McInnis, Melvin G.

ABSTRACT Objectives To investigate pharmacological treatment patterns in individuals with bipolar disorder (BD) with and without comorbid substance use disorder (SUD) and anxiety disorder (AX), we leveraged the Global Bipolar Cohort to analyze cross‐regional practices across North America, Europe, and the Pacific. Methods Fourteen cohorts contributed aggregate data on pharmacotherapy, demographics, diagnostic subtypes, and comorbidities. Proportional meta‐analyses using generalized linear mixed models were conducted to examine prescription trends and identify clinical differences. Results The sample ( N = 11,521) was 60% female and 84% Caucasian. Participants were categorized into four mutually exclusive groups based on comorbidity status: those with comorbid AX only, comorbid SUD only, both AX and SUD, or neither. The AX+SUD subgroup showed higher rates of attention‐deficit/hyperactivity disorder (ADHD), post‐traumatic stress disorder (PTSD), rapid cycling, obesity, and unemployment, reflecting a more severe clinical profile. Regional variations were notable: North American cohorts reported higher prevalence of AX and SUD than European and Pacific cohorts. Antidepressants use for AX were more common in Europe and the Pacific, while North American prescribing patterns were more variable. Benzodiazepine use was high among individuals with SUD across all regions. Lithium and first‐generation antipsychotic prescriptions varied, with higher rates observed in Europe. Conclusions Findings underscore the heterogeneity of BD and the influence of comorbid AX and SUD on illness burden and treatment. Regional prescribing variations underscore the need for context‐specific guidelines. Gaps in data on medication‐assisted treatment for SUD point to areas for future research. These insights can support more individualized and effective care for complex BD presentations.

ABSTRACT Objective To provide expert recommendations for the development of a specialty bipolar clinic that promotes best clinical practices for the delivery of safe and effective care. Methods Members of the National Network of Depression Centers (NNDC) Bipolar Clinics Work Group met in a series of 1‐h monthly video calls over 18 months to discuss all aspects of their respective institution's bipolar clinics, including services provided, administrative processes, staffing models, characteristics of patients treated, patient volumes, finances, and research. The group also invited psychiatrists from outside of the NNDC who ran large bipolar clinics to contribute their thoughts and experiences on the subject. In addition, the NNDC sent a 20‐question survey to all 27 sites asking clinic directors specific questions about their bipolar clinics, if applicable. Further meetings and discussions incorporating results from the survey took place to produce a comprehensive set of recommendations. Results Twenty‐one of 27 NNDC sites (81%) responded to the survey. Twelve of 21 (57%) sites had a specific bipolar clinic, and another 4 (19%) were looking to start one. Clinics were based in university settings. The meetings, clinic survey, and discussions resulted in 10 recommendations describing services and operations for bipolar specialty clinics. Conclusions Given the complexity of bipolar disorder, specialty clinics are important to enhance care. Clinics with a wide array of services that include consultation, medication management, bipolar‐specific psychotherapies, and patient/family psychoeducation provide the most comprehensive care. Challenges to these clinics include maintaining ongoing patient access as well as ensuring long‐term financial stability.

Abstract Background The Global Bipolar Cohort (GBC) was established to identify existing bipolar disorder (BD) cohorts worldwide and foster collaborations focused on descriptive and analytic outcomes relevant to BD. A distributed analytic framework has been implemented to engage multiple sites without the need for central data pooling. This report describes the GBC endeavor and global functional impairment patterns. Cross-cohort comparisons of functional correlates are limited by heterogeneous measures and data-sharing constraints. Large, culturally diverse comparisons are needed to distinguish broadly reproducible correlates from cohort-specific effects. Participating sites completed a 28-item descriptive survey covering diagnostic methods, cognition, genetics, treatment, functioning, and follow-up strategies. We implemented a harmonized local logistic regression model of dichotomized functional outcome and shared summary statistics only. Results We identified 69 cohorts across five continents. Thirty-seven cohorts contributed functional outcome analyses from 17,130 participants. Outcome measures included clinician-rated disability scales and social indicators such as employment and marital status. The proportion classified with poor functioning ranged from 16% to 77% (mean 50%). In 32 of 37 cohorts, the overall regression model significantly explained variance in functioning. Current depressive symptoms were the most robust and reproducible correlate of poor functional outcome: they were assessed in 29 cohorts, significant in 22 (75.8%), ranked among the top three correlates in 22, and were the top-ranked correlates in 19. Associations between depressive burden and poor functioning were observed across clinician-rated disability scales and work or social indicators, and across geographically diverse cohorts. Comorbid substance use disorder and medication-related variables were associated with poorer functioning in subsets of cohorts, whereas sex, ancestry, bipolar subtype, psychosis history, and premorbid IQ showed weak or inconsistent associations. Cognitive measures, available in a minority of regression models, showed modest and non-uniform effects. Conclusions Across heterogeneous international cohorts, current depressive symptom burden emerged as the most consistent correlate of poor functioning in bipolar disorder. These findings replicate earlier multisite work at a larger scale, show that protocol-based distributed analyses can identify reproducible clinical signals without sharing individual-level data, and support prioritizing detection and treatment of depressive symptoms when aiming to improve real-world functioning. Future work should expand longitudinal harmonization and representation of under-studied populations.

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.

Bipolar disorder (BD) is characterized by disrupted circadian rhythms and neuronal loss. Lithium amplifies circadian rhythms and is neuroprotective, indicating mechanistic overlap across cellular systems. We examined the role of neuroprotection in determining lithium response and how circadian clock genes regulate apoptosis. In stem‐cell‐derived neuronal progenitor cells (NPCs) from BD patients, and in immortalized mouse hippocampal neurons, lithium was neuroprotective against staurosporine (STS)‐induced apoptosis. However, neuroprotection did not distinguish lithium‐responders (Li‐Rs) from nonresponders (Li‐NRs). Disruption of selected clock genes—period circadian regulator 1 ( PER1 ), basic helix–loop–helix ARNT like 1 ( ARNTL , also known as BMAL1 ), and nuclear receptor subfamily 1 group D member 1 ( NR1D1 ; also known as REV‐ERBα )—with small interfering RNA (siRNA) had distinct effects on apoptosis in mouse neurons and human NPCs. In BD patient NPCs, reduced expression of PER1 and BMAL1 increased apoptosis more in Li‐NR NPCs vs. Li‐R NPCs. Reduced expression of REV‐ERBα caused more extensive apoptosis in BD vs. control NPCs, but did not distinguish Li‐Rs vs. Li‐NRs. The REV‐ERB agonist GSK4112 was neuroprotective in mouse neurons and control NPCs, but did not reduce apoptosis in BD NPCs. Simultaneous treatment of NPCs with STS and GSK4112 revealed BD‐ and Li‐R‐associated differences in apoptosis‐related gene expression. In summary, the pharmacological effects of lithium in promoting neuroprotection are not sufficient to distinguish between Li‐Rs and Li‐NRs. However, genetic and pharmacological manipulations of the circadian clock reveal distinct roles in apoptosis in BD patient NPCs, some of which do distinguish Li‐Rs and Li‐NRs. We conclude that genetic disruption of cellular circadian clocks may predispose neurons to apoptosis preferentially in BD and/or Li‐NR. These findings imply that differences in BD between Li‐Rs/Li‐NRs primarily arise from defining biological characteristics of patient subgroups, not from distinct pharmacodynamic factors following lithium treatment.

Background: Bipolar disorder (BD) involves significant mood and energy shifts reflected in speech patterns. Detecting these patterns is crucial for diagnosis and monitoring, currently assessed subjectively. Advances in natural language processing offer opportunities to objectively analyze them. Aims: To (i) correlate speech features with manic-depressive symptom severity in BD, (ii) develop predictive models for diagnostic and treatment outcomes, and (iii) determine the most relevant speech features and tasks for these analyses. Methods: This naturalistic, observational study involved longitudinal audio recordings of BD patients at euthymia, during acute manic/depressive phases, and after-response. Patients participated in clinical evaluations, cognitive tasks, standard text readings, and storytelling. After automatic diarization and transcription, speech features, including acoustics, content, formal aspects, and emotionality, will be extracted. Statistical analyses will (i) correlate speech features with clinical scales, (ii) use lasso logistic regression to develop predictive models, and (iii) identify relevant speech features. Results: Audio recordings from 76 patients (24 manic, 21 depressed, 31 euthymic) were collected. The mean age was 46.0 ± 14.4 years, with 63.2% female. The mean YMRS score for manic patients was 22.9 ± 7.1, reducing to 5.3 ± 5.3 post-response. Depressed patients had a mean HDRS-17 score of 17.1 ± 4.4, decreasing to 3.3 ± 2.8 post-response. Euthymic patients had mean YMRS and HDRS-17 scores of 0.97 ± 1.4 and 3.9 ± 2.9, respectively. Following data pre-processing, including noise reduction and feature extraction, comprehensive statistical analyses will be conducted to explore correlations and develop predictive models. Conclusions: Automated speech analysis in BD could provide objective markers for psychopathological alterations, improving diagnosis, monitoring, and response prediction. This technology could identify subtle alterations, signaling early signs of relapse. Establishing standardized protocols is crucial for creating a global speech cohort, fostering collaboration, and advancing BD understanding.

Abstract Bipolar disorder (BD) is characterized by disrupted circadian rhythms and neuronal loss. Lithium is neuroprotective and used to treat BD, but outcomes are variable. Past research identified that circadian rhythms in BD patient neurons are associated with lithium response (Li-R) or non-response (Li-NR). However, the underlying cellular mechanisms remain unknown. To study interactions among circadian clock genes and cell survival, and their role in BD and predicting lithium response, we tested selected genes (PER1, BMAL1 and REV-ERBα) and small molecule modulators of ROR/REV-ERB nuclear receptors in models of cell survival using mouse neurons and stem-cell derived neuronal progenitor cells (NPC) from BD patients and controls. In apoptosis assays using staurosporine (STS), lithium was neuroprotective. Knockdown of PER1, BMAL1 and REV-ERBα modified cell survival across models. In NPCs, reduced expression of PER1 and BMAL1 led to more extensive cell death in Li-NR vs. Li-R. Reduced REV-ERBα expression caused more extensive cell death in BD vs. control NPCs, without distinguishing Li-R and Li-NR. In IMHN, The REV-ERB agonist GSK4112 had strong effects on circadian rhythm amplitude, and was neuroprotective in mouse neurons and control NPCs, but not in BD NPCs. Expression of cell survival genes following STS and GSK4112 treatments revealed BD-associated, and Li-R associated differences in expression profiles. We conclude that the neuroprotective response to lithium is similar in NPCs from Li-R and Li-NR. However, knockdown of circadian clock genes or stimulation of REV-ERBs reveal distinct contributions to cell death in BD patient NPCs, some of which distinguish Li-R and Li-NR.

Abstract The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.

Abstract Objectives To understand treatment practices for bipolar disorders (BD), this study leveraged the Global Bipolar Cohort collaborative network to investigate pharmacotherapeutic treatment patterns in multiple cohorts of well‐characterized individuals with BD in North America, Europe, and Australia. Methods Data on pharmacotherapy, demographics, diagnostic subtypes, and comorbidities were provided from each participating cohort. Individual site and regional pooled proportional meta‐analyses with generalized linear mixed methods were conducted to identify prescription patterns. Results This study included 10,351 individuals from North America ( n = 3985), Europe ( n = 3822), and Australia ( n = 2544). Overall, participants were predominantly female (60%) with BD‐I (60%; vs. BD‐II = 33%). Cross‐sectionally, mood‐stabilizing anticonvulsants (44%), second‐generation antipsychotics (42%), and antidepressants (38%) were the most prescribed medications. Lithium was prescribed in 29% of patients, primarily in the Australian (31%) and European (36%) cohorts. First‐generation antipsychotics were prescribed in 24% of the European versus 1% in the North American cohort. Antidepressant prescription rates were higher in BD‐II (47%) compared to BD‐I (35%). Major limitations were significant differences among cohorts based on inclusion/exclusion criteria, data source, and time/year of enrollment into cohort. Conclusions Mood‐stabilizing anticonvulsants, second‐generation antipsychotics, and antidepressants were the most prescribed medications suggesting prescription patterns that are not necessarily guideline concordant. Significant differences exist in the prescription practices across different geographic regions, especially the underutilization of lithium in the North American cohorts and the higher utilization of first‐generation antipsychotics in the European cohorts. There is a need to conduct future longitudinal studies to further explore these differences and their impact on outcomes, and to inform and implement evidence‐based guidelines to help improve treatment practices in BD.

Abstract Bipolar disorder (BD) is characterized by mood episodes, disrupted circadian rhythms and gray matter reduction in the brain. Lithium is an effective pharmacotherapy for BD, but not all patients respond to treatment. Lithium has neuroprotective properties and beneficial effects on circadian rhythms that may distinguish lithium responders (Li-R) from non-responders (Li-NR). The circadian clock regulates molecular pathways involved in apoptosis and cell survival, but how this overlap impacts BD and/or lithium responsiveness is unknown. In primary fibroblasts from Li-R/Li-NR BD patients and controls, we found patterns of co-expression among circadian clock and cell survival genes that distinguished BD vs. control, and Li-R vs. Li-NR cells. In cellular models of apoptosis using staurosporine (STS), lithium preferentially protected fibroblasts against apoptosis in BD vs. control samples, regardless of Li-R/Li-NR status. When examining the effects of lithium treatment of cells in vitro, caspase activation by lithium correlated with period alteration, but the relationship differed in control, Li-R and Li-NR samples. Knockdown of Per1 and Per3 in mouse fibroblasts altered caspase activity, cell death and circadian rhythms in an opposite manner. In BD cells, genetic variation in PER1 and PER3 predicted sensitivity to apoptosis in a manner consistent with knockdown studies. We conclude that distinct patterns of coordination between circadian clock and cell survival genes in BD may help predict lithium response.