To investigate the association of midlife and late-life undiagnosed mood symptoms, especially their comorbidity, with long-term dementia risk among multi-regional and ethnic adults.

The prospective study used data from the UK Biobank (N = 142,670; mean follow-up 11.0 years) and three Asian studies (N = 1,610; mean follow-up 4.4 years). Undiagnosed mood symptoms (manic symptoms, depressive symptoms and comorbidity of depressive and manic symptoms) and diagnosed mood disorders (depression, mania and bipolar disorders) were classified. Plasma levels of 168 metabolites were measured. The association between undiagnosed mood symptoms and 12-year dementia (including subtypes) risk and domain-specific cognitive function was examined. The contribution of metabolites in explaining the association between symptom comorbidity and dementia risk was estimated.

Undiagnosed mood symptoms were prevalent (11.4% in the UK cohort and 31.2% in Asian cohorts) among 1,462 (1.0%) and 74 (19.4%) participants who developed dementia. Comorbidity of undiagnosed mood symptoms was associated with higher dementia risk (sub-distribution hazard ratios = 9.46; 95% confidence interval = 4.07–21.97), especially Alzheimer’s disease, and with worse reasoning ability, poorer numeric memory and metabolic dysfunction. Glucose and total Esterified Cholesterol explained 9.1% of the association between symptom comorbidity and dementia, with most of the contribution being from glucose (6.8%).

Comorbidity of undiagnosed mood symptoms was associated with a higher cumulative risk of dementia in the long term. Glucose metabolism could be implicated in the development of mood disorders and dementia. The distinctive pathophysiological mechanism between psychiatric and neurodegenerative disorders warrants further exploration.

People with severe mental disorders (SMDs) have about 15 years shorter life expectancy than the general population. Cardiovascular disease (CVD) is among the leading causes of premature mortality and shares genetic underpinnings with SMDs. We investigated the link between clinical traits in SMDs and time to the first CVD diagnosis.

The study included 1,627 well-characterized participants with schizophrenia spectrum (SCZ, N = 998) and bipolar spectrum disorders (BDs, N = 629), and a reference group of 1,201 healthy controls. CVD diagnoses were obtained from two Norwegian national registries (covering both primary and specialist health care) for the period of 2006–2020. Applying Cox proportional hazard models, we investigated associations between SMD clinical traits and time to first CVD diagnosis in SMD participants, adjusting for age, sex, diagnosis, and tobacco use.

Among individuals with SMD, recurring self-harming behavior (SHB) was associated with a shorter time to first CVD diagnosis (p = .029) relative to those without SHB. In the subgroup with SHB and a history of attempted suicide(s), more suicide attempts were associated with shorter time to first CVD diagnosis (p = .041). Significant associations of time to first CVD diagnosis with age at SMD onset and comorbid substance use disorder were not demonstrated.

SHB and a history of suicide attempts in individuals with SMD seem to be associated with earlier CVD onset, and may improve the prediction of CVD, in addition to standard cardiovascular risk factors.

Difficult-to-treat depression (DTD) is a common clinical challenge for major depressive disorder and bipolar disorders. Electro convulsive therapy (ECT) has proven to be one of the most effective treatments for this condition. Although several studies have investigated individually the clinical factors associated with the DTD response, the role of their interplay in the clinical response to ECT remains unknown. In the present study, we aimed to characterize the network of symptoms in DTD, evaluate the effects of ECT on the interrelationship of depressive symptoms, and identify the network characteristics that could predict the clinical response.

A network analysis of clinical and demographic data from 154 patients with DTD was performed to compare longitudinally the patterns of relationships among depressive symptoms after ECT treatment. Furthermore, we estimated the network structure at baseline associated with a greater clinical improvement (≥80% reduction at Montgomery–Åsberg Depression Rating Scale total score).

ECT modulated the network of depressive symptoms, with increased strength of the global network (p = 0.03, Cohen’s d = −0.98, 95% confidence interval = [−1.07, −0.88]). The strength of the edges between somatic symptoms (appetite and sleep) and cognitive-emotional symptoms (tension, lassitude, and pessimistic thoughts) was also increased. A stronger negative relationship between insomnia and pessimistic thoughts was associated with a greater improvement after ECT. Concentration difficulties and apparent sadness showed the greatest centrality.

In conclusion, ECT treatment may affect not only the severity of the symptoms but also their relationship; this may contribute to the response in DTD.

Older people with depression exhibit better response to electroconvulsive therapy (ECT). We aimed to measure the total effect of age on ECT response and investigate whether this effect is mediated by psychotic features, psychomotor retardation, psychomotor agitation, age of onset, and episode duration.

We pooled data from four prospective Irish studies where ECT was administered for a major depressive episode (unipolar or bipolar) with baseline score ≥21 on the 24-item Hamilton Depression Rating Scale (HAM-D). The primary outcome was change in HAM-D between baseline and end of treatment. The estimands were total effect of age, estimated using linear regression, and the indirect effects for each putative mediator, estimated using causal mediation analyses.

A total of 256 patients (mean age 57.8 [SD = 14.6], 60.2% female) were included. For every additional 10 years of age, HAM-D was estimated to decrease by a further 1.74 points over the ECT period (p < 0.001). Age acted on all putative mediators. Mechanistic theories, whereby a mediator drives treatment response, were confirmed for all putative mediators except age of onset. Consequently, mediation of the effect of age on change in HAM-D could be demonstrated for psychotic features, psychomotor retardation, psychomotor agitation, and episode duration but not for age of onset.

A total of 43.1% of the effect of older age on increased ECT response was explained by the mediators. Treatment planning could be improved by preferentially offering ECT to older adults, especially if presenting with psychotic features, greater severity of psychomotor disturbance, and earlier in the episode.

Quality of life is decreased in bipolar disorders (BD) and contributes to poor prognosis. However, little is known about the causal pathways that may affect it. This study aimed to explore health-related QoL (HRQoL) in BD and investigate its relationship with cognition and psychosocial functioning.

This multicenter cross-sectional study used a neuropsychological battery to assess five cognition domains. Functioning was evaluated using global and domain-based tools, and health-related HRQoL was assessed using the EQ-5D-3L. Structural equation modeling was used to test whether the association between cognition and HRQoL would be mediated by functioning in BD while controlling for covariates such as residual depression, anxiety, antipsychotic medication, and psychotic features.

We included 1 190 adults with euthymic BD. The model provided a good fit for the data. In this model, the direct effect of cognition on HRQoL was not significant (β = − 0.03, z = −0.78, p = 0.433). The total effect of cognition on HRQoL was weak, albeit significant (β = 0.05, z = 3.6, p < 0.001), thus suggesting that cognition affected HRQoL only indirectly through functioning. Anxiety was associated with decreased functioning (β = −0.27, z = −7.4, p < 0.001) and QoL (β = −0.39, z = −11.8, p < 0.001).

These findings suggest that improving cognition may not directly lead to a higher HRQoL. Cognitive remediation is expected to improve HRQoL only through functioning enhancement. They also reveal the potential importance of functional remediation and reduction of comorbid anxiety symptoms in improving HRQoL in BD.

There is a significant contribution of genetic factors to the etiology of bipolar disorder (BD). Unaffected first-degree relatives of patients (UR) with BD are at increased risk of developing mental disorders and may manifest cognitive impairments and alterations in brain functional and connective dynamics, akin to their affected relatives.

In this prospective longitudinal study, resting-state functional connectivity was used to explore stable and progressive markers of vulnerability i.e. abnormalities shared between UR and BD compared to healthy controls (HC) and resilience i.e. features unique to UR compared to HC and BD in full or partial remission (UR n = 72, mean age = 28.0 ± 7.2 years; HC n = 64, mean age = 30.0 ± 9.7 years; BD patients n = 91, mean age = 30.6 ± 7.7 years). Out of these, 34 UR, 48 BD, and 38 HC were investigated again following a mean time of 1.3 ± 0.4 years.

At baseline, the UR showed lower connectivity values within the default mode network (DMN), frontoparietal network, and the salience network (SN) compared to HC. This connectivity pattern in UR remained stable over the follow-up period and was not present in BD, suggesting a resilience trait. The UR further demonstrated less negative connectivity between the DMN and SN compared to HC, abnormality that remained stable over time and was also present in BD, suggesting a vulnerability marker.

Our findings indicate the coexistence of both vulnerability-related abnormalities in resting-state connectivity, as well as adaptive changes possibly promoting resilience to psychopathology in individual at familial risk.

This cross-sectional study aimed to observe the occurrence of metabolic syndrome in untreated individuals with bipolar disorders.

A total of 125 untreated individuals with bipolar disorders were collected as the study group, and 201 cases from the health examination centre of our hospital were selected as the control group. The participants enrolled were assessed for general demographic data, case characteristics, and metabolic indexes including body mass index (BMI), blood pressure, triglyceride, high-density lipoprotein-cholesterol, cholesterol, low-density lipoprotein-cholesterol, and fasting plasma glucose.

The incidence of metabolic syndrome in the bipolar disorders group was higher compared to the control group (9.6% VS. 8.5%). After calibrating sex and age data, a significant difference between the two groups was observed (P < 0.05). Diastolic and systolic blood pressure were higher in the bipolar disorders group compared to the control group (P < 0.01). Men with bipolar disorders had a higher risk of developing metabolic syndrome than women (14.5% vs. 5.8%). Bipolar disorders, sex, age, and BMI were identified as independent risk factors for metabolic syndrome. No significant difference was found in terms of metabolic index and incidence of metabolic syndrome between individuals with depressive episodes (n = 37) and manic episodes (n = 75).

Patients with bipolar disorders were found to have a higher risk of developing metabolic syndrome than healthy individuals. Bipolar disorders, male sex, age, and BMI may contribute to an increased risk of developing metabolic syndrome.

Studies about brain structure in bipolar disorder have reported conflicting findings. These findings may be explained by the high degree of heterogeneity within bipolar disorder, especially if structural differences are mapped to single brain regions rather than networks.

We aim to complete a systematic review and meta-analysis to identify brain networks underlying structural abnormalities observed on T1-weighted magnetic resonance imaging scans in bipolar disorder across the lifespan. We also aim to explore how these brain networks are affected by sociodemographic and clinical heterogeneity in bipolar disorder.

We will include case–control studies that focus on whole-brain analyses of structural differences between participants of any age with a standardised diagnosis of bipolar disorder and controls. The electronic databases Medline, PsycINFO and Web of Science will be searched. We will complete an activation likelihood estimation analysis and a novel coordinate-based network mapping approach to identify specific brain regions and brain circuits affected in bipolar disorder or relevant subgroups. Meta-regressions will examine the effect of sociodemographic and clinical variables on identified brain circuits.

Findings from this systematic review and meta-analysis will enhance understanding of the pathophysiology of bipolar disorder. The results will identify brain circuitry implicated in bipolar disorder, and how they may relate to relevant sociodemographic and clinical variables across the lifespan.

Mental imagery, or ‘seeing with the mind’s eye’ (Kosslyn et al. 2001), provokes strong emotional responses (Ji et al., 2016). 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.

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

Forty-two euthymic individuals diagnosed with BD (American Psychiatric Association, 2013) 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).

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.

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.

Individuals with bipolar disorders (BD) are at risk of premature death, mainly due to medical comorbidities. Childhood maltreatment might contribute to this medical morbidity, which remains underexplored in the literature.

We assessed 2891 outpatients with BD (according to DSM-IV criteria). Childhood maltreatment was assessed using the Childhood Trauma Questionnaire. Lifetime diagnoses for medical disorders were retrospectively assessed using a systematic interview and checked against medical notes. Medical morbidity was defined by the sum of medical disorders. We investigated associations between childhood maltreatment (neglect and abuse) and medical morbidity while adjusting for potential confounders.

One quarter of individuals had no medical comorbidities, while almost half of them had at least two. Multivariable regression showed that childhood maltreatment (mainly abuse, but also sexual abuse) was associated with a higher medical morbidity. Medical morbidity was also associated with sex, age, body mass index, sleep disturbances, lifetime anxiety disorders and lifetime density of mood episodes. Childhood maltreatment was associated with an increased prevalence of four (i.e. migraine/headache, drug eruption, duodenal ulcer, and thyroid diseases) of the fifteen most frequent medical disorders, however with no difference in terms of age at onset.

This large cross-sectional study confirmed a high medical morbidity in BD and its association with childhood maltreatment. The assessment of childhood maltreatment in individuals with BD should be systematically included in routine care and the potential impact on physical health of psycho-social interventions targeting childhood maltreatment and its consequences should be evaluated.

Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.

We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.

BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.

We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.

Bipolar disorder is a chronic mental disorder related to cognitive deficits. Low serum vitamin D levels are significantly associated with compromised cognition in neuropsychiatric disorders. Although patients with bipolar disorder frequently exhibit hypovitaminosis D, the association between vitamin D and cognition in bipolar disorder, and their neuroaxonal integrity, is unclear.

To investigate the interaction effects between vitamin D and neurofilament light chain (NfL) levels on cognitive domains in bipolar disorder.

Serum vitamin D and NfL levels were determined in 100 euthymic patients with bipolar disorder in a cross-sectional study. Cognitive function was measured with the Brief Assessment of Cognition in Affective Disorders. We stratified by age groups and used general linear models to identify associations between vitamin D and NfL levels and their interaction effects on cognitive domains.

The mean vitamin D and NfL levels were 16.46 ng/nL and 11.10 pg/mL, respectively; 72% of patients were vitamin D deficient. In the older group, more frequent hospital admissions and lower physical activity were identified in the group with versus without vitamin D deficiency. The age-modified interaction effect of vitamin D and NfL was associated with composite neurocognitive scores and verbal fluency in both age groups, and with processing speed domain in the younger group.

We observed a high vitamin D deficiency prevalence in bipolar disorder. We identified the interaction of vitamin D and NfL on cognitive domains, and the effect was modified by age. Longitudinal or randomised controlled studies enrolling patients with various illness durations and mood statuses are required to validate our findings.

Severe mental disorders experience premature mortality mostly from physical causes. When a patient with a history of bipolar disorder is admitted to the emergency room (ER) for psychiatric symptoms, these are routinely interpreted as a psychiatric disturbance. However, a careful history should be performed to correctly interpret key clinical information to rule out somatic etiology and establish adequate diagnosis.

To describe a patient whose presenting symptoms were misdiagnosed as psychiatric relapse, rather than serious somatic comorbidity debut.

A 70-year-old man, with a history of type I bipolar disorder and multiple cardiovascular conditions, was admitted to the ER for self-referred nervousness, depressed mood, insomnia, and suicidal thoughts. Symptoms had greatly worsened the previous week to his consultation with paroxysmal episodes of severe anxiety, feelings of strangeness, and sensations of unpleasant odors.

During observation, the patient was found lying down with loss of consciousness, urinary incontinence, and amnesia of the event. Generalized tonic-clonic seizures were observed by neurologists while mental status examination was being performed. After symptoms were oriented as having a neurological etiology, the patient suffered cardiac arrest and defibrillation was required. After admittance to the intensive care unit and inpatient cardiology care, the patient was discharged from the hospital with the diagnosis of ventricular fibrillation due to drug-induced QT prolongation. There was no evidence of mixed depression or seizures once the cardiac dysfunction was identified and treated.

The psychiatric symptoms were the clinical manifestation of a generalized seizure-like activities that were attributed to transient cerebral hypoperfusion secondary to ventricular fibrillation.

No significant relationships.

Mood disorders are common psychiatric illnesses with major disability and mortality and it is estimated that 8% to 20% of the population experience a depressive episode at some point in their lives.

To find out the prevalence of cognitive impairment among patients with Mood Disorders i.e, Major Depressive Disorder (MDD) and Bipolar Mood Disorder (BMD), etc. and to find out the status of cognitive impairment with clinical variables of Mood Disorders.

This was a descriptive cross-sectional study conducted among the patients attending both the inpatient and outpatient departments of the National Institute of Mental Health, Dhaka. The duration of the study was fourteen months starting from July 2011 to September 2012. A total of one hundred and thirty-three (n=133) patients who fulfilled the inclusion-exclusion criteria were selected.

The mean age of onset of mood disorder was 30.1± 10.7years.60.2% were male and 39.8% were female respondents. Cognitive impairment was found among 43.6% of the respondents. A substantial proportion of the study population was found to have cognitive impairment. In this study, the cognitive status of the respondents was not associated with the duration of illness (p>0.5).

So assessment of cognitive status should be an essential part of the management of this group of people.

No significant relationships.

Several psychological and psychiatric instruments have been developed to recognize or predict different psychiatric disorders.

We studied the predictive, and discriminant validity of different psychopathology scales and temperament traits for subsequent psychiatric diagnoses due to schizophrenia, bipolar and depressive disorders in a 23-year follow-up.

Temperament traits, perceptual aberration, physical and social anhedonia, depression and anxiety subscales of Symptom Checklist (SCL-D and SCL-A), Hypomanic Personality Scale (HPS), Schizoidia Scale, and Bipolar II Scale were completed as part of the 31-year follow-up survey of the prospective Northern Finland 1966 Birth Cohort (n = 5006). New onset psychiatric diagnoses were followed until age of 54 years using different nationwide registers.

In the follow-up 28 (0.6%) individuals had diagnosis of schizophrenia, 40 (0.8%) bipolar and 405 (8.1%) depressive disorders. Several of the included scales associated statistically significantly with subsequent diagnoses. High SCL-A and SCL-D scores were strong predictors (Cohen’s d’s between 0.76 and 1.08) for schizophrenia and depressive disorders, whereas high HPS score was best predictor (d=0.67) for bipolar disorders. When comparing patient groups, schizophrenia group had low scores in reward dependence when compared with both bipolar (d=-0.80) and depressive (d=-0.66) disorders. Harm avoidance was the best trait to discriminate depressive and bipolar disorders, with higher scores in depressive disorders (d=0.48).

Interestingly we found that differed psychopathology scales were strong but non-specific predictors for these psychiatric disorders, whereas temperament traits were useful predictors regarding discriminating these disorders. The presented scales can be used in population samples when predicting psychiatric illnesses.

No significant relationships.