White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) "OCD vs. healthy controls" (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) "unmedicated OCD vs. healthy controls" (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) "medicated OCD vs. unmedicated OCD" (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6-79.1 in adults; 35.9-63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research.

Sex differences in clinical response to deep brain stimulation in resistant obsessive-compulsive disorder.

INTRODUCTION: Deep brain stimulation (DBS) is an effective alternative to treat severe refractory obsessive-compulsive disorder (OCD), although little is known on factors predicting response. The objective of this study was to explore potential sex differences in the pattern of response to DBS in OCD patients. METHODS: We conducted a prospective observational study in 25 patients with severe resistant OCD. Response to treatment was defined as a ≥35% reduction in Yale-Brown Obsessive Compulsive Scale (Y-BOCS) score. Logistic regression models were calculated to measure the likelihood of response at short and long-term follow-up by sex as measured by Y-BOCS score. Similar analyses were carried out to study changes in depressive symptomatology assessed with the Hamilton Depression Rating Scale (HDRS). Additionally, effect sizes were calculated to assess clinical significance. RESULTS: We did not observe significant clinical differences between men and women prior to DBS implantation, nor in the response after one year of stimulation. At long-term follow-up, 76.9% of men could be considered responders to DBS versus only 33.3% of women. The final response odds ratio in men was 10.05 with significant confidence intervals (88.90-1.14). No other predictors of response were identified. The sex difference in Y-BOCS reduction was clinically significant, with an effect size of 3.2. The main limitation was the small sample size. CONCLUSIONS: Our results suggest that gender could influence the long-term response to DBS in OCD, a finding that needs to be confirmed in new studies given the paucity of results on predictors of response to DBS.

Right Prefrontal Cortical Thickness Is Associated With Response to Cognitive-Behavioral Therapy in Children With Obsessive-Compulsive Disorder.

OBJECTIVE: Cognitive-behavioral therapy (CBT) is considered a first-line treatment for obsessive-compulsive disorder (OCD) in pediatric and adult populations. Nevertheless, some patients show partial or null response. The identification of predictors of CBT response may improve clinical management of patients with OCD. Here, we aimed to identify structural magnetic resonance imaging (MRI) predictors of CBT response in 2 large series of children and adults with OCD from the worldwide ENIGMA-OCD consortium. METHOD: Data from 16 datasets from 13 international sites were included in the study. We assessed which variations in baseline cortical thickness, cortical surface area, and subcortical volume predicted response to CBT (percentage of baseline to post-treatment symptom reduction) in 2 samples totaling 168 children and adolescents (age range 5-17.5 years) and 318 adult patients (age range 18-63 years) with OCD. Mixed linear models with random intercept were used to account for potential cross-site differences in imaging values. RESULTS: Significant results were observed exclusively in the pediatric sample. Right prefrontal cortex thickness was positively associated with the percentage of CBT response. In a post hoc analysis, we observed that the specific changes accounting for this relationship were a higher thickness of the frontal pole and the rostral middle frontal gyrus. We observed no significant effects of age, sex, or medication on our findings. CONCLUSION: Higher cortical thickness in specific right prefrontal cortex regions may be important for CBT response in children with OCD. Our findings suggest that the right prefrontal cortex plays a relevant role in the mechanisms of action of CBT in children.

Long-term comparative effectiveness of deep brain stimulation in severe obsessive-compulsive disorder.

BACKGROUND: Twenty years after the first use of Deep Brain Stimulation (DBS) in obsessive-compulsive disorder (OCD), our knowledge of the long-term effects of this therapeutic option remains very limited. OBJECTIVE: Our study aims to assess the long-term effectiveness and tolerability of DBS in OCD patients and to look for possible predictors of long-term response to this treatment. METHODS: We studied the course of 25 patients with severe refractory OCD treated with DBS over an average follow-up period of 6.4 years (±3.2) and compared them with a control group of 25 patients with severe OCD who refused DBS and maintained their usual treatment. DBS was implanted at the ventral anterior limb of the internal capsule and nucleus accumbens (vALIC-Nacc) in the first six patients and later at the bed nucleus of stria terminalis (BNST) in the rest of patients. Main outcome was change in Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) score between the two groups assessed using mixed models. Secondary effectiveness outcomes included Hamilton Depression Rating Scale (HDRS) and Global Assessment of Functioning (GAF) scores. RESULTS: Obsessive symptoms fell by 42.5% (Y-BOCS score) in patients treated with DBS and by 4.8% in the control group. Fifty-six per cent of DBS-treated patients could be considered responders at the end of follow-up and 28% partial responders. Two patients among those who rejected DBS were partial responders (8%), but none of the non-DBS group achieved criteria for complete response. HDRS and GAF scores improved significantly in 39.2% and 43.6% among DBS-treated patients, while did not significantly change in those who rejected DBS (improvement limited to 6.2% in HDRS and 4.2% in GAF scores). No statistically significant predictors of response were found. Mixed models presented very large comparative effect sizes for DBS (4.29 for Y-BOCS, 1.15 for HDRS and 2.54 for GAF). Few patients experienced adverse effects and most of these effects were mild and transitory. CONCLUSIONS: The long-term comparative effectiveness and safety of DBS confirm it as a valid option for the treatment of severe refractory OCD.

Viability Study of Machine Learning-Based Prediction of COVID-19 Pandemic Impact in Obsessive-Compulsive Disorder Patients.

BACKGROUND: Machine learning modeling can provide valuable support in different areas of mental health, because it enables to make rapid predictions and therefore support the decision making, based on valuable data. However, few studies have applied this method to predict symptoms' worsening, based on sociodemographic, contextual, and clinical data. Thus, we applied machine learning techniques to identify predictors of symptomatologic changes in a Spanish cohort of OCD patients during the initial phase of the COVID-19 pandemic. METHODS: 127 OCD patients were assessed using the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) and a structured clinical interview during the COVID-19 pandemic. Machine learning models for classification (LDA and SVM) and regression (linear regression and SVR) were constructed to predict each symptom based on patient's sociodemographic, clinical and contextual information. RESULTS: A Y-BOCS score prediction model was generated with 100% reliability at a score threshold of ± 6. Reliability of 100% was reached for obsessions and/or compulsions related to COVID-19. Symptoms of anxiety and depression were predicted with less reliability (correlation R of 0.58 and 0.68, respectively). The suicidal thoughts are predicted with a sensitivity of 79% and specificity of 88%. The best results are achieved by SVM and SVR. CONCLUSION: Our findings reveal that sociodemographic and clinical data can be used to predict changes in OCD symptomatology. Machine learning may be valuable tool for helping clinicians to rapidly identify patients at higher risk and therefore provide optimized care, especially in future pandemics. However, further validation of these models is required to ensure greater reliability of the algorithms for clinical implementation to specific objectives of interest.

Changes in the stool and oropharyngeal microbiome in obsessive-compulsive disorder.

Although the etiology of obsessive-compulsive disorder (OCD) is largely unknown, it is accepted that OCD is a complex disorder. There is a known bi-directional interaction between the gut microbiome and brain activity. Several authors have reported associations between changes in gut microbiota and neuropsychiatric disorders, including depression or autism. Furthermore, a pediatric-onset neuropsychiatric OCD-related syndrome occurs after streptococcal infection, which might indicate that exposure to certain microbes could be involved in OCD susceptibility. However, only one study has investigated the microbiome of OCD patients to date. We performed 16S ribosomal RNA gene-based metagenomic sequencing to analyze the stool and oropharyngeal microbiome composition of 32 OCD cases and 32 age and gender matched controls. We estimated different α- and ß-diversity measures and performed LEfSe and Wilcoxon tests to assess differences in bacterial distribution. OCD stool samples showed a trend towards lower bacterial α-diversity, as well as an increase of the relative abundance of Rikenellaceae, particularly of the genus Alistipes, and lower relative abundance of Prevotellaceae, and two genera within the Lachnospiraceae: Agathobacer and Coprococcus. However, we did not observe a different Bacteroidetes to Firmicutes ratio between OCD cases and controls. Analysis of the oropharyngeal microbiome composition showed a lower Fusobacteria to Actinobacteria ratio in OCD cases. In conclusion, we observed an imbalance in the gut and oropharyngeal microbiomes of OCD cases, including, in stool, an increase of bacteria from the Rikenellaceae family, associated with gut inflammation, and a decrease of bacteria from the Coprococcus genus, associated with DOPAC synthesis.

An overview of the first 5 years of the ENIGMA obsessive-compulsive disorder working group: The power of worldwide collaboration.

Neuroimaging has played an important part in advancing our understanding of the neurobiology of obsessive-compulsive disorder (OCD). At the same time, neuroimaging studies of OCD have had notable limitations, including reliance on relatively small samples. International collaborative efforts to increase statistical power by combining samples from across sites have been bolstered by the ENIGMA consortium; this provides specific technical expertise for conducting multi-site analyses, as well as access to a collaborative community of neuroimaging scientists. In this article, we outline the background to, development of, and initial findings from ENIGMA's OCD working group, which currently consists of 47 samples from 34 institutes in 15 countries on 5 continents, with a total sample of 2,323 OCD patients and 2,325 healthy controls. Initial work has focused on studies of cortical thickness and subcortical volumes, structural connectivity, and brain lateralization in children, adolescents and adults with OCD, also including the study on the commonalities and distinctions across different neurodevelopment disorders. Additional work is ongoing, employing machine learning techniques. Findings to date have contributed to the development of neurobiological models of OCD, have provided an important model of global scientific collaboration, and have had a number of clinical implications. Importantly, our work has shed new light on questions about whether structural and functional alterations found in OCD reflect neurodevelopmental changes, effects of the disease process, or medication impacts. We conclude with a summary of ongoing work by ENIGMA-OCD, and a consideration of future directions for neuroimaging research on OCD within and beyond ENIGMA.

Deep brain stimulation for obsessive-compulsive disorder: A systematic review of worldwide experience after 20 years.

BACKGROUND: Twenty years after its first use in a patient with obsessive-compulsive disorder (OCD), the results confirm that deep brain stimulation (DBS) is a promising therapy for patients with severe and resistant forms of the disorder. Nevertheless, many unknowns remain, including the optimal anatomical targets, the best stimulation parameters, the long-term (LT) effects of the therapy, and the clinical or biological factors associated with response. This systematic review of the articles published to date on DBS for OCD assesses the short and LT efficacy of the therapy and seeks to identify predictors of response. AIM: To summarize the existing knowledge on the efficacy and tolerability of DBS in treatment-resistant OCD. METHODS: A comprehensive search was conducted in the PubMed, Cochrane, Scopus, and ClinicalTrials.gov databases from inception to December 31, 2020, using the following strategy: "(Obsessive-compulsive disorder OR OCD) AND (deep brain stimulation OR DBS)." Clinical trials and observational studies published in English and evaluating the effectiveness of DBS for OCD in humans were included and screened for relevant information using a standardized collection tool. The inclusion criteria were as follows: a main diagnosis of OCD, DBS conducted for therapeutic purposes and variation in symptoms of OCD measured by the Yale-Brown Obsessive-Compulsive scale (Y-BOCS) as primary outcome. Data were analyzed with descriptive statistics. RESULTS: Forty articles identified by the search strategy met the eligibility criteria. Applying a follow-up threshold of 36 mo, 29 studies (with 230 patients) provided information on short-term (ST) response to DBS in, while 11 (with 155 patients) reported results on LT response. Mean follow-up period was 18.5 ± 8.0 mo for the ST studies and 63.7 ± 20.7 mo for the LT studies. Overall, the percentage of reduction in Y-BOCS scores was similar in ST (47.4%) and LT responses (47.2%) to DBS, but more patients in the LT reports met the criteria for response (defined as a reduction in Y-BOCS scores > 35%: ST, 60.6% vs LT, 70.7%). According to the results, the response in the first year predicts the extent to which an OCD patient will benefit from DBS, since the maximum symptom reduction was achieved in most responders in the first 12-14 mo after implantation. Reports indicate a consistent tendency for this early improvement to be maintained to the mid-term for most patients; but it is still controversial whether this improvement persists, increases or decreases in the long term. Three different patterns of LT response emerged from the analysis: 49.5% of patients had good and sustained response to DBS, 26.6% were non responders, and 22.5% were partial responders, who might improve at some point but experience relapses during follow-up. A significant improvement in depressive symptoms and global functionality was observed in most studies, usually (although not always) in parallel with an improvement in obsessive symptoms. Most adverse effects of DBS were mild and transient and improved after adjusting stimulation parameters; however, some severe adverse events including intracranial hemorrhages and infections were also described. Hypomania was the most frequently reported psychiatric side effect. The relationship between DBS and suicide risk is still controversial and requires further study. Finally, to date, no clear clinical or biological predictors of response can be established, probably because of the differences between studies in terms of the neuroanatomical targets and stimulation protocols assessed. CONCLUSION: The present review confirms that DBS is a promising therapy for patients with severe resistant OCD, providing both ST and LT evidence of efficacy.

First manic/hypomanic episode in obsessive-compulsive disorder patients treated with antidepressants: A systematic review.

High doses of antidepressants, particularly clomipramine and selective serotonin reuptake inhibitors (SSRIs), are the well-established treatment for obsessive-compulsive disorder (OCD), but manic/hypomanic episodes are potential adverse events associated with this treatment. A systematic literature review was performed on manic/hypomanic episodes in non-bipolar OCD patients. Clinical, sociodemographic and antidepressant characteristics during the manic/hypomanic switch were extracted using descriptive statistics. Data were obtained from 20 case reports and case series. Switching episodes mostly appeared in the first 12 weeks after antidepressant initiation and took place more frequently during SSRI use (mostly fluoxetine) in 64.3% of cases. Clomipramine and SSRI use differed non-significantly between the switching episodes that appeared during the first 12 weeks of antidepressant treatment and the episodes that appeared beyond 12 weeks. Switching episodes emerging before 12 weeks were associated with a lower defined daily dose of antidepressants than episodes emerging after 12 weeks. These findings suggest that there are two independent characteristics involved in manic/hypomanic switch in OCD: a) they appeared most frequently with SSRI use (fluoxetine) regardless of the time of it use, and b) episodes appeared in the first 12 weeks after SSRI or clomipramine initiation had a lower dose of antidepressant than episodes appeared after 12 weeks.

Sleep disturbances in obsessive-compulsive disorder: influence of depression symptoms and trait anxiety.

BACKGROUND: Sleep disturbances have been reported in obsessive-compulsive disorder (OCD) patients, with heterogeneous results. The aim of our study was to assess sleep function in OCD and to investigate the relationship between sleep and the severity of obsessive-compulsive (OC) symptoms, depressive symptoms and trait anxiety. METHODS: Sleep quality was measured in 61 OCD patients and 100 healthy controls (HCs) using the Pittsburgh Sleep Quality Index (PSQI). Multiple linear regression was conducted to explore the association between sleep and psychopathological measures; a mediation analysis was also performed. RESULTS: OCD patients showed poor sleep quality and more sleep disturbances compared to HCs. The severity of depression, trait anxiety and OC symptomatology were correlated with poor sleep quality. Multiple linear regression analyses controlling for potential confounders revealed that the severity of depression and trait anxiety were independently related to poor sleep quality in OCD. A mediation analysis showed that both the severity of trait anxiety and depression mediate the relationship between the severity of OC symptoms and poor sleep quality among patients with OCD. CONCLUSIONS: Our findings support the existence of sleep disturbances in OCD. Trait anxiety and depression play a key role in sleep quality among OCD patients.

Looking into the genetic bases of OCD dimensions: a pilot genome-wide association study.

The multidimensional nature of obsessive-compulsive disorder (OCD) has been consistently reported. Clinical and biological characteristics have been associated with OCD dimensions in different ways. Studies suggest the existence of specific genetic bases for the different OCD dimensions. In this study, we analyze the genomic markers, genes, gene ontology and biological pathways associated with the presence of aggressive/checking, symmetry/order, contamination/cleaning, hoarding, and sexual/religious symptoms, as assessed via the Dimensional Yale-Brown Obsessive Compulsive Scale (DY-BOCS) in 399 probands. Logistic regression analyses were performed at the single-nucleotide polymorphism (SNP) level. Gene-based and enrichment analyses were carried out for common (SNPs) and rare variants. No SNP was associated with any dimension at a genome-wide level (p < 5 × 10-8). Gene-based analyses showed one gene to be associated with hoarding (SETD3, p = 1.89 × 10-08); a gene highly expressed in the brain and which plays a role in apoptotic processes and transcriptomic changes, and another gene associated with aggressive symptoms (CPE; p = 4.42 × 10-6), which is involved in neurotrophic functions and the synthesis of peptide hormones and neurotransmitters. Different pathways or biological processes were represented by genes associated with aggressive (zinc ion response and lipid metabolism), order (lipid metabolism), sexual/religious (G protein-mediated processes) and hoarding (metabolic processes and anion transport) symptoms after FDR correction; while no pathway was associated with contamination. Specific genomic bases were found for each dimension assessed, especially in the enrichment analyses. Further research with larger samples and different techniques, such as next-generation sequencing, are needed to better understand the differential genetics of OCD dimensions.

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Exploring genetic variants in obsessive compulsive disorder severity: A GWAS approach.

BACKGROUND: The severity of Obsessive-Compulsive Disorder (OCD) varies significantly among probands. No study has specifically investigated the genetic base of OCD severity. A previous study from our group found an OCD polygenic risk score to predict pre- and post-treatment severity. This study explores the genomic bases of OCD severity. METHODS: We administered the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) to 401 patients at their first visit to our clinic to measure their OCD severity. Genotyping data was collected by using the Infinium PsychArray-24 BeadChip kit (Illumina). We analyzed genetic association with OCD severity in a linear regression analysis at single-nucleotide polymorphism (SNP)- and gene-levels, this last also considering rare variants. Enrichment analyses were performed from gene-based analyses' results. RESULTS: No SNP reached significant association (p < 10-8) with the YBOCS. Six markers showed suggestive association (p < 10-5). The top SNP was an intergenic variant in chromosome 2: rs7578149 (p < 1.89 × 10-6), located in a region suggestively associated with MDD. Linkage disequilibrium was found for two clusters of SNPs located between SLC16A14 and SP110 in chromosome 2, all of them forming one peak of association. Enrichment analyses revealed OCD genes to be associated with porin activity (FDR = 0.01) and transmembrane structure (FDR = 0.04). LIMITATIONS: The size of the sample and the transversal nature of the severity measure are limitations of this study. CONCLUSION: This study contributes to better characterize OCD at an individual level, helping to know more about the prognosis of the disorder and develop more individualized treatments.

Do polygenic risk and stressful life events predict pharmacological treatment response in obsessive compulsive disorder? A gene-environment interaction approach.

The rate of response to pharmacological treatment in Obsessive-compulsive disorder (OCD) oscillates between 40 and 70%. Genetic and environmental factors have been associated with treatment response in OCD. This study analyzes the predictive ability of a polygenic risk score (PRS) built from OCD-risk variants, for treatment response in OCD, and the modulation role of stressful life events (SLEs) at the onset of the disorder. PRSs were calculated for a sample of 103 patients. Yale-Brown Obsessive Compulsive Scale (YBOCS) scores were obtained before and after a 12-week treatment. Regression analyses were performed to analyze the influence of the PRS and SLEs at onset on treatment response. PRS did not predict treatment response. The best predictive model for post-treatment YBOCS (post YBOCS) included basal YBOCS and age. PRS appeared as a predictor for basal and post YBOCS. SLEs at onset were not a predictor for treatment response when included in the regression model. No evidence for PRS predictive ability for treatment response was found. The best predictor for treatment response was age, agreeing with previous literature specific for SRI treatment. Suggestions are made on the possible role of neuroplasticity as a mediator on this association. PRS significantly predicted OCD severity independent on pharmacological treatment. SLE at onset modulation role was not evidenced. Further research is needed to elucidate the genetic and environmental bases of treatment response in OCD.

Risperidone adjunctive therapy duration in the maintenance treatment of bipolar I disorder: A post hoc analysis.

BACKGROUND: Risperidone, an atypical antipsychotic medication, is recommended as a first line treatment for acute mania in patients with bipolar disorder I (BD I). It is unknown if continuing treatment with risperidone adjunct to lithium or valproate after remission of the manic episode offers additional benefit in prevention of mood episode relapse. METHODS: A post-hoc subgroup analysis was conducted using data from a 52-week, double-blind, placebo controlled trial involving 93 patients treated with oral risperidone adjunct to mood stabilizer, randomized to arms discontinuing risperidone at entry ("0-week arm"), 24 weeks after entry ("24-week arm") or continuing risperidone ("52-week arm"). Time to any episode, manic episode, and depressive episode was compared between arms using Cox regression models. RESULTS: Time to any mood episode was longer in the 24-week arm versus the 0-week arm (HR: 0.57, 95% CI: 0.31-1.05, P = 0.07) and shorter in the 52-week arm versus 24-week arm (HR: 1.85, 95% CI: 1.00-3.41, P = 0.05), though these results were not significant. Time to relapse into manic episode was significantly longer in the 24-week arm versus 0-week arm (HR: 0.14, 95% CI: 0.03, 0.65, P = 0.01). No other significant differences were observed between arms. LIMITATIONS: The sample size was modest, as the original dataset was powered to study optimal duration for two atypical antipsychotics. CONCLUSIONS: Adjunctive risperidone treatment was observed to reduce the risk of manic episodes during the first 24 weeks, but not after 24 weeks. Treatment did not appear to reduce the risk of depressive episodes.