Several psychological models of bipolar disorder propose that certain types of appraisals can lead to increases in manic symptoms.

We tested whether the belief that being ‘high’ is a natural part of one’s personality and correlates with manic symptoms 4 months later when controlling for manic symptoms at baseline.

This was a prospective 4-month follow-up design using self-report measures. Forty people with a diagnosis of bipolar disorder completed a measure of manic symptoms, a measure of appraisals associated with bipolar disorder, and a single-item measure, ‘To what extent do you feel like being “high” is a natural part of your personality?’, at baseline and follow-up.

The single-item measure showed modest stability over time and construct validity in its correlation with a standardised measure of appraisals in bipolar disorder. As predicted, the single-item measure correlated with manic symptoms at follow-up when controlling for manic symptoms at baseline.

The belief that being ‘high’ is a natural part of one’s personality is a potential predictor of manic symptoms. Further research needs to study the potential mediating mechanisms such as activating behaviours, and control for indicators of the bipolar endophenotype.

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.

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.

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.

Recruitment is ongoing.

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.

Identification of the predominant polarity, i.e. hypomanic/manic (mPP) or depressive predominant polarity (dPP), might help clinicians to improve personalised management of bipolar disorder.

We performed a systematic review and meta-analysis to estimate prevalence and correlates of mPP and dPP in bipolar disorder.

The protocol was registered in the Open Science Framework Registries (https://doi.org/10.17605/OSF.IO/8S2HU). We searched main electronic databases up to December 2023 and performed random-effects meta-analyses of weighted prevalence of mPP and dPP. Odds ratios and weighted mean differences (WMDs) were used for relevant correlates.

We included 28 studies, providing information on rates and/or correlates of mPP and dPP. We estimated similar rates of mPP (weighted prevalence = 30.0%, 95% CI: 23.1 to 37.4%) and dPP (weighted prevalence = 28.5%, 95% CI: 23.7 to 33.7%) in bipolar disorder. Younger age (WMD = −3.19, 95% CI: −5.30 to −1.08 years), male gender (odds ratio = 1.39, 95% CI: 1.10 to 1.76), bipolar-I disorder (odds ratio = 4.82, 95% CI: 2.27 to 10.24), psychotic features (odds ratio = 1.56, 95% CI: 1.01 to 2.41), earlier onset (WMD = −1.57, 95% CI: −2.88 to −0.26 years) and manic onset (odds ratio = 13.54, 95% CI: 5.83 to 31.46) were associated with mPP (P < 0.05). Depressive onset (odds ratio = 12.09, 95% CI: 6.38 to 22.90), number of mood episodes (WMD = 0.99, 95% CI: 0.28 to 1.70 episodes), history of suicide attempts (odds ratio = 2.09, 95% CI: 1.49 to 2.93) and being in a relationship (odds ratio = 1.98, 95% CI: 1.22 to 3.22) were associated with dPP (P < 0.05). No differences were estimated for other variables.

Despite some limitations, our findings support the hypothesis that predominant polarity might be a useful specifier of bipolar disorder. Evidence quality was mixed, considering effects magnitude, consistency, precision and publication bias. Different predominant polarities may identify subgroups of patients with specific clinical characteristics.

Cardiometabolic disease risk factors are disproportionately prevalent in bipolar disorder (BD) and are associated with cognitive impairment. It is, however, unknown which health risk factors for cardiometabolic disease are relevant to cognition in BD. This study aimed to identify the cardiometabolic disease risk factors that are the most important correlates of cognitive impairment in BD; and to examine whether the nature of the relationships vary between mid and later life.

Data from the UK Biobank were available for 966 participants with BD, aged between 40 and 69 years. Individual cardiometabolic disease risk factors were initially regressed onto a global cognition score in separate models for the following risk factor domains; (1) health risk behaviors (physical activity, sedentary behavior, smoking, and sleep) and (2) physiological risk factors, stratified into (2a) anthropometric and clinical risk (handgrip strength, body composition, and blood pressure), and (2b) cardiometabolic disease risk biomarkers (CRP, lipid profile, and HbA1c). A final combined multivariate regression model for global cognition was then fitted, including only the predictor variables that were significantly associated with cognition in the previous models.

In the final combined model, lower mentally active and higher passive sedentary behavior, higher levels of physical activity, inadequate sleep duration, higher systolic and lower diastolic blood pressure, and lower handgrip strength were associated with worse global cognition.

Health risk behaviors, as well as blood pressure and muscular strength, are associated with cognitive function in BD, whereas other traditional physiological cardiometabolic disease risk factors are not.

Increased autocorrelation (AR) of system-specific measures has been suggested as a predictor for critical transitions in complex systems. Increased AR of mood scores has been reported to anticipate depressive episodes in major depressive disorder, while other studies found AR increases to be associated with depressive episodes themselves. Data on AR in patients with bipolar disorders (BD) is limited and inconclusive.

Patients with BD reported their current mood via daily e-diaries for 12 months. Current affective status (euthymic, prodromal, depressed, (hypo)manic) was assessed in 26 bi-weekly expert interviews. Exploratory analyses tested whether self-reported current mood and AR of the same item could differentiate between prodromal phases or affective episodes and euthymia.

A total of 29 depressive and 20 (hypo)manic episodes were observed in 29 participants with BD. Self-reported current mood was significantly decreased during the two weeks prior to a depressive episode (early prodromal, late prodromal), but not changed prior to manic episodes. The AR was neither a significant predictor for the early or late prodromal phase of depression nor for the early prodromal phase of (hypo)mania. Decreased AR was found in the late prodromal phase of (hypo)mania. Increased AR was mainly found during depressive episodes.

AR changes might not be better at predicting depressive episodes than simple self-report measures on current mood in patients with BD. Increased AR was mostly found during depressive episodes. Potentially, changes in AR might anticipate (hypo)manic episodes.

Exploring the neural basis related to different mood states is a critical issue for understanding the pathophysiology underlying mood switching in bipolar disorder (BD), but research has been scarce and inconsistent.

Resting-state functional magnetic resonance imaging data were acquired from 162 patients with BD: 33 (hypo)manic, 64 euthymic, and 65 depressive, and 80 healthy controls (HCs). The differences of large-scale brain network functional connectivity (FC) between the four groups were compared and correlated with clinical characteristics. To validate the generalizability of our findings, we recruited a small longitudinal independent sample of BD patients (n = 11). In addition, we examined topological nodal properties across four groups as exploratory analysis.

A specific strengthened pattern of network FC, predominantly involving the default mode network (DMN), was observed in (hypo)manic patients when compared with HCs and bipolar patients in other mood states. Longitudinal observation revealed an increase in several network FCs in patients during (hypo)manic episode. Both samples evidenced an increase in the FC between the DMN and ventral attention network, and between the DMN and limbic network (LN) related to (hypo)mania. The altered network connections were correlated with mania severity and positive affect. Bipolar depressive patients exhibited decreased FC within the LN compared with HCs. The exploratory analysis also revealed an increase in degree in (hypo)manic patients.

Our findings identify a distributed pattern of large-scale network disturbances in the unique context of (hypo)mania and thus provide new evidence for our understanding of the neural mechanism of BD.

Frequently associated with early psychosis, depressive and manic dimensions may play an important role in its course and outcome. While manic and depressive symptoms can alternate and co-occur, most of the studies in early intervention investigated these symptoms independently. The aim of this study was therefore to explore the co-occurrence of manic and depressive dimensions, their evolution and impact on outcomes.

We prospectively studied first-episode psychosis patients (N = 313) within an early intervention program over 3 years. Based on latent transition analysis, we identified sub-groups of patients with different mood profiles considering both manic and depressive dimensions, and studied their outcomes.

Our results revealed six different mood profiles at program entry and after 1.5 years follow-up (absence of mood disturbance, co-occurrence, mild depressive, severe depressive, manic and hypomanic), and four after 3 years (absence of mood disturbance, co-occurrence, mild depressive and hypomanic). Patients with absence of mood disturbance at discharge had better outcomes. All patients with co-occurring symptoms at program entry remained symptomatic at discharge. Patients with mild depressive symptoms were less likely to return to premorbid functional level at discharge than the other subgroups. Patients displaying a depressive component had poorer quality of physical and psychological health at discharge.

Our results confirm the major role played by mood dimensions in early psychosis, and show that profiles with co-occurring manic and depressive dimensions are at risk of poorer outcome. An accurate assessment and treatment of these dimensions in people with early psychosis is crucial.

Psychiatric disturbances induced by substances are registered in both CIE-10 and DSM-5. It is also well known, since many years, the association between mania and corticosteroids (more than 200 results in PubMed found), recently widely used during the last pandemic against COVID-19.

To remember and to point out the association of substance-induced mental disorders, warning about the experimentation in new clinical settings and raising awareness to prevent or treat its possible consequences in mental health.

A two cases clinical series with COVID-19 pneumonia treated with high-doses intravenous corticosteroids during more than a week. Two women, after theirs 50s, with no personal or family psychiatric history, developing after finishing the hospital treatment, insomnia, motor and behavioral hyperactivity and dysphoric mood with irritability, but preserving clinical insight.

At first, these states were assessed by internists and psychologists as reactive stress anxiety and were treated with benzodiazepines and psychotherapy, without success, during more than two weeks. After a psychiatric evaluation, considering the medical history and recent use of corticosteroids, the hipomania diagnosis was pointed out. Antipsychotic treatment (low doses olanzapine chosen) was induced with total remission of symptoms in less than 15 days with restitutio ad integrum. Regarding these cases, an updated bibliographic review on corticosteroid-induced mania and its treatment was carried out.

With this presentation, the authors would like to highlight, in these times of pandemic, the importance of remembering the influence and relationship of drugs use in major psychiatric syndromes, both in the causal origin and in the treatment.

No significant relationships.

Antidepressant withdrawal manic states are rare and controversial phenomena. The underlying pathophysiology and the clinical implications have not been thoroughly discussed in the literature.

We aimed to review reports of antidepressant discontinuation manic states and to discuss the different hypothetical pathophysiological changes underlying this phenomenon. We also argued in favor of its inclusion in the bipolar spectrum.

We searched Pubmed using the key words: ‘antidepressant withdrawal’ or ‘antidepressant discontinuation’ plus ‘mania’ or ‘hypomania’ from January 2008 until January 2018.

Twenty-nine cases of antidepressant discontinuation manic states were identified. Hypotheses involve the implication of Catecholamines, Acetylcholine and Serotonin in the pathophysiology of this paradoxical phenomenon. The search for red flags for bipolar disorder in these case reports revealed psychiatric histories in favor of a bipolar spectrum disorder in 12 individuals while five were already known to have bipolar disorder.

Antidepressant discontinuation mania should be considered on the bipolar spectrum.

No significant relationships.

Sleep plays a key role in the pathogenesis and clinic of mood disorders. However, few studies have investigated electroencephalographic sleep parameters during the manic phases of Bipolar Disorder (BD).

Sleep management is a priority objective in the treatment of the manic phases of BD and the polysomnographic investigation can be a valid tool both in the diagnostic phase and in monitoring clinical progress.

Twenty-one patients affected by BD, manic phase, were subjected to sleep monitoring via PSG in the acute phase (at the entrance to the ward) and in the resolution phase (near discharge). All participants were also clinically evaluated using Young Manic Rating Scale (YMRS) Pittsburgh Sleep Quality Index (PSQI), Morningness-eveningness Questionnaire (MEQ) at different timepoints.

Over the hospitalization time frame there was an increase in quantity (Total Sleep Time) and an improvement in the quality and effectiveness of sleep (Sleep Efficiency). In addition, from the point of view of the EEG structure, clinical improvement was accompanied by an increase in the percentage of REM sleep.

Sleep monitoring by PSG can be a valuable tool in the clinical setting both in the diagnostic phase, “objectively” ascertaining the amount of sleep, and in the prognostic phase, identifying electroencephalographic characteristics that can predict the patient’s progress and response to drug therapy. The improvement in effectiveness and continuity of sleep and the change in its structure that accompanies the resolution of manic symptoms also testifies how the regularization of the sleep-wake rhythm is to be considered a priority in treating manic phases.

No significant relationships.