Bipolar Disorders最新文献

Introduction: Bipolar disorder (BD) patients present an increased risk of suicide attempts. Most current machine learning (ML) studies predicting suicide attempts are cross-sectional, do not employ time-dependent variables, and do not assess more than one modality. Therefore, we aimed to predict 12-month suicide attempts in a sample of BD patients, using clinical and brain imaging data.

Methods: A sample of 163 BD patients were recruited and followed up for 12 months. Gray matter volumes and cortical thickness were extracted from the T1-weighted images. Based on previous literature, we extracted 56 clinical and demographic features from digital health records. Support Vector Machine was used to differentiate BD subjects who attempted suicide. First, we explored single modality prediction (clinical features, GM, and thickness). Second, we implemented a multimodal stacking-based data fusion framework.

Results: During the 12 months, 6.13% of patients attempted suicide. The unimodal classifier based on clinical data reached an area under the curve (AUC) of 0.83 and balanced accuracy (BAC) of 72.7%. The model based on GM reached an AUC of 0.86 and BAC of 76.4%. The multimodal classifier (clinical + GM) reached an AUC of 0.88 and BAC of 83.4%, significantly increasing the sensitivity. The most important features were related to suicide attempts history, medications, comorbidities, and depressive polarity. In the GM model, the most relevant features mapped in the frontal, temporal, and cerebellar regions.

Conclusions: By combining models, we increased the detection of suicide attempts, reaching a sensitivity of 80%. Combining more than one modality proved a valid method to overcome limitations from single-modality models and increasing overall accuracy.

Background: Hippocampal subfield pathology is established in bipolar disorder (BD); yet no studies have investigated these alterations in adolescents at clinical high risk for BD (MDD-Sub), which is a critical gap given adolescence as a neurodevelopmental window for early intervention.

Methods: We analyzed baseline 3D T1-weighted MRI data from 72 adolescents at Clinical High Risk for BD "MDD-Sub"MDD-Sub vs. MDD-nSub, 74 pure adolescents with MDD (MDD-nSub), and 72 healthy adolescents (HC) aged 12-18 years in the sBEAD cohort. Hippocampal subfields were segmented using FreeSurfer 7.3.1. All patients were followed up for at least 12 months to ensure that no participants progressed to schizophrenia or developed new manic symptoms in the MDD-nSub group.

Results: MDD-Sub exhibited significant volume reductions in the left cornu ammonis (CA)1, CA3, CA4, molecular layer (ML) and dentate gyrus (DG) even after controlling for medication effects (d_{Hc Vs. Mdd-sub} = 0.70-0.78; d_{MDD-Sub vs. MDD-nSub} = 0.50-0.61). Strikingly, illness duration > 1 year predicted volumetric increases in bilateral CA1/ML/DG and left CA3/CA4 (R² = 0.13-0.21, p < 0.05), replicated in medication-naïve MDD-Sub (n = 32). MDD-nSub showed no subfield differences versus HC and MDD-Sub.

Conclusions: This first hippocampal subfield study in BD high-risk adolescents suggests that prodromal-specific left CA1, CA3, CA4, ML, and DG atrophy may help differentiate BD risk from unipolar depression, while nonlinear volumetric trajectories, characterized by early reductions followed by compensatory increases with prolonged illness duration, provide new perspectives on classical neurodegeneration paradigms. These findings provide initial biological support for stage-specific interventions, enhancing neuroplasticity pre-conversion versus neuroprotection post-conversion.

Introduction: Inpatient depression is associated with high morbidity and significant cognitive impairment. Inpatient treatment often focuses on short-term stabilization with medication. Readmission rates are high. We examined the impact of a novel psychological intervention, activation therapy (AT, Behavioural Activation combined with Cognitive Activation), versus treatment as usual (TAU) on readmission rates, and cognitive, functional, and depression outcomes, in inpatient depression.

Method: A randomised controlled trial in adults hospitalised with a major depressive episode. Inpatients were randomised to AT (8 individual sessions over 2 weeks) or not (TAU). Key time points were baseline (on admission) and 14 weeks after baseline. The primary outcome was psychiatric hospital readmission rates within 12 weeks of discharge. Secondary outcomes were cognition, general functioning, depression, and 'deactivation' symptoms (change from baseline to 14 weeks).

Results: Ninety-seven individuals were randomised to AT (n = 47) or TAU (n = 50). Readmission rates did not differ between treatment arms (34% vs. 40%; OR = 0.76, CI = 0.30-1.90). Significant improvements for verbal learning and memory (d = 0.42) and general functioning (d = 0.58) were in favour of the AT versus TAU arms. Per protocol analysis showed additional significant effects of AT on psychomotor speed (d = 0.64) and clinician-rated depression symptoms (d = 0.56). No significant effects were observed for other secondary outcomes (subjective cognition, self-reported depression symptoms, and deactivation symptoms).

Conclusions: The AT intervention showed durable, pro-cognitive effects. Further adaptations of AT, such as the addition of maintenance sessions as patients transition to community-based care, need exploring.

Background: Insomnia and substance use disorders (SUD) are common comorbidities of bipolar disorder (BD). Genome-wide association studies (GWAS) have uncovered shared genetic contributions to insomnia and BD as well as SUDs and BD. Electronic health record (EHR) derived phenotypes (phecodes) and questionnaire data were used to examine the relationship between insomnia genetic liability and SUDs in BD.

Methods: 40,839 participants from the Mayo Clinic Bipolar Disorder Biobank (BD Biobank; n = 774) and Mayo Clinic Biobank (n = 485 BD cases, n = 39,580 controls) were included in the analyses of diagnosis (phecode) outcomes (insomnia, SUD, alcohol use disorder [AUD] and tobacco use disorder [TUD]). Analyses of specific SUD outcomes obtained through the BD Biobank questionnaire included 1789 cases and considered BD subtype. Logistic regression was used to test for associations between insomnia polygenic risk scores (PRS) and insomnia and SUD outcomes in BD cases and controls.

Results: Insomnia PRS was associated with having an insomnia diagnosis (phecode) in the EHR in controls (OR = 1.19, p = 9.64e-33) but not in BD cases (OR = 1, p = 0.95). Associations between insomnia PRS and SUD diagnoses were significant in BD cases and controls, with the association being stronger in BD cases (interaction p = 0.024). In the BD Biobank data, the insomnia PRS was associated with increased odds of AUD (OR = 1.19, p = 4.26e-04), TUD (OR = 1.21, p = 1.25e-05) and cannabis use disorder (OR = 1.16, p = 4.19e-03).

Conclusion: The effect of genetic predisposition to insomnia on SUD risk may be stronger in BD cases than in controls, which could have clinical care implications for individuals with BD and comorbid SUD.

Background: Individuals with bipolar disorder have been reported to have increased white matter hyperintensities (WMH) in fluid-attenuated inversion recovery (FLAIR) magnetic resonance scans. However, it is unknown whether this WMH increase has any impact on white matter connectivity. The present study aimed to evaluate the effects of the bipolar disorder-related WMH increase on white matter tracts and networks.

Methods: An expert neuroradiologist blindly assessed the type, size, and location of WMH from 128 FLAIR scans (bipolar disorder: n = 64, age = 38 ± 7 years; 53% females; matched healthy controls: n = 64, age = 36 ± 10 years, 58% females). Afterward, we conducted an atlas-based analysis comparing the mean percentage parcel of damage in the white matter tracts of the Human Connectome Project tractography template and the networks of the 7-Network Cortical Parcellation template.

Results: We did not detect WMH-related effects on white matter connectivity when correcting for multiple comparisons. However, at the uncorrected level, we found a higher WMH-related white matter disconnection in the right inferior fronto-occipital fasciculus and the right middle longitudinal fasciculus.

Conclusion: This study evaluates, for the first time, the impact of WMH on bipolar brain structural connectivity. It finds an effect on two fasciculi, providing hints into one potential origin of the brain networks' alterations reported in the disorder. However, we only observed these results at the uncorrected statistical level, for which they are likely small and should be taken with caution until replicated.

Objectives: To elucidate the differences in associated factors beyond bipolarity between Benazzi's depressive mixed state (DMX), defined as a major depressive episode (MDE) with ≥ 3 manic/hypomanic symptoms, and the Diagnostic and Statistical Manual of Mental Disorders fifth edition criteria for mixed features (DSM-5-DMX), defined as an MDE with ≥ 3 non-overlapping manic/hypomanic symptoms.

Methods: The associations of DMX definitions with bipolarity, anxious distress (ANXD), autism spectrum disorder, attention-deficit hyperactivity disorder, and older age were retrospectively examined in 160 patients with MDEs.

Results: Benazzi's DMX and DSM-5-DMX were identified in 48.8% and 1.9% of participants, respectively. Bipolar disorder (BD) and ANXD diagnoses were independently associated with Benazzi's DMX (odds ratio, 95% confidence interval: 3.70 [1.79-7.67], p < 0.001, and 6.14 [2.96-12.76], p < 0.001, respectively). Benazzi's DMX was also associated with several features of poor prognosis and psychiatric adverse events related to antidepressant treatment. As the low frequency of DSM-5-DMX did not allow for its statistical analysis, a post hoc analysis of an MDE with ≥ 2 non-overlapping symptoms, accounting for 19.4% of participants, was performed. Similar to Benazzi's DMX, BD and ANXD diagnoses were independently associated with this definition of DMX. Moreover, the odds ratio of BD diagnosis was higher than that of ANXD.

Conclusion: Benazzi's DMX was independently associated with bipolarity and ANXD, and was also associated with poor prognosis. Exclusively defined DMX, such as DSM-5-DMX, may be more specifically associated with bipolarity; however, its sensitivity for predicting bipolarity is low for clinical practice. Further studies are required to validate these findings.

Background: The link between ventricular enlargement and asymmetry with other indices of brain structure remains underexplored in individuals with bipolar (BD) and depressive (DD) disorders. Our study compared the lateral ventricular size, ventricular asymmetry, and cortical myelin content in individuals with BD versus those with DD versus healthy controls (HC).

Methods: We obtained T1w and T2w images from 149 individuals (age = 27.7 (SD = 6.1) years, 78% female, BD = 38, DD = 57, HC = 54) using Magnetic Resonance Imaging (MRI). The BD group consisted of individuals with BD Type I (n = 11) and BD Type II (n = 27), while the DD group consisted of individuals with major depressive disorder (MDD, n = 38) and persistent depressive disorder (PDD, n = 19) Cortical myelin content was calculated using the T1w/T2w ratio. Elastic net regularized regression identified brain regions whose myelin content was associated with ventricular size and asymmetry. A post hoc linear regression examined how participants' diagnosis, illness duration, and current level of depression moderated the relationship between the size and asymmetry of the lateral ventricles and levels of cortical myelin in the selected brain regions.

Results: Individuals with BD and DD had larger lateral ventricles than HC. Larger ventricles and lower asymmetry were observed in individuals with BD who had longer lifetime illness duration and more severe current depressive symptoms. A greater left asymmetry was observed in participants with DD than in those with BD (p < 0.01). Elastic net revealed that both ventricular enlargement and asymmetry were associated with altered myelin content in cingulate, frontal, and sensorimotor cortices. In BD, but not in other groups, ventricular enlargement was related to altered myelin content in the right insular regions.

Conclusions: Lateral ventricular enlargement and asymmetry are linked to myelin content imbalance, thus potentially leading to emotional and cognitive dysfunction in mood disorders.