Romo-Nava, F

ABSTRACT Background This study aimed to explore the effect of family history (FH) and polygenic risk scores (PRS) for multiple psychiatric disorders on lithium response in bipolar disorder (BD). Method The sample included patients from the Mayo Clinic BD Biobank. FH in first‐degree relatives was obtained via the patient questionnaire. Linear regression models tested the association of FH and PRS for BD, major depressive disorder (MDD), schizophrenia (SCZ), alcohol use disorder (AUD), anxiety disorder (ANX), and attention‐deficit/hyperactivity disorder (ADHD) with lithium response measured by the Alda A score adjusted for the Alda B sum score. Post hoc models additionally adjusted for clinical covariates (age at onset, rapid cycling, and BD subtype). Results 716 patients had Alda scores for lithium response (61.9% females, mean age = 43.4 years). FH‐BD ( β = −0.57, p = 0.015), AUD ( β = −0.44, p = 0.045), and ANX ( β = −0.61, p = 0.050) were associated with worse lithium response. After adjusting for clinical covariates, associations for FH‐BD and FH‐ANX were no longer significant. PRS‐BD was associated with better response ( β = 0.22, p = 0.041), while PRS‐MDD ( β = −0.28, p = 0.01) and PRS‐ADHD ( β = −0.24, p = 0.028) were associated with worse response, with effects largely unchanged after adjusting for clinical covariates. In the combined model considering all FHs simultaneously, only FH‐BD remained significantly associated with worse lithium response ( β = −0.71, p = 0.039). In the combined model for PRS, only PRS‐BD ( β = 0.31, p = 0.008; better response) and PRS‐MDD ( β = −0.29, p = 0.020; worse response) showed significant associations. Conclusions In this exploratory study, FH‐BD, AUD, and ANX were associated with poor response, though only FH‐AUD remained significant after adjusting for clinical factors. PRS‐BD predicted better response, while PRS‐MDD was associated with worse response. These findings suggest independent and potentially complementary roles of FH and PRS. Integrating both familial and genetic risk measures may improve personalized treatment strategies and outcomes for BD patients.

ABSTRACT Background Mood episodes in bipolar disorder (BD) follow a seasonal pattern in approximately 25% of patients. We aimed to examine the associations of specific seasonality patterns in BD with various clinical phenotypes and treatment‐related outcomes. Methods Patients from the Mayo Clinic Bipolar Disorder Biobank with available seasonality data were included in the study. Among those reporting any seasonality, participants were further categorized into four seasonality groups: fall/winter depression, spring/summer (hypo)mania, biphasic (fall/winter depression with spring/summer (hypo)mania), and equinoctial seasonality (any mood episode occurring in spring or fall). Regression models were used, treating seasonality patterns as the predictor of clinical phenotypes (BD subtype, early onset, history of psychosis, suicide attempt, rapid cycling), lifetime medication exposure (number of unique antidepressants, antipsychotics, and any psychotropics) and treatment response to mood stabilizers (Alda A score). Results Among 1702 patients with BD (61.5% female, mean age = 41.43 ± 14.73 years), 44.6% reported seasonal mood episodes. Individuals with any seasonality were more likely to have BD‐I (OR = 1.29, p = 0.024), early onset (OR = 1.29, p = 0.026), exposure to higher lifetime number of antipsychotics (IRR = 1.20, p < 0.001) and any psychotropics (IRR = 1.13, p < 0.001). Fall/winter depression was associated with a higher lifetime number of antidepressants (IRR = 1.18, p = 0.021), any psychotropics (IRR = 1.14, p = 0.013), worse response to lithium ( β = −0.82, p = 0.029) and all mood stabilizers ( β = −0.69, p = 0.014). Spring/summer (hypo)mania showed negative associations with rapid cycling (OR = 0.36, p < 0.001) and lifetime number of antidepressants (IRR = 0.70, p = 0.013). Equinoctial seasonality was linked to a history of psychosis (OR = 1.76, p = 0.004). Conclusion Seasonality in BD is associated with distinct clinical features and treatment‐related outcomes. Specific seasonality patterns, particularly fall/winter depression, may reflect a more complex and difficult‐to‐treat illness course. These findings highlight the need for research to better characterize seasonality subtypes beyond a binary “seasonal” vs. “non‐seasonal” classification and to explore how these patterns influence the illness course and management of BD.

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.

ABSTRACTBackgroundInsomnia 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.Methods40,839 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.ResultsInsomnia 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).ConclusionThe 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.

Abstract Purpose Recognizing the negative impact that antipsychotic-induced movement disorders have on the quality of life and treatment outcomes in bipolar disorder (BD), this study aimed to assess clinical correlates and antipsychotic use patterns of tardive dyskinesia (TD+) in BD. Materials and Methods Participants with and without TD were included. Clinical variables were compared using t-test and χ2 test. Antipsychotic use patterns in TD+, including number of trials, mean doses, and estimated cumulative exposure, were assessed in a case-only analysis. Results The prevalence rate of TD was 5.1%. In comparison to the TD− group (n = 1074), TD+ participants (n = 58) were older, more likely to be female and have type I bipolar illness. There were 60.3% of the TD+ group that continued using antipsychotics at study entry and had a mean cumulative exposure to antipsychotics of 18.2 ± 15.6 years. Average dose, in haloperidol equivalents, was 5.9 ± 3.5 mg and 77.7% of the trials were second-generation antipsychotics. Conclusions This study confirms previously identified TD risk factors, such as age, sex, and bipolar subtype in a large BD cohort. Limitations included a cross-sectional design and the lack of tardive illness severity assessment. As atypical antipsychotics continue to be primary mood stabilization treatment, attempting to harmonize large data sets to identify additional biomarkers of tardive risk will optimize individualized care for patients with BD.

Objective Our aim was to evaluate the relationship between evening chronotype, a proxy marker of circadian system dysfunction, and disordered eating behavior and poor dietary habits in individuals with bipolar disorder (BD). Methods In this cross‐sectional study, we evaluated 783 adults with BD. Chronotype was determined using item 5 from the reduced Morningness‐Eveningness Questionnaire. The Eating Disorder Diagnostic Scale (EDDS) and the Rapid Eating Assessment for Participants—Shortened Version (REAP‐S) were used to assess disordered eating behavior and dietary habits respectively. General linear models and logistic regression models were utilized to evaluate differences between chronotype groups. Results Two hundred and eight (27%) BD participants self‐identified as having evening chronotypes. Compared to non‐evening types, evening types were younger ( P < 0.01) and, after controlling for age, had higher mean EDDS composite z‐scores ( P < 0.01); higher rates of binge‐eating (BE) behavior ( P = 0.04), bulimia nervosa ( P < 0.01), and nocturnal eating binges ( P < 0.01); and a higher body mass index ( P = 0.04). Compared to non‐evening types, evening chronotypes had a lower REAP‐S overall score ( P < 0.01) and scored lower on the ‘healthy foods’ and ‘avoidance of unhealthy food’ factors. Evening types also skipped breakfast more often ( P < 0.01), ate less fruit ( P = 0.02) and vegetables ( P = 0.04), and consumed more fried foods ( P < 0.01), unhealthy snacks ( P = 0.02), and soft drinks ( P = 0.01). Conclusions Our findings suggest that the circadian system plays a role in the disordered eating and unhealthy dietary behaviors observed in BD patients. The circadian system may therefore represent a therapeutic target in BD‐associated morbidity that warrants further investigation.

Abstract Objective The aim of this study was to evaluate the efficacy and safety of the dopaminergic‐enhancing agent modafinil/armodafinil (MoArm) as adjunctive treatment for bipolar depression. Methods A comprehensive search of major electronic databases was conducted to identify randomized controlled trials (RCTs) of adjunctive MoArm that included patients with bipolar I (BP‐I) or bipolar II (BP‐II) depression. Data for response/remission and all‐cause discontinuation were analyzed. Effect size was summarized by relative risk (RR) using a random effect model. Results Of 58 studies, five RCTs (N = 795 drug, N = 792 placebo) met inclusion criteria. Four armodafinil studies included only BP‐I patients and one modafinil study included both bipolar subtypes with limited heterogeneity ( I 2 = 34%, P = .19; I 2 = 18%, P = .30). Compared to placebo, augmentation with MoArm was associated with significantly greater rates of treatment response (RR, 1.18; 95% CI, 1.01‐1.37; P = .03) and remission (RR, 1.38; 95% CI, 1.10‐1.73; P = .005). All‐cause discontinuation was not different than placebo (RR, 1.08; 95% CI, 0.89‐1.30; P = .45) with no evidence of increased risk of mood switch or suicide attempts with MoArm (RR, 0.99; 95% CI, 0.39‐2.5; P = .98; RR, 1.02; 95% CI, 0.37‐2.85; P = .97). Conclusion This narrower scope meta‐analysis of one drug for one disease suggests that adjunctive MoArm may represent a novel therapeutic intervention. Further studies delineating the subtypes of bipolar depression responsive to these novel dopaminergic‐enhancing agents are encouraged.