New Data Relevant to Treating Substance Use Disorders, Bipolar Disorder, and Pediatric Anxiety Disorders.
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Anxiety Disorders↗
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Chronotype and cellular circadian rhythms predict the clinical response to lithium maintenance treatment in patients with bipolar disorder.
Bipolar disorder (BD) is a serious mood disorder associated with circadian rhythm abnormalities. Risk for BD is genetically encoded and overlaps with systems that maintain circadian rhythms. Lithium is an effective mood stabilizer treatment for BD, but only a minority of patients fully respond to monotherapy. Presently, we hypothesized that lithium-responsive BD patients (Li-R) would show characteristic differences in chronotype and cellular circadian rhythms compared to lithium non-responders (Li-NR). Selecting patients from a prospective, multi-center, clinical trial of lithium monotherapy, we examined morning vs. evening preference (chronotype) as a dimension of circadian rhythm function in 193 Li-R and Li-NR BD patients. From a subset of 59 patient donors, we measured circadian rhythms in skin fibroblasts longitudinally over 5 days using a bioluminescent reporter (Per2-luc). We then estimated circadian rhythm parameters (amplitude, period, phase) and the pharmacological effects of lithium on rhythms in cells from Li-R and Li-NR donors. Compared to Li-NRs, Li-Rs showed a difference in chronotype, with higher levels of morningness. Evening chronotype was associated with increased mood symptoms at baseline, including depression, mania, and insomnia. Cells from Li-Rs were more likely to exhibit a short circadian period, a linear relationship between period and phase, and period shortening effects of lithium. Common genetic variation in the IP3 signaling pathway may account for some of the individual differences in the effects of lithium on cellular rhythms. We conclude that circadian rhythms may influence response to lithium in maintenance treatment of BD.
Adult↗
Genomic dimensions deconstruct the clinical heterogeneity of bipolar disorder.
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 subtypes.
Journal Article↗
Clinical impact of obsessive-compulsive disorder comorbidity in bipolar disorder: a systematic review and meta-analysis.
BACKGROUND: Bipolar disorder (BD) is commonly comorbid with other psychiatric conditions, such as obsessive-compulsive disorder (OCD). Despite increasing interest in this comorbidity, quantitative data on its clinical characteristics remain limited. This systematic review and meta-analysis aimed to evaluate the clinical impact of OCD comorbidity in BD by comparing individuals with BD and OCD (BD-OCD) to those with BD without OCD. METHODS: We systematically searched the PubMed/MEDLINE, Scopus, PsycINFO, and Web of Science databases up to April 15, 2024. Meta-analyses were conducted to compare BD-OCD and BD without OCD groups across multiple clinical domains. RESULTS: From 11,959 initial records screened, 26 studies were included in the qualitative synthesis, with 22 eligible for meta-analysis. Individuals with BD-OCD showed higher odds of experiencing chronic mood episodes (OR = 9.42; 95%CI = 2.23, 39.9), rapid cycling (OR = 1.92; 95%CI = 1.04, 3.53), comorbid eating disorders (OR = 3.37; 95%CI = 1.99, 5.7), panic disorder (OR = 3.3; 95%CI = 2.11, 5.2), substance use disorders (OR = 1.39; 95%CI = 1.02, 1.89), and lifetime suicide attempts (OR = 1.85; 95%CI = 1.21, 2.84). Additionally, they presented earlier onset of BD (SMD = -0.27; 95%CI = -0.52, -0.01) and reduced functioning (SMD = -0.42; 95%CI = -0.59, -0.24). Most data were derived from adult populations, limiting the evidence available for children and adolescents. CONCLUSIONS: BD-OCD presents a more severe and complex clinical profile, requiring specialized assessment and integrated treatment approaches. Identifying these features may support earlier recognition and inform personalized interventions for this population.
Humans↗
Machine learning-assisted plasma PEA proteomics enables differential diagnosis of melancholic depression and bipolar disorder.
Differentiating bipolar disorder (BD) from major depressive disorder (MDD) remains a critical unmet need in psychiatry due to overlapping clinical presentations and the absence of reliable biological markers. In this study, we assessed the capacity of multivariate machine learning models to accurately differentiate BD from MDD with melancholic features using plasma proteomic profiles obtained via Proximity Extension Assay (PEA) technology. A total of 67 participants were included (23 BD, 20 MDD, and 24 HC), and plasma protein expression was assessed using the Olink Target 96 Neurology panel. Differential proteomic analysis revealed distinct disorder-specific expression patterns, identifying 21 differentially expressed proteins in BD versus MDD, 18 in BD versus healthy controls, and 7 in MDD versus healthy controls. Using a stepwise feature reduction strategy, machine learning models were trained on three feature sets comprising all proteins, the top 20 most informative proteins, and the top 5 most beneficial proteins, and evaluated across BD-MDD, BD-HC, and MDD-HC classification tasks using five algorithms. For BD-MDD discrimination, the Random Forest model achieved the highest performance when trained on the top 5 protein set (LXN, HAGH, MATN3, PLXNB1, and CTSC), yielding an AUC of 0.905, with similarly strong performance observed using the top 20 protein set. Feature importance analysis highlighted proteins involved in neurodevelopmental processes, immune regulation, and extracellular matrix organization. Overall, these findings demonstrate that integrating plasma proteomics with machine learning enables robust differentiation between BD and MDD with melancholic features, supporting the development of scalable and biologically informed diagnostic tools for precision psychiatry.
Bipolar disorder↗
Genomic relationship between polyendocrine metabolic ovarian syndrome and bipolar disorder.
Women with bipolar disorder (BIP) have a higher risk of developing polyendocrine metabolic ovarian syndrome (PMOS). Shared genetic architecture may underlie this comorbidity. Valproate, a mood-stabilizer commonly used to treat BIP, increases the risk of PMOS. Still, the mechanism underlying PMOS in BIP remains unknown. Here, we aimed to identify genetic variants shared between BIP and PMOS, as well as their interaction with valproate. We used the results of large-scale genome-wide association studies of BIP (41,510 cases and 354,340 controls), and PMOS (3609 cases and 229,788 controls). Using conditional false discovery rate, we discovered genetic variants jointly associated with BIP and PMOS. Gene mapping of identified variants was performed using the Open Targets platforms. We analyzed the tissue-specific expression, interaction with valproate, and involvement in biological pathways of the mapped genes. We identified two loci shared between BIP and PMOS. Among the 10 genes mapped to the locus on chromosome 8:11,444,837-11,463,015, GATA4, NEIL2, and FDFT1 showed expression profiles suggesting their role in the observed comorbidity. Mapped to the locus on chromosome 12:2499,849-2514,270, CACNA1C, FKBP4, DCP1B, and ITFG2 are expressed in both the ovaries and the brain. Valproate interacts with CACNA1C, and CACNA1C is part of biological pathways that also include other genes interacting with valproate. We identified shared genetic underpinnings of BIP and PMOS and highlighted genes that may potentially contribute to the biological mechanisms underlying their comorbidity and to a hypothesized role of valproate in these mechanisms.
Female↗
Integrative multi-omics identifies DOC2A as a novel pharmacological target for bipolar disorder.
BACKGROUND: Current bipolar disorder (BD) therapies suffer from limited efficacy and adverse effects, necessitating mechanistically grounded targets. METHODS: We integrated BD genome-wide association study data (158,036 cases; 2,796,499 controls) with brain proteomics (ROSMAP and Banner dorsolateral prefrontal cortex, n = 376 and 152) to perform proteome-wide association studies (PWAS). Bayesian colocalization and summary-data-based Mendelian randomization (SMR) prioritized causal genes. Cell-type-specific transcriptomics validated dysregulation in iPSC-derived neurons, astrocytes, and postmortem hippocampus/prefrontal cortex. Weighted gene co-expression networks (WGCNAs), functional enrichment, and molecular docking assessed functional pathways and druggability. RESULTS: PWAS identified eight BD-associated genes (false discovery rate < 0.05), with DOC2A emerging as the top candidate. Colocalization (H4 > 0.8) and SMR supported a causal association of DOC2A with BD, with no pleiotropy (heterogeneity in dependent instruments P > 0.01); DOC2A expression decreased in BD across neurons (P = 4.26 × 10-2), astrocytes (P = 2.09 × 10-2), hippocampus (P = 9.80 × 10-3, t = -2.738), and prefrontal cortex (P = 1.44 × 10-2, t = -2.580); WGCNA positioned DOC2A as a key regulator (module membership/gene significance P < 0.05) of co-expression networks enriched for BD-associated processes including neurotransmitter secretion and postsynaptic actin cytoskeleton organization (P < 0.05); molecular docking revealed favorable-affinity binding (ΔG < -4 kcal/mol) between DOC2A and BD-related drugs and neuroprotective compounds. CONCLUSIONS: Our convergent multi-omics framework highlights DOC2A dysregulation as a key contributor to synaptic dysfunction in BD and nominates it as a promising therapeutic target. The demonstrated interaction with existing neuroactive compounds provides immediate translational avenues.
Bipolar Disorder↗
Genomic relationship between polycystic ovary syndrome and bipolar disorder.
Women with bipolar disorder (BIP) have a higher risk of developing polycystic ovary syndrome (PCOS). Shared genetic architecture may underlie this comorbidity. Valproate, a mood-stabilizer commonly used to treat BIP, increases the risk of PCOS. Still, the mechanism underlying PCOS in BIP remains unknown. Here, we aimed to identify genetic variants shared between BIP and PCOS, as well as their interaction with valproate. We used the results of large-scale genome-wide association studies of BIP (41,510 cases and 354,340 controls), and PCOS (3,609 cases and 229,788 controls). Using conditional false discovery rate, we discovered genetic variants jointly associated with BIP and PCOS. Gene mapping of identified variants was performed using the Open Targets platforms. We analyzed the tissue-specific expression, interaction with valproate, and involvement in biological pathways of the mapped genes. We identified two loci shared between BIP and PCOS. Among the 10 genes mapped to the locus on chromosome 8:11455262, GATA4, NEIL2, and FDFT1 showed expression profiles suggesting their role in the observed comorbidity. Mapped to the locus on chromosome 12:2499849, CACNA1C, FKBP4, DCP1B, and ITFG2 are expressed in both the ovaries and the brain. CACNA1C expression is affected by valproate, and CACNA1C plays a role in biological pathways involving other valproate-affected genes. We identified shared genetic underpinnings of BIP and PCOS, and implicated genes which may explain the biological mechanisms of the comorbidity between these disorders and a potential mechanism for the role of valproate.
bipolar disorder↗
Identification of autophagy-related genes as potential biomarkers correlated with immune infiltration in bipolar disorder: a bioinformatics analysis.
BACKGROUND: Bipolar disorder (BPD) is a kind of manic and depressive phase alternate episodes of serious mental illness, and it is correlated with well-documented cortical brain abnormalities. Emerging evidence supports that autophagy dysfunction in neuronal system contributes to pathophysiological changes in neurological disease. However, the role of autophagy in bipolar disorder has rarely been elucidated. This study aimed to identify the autophagy-related gene as a potential biomarker Correlated to immune infiltration in BPD. METHODS: The microarray dataset GSE23848 and autophagy-related genes (ARGs) were downloaded. Differentially expressed genes (DEGs) between normal and BPD samples were screened using the R software. Machine learning algorithms were performed to screen the significant candidate biomarker from autophagy-related differentially expressed genes (ARDEGs). The correlation between the screened ARDEGs and infiltrating immune cells was explored through correlation analysis. RESULTS: In this study, the autophagy pathway was abundantly enriched and activated in BPD, as indicated by Pathway enrichment analysis. We identified 16 ARDEGs in BPD compared to the normal group. A signature of 4 ARDEGs (ERN1, ATG3, CTSB, and EIF2AK3) was screened. ROC analysis showed that the above genes have good diagnostic performance. In addition, immune correlation analysis considered that the above four genes significantly correlated with immune cells in BPD. CONCLUSIONS: Autophagy - immune cell axis mediates pathophysiological changes in BPD. Four important ARDEGs are prospective to be potential biomarkers associated with immune infiltration in BPD and helpful for the prediction or diagnosis of BPD.
Bipolar Disorder↗
Memantine Augmentation for Obsessive-Compulsive Symptoms in Bipolar Disorder: A Randomized, Double-Blind, Placebo-Controlled Trial.
BACKGROUND: Obsessive-compulsive symptoms are frequently observed in patients with bipolar disorder and present a significant therapeutic challenge. This study evaluated the efficacy and safety of memantine as an adjunctive therapy for obsessive-compulsive disorder in patients with bipolar disorder. METHODS: In this randomized, double-blind, placebo-controlled trial, 46 patients with bipolar disorder and obsessive-compulsive disorder, stabilized on quetiapine and lithium, were randomly assigned to receive either memantine (n = 23) or placebo (n = 23) for 6 weeks. RESULTS: The memantine group showed a significant reduction in Yale-Brown Obsessive-Compulsive Scale scores compared with the placebo group (Cohen d = 1.57 vs 0.42, P < 0.001). Nausea was the most common side effect, but overall adverse effects were minimal. CONCLUSION: Memantine appears to be a safe and effective adjunctive treatment for obsessive-compulsive disorder in patients with bipolar disorder, warranting further investigation.
Humans↗
The Effect of Mindfulness-Based Psychoeducation Program on Mindfulness, Self-Compassion, and Forgiveness Tendencies of Patients with Bipolar Disorder: A Randomized Controlled Trial.
This study examined the effects of a mindfulness-based psychoeducation program on mindfulness, self-compassion, and forgiveness in patients with bipolar disorder using a pretest-posttest randomized controlled experimental design. The study sample comprised of 40 patients (experimental group, n = 20; control group, n = 20). A mindfulness-based psychoeducation program was administered to the experimental group, while no intervention was administered to the control group. Data were collected using a personal information form, the Mindfulness Scale, the Self-Compassion Scale Short Form, and the Heartland Forgiveness Scale. The study revealed that the experimental group's mean scores on the mindfulness, self-compassion, and forgiveness scales following the intervention were significantly higher than those of the control group (p < .05). This study found that a mindfulness-based psychoeducation program increased mindfulness, self-compassion, and forgiveness in patients with bipolar disorder. The findings are limited to a small outpatient sample from a single CMHC and may not be generalizable to hospitalized patients with more severe clinical presentations. Mindfulness-based educational programs may enhance mental health, improve illness insight, support symptom management, and strengthen social functioning in individuals with bipolar disorder. The results emphasize the importance of integrating these programs into treatment processes and reveal the necessity for psychiatric nurses to actively implement mindfulness-based interventions. Psychiatric nurses should consider incorporating mindfulness-based techniques into their practice to improve the mental health of individuals with bipolar disorder, better understand the disorder, control symptoms, and improve social interactions.
Humans↗
Expression of ZNF804A in human brain and alterations in schizophrenia, bipolar disorder, and major depressive disorder: a novel transcript fetally regulated by the psychosis risk variant rs1344706.
IMPORTANCE: The single-nucleotide polymorphism rs1344706 in the zinc finger protein 804A gene (ZNF804A) shows genome-wide association with schizophrenia and bipolar disorder. Little is known regarding the expression of ZNF804A and the functionality of rs1344706. OBJECTIVES: To characterize ZNF804A expression in human brain and to investigate how it changes across the life span and how it is affected by rs1344706, schizophrenia, bipolar disorder, and major depressive disorder. DESIGN, SETTING, AND PARTICIPANTS: Molecular and immunochemical methods were used to study ZNF804A messenger RNA (mRNA) and ZNF804A protein, respectively. ZNF804A transcripts were investigated using next-generation sequencing and polymerase chain reaction-based methods, and ZNF804A protein was investigated using Western blots and immunohistochemistry. Samples of dorsolateral prefrontal cortex and inferior parietal lobe tissue were interrogated from 697 participants between 14 weeks' gestational age and age 85 years, including patients with schizophrenia, bipolar disorder, or major depressive disorder. MAIN OUTCOMES AND MEASURES: Quantitative measurements of ZNF804A mRNA and immunoreactivity, and the effect of diagnosis and rs1344706 genotype. RESULTS: ZNF804A was expressed across the life span, with highest expression prenatally. An abundant and developmentally regulated truncated ZNF804A transcript was identified, missing exons 1 and 2 (ZNF804AE3E4) and predicted to encode a protein lacking the zinc finger domain. rs1344706 influenced expression of ZNF804AE3E4 mRNA in fetal brain (P = .02). In contrast, full-length ZNF804A showed no association with genotype (P > .05). ZNF804AE3E4 mRNA expression was decreased in patients with schizophrenia (P = .006) and increased in those with major depressive disorder (P < .001), and there was a genotype-by-diagnosis interaction in bipolar disorder (P = .002). ZNF804A immunoreactivity was detected in fetal and adult human cerebral cortex. It was localized primarily to pyramidal neurons, with cytoplasmic as well as dendritic and nuclear staining. No differences in ZNF804A-immunoreactive neurons were seen in schizophrenia or related to rs1344706 (P > .05). CONCLUSIONS AND RELEVANCE: rs1344706 influences the expression of ZNF804AE3E4, a novel splice variant. The effect is limited to fetal brain and to this isoform. It may be part of the mechanism by which allelic variation in ZNF804A affects risk of psychosis. ZNF804A is translated in human brain, where its functions may extend beyond its predicted role as a transcription factor.
Adolescent↗
Psychiatric Polygenic Risk Scores and Week-by-Week Symptomatic Status in Youth with Bipolar Disorder: An Exploratory Study.
Introduction: Prior studies have demonstrated that, in both adults and youth, bipolar disorder (BD) is a polygenic illness. However, no studies have examined polygenic risk scores (PRSs) in relation to the longitudinal course of mood symptoms in youth with BD. Methods: This study included 246 youth of European ancestry with BD (7-20 years old at intake) from the Course and Outcome of Bipolar Youth study and Centre for Youth Bipolar Disorder. Mood symptom severity was assessed at intake and, for 168 participants, prospectively for a median of 8.7 years. PRSs for BD, schizophrenia (SCZ), major depressive disorder (MDD), and attention-deficit/hyperactivity disorder (ADHD) were constructed using genome-wide summary statistics from independent adult cohorts. Results: Higher BD-PRS was significantly associated with lower most severe lifetime depression score at intake (β = -0.14, p = 0.03). Higher SCZ-PRS and MDD-PRS were associated with significantly less time spent in euthymia (SCZ-PRS: β = -0.21, p = 0.02; MDD-PRS: β = -0.22, p = 0.01) and more time with any subsyndromal mood symptoms (i.e., any mania, mixed, or depression symptoms; SCZ-PRS: β = 0.15, p = 0.04; MDD-PRS: β = 0.17, p = 0.01) during follow-up. PRSs for BD and ADHD were not significantly associated with any longitudinal mood variable. Conclusions: This exploratory analysis was the first to examine psychiatric PRSs in relation to the prospective course of mood symptoms among youth with BD. Results from the current study can serve to guide future youth BD studies with larger sample sizes on this topic.
Humans↗
Integrative TWAS and multi-omics analyses prioritize HSPE1 as a candidate risk gene for bipolar disorder with immune cell-specific regulatory evidence.
BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder associated with substantial disability. Although genome-wide association studies have identified multiple BD-associated loci, the underlying genes and mechanisms remain incompletely understood. METHODS: We integrated a European-ancestry BD genome-wide association dataset with cross-tissue and tissue-specific transcriptome-wide association studies (TWAS) and complementary gene-based analysis. Candidate genes were further evaluated using differential expression analysis, consensus clustering, immune infiltration analysis, machine learning, summary-data-based Mendelian randomization, Mendelian randomization using single-cell expression quantitative trait locus data, single-nucleus transcriptomics, phenome-wide association analysis, and virtual screening. RESULTS: The integrative analyses prioritized 37 candidate genes. Peripheral-blood differential-expression analysis identified 14 genes that remained significant after FDR correction, and their expression profiles separated BD samples into two expression-defined clusters. Machine-learning analysis selected UNC50, LMAN2L, LYG2, HSPE1, and KANSL3 for an exploratory classification nomogram. SMR associated genetically predicted higher HSPE1 expression with increased BD risk in two blood eQTL datasets. Cell-type-specific analyses indicated HSPE1-related associations in T-cell and natural killer cell subsets, while single-nucleus analysis descriptively showed higher HSPE1 expression in medial thalamic T cells from BD samples. PheWAS identified no genome-wide significant associations for HSPE1, whereas virtual screening identified candidate compounds with favorable predicted docking scores against the HSPE1 structure. CONCLUSION: This integrative multi-omics study identified HSPE1 as a candidate BD risk gene with immune-cell-related regulatory evidence, providing insight into BD pathogenesis and supporting functional validation.
Humans↗
Novel epigenetic loci identified from an epigenome-wide association study underlying brain structural changes in bipolar disorder.
BACKGROUND: DNA methylation influences gene-environment interactions and brain development in bipolar disorder (BD). We aimed to identify BD-associated epigenetic loci and examine their associations with brain structural variation. METHODS: We conducted an epigenome-wide association study (BD group, n = 90; healthy controls group, n = 161) to identify BD-associated DNA methylation loci, and we additionally performed copy number alteration and functional enrichment analyses. The correlations between epigenetic loci and cortical thickness (CT) were assessed using Pearson's partial correlation analysis, and the co-methylation effect of the epigenetic loci identified in the neuroimaging-epigenetic analysis was investigated. FINDINGS: A total of 156 differentially methylated positions (DMPs) and 7 differentially methylated regions were identified, and the genes associated with them were observed to be enriched in biological processes related to muscle hypertrophy and neuronal activity. Significant correlations between the methylation levels of 13 DMPs associated with three genes (miR886, PLEC1, and ICAM5) and the CT of the right postcentral gyrus and inferior frontal gyrus were identified. Specifically, 10 DMPs associated with the CpG island in the upstream region of the miR886 gene showed negative correlations with the right postcentral gyrus CT, implicating miR886-associated CpG-island methylation in regional cortical thinning. CONCLUSION: Epigenetic changes might play an important role in brain structural changes in BD. These multimodal findings nominate miR886-related methylation as a candidate molecular correlate of cortical thinning and warrant replication and mechanistic follow-up in larger, state-diverse cohorts.
Humans↗
Sustained cognitive and functional effects of pro-cognitive interventions for bipolar disorder: A systematic review of randomised controlled trials.
A substantial proportion of individuals with bipolar disorder (BD) experience considerable cognitive deficits. Existing systematic reviews have evaluated the efficacy of pro-cognitive interventions in BD, but have not established whether any cognitive benefits translate into functional improvements, with evidence for sustained functional effects remaining limited. A systematic search was conducted on MEDLINE, EMBASE, PsycINFO and Cochrane Library from inception until 21 May 2026. Eligible studies were randomised controlled trials (RCTs) in BD reporting cognitive or functional outcomes at three or more months following a pro-cognitive intervention, or examining the translation of cognitive benefits into improvements in functional outcomes at any timepoint. Seven unique RCTs plus three secondary analyses of these trials (n = 615) met the inclusion criteria. Approximately 13% (7/55) of RCTs identified in the search of pro-cognitive interventions in adult BD assessed cognitive or functional outcomes at least 3 months after treatment end. Of the seven unique RCTs, most evaluated cognitive remediation (CR; k = 4). The average follow-up length was 4 months (range: 3-6 months). Three of the four RCTs examining CR reported cognitive benefits at 3 to 6 months, whereas only one CR RCT found consistent functional effects at 3 months. Evidence on the translation of cognitive benefits to functional improvements is scarce and inconsistent. Most trials examining pro-cognitive interventions do not examine whether potential benefits are sustained or whether they translate into improvements in real-world functioning. CR appears to be a promising intervention for achieving durable cognitive gains in BD, although evidence for sustained effects of other interventions is limited.
Humans↗
Schizophrenia and bipolar disorder: a comparative analysis of genetic and brain network connectivity.
BACKGROUND: Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric conditions with overlapping clinical presentations, genetic risk factors, and brain network dysfunction. Whether alterations in large-scale intrinsic brain networks reflect shared or disorder-specific genetic influences remains poorly understood. Clarifying this distinction is essential for refining etiological models and improving diagnostic precision. METHODS: Genome-wide inferred statistics (GWIS) were applied to decompose the genetic architecture of SCZ and BD into shared and unique components. Using resting-state network (RSN) data from the UK Biobank, functional connectivity (FC) and structural connectivity (SC) were extracted as neuroimaging phenotypes. Causal inference approaches were subsequently employed to infer potential directional relationships between brain network connectivity and each disorder. RESULTS: Analyses revealed both common and distinct patterns of brain network connectivity associated with SCZ and BD. Notably, SC within the default mode network (DMN) exhibited opposing effects across the two disorders, suggesting divergent structural underpinnings despite clinical overlap. Additionally, SC within the limbic network (LN) and frontotemporal control network demonstrated potential causal relationships with both conditions, implicating these circuits astransdiagnostic neural substrates. CONCLUSION: These findings illuminate the shared and disorder-specific genetic and neural architecture underlying SCZ and BD. Integrating genome-wide genetic methods with large-scale neuroimaging data offers a powerful framework for disentangling psychiatric comorbidity and may inform more targeted diagnostic criteria and individualized treatment strategies.
Humans↗
The Safety, Efficacy, and Feasibility of Fecal Microbiota Transplantation in a Population With Bipolar Disorder During Depressive Episodes: A Pilot Parallel Arm Randomized Controlled Trial: Sécurité, efficacité et faisabilité de la transplantation de microbiote fécal chez une population atteinte de troubles bipolaires, au cours d'épisodes dépressifs : essai pilote contrôlé à répartition aléatoire et à groupes parallèles.
BackgroundThe gut microbiome has been proposed as a potential modifiable target to treat mental illness. This double-blind randomized control trial investigated fecal microbiota transplant (FMT) in bipolar disorder (BD) to assess efficacy, safety, and feasibility. The primary outcome evaluated the effectiveness of standard approved therapy for BD depression + FMT in individuals not responding to standard treatment, measured by change in the Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to week 24. Secondary outcomes included FMT's impact on anxiety, global function, side-effects, and safety. The feasibility of this novel intervention was also assessed. Microbial analysis utilized whole-genome shotgun metagenomic sequencing, comparing outcomes between allogenic (donor) and autologous (participants own) FMT.MethodsA total of 35 participants (28 women and 7 men) with at least moderate depressive-phase BD (MADRS) were randomized to receive either allogenic FMT (n = 17) or autologous FMT (n = 18) via colonoscopy and were followed for 24 weeks.ResultsMADRS scores significantly improved from baseline to the last visit in both treatment arms. There was no significant difference between allogenic FMT (16.74-point improvement) and autologous FMT (15.4-point improvement) regarding clinical efficacy (t = -0.47, p-value = .64, 95% confidence interval [CI] = -7.3-4.6). Microbiota analysis showed that allogenic FMT let to a bacterial profile similar to the healthy donor and increased bacterial diversity at the 6-month mark, whereas those receiving autologous FMT did not. The intervention was well tolerated with no significant adverse events. Recruitment, randomization, and retention metrics support feasibility of a larger trial.ConclusionFeasibility and tolerability data indicate further investigation into microbial manipulation in BD is warranted. The absence of efficacy differences between the two types of FMT, despite microbial change, highlights the importance of a true placebo in future studies, as well as the importance of understanding exactly what bacteria are linked to improvements. ClinicalTrials.gov, NCT0327922Plain Language Summary TitleResults of a Double-Blind Randomized Control Trial Investigating Fecal Microbiota Transplant (FMT) as an Add-on Treatment for Depression in Bipolar Disorder and Analyzing Microbial Diversity Changes Over 24 Weeks.
Humans↗