Cuéllar‐Barboza, Alfredo B.

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 Introduction Sodium‐glucose cotransporter‐2 inhibitors (SGLT2i), initially developed for type 2 diabetes, have shown promise in improving renal outcomes in patients with and without diabetes. However, their effect on lithium‐associated kidney dysfunction remains unknown. Methods This historical cohort study included patients from Mayo Clinic (2001–2023) with mood disorders who received lithium for ≥ 6 months and later used SGLT2i for ≥ 1 month. Data on SGLT2i use and lithium treatment were extracted from electronic health records. Serum creatinine values were used to calculate estimated glomerular filtration rate (eGFR) trajectories. Linear mixed‐effects models with piecewise linear splines were used to estimate eGFR slopes before and after SGLT2i initiation, adjusted for age and sex. Results Fifty‐six patients (mean age 57.4 years, 46.4% female), predominantly with bipolar disorder (87.5%), were included. The mean eGFR, measured nearest to SGLT2i initiation, was 77.9 ± 26.0 mL/min/1.73 m 2 , and the mean duration of SGLT2i use was 19.5 ± 17.8 months. Before SGLT2i initiation, eGFR declined at a rate of −1.43 mL/min/1.73 m 2 per year ( p < 0.001). After initiation, eGFR increased by 0.69 mL/min/1.73 m 2 per year, reflecting a + 2.13 change ( p = 0.025). Sensitivity analyses, including only patients on lithium at SGLT2i initiation ( n = 22) or who had > 1 year of SGLT2i use ( n = 29) showed similar, though non‐significant, changes in slopes. Conclusion SGLT2i treatment was associated with a significant improvement in eGFR trajectory in patients with mood disorders who received long‐term lithium therapy. These findings suggest a potential role for SGLT2is in mitigating lithium‐associated kidney dysfunction and highlight the need for randomized controlled trials in this population.

Abstract Background Anxiety disorders (ANX) affect 30–60% of individuals with bipolar disorder (BD), yet limited research has systematically examined clinical characteristics and treatment patterns in this comorbid population. This study investigated demographic, clinical, and pharmacotherapeutic differences between individuals with BD with and without comorbid ANX. Methods Cross-sectional data from 2,225 adults with BD enrolled in the Mayo Clinic Bipolar Disorder Biobank were analyzed. Participants were assessed for comorbid ANX, demographics, clinical characteristics, medication use, and treatment response using the Alda-A scale. Results Overall, 61% (n = 1,366) had comorbid ANX. Individuals with BD + ANX were younger (40.4 vs. 43.6 years, p < 0.001), more likely female (66.6% vs. 54.8%, p < 0.001), and exhibited higher rates of rapid cycling (64.2% vs. 45.2%, p < 0.001), suicide attempts (40.4% vs. 24.8%, p < 0.001), substance use disorders (63.5% vs. 54.8%, p < 0.001), and somatic comorbidities (MCIRS: 6.68 vs. 5.42, p < 0.001). Pharmacotherapeutically, BD + ANX individuals were less likely to receive lithium (37.1% vs. 47.8%, p = 0.005) and valproic acid (21.7% vs. 29.6%, p = 0.047), but more likely to receive antidepressants (53.8% vs. 39.5%, p < 0.001), benzodiazepines (39.9% vs. 26.6%, p < 0.001), and gabapentinoids (8.5% vs. 4.5%, p < 0.001). Notably, 17.3% of BD + ANX individuals received antidepressants without mood stabilizer coverage. Treatment response (Alda-A) scores were significantly lower in BD + ANX for lithium (4.91 vs. 6.05, p < 0.001), mood-stabilizing anticonvulsants (5.09 vs. 6.22, p < 0.001), and second-generation antipsychotics (4.67 vs. 5.73, p < 0.001). Similar patterns were observed in both BD-I and BD-II subtypes. Conclusions Individuals with BD + ANX represent a more severely affected subgroup with distinct prescribing patterns favoring antidepressants over mood stabilizers and attenuated mood stabilizers response. These findings highlight the need for anxiety-informed treatment algorithms recognizing anxiety comorbidity as a negative prognostic factor.

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.

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 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.

Major depressive disorder (MDD) and obesity have a complex bidirectional relationship. However, most studies do not assess increased appetite or weight as a depressive symptom due to limitations in rating scales. Here we aimed to analyze frequently employed depressive-symptom scales and discuss the relevance of weight and appetite assessment items. To elaborate this perspective, we searched for validated questionnaires and scales evaluating depressive symptoms in English. We analyzed appetite and weight items from 20 depressive-symptoms rating scales. Only 8 of 20 rating scales assessed for increased weight or appetite. The scales reported in the literature as the most employed in antidepressants efficacy trials do not assess increased appetite or weight. The current use of rating scales limits our understanding of the relationship between MDD, antidepressants, and obesity. It is necessary to improve our weight and appetite measurements in MDD to clarify the respective impact of depressive symptoms and antidepressants on weight change.

AbstractBackgroundKetamine is increasingly used for treatment‐resistant depression (TRD) while its mechanism of action is still being investigated. In this systematic review, we appraise the current evidence of metabolomic biomarkers for racemic ketamine and esketamine in patients with TRD and healthy controls (HCs).MethodsA comprehensive search of several databases (Ovid MEDLINE®, Embase, and Epub Ahead of Print) was performed from each database's inception to June 29, 2022, in any language, was conducted. We included studies wherein the metabolomic biomarkers for racemic ketamine or esketamine were investigated in TRD or HCs. Our main outcomes were to examine changes in metabolites among patients treated with ketamine/esketamine and explore the association with response to ketamine/esketamine.ResultsA total of 1859 abstracts were screened of which 11 were included for full‐text review. Of these, a total of five articles were included (N = 147), including three RCTs (n = 129) and two open‐label trials (n = 18). All studies used racemic ketamine; one study additionally used esketamine. The included studies evaluated patients with treatment‐resistant bipolar depression (n = 22), unipolar depression (n = 91), and HCs (n = 34). The included studies reported alteration in several metabolites including acylcarnitines, lipids, kynurenine (KYN), and arginine with ketamine in TRD. Studies suggest the involvement of energy metabolism, KYN, and arginine pathways. In HCs, acetylcarnitine decreased post‐infusion, whereas inconsistent findings were observed after the ketamine infusion in TRD patients.ConclusionsThis systematic review provides preliminary evidence that ketamine may cause changes in several important pathways involved in energy metabolism and inflammation. Larger and more rigorous studies are needed.

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.