Citations

ABSTRACT Objectives To explore the clinical impact of social determinants of health (SDoH) stress in bipolar disorder (BD) course of illness and to explore potential gender differences in SDoH stress endorsement. Methods 2280 individuals living with BD type I or II (62% women; 67.5% BD‐I) participating in the Mayo Clinic Bipolar Biobank who completed a questionnaire assessing positive and negative‐valent stressors in the 12 months prior to study enrollment were included for this analysis. Six negative stressors were used as proxies of SDoH. Generalized linear models were used to test the association between SDoH stressors and markers of illness severity as well as potential differences by sex by including an interaction term. Results After adjusting for age, sex, and recruitment site, SDoH‐related stressors were significantly associated with a more severe course of illness in both men and women. Except for unemployment rates, women reported more frequently SDoH‐related stress (i.e., lack of family support, financial problems, health coverage and access problems). Conclusions The study found significant gender differences in both the endorsement of specific SDoH stressors and in the prevalence of specific illness severity markers; however, it did not directly test the predictive relationship between gender differences in SDoH and illness severity markers. Future studies aiming to achieve health equity in mental health care should continue assessing social determinants of health stressors, incorporating a gender perspective to better understand their influence on bipolar disorder.

Abstract Background: Responsiveness to mood-stabilizing pharmacotherapy varies in bipolar disorder (BD). We investigated clinical correlates of second-generation antipsychotic (SGA) treatment response and conducted the first genome-wide association study (GWAS), including exploratory polygenic scores (PGS), of SGA pharmacogenomic treatment response in BD. Methods: Treatment response was quantified using the Alda scale, and GWAS was performed using Alda-A score, controlling for sex, genotyping batch, and the genomic principal components. Results: The cohort included 2,159 adults with BD (1,416 BD-I, 691 BD-II, 51 schizoaffective BD), mean age 41.8 years, 62% female, 84% white, and 14% Hispanic. Nearly half (48%) were treated with SGAs. Current SGA users were younger (41.2±14.7 vs. 42.5±15.3 years, p =0.040), more likely to be Hispanic (14% vs. 11%, p =0.047), had a higher body mass index (BMI; 30.4±7.6 vs. 29.5±7.1 kg/m 2 , p =0.005). Lifetime comorbidity patterns for current SGA users include higher rates of manic psychosis (29% vs. 17%, p <0.001) and eating disorders — Anorexia Nervosa (7% vs. 4%, p =0.003), Bulimia Nervosa (7% vs. 4%, p =0.003), and Binge Eating Disorder (14% vs. 11%, p =0.030). We detected a genome-wide significant association between SGA Alda-A scores and GAS7 variants (top variant: rs202127418, β =-2.998, p =4.96E-08). However, SGA response was not significantly associated with PGS for schizophrenia, BD, and major depression (FDR>0.05). Conclusions: SGAs are frequently utilized as mood stabilizers in patients with BD and are associated with manic psychosis and eating disorders. GAS7 variants may predict SGA response, but larger, more diverse cohorts are needed for validation.

Abstract The lack of a molecular understanding of mood disorders has impeded progress in diagnosis and treatment. Glycosylation may provide insights into the complex mechanisms underlying these conditions. We conducted N-glycoproteomic analysis on dorsolateral prefrontal cortex samples from individuals with major depressive disorder (MDD) and bipolar disorder (BD), in depressive or manic states at death. Additionally, we examined depression prevalence in congenital disorders of glycosylation (CDG) through a literature review and assessment of 110 CDG patients. Glycoproteomic analysis revealed a significant increase in protein glycosylation in individuals with MDD relative to both controls and individuals with BD. Depression prevalence was lower in our pediatric and adult cohort of individuals with CDG. These results suggest brain glycosylation changes may play a role in mood disorder pathology and highlight the distinct biology of unipolar and bipolar depression. Our findings propose that impaired glycosylation may confer resilience to depression, offering potential therapeutic insights.

ABSTRACT Bipolar disorder’s (BD) clinical heterogeneity has an unresolved genetic basis. We meta-analyzed genome-wide association studies (GWAS) of 16 BD subphenotypes in 226,032 individuals from 57 cohorts (38,022 cases); 10 advanced to multivariate and multi-trait analyses. Four factors (compulsive, psychotic, dysregulated, internalizing) explained 82.8% of shared genetic variance. BD1 and BD2 loaded on distinct factors despite a high genetic correlation; 87.0% of common-factor loci were significant in neither subtype. Unipolar mania aligned with psychosis over internalizing, and was distinguishable from BD1, and rapid cycling showed heritable cross-domain liability. We identified 356 risk loci, 158 novel, including the first univariate-GWAS associations for psychosis, unipolar mania, rapid cycling and schizoaffective disorder—and 249 credible genes (89 high-confidence), 12 with approved-drug or clinical-phase annotations. Cell-type association showed a midbrain dopaminergic–GABAergic gradient along the psychotic factor. BD’s genetic architecture appears hierarchical—a general liability resolving into dimensions of course and comorbidity beyond diagnostic subtypes.

ABSTRACT Background Despite the classic Kraepelinian dichotomy between bipolar disorder (BD) and schizophrenia (SZ), contemporary evidence suggests shared antecedent risk factors and similarities in the early course. This study aimed to identify distinct trajectories leading to first‐episode mania (FEM) and first‐episode psychosis (FEP) by examining antecedent psychopathology, including psychiatric diagnoses, symptoms, substance use, and psychotropic medication exposure. Methods Individuals born after 1985 who resided in Olmsted County, Minnesota, USA, and had FEM/FEP were identified through the Rochester Epidemiology Project. Latent class analysis (LCA) was used to identify subgroups based on antecedent psychopathology incorporating 57 dichotomous antecedent measures before FEM/FEP. Results A total of 202 individuals ( BD n = 73, SZ n = 129; 26.7% female, mean age 20.8 ± 3.7 years) were included. A 3‐class LCA model optimally fits the data. Class 1 (Neurodevelopmental, 29.7%) had a high prevalence of neurodevelopmental disorders, behavioral symptoms, and ADHD medication use. Class 2 (Depressive‐Anxious, 31.2%) included depressive and anxiety disorders, mood‐related symptoms, and SSRI / SNRI use. Class 3 (Minimal Psychiatric Morbidity, 39.1%) had a low prevalence of antecedent diagnoses and symptoms, with comparable substance use to other classes. There were significant diagnostic differences, with SZ being more common in the Neurodevelopmental (71.7%) and Minimal Psychiatric Morbidity (70.9%) classes, while BD was more common in the Depressive‐Anxious class ( p = 0.007). Neurodevelopmental and Minimal Psychiatric Morbidity classes had higher proportions of males (85.0% and 82.3%, respectively) compared to the Depressive‐Anxious class (50.8%, p < 0.001). The Neurodevelopmental class showed an earlier age at first mental health visit (9.5 ± 5.5 years) and a longer antecedent illness duration (10.8 ± 6.1 years) than the other classes ( p < 0.001). Conclusion This study identified three distinct pathways to FEM and FEP, offering a transdiagnostic perspective on the antecedent illness trajectories of BD and SZ. Future research should validate these categories that are more inclusive than the classic BD versus SZ dichotomy and explore their potential for predicting illness course and guiding personalized early interventions.

ABSTRACTObjectiveTo build consensus from different stakeholders on the content and digital interactivity of a shared decision making (SDM) tool to guide patient‐clinician collaborative conversations about treatment for bipolar depression.Patients and MethodsThis study was conducted between September 2022 and September 2023. In the first phase, we conducted a narrative review on pharmacological, neuromodulatory, and psychotherapeutic treatments available for bipolar depression. For each option, we assessed treatment effectiveness, side effects, need for clinical monitoring, clinical considerations, and cost. In the second phase, committees comprised of mental health clinicians and people with lived experience with bipolar disorder from a national mood disorders advocacy group identified key features and content to be included in the SDM tool. A thematic analysis of these data then contributed to populate the SDM tool.ResultsTwenty‐one evidence‐based treatment options identified from the narrative review were presented to the four convened committees (clinical, lived experience, peer council, and integrated steering committees) in five meetings. After discussions and thematic analysis, 12 outcomes of interest for each of the therapeutic interventions were delineated for inclusion in a web‐based SDM tool. A detailed description of the development process and SDM tool is provided.ConclusionThis is the first partnership between clinicians and persons with bipolar disorder lived experience charged with the development of a patient‐centered SDM tool to integrate clinical evidence with real‐world clinical practice and patient preferences for use during clinical encounters. Human‐centered design and testing in real clinical encounters will now contribute to refining the instrument and readying it for rigorous evaluation and implementation in practice.

Abstract Bipolar Disorder (BD) is a highly complex and heterogeneous disorder. As such, accurate diagnosis is often delayed, and effective treatment options are limited. The Integrated Network, a program of Breakthrough Discoveries for thriving with Bipolar Disorder (BD 2 ), was designed as a platform for longitudinal deep phenotyping of a diverse group of people with bipolar disorder to define disease trajectories and to gain insight into the biological drivers of the illness. Biosamples, including whole blood, serum, plasma, and peripheral blood mononuclear cells (PBMCs) will be collected longitudinally and will also be made available. The Integrated Network is designed to be the largest and most comprehensive prospective longitudinal study conducted in bipolar disorder, allowing for the development of precision-based treatment strategies that optimize quality of life for people living with bipolar disorder.

Abstract Background: While bipolar disorder is strongly linked to an increased risk of suicide, recent evidence has challenged the assumption that mixed symptoms play a distinct role in suicidal ideation beyond depressive severity. This study examines how depressive, hypo/manic, and mixed features influence suicidal ideation in individuals with bipolar disorder. Data from 903 participants in the Stanley Foundation Bipolar Network (1995–2002) were analyzed to assess associations between mood states, classified by the Inventory of Depressive Symptomatology–Clinician-Rated (IDS-C) and the Young Mania Rating Scale (YMRS), and suicidal ideation, measured using IDS-C item 18, using generalized estimating equations. Results: Depressive symptoms were strongly associated with suicidal ideation (OR = 21.98, 95% CI: 15.31–31.54). Moderate hypo/manic symptoms also conferred risk (OR = 3.11, 95% CI: 1.51–6.49), and milder hypo/mania showed a weaker but significant association (OR = 1.74, 95% CI: 1.05–2.89). The highest suicidal ideation was observed in individuals with hypo/mania featuring mixed symptoms (OR = 29.43), exceeding that of depression or depression with mixed features (OR = 21.98). However, findings diverged based on modeling approach: in continuous predictor models, SI was driven solely by depressive symptom severity, with no significant association observed for hypo/mania or its interaction with depression. In contrast, when mood states were categorized using clinically meaningful thresholds, hypo/mania with mixed features emerged as a distinct contributor to suicidal ideation risk. Conclusion: These findings underscore the need for integrating both dimensional and categorical approaches to mood state classification in research on suicidality in bipolar disorder.