Ozerdem, Aysegul

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 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.

Abstract Background: Pharmacogenomic studies on antidepressant treatment outcomes could be conducted using previously collected data from electronic health record (EHR)-linked biobanks. However, absence of EHR based outcome measures is an unmet need in designing such studies We aimed to define EHR-derived antidepressant outcome measures and explore their utility in showing associations between treatment outcomes and Cytochrome P450 (CYP) metabolizer phenotypes in a proof-of-concept study. Methods: Using data from the EHR-linked cohort, Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT 10K) Study, we collected prescription data and patient health questionnaire 9 (PHQ-9) scores to compute 3 proxy measures for antidepressant response, efficacy, and acceptability: change in PHQ-9 scores, longest treatment interval with a single antidepressant, and antidepressant non-refill. Subsequently, we tested the association of both prescription-based outcomes with DNA-predicted CYP metabolizer phenotypes in European-ancestry participants. Results: We identified 3920 RIGHT 10K participants with at least 1 antidepressant prescription and European-ancestry. Participants had a mean age of 61 years and 72% were women. Implementation of the PHQ-9 outcome was not feasible because of missingness. Of both prescription-based outcomes, antidepressant non-refill reproduced several known antidepressant-CYP interactions. However, the pilot was limited by small subgroups of participants with non-normal metabolizer phenotypes. Conclusions: Derived from structured data, antidepressant non-refill is a promising outcome measure for EHR-linked biobanks that partially reproduced antidepressant-CYP interactions. However, testing on larger datasets is necessary to understand whether it would be a useful for pharmacogenomic research.

Abstract Background Clozapine is effective for treatment-resistant schizophrenia and bipolar disorder but is often discontinued due to adverse effects. This study compared early clozapine discontinuation rates and reasons in patients with mood and psychotic disorders. Methods Data from all individuals with mood or psychotic disorders who initiated clozapine for the first time at the inpatient psychiatric unit of Mayo Clinic, Rochester, Minnesota, between 2014 and 2022 were retrospectively analyzed. Early clozapine discontinuation, defined as discontinuation within 90 days of initiation, was the primary outcome. Cox proportional hazards regression was used to assess factors associated with discontinuation. Results Of 83 patients (mood group n = 37, psychosis group n = 46), those in the mood group were older (P = 0.022) and more likely to be nonsmokers (P = 0.034). The overall 90-day clozapine discontinuation rate was 45.7%. Early discontinuation was significantly higher in the mood group than in the psychosis group (hazard ratio = 2.41, 95% confidence interval = 1.26–4.64, P = 0.008). Other factors associated with early discontinuation were female sex (P = 0.033), older age (P = 0.026), and nonsmoking (P = 0.001). In multivariable analysis, smoking status was the only factor significantly inversely associated with early clozapine discontinuation (hazard ratio = 0.47, 95% confidence interval = 0.22–0.99, P = 0.048), while diagnostic group, sex, and age did not show significant associations (all P > 0.05). Discontinuations were primarily due to adverse drug reactions in both groups. Conclusions Nearly half of the patients discontinued clozapine early, with higher rates in the mood group. Studies should further explore potential pharmacodynamic and pharmacokinetic factors associated with discontinuation, including the influence of smoking. Careful monitoring and personalized management of side effects are crucial for optimizing clozapine therapy and improving treatment outcomes.

Background: Antidepressants are among the most prescribed medications in the United States. The aim of this study was to explore the prevalence of antidepressant prescriptions and investigate sex differences and age-sex interactions in adults enrolled in the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT) study. Materials and Methods: We conducted a retrospective analysis of the RIGHT study. Using electronic prescriptions, we assessed 12-month prevalence of antidepressant treatment. Sex differences and age-sex interactions were evaluated using multivariable logistic regression and flexible recursive smoothing splines. Results: The sample consisted of 11,087 participants (60% women). Antidepressant prescription prevalence was 22.24% (27.96% women, 13.58% men). After adjusting for age and enrollment year, women had significantly greater odds of antidepressant prescription (odds ratio = 2.29; 95% confidence interval = 2.07, 2.54). Furthermore, selective serotonin reuptake inhibitors (SSRIs) had a significant age-sex interaction. While SSRI prescriptions in men showed a sustained decrease with age, there was no such decline for women until after reaching ∼50 years of age. There are important limitations to consider in this study. Electronic prescription data were cross-sectional; information on treatment duration or adherence was not collected; this cohort is not nationally representative; and enrollment occurred over a broad period, introducing confounding by changes in temporal prescribing practices. Conclusions: Underscored by the significant interaction between age and sex on odds of SSRI prescription, our results warrant age to be incorporated as a mediator when investigating sex differences in mental illness, especially mood disorders and their treatment.

Abstract Background The purpose of this study was to review the association between the SLC6A4 5-HTTLPR polymorphism and antidepressant (AD)-associated treatment emergent mania (TEM) in bipolar disorder alongside starting a discussion on the merits of developing risk stratification models to guide when not to provide AD treatment for bipolar depression. Methods Studies that examined the association between clinical and genetic risk factors, specifically monoaminergic transporter genetic variation, and TEM were identified. A meta-analysis was performed using the odds ratio to estimate the effect size under the Der-Simonian and Laird model. Results Seven studies, referencing the SLC6A4 5-HTTLPR polymorphism and TEM (total N = 1578; TEM+ =594, TEM− = 984), of 142 identified articles were included. The time duration between the start of the AD to emergence of TEM ranged from 4 to 12 weeks. There was a nominally significant association between the s allele of the 5-HTTLPR polymorphism and TEM (odds ratio, 1.434; 95% confidence interval, 1.001–2.055; P = 0.0493; I 2 = 52%). No studies have investigated norepinephrine or dopamine transporters. Conclusion Although the serotonin transporter genetic variation is commercially available in pharmacogenomic decision support tools, greater efforts, more broadly, should focus on complete genome-wide approaches to determine genetic variants that may contribute to TEM. Moreover, these data are exemplary to the merits of developing risk stratification models, which include both clinical and biological risk factors, to guide when not to use ADs in bipolar disorder. Future studies will need to validate new risk models that best inform the development of personalized medicine best practices treating bipolar depression.

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women’s worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women’s brains and provide initial evidence for neuroscience-informed policies for gender equality.

Lithium has been a cornerstone treatment for bipolar disorder (BD). Despite descriptions in the literature regarding associations between long-term lithium therapy (LTLT) and development of a thyroid disorder (overt/subclinical hypo/hyperthyroidism, thyroid nodule, and goiter) in BD, factors such as time to onset of thyroid abnormalities and impact on clinical outcomes in the course of illness have not been fully characterized. In this study we aimed to compare clinical characteristics of adult BD patients with and without thyroid disorders who were on LTLT. We aimed to identify the incidence of thyroid disorders in patients with BD on LTLT and response to lithium between patients with and without thyroid disorders in BD. The Cox proportional model was used to find the median time to the development of a thyroid disorder. Our results showed that up to 32% of patients with BD on LTLT developed a thyroid disorder, of which 79% developed hypothyroidism, which was corrected with thyroid hormone replacement. We did not find significant differences in lithium response between patients with or without thyroid disorders in BD. Findings from this study suggest that patients with BD and comorbid thyroid disorders when adequately treated have a response to lithium similar to patients with BD and no thyroid disorders.

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.