The structure of mania: An overview of factorial analysis studies

Day-to-day variability in sleep and activity predict the onset of a hypomanic episode in patients with bipolar disorder

Detecting transitions in bipolar disorder (BD) is essential for implementing early interventions. Our aim was to identify the earliest indicator(s) of the onset of a hypomanic episode in BD. We hypothesized that objective changes in sleep would be the earliest indicator of a new hypomanic or manic episode. In this prospective, observational, contactless study, participants used wearable technology continuously to monitor their daily activity and sleep parameters. They also completed weekly self-ratings using the Altman Self-Rating Mania Scale (ASRM). Using time-frequency spectral derivative spike detection, we assessed the sensitivity, specificity, and balanced accuracy of wearable data to identify a hypomanic episode, defined as at least one or more weeks with consecutive ASRM scores ≥10. Of 164 participants followed for a median (IQR) of 495.0 (410.0) days, 50 experienced one or more hypomanic episodes. Within-night variability in sleep stages was the earliest indicator identifying the onset of a hypomanic episode (mean ± SD): sensitivity: 0.94 ± 0.19; specificity: 0.80 ± 0.19; balanced accuracy: 0.87 ± 0.13; followed by within-day variability in activity levels: sensitivity: 0.93 ± 0.18; specificity: 0.84 ± 0.13; balanced accuracy: 0.89 ± 0.11. Limitations of our study includes a small sample size. Strengths include the use of densely sampled data in a well-characterized cohort followed for over a year, as well as the use of a novel approach using time-frequency analysis to dynamically assess behavioral features at a granular level. Detecting and predicting the onset of hypomanic (or manic) episodes in BD is paramount to implement individualized early interventions.

PTN activity in quiescent neural stem cells mediates Shank3 overexpression-induced manic behavior

Mania is a complex psychiatric disease characterized by hyperactivity, elevated mood and reduced anxiety. Despite extensive studies on the mechanism of the manic episodes, the molecular targets that control manic pathogenesis remain largely unclear. Here, through single-cell RNA sequencing (scRNA-seq) analysis, we show aberrant adult neurogenesis due to increased numbers of quiescent neural stem cells (qNSC) in a manic mouse model with Shank3 overexpression. Particularly, we found that the excessive Pleiotrophin (PTN), released by dysregulated qNSCs, is a key factor contributing to the manic-like phenotypes in Shank3-overexpressing mouse models. Pharmacological and molecular inhibition of PTN in qNSCs rescued aberrant neurogenesis and effectively alleviated the manic-like social deficits observed in Shank3-overexpressing mice. Taken together, our findings present an approach for modulating PTN activity in qNSCs, proposing it as a promising therapeutic target for manic development.

Causal relationships between neuropsychiatric disorders and nonalcoholic fatty liver disease: A bidirectional Mendelian randomization study

BACKGROUND

Increasing evidences suggest that nonalcoholic fatty liver disease (NAFLD) is associated with neuropsychiatric disorders. Nevertheless, whether there were causal associations between them remained vague. A causal association between neuropsychiatric disorders and NAFLD was investigated in this study.

METHODS

We assessed the published genome-wide association study summary statistics for NAFLD, seven mental disorder-related diseases and six central nervous system dysfunction-related diseases. The causal relationships were first assessed using two-sample and multivariable Mendelian randomization (MR). Then, sensitivity analyses were performed, followed by a reverse MR analysis to determine whether reverse causality is possible. Finally, we performed replication analyses and combined the findings from the above studies.

RESULTS

Our meta-analysis results showed NAFLD significantly increased the risk of anxiety disorders (OR = 1.016, 95% CI = 1.010-1.021, P value < 0.0001). In addition, major depressive disorder was the potential risk factor for NAFLD (OR = 1.233, 95% CI = 1.063-1.430, P value = 0.006). Multivariable MR analysis showed that the causal effect of major depressive disorder on NAFLD remained significant after considering body mass index, but the association disappeared after adjusting for the effect of waist circumference. Furthermore, other neuropsychiatric disorders and NAFLD were not found to be causally related.

CONCLUSIONS

These results implied causal relationships of NAFLD with anxiety disorders and Major Depressive Disorder. This study highlighted the need to recognize and understand the connection between neuropsychiatric disorders and NAFLD to prevent the development of related diseases.

Identifying digital biomarkers of illness activity and treatment response in bipolar disorder with a novel wearable device (TIMEBASE): protocol for a pragmatic observational clinical study

BACKGROUND

Bipolar disorder is highly prevalent and consists of biphasic recurrent mood episodes of mania and depression, which translate into altered mood, sleep and activity alongside their physiological expressions.

AIMS

The IdenTifying dIgital bioMarkers of illnEss activity and treatment response in BipolAr diSordEr with a novel wearable device (TIMEBASE) project aims to identify digital biomarkers of illness activity and treatment response in bipolar disorder.

METHOD

We designed a longitudinal observational study including 84 individuals. Group A comprises people with acute episode of mania (n = 12), depression (n = 12 with bipolar disorder and n = 12 with major depressive disorder (MDD)) and bipolar disorder with mixed features (n = 12). Physiological data will be recorded during 48 h with a research-grade wearable (Empatica E4) across four consecutive time points (acute, response, remission and episode recovery). Group B comprises 12 people with euthymic bipolar disorder and 12 with MDD, and group C comprises 12 healthy controls who will be recorded cross-sectionally. Psychopathological symptoms, disease severity, functioning and physical activity will be assessed with standardised psychometric scales. Physiological data will include acceleration, temperature, blood volume pulse, heart rate and electrodermal activity. Machine learning models will be developed to link physiological data to illness activity and treatment response. Generalisation performance will be tested in data from unseen patients.

RESULTS

Recruitment is ongoing.

CONCLUSIONS

This project should contribute to understanding the pathophysiology of affective disorders. The potential digital biomarkers of illness activity and treatment response in bipolar disorder could be implemented in a real-world clinical setting for clinical monitoring and identification of prodromal symptoms. This would allow early intervention and prevention of affective relapses, as well as personalisation of treatment.

The clinical significance of emotional urgency in bipolar disorder: a scoping review

BACKGROUND

Emotional urgency, defined as a trait concept of emotion-based impulsivity, is at least moderately associated with general psychopathology. However, its clinical significance and associations with clinically relevant features of bipolar disorder remain unclear. This scoping review aims address this gap by determining the extent of evidence in this niche scope of study.

METHODS

Evidence of between-group differences of positive and negative urgency, its associations with mood severity, and all peripheral associations related to illness and psychosocial outcomes were synthesized based on PRISMA checklists and guidelines for scoping reviews (PRISMA-ScR).

DESIGN

Electronic databases were searched for articles published between January 2001 and January 2024. A total of 1013 entries were gathered, and a total of 10 articles were included in the final selection after the removal of duplicates and ineligible articles.

RESULTS

Differences in urgency scores between bipolar disorder and healthy controls were large (Cohen's d ranged from 1.77 to 2.20). Negative urgency was at least moderately associated with overall trauma, emotional abuse, neglect, suicide ideation, neuroticism, and irritable/cyclothymic temperament, whereas positive urgency was at least moderately associated with various aspects of aggression and quality of life. Positive but not negative urgency was associated with quality of life in bipolar disorder.

CONCLUSION

Large between-group differences found for emotional urgency in bipolar disorder imply large clinical significance. Emotional urgency was associated with worse clinical features and outcomes. Given the high clinical heterogeneity of the disorder, emotional urgency may be an important phenotype indicative of greater disorder severity.

Genetic examination of the Mood Disorder Questionnaire and its relationship with bipolar disorder

The Mood Disorder Questionnaire (MDQ) is a common screening tool for bipolar disorder that assesses manic symptoms. Its utility for genetic studies of mania or bipolar traits has not been fully examined. We psychometrically compared the MDQ to self-reported bipolar disorder in participants from the United Kingdom National Institute of Health and Care Research Mental Health BioResource. We conducted genome-wide association studies of manic symptom quantitative traits and symptom subgroups, derived from the MDQ items (N = 11,568-19,859). We calculated genetic correlations with bipolar disorder and other psychiatric and behavioral traits. The MDQ screener showed low positive predictive value (0.29) for self-reported bipolar disorder. Neither concurrent nor lifetime manic symptoms were genetically correlated with bipolar disorder. Lifetime manic symptoms had a highest genetic correlation (rg  = 1.0) with posttraumatic stress disorder although this was not confirmed by within-cohort phenotypic correlations (rp  = 0.41). Other significant genetic correlations included attention deficit hyperactivity disorder (rg  = 0.69), insomnia (rg  = 0.55), and major depressive disorder (rg  = 0.42). Our study adds to existing literature questioning the MDQ's validity and suggests it may capture symptoms of general distress or psychopathology, rather than hypomania/mania specifically, in at-risk populations.

What's in the mind's eye of individuals with bipolar disorders: an exploration of the content and characteristics of mental images in different thymic phases

BACKGROUND

Mental imagery, or 'seeing with the mind's eye' (Kosslyn et al. ), provokes strong emotional responses (Ji et al., ). To date, there is a lack of data on the content and clinical characteristics (e.g. vividness, likelihood, emotional effects) of spontaneous mental images (MI) in people with bipolar disorder (BD) according to their thymic states.

AIM

The current study sought to assess the characteristics associated with the contents of MI in people with BD.

METHOD

Forty-two euthymic individuals diagnosed with BD (American Psychiatric Association, ) were asked to self-report their MI during depression, (hypo)mania and euthymia. Participants also rated levels of vividness, likelihood and emotional activation related to MI (i.e. valence, arousal, type of emotion).

RESULTS

The contents of the MI revealed phenomenological aspects of BD. Different themes were associated with each thymic phase. In (hypo)mania and in euthymia, the mental images were assessed as being as vivid as probable (p>.05). (Hypo)manic and euthymic-related MI activated more pleasure than displeasure (p<.001) and were mainly associated with joy. In depression, MI were assessed as more vivid than likely (p<.05). In depression, MI activated more displeasure than pleasure (p<.0001) and induced mainly sadness.

DISCUSSION

Overall, a congruence between the contents of images and the three thymic phases was found. The content of the MI was related to self-reported emotional effects that were congruent with the thymic phases concerned. The results add new clinical information for the use of imagery-based cognitive therapy in individuals with BD.

Exploring Digital Biomarkers of Illness Activity in Mood Episodes: Hypotheses Generating and Model Development Study

BACKGROUND

Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity, alongside physiological alterations wearables can capture.

OBJECTIVE

Firstly, we explored whether physiological wearable data could predict (aim 1) the severity of an acute affective episode at the intra-individual level and (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to prior predictions, generalization across patients, and associations between affective symptoms and physiological data.

METHODS

We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded using a research-grade wearable (Empatica E4) across 3 consecutive time points (acute, response, and remission of episode). Euthymic patients and healthy controls were recorded during a single session (approximately 48 h). Manic and depressive symptoms were assessed using standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), skin temperature, blood volume pulse, heart rate (HR), and electrodermal activity (EDA). Invalid physiological data were removed using a rule-based filter, and channels were time aligned at 1-second time units and segmented at window lengths of 32 seconds, as best-performing parameters. We developed deep learning predictive models, assessed the channels' individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales' items normalized mutual information (NMI). We present a novel, fully automated method for the preprocessing and analysis of physiological data from a research-grade wearable device, including a viable supervised learning pipeline for time-series analyses.

RESULTS

Overall, 35 sessions (1512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 healthy controls (mean age 39.7, SD 12.6 years; 6/19, 32% female) were analyzed. The severity of mood episodes was predicted with moderate (62%-85%) accuracies (aim 1), and their polarity with moderate (70%) accuracy (aim 2). The most relevant features for the former tasks were ACC, EDA, and HR. There was a fair agreement in feature importance across classification tasks (Kendall W=0.383). Generalization of the former models on unseen patients was of overall low accuracy, except for the intra-individual models. ACC was associated with "increased motor activity" (NMI>0.55), "insomnia" (NMI=0.6), and "motor inhibition" (NMI=0.75). EDA was associated with "aggressive behavior" (NMI=1.0) and "psychic anxiety" (NMI=0.52).

CONCLUSIONS

Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression, respectively. These findings represent a promising pathway toward personalized psychiatry, in which physiological wearable data could allow the early identification and intervention of mood episodes.

Bipolar disorder in the International Classification of Diseases-Eleventh version: A review of the changes, their basis, and usefulness

The World Health Organization’s 11^th revision of the International Classification of Diseases (ICD-11) including the chapter on mental disorders has come into effect this year. This review focuses on the “Bipolar or Related Disorders” section of the ICD-11 draft. It describes the benchmarks for the new version, particularly the foremost principle of clinical utility. The alterations made to the diagnosis of bipolar disorder (BD) are evaluated on their scientific basis and clinical utility. The change in the diagnostic requirements for manic and hypomanic episodes has been much debated. Whether the current criteria have achieved an optimum balance between sensitivity and specificity is still not clear. The ICD-11 definition of depressive episodes is substantially different, but the lack of empirical support for the changes has meant that the reliability and utility of bipolar depression are relatively low. Unlike the Diagnostic and Statistical Manual of Mental Disorders, 5^th edition (DSM-5), the ICD-11 has retained the category of mixed episodes. Although the concept of mixed episodes in the ICD-11 is not perfect, it appears to be more inclusive than the DSM-5 approach. Additionally, there are some uncertainties about the guidelines for the subtypes of BD and cyclothymic disorder. The initial results on the reliability and clinical utility of BD are promising, but the newly created diagnostic categories also appear to have some limitations. Although further improvement and research are needed, the focus should now be on facing the challenges of implementation, dissemination, and education and training in the use of these guidelines.

Affective symptom dimensions in early-onset psychosis over time: a principal component factor analysis of the Young Mania Rating Scale and the Hamilton Depression Rating Scale

Early-onset psychosis (EOP) is a complex disorder characterized by a wide range of symptoms, including affective symptoms. Our aim was to (1) examine the dimensional structure of affective symptoms in EOP, (2) evaluate the predominance of the clinical dimensions and (3) assess the progression of the clinical dimensions over a 2-year period. STROBE-compliant prospective principal component factor analysis of Young Mania Rating Scale (YMRS) and Hamilton Depression Rating Scale-21 (HDRS-21) at baseline, 6-months, 1-year and 2-year follow-up. We included 108 EOP individuals (mean age = 15.5 ± 1.8 years, 68.5% male). The factor analysis produced a four-factor model including the following dimensions: mania, depression/anxiety, sleep and psychosis. It explained 47.4% of the total variance at baseline, 60.6% of the total variance at 6-months follow-up, 54.5% of the total variance at 1-year follow-up and 49.5% of the total variance at 2-year follow-up. According to the variance explained, the mania factor was predominant at baseline (17.4%), 6-month follow-up (23.5%) and 2-year follow-up (26.1%), while the depression/anxiety factor was predominant at 1-year follow-up (23.1%). The mania factor was the most stable; 58.3% items that appeared in this factor (with a load > 0.4) at any time point appeared in the same factor at ≥ 3/4 time points. Affective symptoms are frequent and persistent in EOP. Mania seems to be the most predominant and stable affective dimension. However, depression and anxiety may gain predominance with time. A comprehensive evaluation of the dimensional structure and the progression of affective symptoms may offer clinical and therapeutic advantages.

The clinical characterization of the adult patient with bipolar disorder aimed at personalization of management

Bipolar disorder is heterogeneous in phenomenology, illness trajectory, and response to treatment. Despite evidence for the efficacy of multimodal-ity interventions, the majority of persons affected by this disorder do not achieve and sustain full syndromal recovery. It is eagerly anticipated that combining datasets across various information sources (e.g., hierarchical "multi-omic" measures, electronic health records), analyzed using advanced computational methods (e.g., machine learning), will inform future diagnosis and treatment selection. In the interim, identifying clinically meaningful subgroups of persons with the disorder having differential response to specific treatments at point-of-care is an empirical priority. This paper endeavours to synthesize salient domains in the clinical characterization of the adult patient with bipolar disorder, with the overarching aim to improve health outcomes by informing patient management and treatment considerations. Extant data indicate that characterizing select domains in bipolar disorder provides actionable information and guides shared decision making. For example, it is robustly established that the presence of mixed features - especially during depressive episodes - and of physical and psychiatric comorbidities informs illness trajectory, response to treatment, and suicide risk. In addition, early environmental exposures (e.g., sexual and physical abuse, emotional neglect) are highly associated with more complicated illness presentations, inviting the need for developmentally-oriented and integrated treatment approaches. There have been significant advances in validating subtypes of bipolar disorder (e.g., bipolar I vs. II disorder), particularly in regard to pharmacological interventions. As with other severe mental disorders, social functioning, interpersonal/family relationships and internalized stigma are domains highly relevant to relapse risk, health outcomes, and quality of life. The elevated standardized mortality ratio for completed suicide and suicidal behaviour in bipolar disorder invites the need for characterization of this domain in all patients. The framework of this paper is to describe all the above salient domains, providing a synthesis of extant literature and recommendations for decision support tools and clinical metrics that can be implemented at point-of-care.

Character strengths as protective factors against behavior problems in early adolescent

Character strengths could effectively prevent negative psychological outcomes in adults. However, there was little research conducted among early adolescents. The present study aimed to explore character strengths that were independently related to fewer behavior problems in early adolescents. In total, 521 early adolescents (mean age 10.92 ± 0.04, range 10-12 years) were recruited from primary schools in Sichuan, China. Character strengths were measured using the Values in Action Inventory of Strengths for Youth (VIA-Youth). Behavior problems were measured using the Conners Parent Symptom Questionnaire (PSQ). The results showed that behavior problems were negatively correlated with character strengths (r = -0.14 to -0.3, p < 0.05 Bonferroni corrected). Character strengths explained a significant proportion of additional variance (14-22%) in five types of behavior problems after controlling the effect of demographic factors (residence, left-behind experiences, maternal education level). Moreover, several specific character strengths showed an independent contribution (β = -0.34 to -0.14 for self-regulation, perseverance, zest, humility, and leadership; β = 0.21 to 0.34, for hope; all p < 0.05) to behavior problems. Our study revealed that character strengths were protective factors against behavior problems in early adolescents.

Bipolar Depression: A Historical Perspective of the Current Concept, with a Focus on Future Research

The aim of this narrative review is to trace the origin of the concept of bipolar depression and to expose some of its limitations. Bipolar depression is a broad clinical construct including experiences ranging from traditional melancholic and psychotic episodes ascribed to "manic-depressive insanity," to another heterogeneous group of depressive episodes originally described in the context of binary models of unipolar depression (e.g., psychogenic depression, neurotic depression). None of the available empirical evidence suggests, however, that these subsets of "bipolar" depression are equivalent in terms of clinical course, disability, family aggregation, and response to treatment, among other relevant diagnostic validators. Therefore, the validity of the current concept of bipolar depression should be a matter of concern. Here, we discuss some of the potential limitations that this broad construct might entail in terms of pathophysiological, clinical, and therapeutic aspects. Finally, we propose a clinical research program for bipolar depression in order to delimit diagnostic entities based on empirical data, with subsequent validation by laboratory or neuroimaging biomarkers. This process will then aid in the development of more specific treatments.

How Does Adding the DSM-5 Criterion Increased Energy/Activity for Mania Change the Bipolar Landscape?

According to DSM-IV, the criterion (A) for diagnosing hypomanic/manic episodes is mood change (i.e., elevated, expansive or irritable mood). Criterion (A) was redefined in DSM-5 in 2013, adding increased energy/activity in addition to mood change. This paper examines a potential change of prevalence data for bipolar I or II when adding increased energy/activity to the criterion (A) for the diagnosis of hypomania/mania. Own research suggests that the prevalence of manic/hypomanic episodes drops by at least one third when using DSM-5 criteria. Whether this has positive or negative impact on clinical practice and research still needs further evaluation.