symptom severity. Finally, social rhythm stability moderated the relationship between unfavorable illness perceptions and clinician-rated manic symptoms.

LIMITATIONS

The cross-sectional design limits our ability to make causal conclusions. Also, the effects pertain to patients in remission and may not generalize to more severely ill or hospitalized bipolar patients.

CONCLUSIONS

This study indicates that in patients with BD, illness perceptions are associated with symptom severity. Interventions to enhance favorable IPs and reduce unfavorable IPs may improve mood outcomes, particularly when patients have adopted regular social rhythms.