Audrey Berardi, Jennifer A. Brown, Brooke S. Jackson, Ling-Yu Huang, Rebekah L. Trotti, David A. Parker, Scot K. Hill, Elena Ivleva, Godfrey D. Pearlson, Carol A. Tamminga, Matcheri S. Keshavan, Sarah K. Keedy, Elliot S. Gershon, John A. Sweeney, Brett A. Clementz, Jennifer E. McDowell
Aim
This study aimed to evaluate associations in bipolar disorder (BD) across multimodal measures of white matter microstructure (using diffusion tensor imaging; DTI), cognitive, behavioral, and brain electrophysiological measures (using electroencephalography; EEG).
Methods
Subjects were recruited through the Psychosis and Affective Research Domains and Intermediate Phenotypes Consortium (n = 45 bipolar with psychosis, n = 40 bipolar without psychosis, n = 66 healthy subjects). DTI data were used to quantify the white matter variables, fractional anisotropy (FA) and radial diffusivity (RD). The Brief Assessment of Cognition in Schizophrenia (BACS), Stop Signal Task (SST), pro- and anti-saccades, auditory event-related potentials (ERPs), and intrinsic brain activity were used as estimates of brain function.
Results
The combined BD group differed from healthy controls, but no differences between BD with and without psychosis were observed. BD-related white matter abnormalities were seen across multiple tracts: right cingulum–cingulate gyrus, bilateral anterior thalamic radiation, bilateral superior longitudinal fasciculus, right inferior longitudinal fasciculus, and forceps major. Results also showed modestly compromised cognitive performance and elevated intrinsic EEG activity associated with BD.
Conclusions
Further analysis indicated worse white matter integrity related to higher intrinsic EEG and modestly higher ERPs. These multimodal analyses are likely to aid in creating future informative diagnostic, etiological, and treatment targets for BD.
{"title":"White Matter, Cognition, and Electrophysiological Variables in Bipolar Disorder: Using Multimodal Integration of Biomarker Variables Associated With Bipolar Disorder to Elucidate Deficits","authors":"Audrey Berardi, Jennifer A. Brown, Brooke S. Jackson, Ling-Yu Huang, Rebekah L. Trotti, David A. Parker, Scot K. Hill, Elena Ivleva, Godfrey D. Pearlson, Carol A. Tamminga, Matcheri S. Keshavan, Sarah K. Keedy, Elliot S. Gershon, John A. Sweeney, Brett A. Clementz, Jennifer E. McDowell","doi":"10.1111/bdi.70010","DOIUrl":"10.1111/bdi.70010","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>This study aimed to evaluate associations in bipolar disorder (BD) across multimodal measures of white matter microstructure (using diffusion tensor imaging; DTI), cognitive, behavioral, and brain electrophysiological measures (using electroencephalography; EEG).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Subjects were recruited through the Psychosis and Affective Research Domains and Intermediate Phenotypes Consortium (<i>n</i> = 45 bipolar with psychosis, <i>n</i> = 40 bipolar without psychosis, <i>n</i> = 66 healthy subjects). DTI data were used to quantify the white matter variables, fractional anisotropy (FA) and radial diffusivity (RD). The Brief Assessment of Cognition in Schizophrenia (BACS), Stop Signal Task (SST), pro- and anti-saccades, auditory event-related potentials (ERPs), and intrinsic brain activity were used as estimates of brain function.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The combined BD group differed from healthy controls, but no differences between BD with and without psychosis were observed. BD-related white matter abnormalities were seen across multiple tracts: right cingulum–cingulate gyrus, bilateral anterior thalamic radiation, bilateral superior longitudinal fasciculus, right inferior longitudinal fasciculus, and forceps major. Results also showed modestly compromised cognitive performance and elevated intrinsic EEG activity associated with BD.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Further analysis indicated worse white matter integrity related to higher intrinsic EEG and modestly higher ERPs. These multimodal analyses are likely to aid in creating future informative diagnostic, etiological, and treatment targets for BD.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8959,"journal":{"name":"Bipolar Disorders","volume":"27 3","pages":"205-216"},"PeriodicalIF":5.0,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bdi.70010","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143623375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alessandro Pigoni, Isidora Tesic, Cecilia Pini, Paolo Enrico, Lorena Di Consoli, Francesca Siri, Guido Nosari, Adele Ferro, Letizia Squarcina, Giuseppe Delvecchio, Paolo Brambilla
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.
{"title":"Multimodal Machine Learning Prediction of 12-Month Suicide Attempts in Bipolar Disorder","authors":"Alessandro Pigoni, Isidora Tesic, Cecilia Pini, Paolo Enrico, Lorena Di Consoli, Francesca Siri, Guido Nosari, Adele Ferro, Letizia Squarcina, Giuseppe Delvecchio, Paolo Brambilla","doi":"10.1111/bdi.70011","DOIUrl":"10.1111/bdi.70011","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8959,"journal":{"name":"Bipolar Disorders","volume":"27 3","pages":"217-231"},"PeriodicalIF":5.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bdi.70011","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143571594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alexander Kautzky, Emma Pettersson, Ridwanul Amin, Aemal Akhtar, Antti Tanskanen, Heidi Taipale, Johannes Wancata, Katalin Gemes, Ellenor Mittendorfer-Rutz
<div> <section> <h3> Background</h3> <p>Deviations in treatment practices toward immigrant groups compared to host populations are common in mental disorders but unknown in bipolar disorder (BD). We aim to close this research gap by analyzing age-stratified use patterns of antidepressants, mood stabilizers, and antipsychotics following an incident diagnosis of BD in Swedish-born, second- and first-generation nonrefugee immigrants, and refugees.</p> </section> <section> <h3> Methods</h3> <p>Individuals with incident BD between 2006 and 2018 were identified through Swedish national registers. Medication use was followed up until 5 years after diagnosis. Use rates adjusted for sociodemographic and disease-related covariates were computed with generalized estimation equations for each population group. Marginal means with 95% confidence intervals (CIs) and significance tests for main and interaction effects of population group and time points are presented. Furthermore, significant effects of population group, age group, time point, and their interaction were tested by Type III joint test yielding <i>F</i> and <i>p</i> values.</p> </section> <section> <h3> Results</h3> <p>Three months after diagnosis, estimated rates of lack of treatment differed significantly between population groups (<i>p</i> < 0.0001) as Swedish-born (17.3%, CI: 16.8–17.7) lacked disease-specific treatment less often than second-generation immigrants (21.1%, 19.7–22.5), first-generation nonrefugee immigrants (23.1%, 21.3–25.0) and refugees (26.8%, 24.4–29.4). Antidepressant monotherapy was estimated in 17.7% (17.2–18.1) of Swedish-born, 16.8% (15.5–18.3) of second-generation immigrants, 17.7% (16.2–19.4) of first-generation nonrefugee immigrants, and was most prevalent in refugees (20.3%, 18.2–22.7; population group <i>p</i> = 0.0002). Mood stabilizers were most dispensed by Swedish-born (51.3%, 50.6–51.9), followed by second-generation (47.9%, 46.1–49.8) and first-generation nonrefugee immigrants (44.5%, 42.4–46.7) and refugees (35.4%, 32.8–38.2; population group <i>p</i> < 0.0001). Use rates of antipsychotics were similar between population groups (<i>p</i> > 0.05) and estimated at 14.1% (13.7–14.6) in Swedish-born, 14.0% (12.8–15.3) in second-generation, 13.0% in first-generation nonrefugee immigrants (12.0–14.6), and 12.9% (11.1–15.0) in refugees. Following up significant interactions of population and age group, lithium use was estimated to be lower in refugees aged 36–65 years (9.9%, 7.9–12.5; population group <i>p</i> = 0.0008) and olanzapine use to be higher in refugees aged 16–35 (9.2%, 7.1–11.9; population group <i>p</i> = 0.0002), respectively, compared to other
{"title":"Treatment Patterns for Incident Bipolar Disorder Among Nonrefugee Immigrants, Refugees, Second-Generation Immigrants, and Host Population in Sweden","authors":"Alexander Kautzky, Emma Pettersson, Ridwanul Amin, Aemal Akhtar, Antti Tanskanen, Heidi Taipale, Johannes Wancata, Katalin Gemes, Ellenor Mittendorfer-Rutz","doi":"10.1111/bdi.70007","DOIUrl":"10.1111/bdi.70007","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Deviations in treatment practices toward immigrant groups compared to host populations are common in mental disorders but unknown in bipolar disorder (BD). We aim to close this research gap by analyzing age-stratified use patterns of antidepressants, mood stabilizers, and antipsychotics following an incident diagnosis of BD in Swedish-born, second- and first-generation nonrefugee immigrants, and refugees.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Individuals with incident BD between 2006 and 2018 were identified through Swedish national registers. Medication use was followed up until 5 years after diagnosis. Use rates adjusted for sociodemographic and disease-related covariates were computed with generalized estimation equations for each population group. Marginal means with 95% confidence intervals (CIs) and significance tests for main and interaction effects of population group and time points are presented. Furthermore, significant effects of population group, age group, time point, and their interaction were tested by Type III joint test yielding <i>F</i> and <i>p</i> values.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Three months after diagnosis, estimated rates of lack of treatment differed significantly between population groups (<i>p</i> < 0.0001) as Swedish-born (17.3%, CI: 16.8–17.7) lacked disease-specific treatment less often than second-generation immigrants (21.1%, 19.7–22.5), first-generation nonrefugee immigrants (23.1%, 21.3–25.0) and refugees (26.8%, 24.4–29.4). Antidepressant monotherapy was estimated in 17.7% (17.2–18.1) of Swedish-born, 16.8% (15.5–18.3) of second-generation immigrants, 17.7% (16.2–19.4) of first-generation nonrefugee immigrants, and was most prevalent in refugees (20.3%, 18.2–22.7; population group <i>p</i> = 0.0002). Mood stabilizers were most dispensed by Swedish-born (51.3%, 50.6–51.9), followed by second-generation (47.9%, 46.1–49.8) and first-generation nonrefugee immigrants (44.5%, 42.4–46.7) and refugees (35.4%, 32.8–38.2; population group <i>p</i> < 0.0001). Use rates of antipsychotics were similar between population groups (<i>p</i> > 0.05) and estimated at 14.1% (13.7–14.6) in Swedish-born, 14.0% (12.8–15.3) in second-generation, 13.0% in first-generation nonrefugee immigrants (12.0–14.6), and 12.9% (11.1–15.0) in refugees. Following up significant interactions of population and age group, lithium use was estimated to be lower in refugees aged 36–65 years (9.9%, 7.9–12.5; population group <i>p</i> = 0.0008) and olanzapine use to be higher in refugees aged 16–35 (9.2%, 7.1–11.9; population group <i>p</i> = 0.0002), respectively, compared to other","PeriodicalId":8959,"journal":{"name":"Bipolar Disorders","volume":"27 3","pages":"192-204"},"PeriodicalIF":5.0,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bdi.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143571668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaofei Zhang, Tao lin, Guanjie Zhang, Jianshan Chen, Xichao Wang, Wanheng Zhang, Xiaoqing Zhang, Jiaqi Sun, Weiming Li, Yutong Liu, Xuanlin Zeng, Lei Chen, Yimiao Mao, Biyu Ye, Yanling Zhou, Xuan Li, Chanjuan Yang, Liping Cao, Yuping Ning
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 (dHc Vs. Mdd-sub = 0.70–0.78; dMDD-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.
背景：双相情感障碍（BD）的海马亚区病理已经确立；然而，目前还没有研究调查临床双相障碍高风险青少年（MDD-Sub）的这些改变，这是一个关键的空白，因为青春期是早期干预的神经发育窗口。方法：我们分析了sBEAD队列中72名临床BD“MDD- sub”高危青少年MDD- sub与MDD- nsub、74名单纯MDD青少年（MDD- nsub）和72名12-18岁健康青少年（HC）的基线3D t1加权MRI数据。使用FreeSurfer 7.3.1对海马子区进行分割。所有患者随访至少12个月，以确保在MDD-nSub组中没有参与者进展为精神分裂症或出现新的躁狂症状。结果：即使在控制药物效应后，MDD-Sub仍表现出左角氨（CA）1、CA3、CA4、分子层（ML）和齿状回（DG）体积的显著减少(dHc Vs. MDD-Sub = 0.70-0.78；mddd - sub vs. MDD-nSub = 0.50-0.61)。引人注目的是，病程bbbb1年预测双侧CA1/ML/DG和左侧CA3/CA4容量增加（R2 = 0.13-0.21, p）。这项针对双相障碍高危青少年的首次海马亚区研究表明，前驱症状特异性左侧CA1、CA3、CA4、ML和DG萎缩可能有助于区分双相障碍与单极抑郁症的风险，而非线性体积轨迹（早期减少，随后随着病程延长代偿性增加）为经典神经变性范式提供了新的视角。这些发现为阶段特异性干预提供了初步的生物学支持，增强了转换前的神经可塑性和转换后的神经保护。
{"title":"Hippocampal Volume Reductions in Key Regions and Their Role in Disease Progression in Adolescents at High Risk for Bipolar Disorder: Findings From the sBEAD Cohort","authors":"Xiaofei Zhang, Tao lin, Guanjie Zhang, Jianshan Chen, Xichao Wang, Wanheng Zhang, Xiaoqing Zhang, Jiaqi Sun, Weiming Li, Yutong Liu, Xuanlin Zeng, Lei Chen, Yimiao Mao, Biyu Ye, Yanling Zhou, Xuan Li, Chanjuan Yang, Liping Cao, Yuping Ning","doi":"10.1111/bdi.70014","DOIUrl":"10.1111/bdi.70014","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>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<sub>Hc Vs. Mdd-sub</sub> = 0.70–0.78; d<sub>MDD-Sub vs. MDD-nSub</sub> = 0.50–0.61). Strikingly, illness duration > 1 year predicted volumetric increases in bilateral CA1/ML/DG and left CA3/CA4 (<i>R</i><sup>2</sup> = 0.13–0.21, <i>p</i> < 0.05), replicated in medication-naïve MDD-Sub (<i>n</i> = 32). MDD-nSub showed no subfield differences versus HC and MDD-Sub.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8959,"journal":{"name":"Bipolar Disorders","volume":"27 3","pages":"232-245"},"PeriodicalIF":5.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143540052","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Katie M. Douglas, Zoe A. Odering, Jennifer Jordan, Marie T. Crowe, Cameron J. Lacey, Christopher M. Frampton, Ian R. E. Averill, Cecilia Smith Hamel, Christopher R. Bowie, Richard J. Porter
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.
{"title":"Impact of Activation Therapy for Inpatients With Major Depression: Primary and Secondary Outcomes From a Randomised Controlled Trial","authors":"Katie M. Douglas, Zoe A. Odering, Jennifer Jordan, Marie T. Crowe, Cameron J. Lacey, Christopher M. Frampton, Ian R. E. Averill, Cecilia Smith Hamel, Christopher R. Bowie, Richard J. Porter","doi":"10.1111/bdi.70021","DOIUrl":"10.1111/bdi.70021","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Method</h3>\u0000 \u0000 <p>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).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Ninety-seven individuals were randomised to AT (<i>n</i> = 47) or TAU (<i>n</i> = 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 (<i>d</i> = 0.42) and general functioning (<i>d</i> = 0.58) were in favour of the AT versus TAU arms. Per protocol analysis showed additional significant effects of AT on psychomotor speed (<i>d</i> = 0.64) and clinician-rated depression symptoms (<i>d</i> = 0.56). No significant effects were observed for other secondary outcomes (subjective cognition, self-reported depression symptoms, and deactivation symptoms).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8959,"journal":{"name":"Bipolar Disorders","volume":"27 4","pages":"298-309"},"PeriodicalIF":5.0,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/bdi.70021","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143536377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lindsay M. Melhuish Beaupre, Brandon J. Coombes, Anthony Batzler, Jorge A. Sanchez-Ruiz, Bhanu Prakash Kolla, Francisco Romo-Nava, Vanessa Pazdernik, Gregory Jenkins, T. Cameron Waller, Michelle Skime, Susan L. McElroy, Mark A. Frye, Joanna M. Biernacka
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.
背景：失眠和物质使用障碍（SUD）是双相情感障碍（BD）的常见合并症。全基因组关联研究（GWAS）发现了失眠和双相障碍以及sud和BD的共同遗传贡献。电子健康记录（EHR）衍生表型（phecodes）和问卷数据用于检查失眠遗传倾向与BD中sud之间的关系。n = 774)和Mayo Clinic Biobank （n = 485例BD病例，n = 39580名对照）纳入诊断（phecode）结局（失眠、SUD、酒精使用障碍[AUD]和烟草使用障碍[TUD]）的分析。通过BD Biobank问卷调查获得的特定SUD结果分析包括1789例，并被认为是BD亚型。采用Logistic回归检验失眠多基因风险评分（PRS）与BD病例和对照组失眠和SUD结局之间的关系。结果：失眠PRS与对照组EHR中失眠诊断（phecode）相关（OR = 1.19, p = 9.64e-33），但与BD病例无关（OR = 1, p = 0.95）。失眠PRS与SUD诊断在双相障碍组和对照组中存在显著相关性，其中双相障碍组相关性更强（交互作用p = 0.024）。在BD Biobank的数据中，失眠PRS与AUD （OR = 1.19, p = 4.26e-04）、TUD （OR = 1.21, p = 1.25e-05）和大麻使用障碍（OR = 1.16, p = 4.19e-03）的几率增加相关。结论：遗传失眠易感性对双相障碍患者SUD风险的影响可能强于对照组，这可能对双相障碍合并合并SUD的个体具有临床护理意义。
{"title":"Exploration of Genetic Liability to Insomnia and Substance Use Disorders in Patients With Bipolar Disorder","authors":"Lindsay M. Melhuish Beaupre, Brandon J. Coombes, Anthony Batzler, Jorge A. Sanchez-Ruiz, Bhanu Prakash Kolla, Francisco Romo-Nava, Vanessa Pazdernik, Gregory Jenkins, T. Cameron Waller, Michelle Skime, Susan L. McElroy, Mark A. Frye, Joanna M. Biernacka","doi":"10.1111/bdi.70018","DOIUrl":"10.1111/bdi.70018","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>40,839 participants from the Mayo Clinic Bipolar Disorder Biobank (BD Biobank; <i>n</i> = 774) and Mayo Clinic Biobank (<i>n</i> = 485 BD cases, <i>n</i> = 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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Insomnia PRS was associated with having an insomnia diagnosis (phecode) in the EHR in controls (OR = 1.19, <i>p</i> = 9.64e-33) but not in BD cases (OR = 1, <i>p</i> = 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 <i>p</i> = 0.024). In the BD Biobank data, the insomnia PRS was associated with increased odds of AUD (OR = 1.19, <i>p</i> = 4.26e-04), TUD (OR = 1.21, <i>p</i> = 1.25e-05) and cannabis use disorder (OR = 1.16, <i>p</i> = 4.19e-03).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8959,"journal":{"name":"Bipolar Disorders","volume":"27 4","pages":"280-288"},"PeriodicalIF":5.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143498823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Miguel Ángel Rivas-Fernández, Montserrat Domingo-Ayllón, Michele De Prisco, Paloma Fernández-Corcuera, Erick J. Canales-Rodríguez, Eduard Vieta, Edith Pomarol-Clotet, Joaquim Radua
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.
{"title":"Impact of Bipolar Disorder Increased White Matter Hyperintensities on White Matter Connectivity","authors":"Miguel Ángel Rivas-Fernández, Montserrat Domingo-Ayllón, Michele De Prisco, Paloma Fernández-Corcuera, Erick J. Canales-Rodríguez, Eduard Vieta, Edith Pomarol-Clotet, Joaquim Radua","doi":"10.1111/bdi.70019","DOIUrl":"10.1111/bdi.70019","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>An expert neuroradiologist blindly assessed the type, size, and location of WMH from 128 FLAIR scans (bipolar disorder: <i>n</i> = 64, age = 38 ± 7 years; 53% females; matched healthy controls: <i>n</i> = 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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8959,"journal":{"name":"Bipolar Disorders","volume":"27 4","pages":"289-297"},"PeriodicalIF":5.0,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143498785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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.
{"title":"What Is the Depressive Mixed State?—Associated Factors Beyond Bipolarity","authors":"Minoru Takeshima, Takeshi Inoue","doi":"10.1111/bdi.70016","DOIUrl":"10.1111/bdi.70016","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Objectives</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>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], <i>p</i> < 0.001, and 6.14 [2.96–12.76], <i>p</i> < 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.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>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.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8959,"journal":{"name":"Bipolar Disorders","volume":"27 2","pages":"144-151"},"PeriodicalIF":5.0,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143490731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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