Metabolic syndrome and actigraphy measures of sleep and circadian rhythms in bipolar disorders during remission

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.

Medical comorbidities in bipolar disorder (BIPCOM): clinical validation of risk factors and biomarkers to improve prevention and treatment. Study protocol

BACKGROUND

BIPCOM aims to (1) identify medical comorbidities in people with bipolar disorder (BD); (2) examine risk factors and clinical profiles of Medical Comorbidities (MC) in this clinical group, with a special focus on Metabolic Syndrome (MetS); (3) develop a Clinical Support Tool (CST) for the personalized management of BD and medical comorbidities.

METHODS

The BIPCOM project aims to investigate MC, specifically MetS, in individuals with BD using various approaches. Initially, prevalence rates, characteristics, genetic and non-genetic risk factors, and the natural progression of MetS among individuals with BD will be assessed by analysing Nordic registers, biobanks, and existing patient datasets from 11 European recruiting centres across 5 countries. Subsequently, a clinical study involving 400 participants from these sites will be conducted to examine the clinical profiles and incidence of specific MetS risk factors over 1 year. Baseline assessments, 1-year follow-ups, biomarker analyses, and physical activity measurements with wearable biosensors, and focus groups will be performed. Using this comprehensive data, a CST will be developed to enhance the prevention, early detection, and personalized treatment of MC in BD, by incorporating clinical, biological, sex and genetic information. This protocol will highlight the study's methodology.

DISCUSSION

BIPCOM's data collection will pave the way for tailored treatment and prevention approaches for individuals with BD. This approach has the potential to generate significant healthcare savings by preventing complications, hospitalizations, and emergency visits related to comorbidities and cardiovascular risks in BD. BIPCOM's data collection will enhance BD patient care through personalized strategies, resulting in improved quality of life and reduced costly interventions. The findings of the study will contribute to a better understanding of the relationship between medical comorbidities and BD, enabling accurate prediction and effective management of MetS and cardiovascular diseases.

TRIAL REGISTRATION

ISRCTN68010602 at https://www.isrctn.com/ISRCTN68010602 . Registration date: 18/04/2023.

Metabolic Syndrome in people treated with Antipsychotics (RISKMet): A multimethod study protocol investigating genetic, behavioural, and environmental risk factors

INTRODUCTION

The RISKMet project aims to: (1) identify risk factors for metabolic syndrome (MetS) by comparing patients with and without MetS; (2) characterise patients treated with second-generation antipsychotics (SGAs) about MetS diagnosis; (3) study behavioural patterns, including physical activity (PA) and dietary habits, in patients and healthy individuals using a prospective cohort design.

METHOD

The RISKMet project investigates MetS in individuals treated with SGAs, focusing on both adult and paediatric populations. The study utilizes a case-control design to examine potential risk factors for MetS, categorizing participants as MetS+ considered as "Cases" and MetS- considered as "Controls" matched by sex and age. The evaluation of factors such as MetS, lifestyle habits, and environmental influences is conducted at two time points, T0 and T3, after 3 months. Subsequently, the project aims to assess body parameters, including physical examinations, and blood, and stool sample collection, to evaluate metabolic markers and the impact of SGAs. The analysis includes pharmacological treatment data and genetic variability. Behavioural markers related to lifestyle, eating behaviour, PA, and mood are assessed at both T0 and T3 using interviews, accelerometers, and a mobile app. The study aims to improve mental and physical well-being in SGA-treated individuals, establish a biobank for MetS research, build an evidence base for physical health programs, and develop preventive strategies for SGA-related comorbidities.

CONCLUSIONS

This project innovates MetS monitoring in psychiatry by using intensive digital phenotyping, identifying biochemical markers, assessing familial risks, and including genetically similar healthy controls.

STUDY REGISTRATION NUMBER

ISRCTN18419418 at www.isrctn.com.

Chronotype and Cardiometabolic Parameters in Patients with Bipolar Disorder: Preliminary Findings

Cardiometabolic alterations are very common in bipolar disorder (BD). The aim of this study was to investigate the relationship between chronotype and cardiometabolic parameters in patients with a primary diagnosis of BD. This study is an observational clinical investigation including 170 subjects consecutively admitted to the Psychiatric Inpatient Unit of the IRCCS Ospedale Policlinico San Martino (Genoa, Italy), recruited over a period of 48 months. A psychometric tool assessing chronotype was administered and blood tests were performed. Furthermore, the atherogenic coefficient ((total cholesterol-HDL cholesterol)/HDL cholesterol), and Castelli risk index-I (total cholesterol/HDL cholesterol) and -II (LDL cholesterol/HDL cholesterol) were calculated. Patients with BD and an eveningness chronotype showed a higher body mass index, total and low-density lipotrotein cholesterol compared to patients with BD and an intermediate or morning chronotype. Furthermore, the Atherogenic Coefficient and Castelli Risk-Index I-II were found to be higher in bipolar patients with an evening chronotype. The role of chronotype in the development of obesity and cardiovascular risk is, therefore, a relationship worth being investigated, especially in the context of BD, to ameliorate the clinical and therapeutic approach, aiming at increasing the quality of life and reducing the mortality.

Identifying pathways to early-onset metabolic dysfunction, insulin resistance and inflammation in young adult inpatients with emerging affective and major mood disorders

AIM

Young people with common mood disorders face the prospect of shortened life expectancy largely due to premature cardiovascular disease. Metabolic dysfunction is a risk factor for premature cardiovascular disease. There is an ongoing debate whether metabolic dysfunction can be simply explained by weight gain secondary to psychotropic medications or whether shared genetic vulnerability, intrinsic immune-metabolic disturbances or other system perturbations (e.g. dysregulated sympathetic nervous system, circadian dysfunction) are more relevant determinants of premature cardiovascular disease. Thus, we aimed to investigate underlying drivers of metabolic dysfunction and premature cardiovascular disease in young people in the early phases of common mood disorders.

METHODS

We evaluated the relationships between insulin resistance (assessed by HOMA2-IR) and body mass index (BMI), sex, diagnosis, medication, inflammatory markers and hormonal factors in 327 inpatients with emerging affective and major mood disorders admitted to the Young Adult Mental Health Unit, St Vincent's Private Hospital, Sydney.

RESULTS

While HOMA2-IR scores were positively associated with BMI (r_s  = 0.465, p < .001), they were also higher in those prescribed mood stabilizers (p = .044) but were not associated with specific diagnoses, other medication types or the number of prescribed medications. Further, high-sensitivity C-reactive protein levels (but not thyroid-stimulating hormone and ferritin levels) were positively associated with HOMA2-IR (r_s  = 0. 272, p < .001) and BMI (r_s  = . 409, p < .001).

CONCLUSIONS

In addition to BMI, other non-specific markers of inflammation are associated with early metabolic dysfunction in young people with emerging affective and major mood disorders.

Developing “MinDag” – an app to capture symptom variation and illness mechanisms in bipolar disorder

Introduction

The illness course of bipolar disorder (BD) is highly heterogeneous with substantial variation between individuals with the same BD subtype and within individuals over time. This heterogeneity is not well-delineated and hampers the development of more targeted treatment. Furthermore, although lifestyle-related behaviors are believed to play a role in the illness course, such mechanisms are poorly understood. To address some of these knowledge gaps, we aimed to develop an app for collection of multi-dimensional longitudinal data on BD-relevant symptoms and lifestyle-related behaviors.

Methods

An app named MinDag was developed at the Norwegian Center for Mental Disorders Research in Oslo, Norway. The app was designed to tap into selected areas: mood, sleep, functioning/activities (social, occupational, physical exercise, leisure), substance use, emotional reactivity, and psychotic experiences. Ethical, security and usability issues were highly prioritized throughout the development and for the final app solution. We conducted beta- and pilot testing to eliminate technical problems and enhance usability and acceptability.

Results

The final version of MinDag comprises six modules; three which are presented for the user once daily (the Sleep module in the morning and the Mood and Functoning/Activities modules in the evening) and three which are presented once weekly (Substance Use, Emotional Reactivity, and Psychotic Experiences modules). In general, MinDag was well received in both in the beta-testing and the pilot study, and the participants provided valuable feedback that was taken into account in the final development. MinDag is now in use as part of the research protocol at the NORMENT center and in a specialized treatment unit for BD at Oslo University Hospital in Norway.

Discussion

We believe that MinDag will generate unique longitudinal data well suited for capturing the heterogeneity of BD and clarifying important unresolved issues such as how life-style related behavior may influence BD symptoms. Also, the experiences and knowledge derived from the development of MinDag may contribute to improving the security, acceptability, and benefit of digital tools in mental health.

Toward a Digital Future in Bipolar Disorder Assessment: A Systematic Review of Disruptions in the Rest-Activity Cycle as Measured by Actigraphy

BACKGROUND

Disruptions in rest and activity patterns are core features of bipolar disorder (BD). However, previous methods have been limited in fully characterizing the patterns. There is still a need to capture dysfunction in daily activity as well as rest patterns in order to more holistically understand the nature of 24-h rhythms in BD. Recent developments in the standardization, processing, and analyses of wearable digital actigraphy devices are advancing longitudinal investigation of rest-activity patterns in real time. The current systematic review aimed to summarize the literature on actigraphy measures of rest-activity patterns in BD to inform the future use of this technology.

METHODS

A comprehensive systematic review using PRISMA guidelines was conducted through PubMed, MEDLINE, PsycINFO, and EMBASE databases, for papers published up to February 2021. Relevant articles utilizing actigraphy measures were extracted and summarized. These papers contributed to three research areas addressed, pertaining to the nature of rest-activity patterns in BD, and the effects of therapeutic interventions on these patterns.

RESULTS

Seventy articles were included. BD was associated with longer sleep onset latency and duration, particularly during depressive episodes and with predictive value for worsening of future manic symptoms. Lower overall daily activity was also associated with BD, especially during depressive episodes, while more variable activity patterns within a day were seen in mania. A small number of studies linked these disruptions with differential patterns of brain functioning and cognitive impairments, as well as more adverse outcomes including increased suicide risk. The stabilizing effect of therapeutic options, including pharmacotherapies and chronotherapies, on activity patterns was supported.

CONCLUSION

The use of actigraphy provides valuable information about rest-activity patterns in BD. Although results suggest that variability in rhythms over time may be a specific feature of BD, definitive conclusions are limited by the small number of studies assessing longitudinal changes over days. Thus, there is an urgent need to extend this work to examine patterns of rhythmicity and regularity in BD. Actigraphy research holds great promise to identify a much-needed specific phenotypic marker for BD that will aid in the development of improved detection, treatment, and prevention options.

Sleep fragmentation and the risk of obesity: The Sleep Heart Health Study

OBJECTIVE

Sleep disturbances have been recognized as a risk factor for obesity. This study used polysomnography records to investigate associations between sleep fragmentation and obesity.

METHODS

Objectively measured sleep fragmentation data recorded by in-home polysomnography, including total arousal index (ArI-total), ArI in rapid eye movement (REM) sleep (ArI-REM), ArI in non-REM sleep (ArI-NREM), sleep fragmentation index, sleep efficiency (SE), and wake after sleep onset (WASO), were based on the Sleep Heart Health Study (2,835 men and 2,888 women with a mean [SD] age of 63.2 [11.2] years). Multivariable regression analyses were used to examine the relationship between sleep fragmentation and obesity.

RESULTS

Multinomial logistic regression showed that participants with obesity have a significantly higher ArI-total (odds ratio [OR] 1.018; 95% CI: 1.010-1.026, p < 0.001), ArI-REM (OR 1.010; 95% CI: 1.002-1.018, p = 0.009), ArI-NREM (OR 1.017; 95% CI: 1.009-1.024, p < 0.001), and WASO (OR 1.003; 95% CI: 1.001-1.005, p = 0.007) compared with those with normal weight. Furthermore, multiple linear regression analyses showed an obvious correlation between ArI-total, ArI-REM, ArI-NREM, SE, WASO, and BMI.

CONCLUSIONS

The results revealed that ArI-total, ArI-REM, ArI-NREM, SE, and WASO were associated with obesity. The improvement of sleep fragmentation may contribute to decreasing the risk of obesity.

Misperception of sleep in bipolar disorder: an exploratory study using questionnaire versus actigraphy

Background

The concept of misperception of sleep refers to the estimated discrepancy between subjective and objective measures of sleep. This has been assessed only in a few prior studies in individuals with Bipolar Disorder (BD) as compared to Healthy Controls (HC) and with mixed results.

Methods

We assessed a sample of 133 euthymic individuals with BD and 63 HC for retrospective subjective (Pittsburgh Sleep Quality Index) and objective (21 days of actigraphy recording) measures of total sleep time, sleep latency and sleep efficiency. We first investigated the correlations between these subjective and objective measures in the two groups. We then compared individuals with BD and HC for the absolute values of the differences between subjective and objective sleep parameters, used as a proxy of the magnitude of misperception of sleep. Finally, we undertook regression analyses to assess associations between clinical groups, core demographics, clinical factors and misperception of sleep.

Results

The correlation coefficients between subjective and objective measures of sleep did not differ between groups (total sleep time: rho = .539 in BD and rho = .584 in HC; sleep latency: rho = .190 in BD and rho = .125 in HC; sleep efficiency: rho = .166 in BD and rho = .222 in HC). Individuals with BD did not differ from HC in the magnitude of misperception of total sleep time, sleep latency nor sleep efficiency. Individuals with BD type 1 misperceived their sleep efficiency significantly more than individuals with BD type 2, with no further difference between BD type 1 and BD type 2 regarding sleep latency and sleep duration misperceptions. Three factors (age, symptoms of obstructive sleep apnea, and mild depressive symptoms), were the main contributors to the magnitude of misperception of sleep.

Conclusions

Misperception of sleep was not associated with a diagnosis of BD. In this sample, mild depressive symptoms, older age, or symptoms of obstructive sleep apnea may be related to greater sleep misperception. In that case, the reliability of subjective measures may decrease as the misperception of sleep increases. This study may help guide clinicians in selecting the best approach for assessing sleep (objective versus subjective measures) in individuals with BD.

Can an Integrated Science Approach to Precision Medicine Research Improve Lithium Treatment in Bipolar Disorders?

Clinical practice guidelines identify lithium as a first line treatment for mood stabilization and reduction of suicidality in bipolar disorders (BD); however, most individuals show sub-optimal response. Identifying biomarkers for lithium response could enable personalization of treatment and refine criteria for stratification of BD cases into treatment-relevant subgroups. Existing systematic reviews identify potential biomarkers of lithium response, but none directly address the conceptual issues that need to be addressed to enhance translation of research into precision prescribing of lithium. For example, although clinical syndrome subtyping of BD has not led to customized individual treatments, we emphasize the importance of assessing clinical response phenotypes in biomarker research. Also, we highlight the need to give greater consideration to the quality of prospective longitudinal monitoring of illness activity and the differentiation of non-response from partial or non-adherence with medication. It is unlikely that there is a single biomarker for lithium response or tolerability, so this review argues that more research should be directed toward the exploration of biosignatures. Importantly, we emphasize that an integrative science approach may improve the likelihood of discovering the optimal combination of clinical factors and multimodal biomarkers (e.g., blood omics, neuroimaging, and actigraphy derived-markers). This strategy could uncover a valid lithium response phenotype and facilitate development of a composite prediction algorithm. Lastly, this narrative review discusses how these strategies could improve eligibility criteria for lithium treatment in BD, and highlights barriers to translation to clinical practice including the often-overlooked issue of the cost-effectiveness of introducing biomarker tests in psychiatry.