Early intervention for people at high risk of developing bipolar disorder: a systematic review of clinical trials

The German research consortium for the study of bipolar disorder (BipoLife): a quality assurance protocol for MR neuroimaging data

BACKGROUND

The German multicenter research consortium BipoLife aims to investigate the mechanisms underlying bipolar disorders. It focuses in particular on people at high risk of developing the disorder and young patients in the early stages of the disease. Functional and structural magnetic resonance imaging (MRI) data was collected in all participating centers. The collection of neuroimaging data in a longitudinal, multicenter study requires the implementation of a comprehensive quality assurance (QA) protocol. Here, we outline this protocol and illustrate its application within the BipoLife consortium.

METHODS

The QA protocol consisted of (1) a training of participating research staff, (2) regular phantom measurements to evaluate the MR scanner performance and its temporal stability across the course of the study, and (3) the assessment of the quality of human MRI data by evaluating a variety of image metrics (e.g., signal-to-noise ratio, ghosting level). In this article, we will provide an overview on these QA procedures and show exemplarily the influence of its application on the results of standard neuroimaging analysis pipelines.

DISCUSSION

The QA protocol helped to characterize the various MR scanners, to record their performance over the course of the study and to detect possible malfunctions at an early stage. It also assessed the quality of the human MRI data systematically to characterize its influence on various analyses. Furthermore, by setting up and publishing this protocol, we define standards that must be considered when analyzing data from the BipoLife consortium. It further promotes a systematic evaluation of data quality and a definition of subject inclusion criteria. In the long term, it will help to increase the chance of achieving clinically relevant results.

Bipolar disorder staging and the impact it has on its management: an update

INTRODUCTION

The longitudinal course of bipolar disorder (BD) is associated with an active process of neuroprogression, characterized by structural brain alterations and progressive functional impairment. In the last decades, a growing need of a standardized staging model for BD arose, with the aim of a more appropriate definition of stage-specific clinical manifestations and the identification of more customized therapeutic tools.

AREAS COVERED

The authors review the literature on clinical aspects, neurobiological correlates and treatment issues related to BD progression. Thereafter, they address the definition, constructs, and evolution of the staging concept, focusing on the clinical applications of BD staging models available in literature.

EXPERT OPINION

Although several staging models for BD have been proposed to date, their application in clinical practice is still relatively scant. This may have a detrimental impact on the clinical and therapeutic management of BD, in terms of early and proper diagnosis as well as tailored treatment interventions according to the different stages of illness. Future research efforts should tend to the integration of recent insights on neuroimaging and epigenetic markers, toward a standardized and multidimensional staging model.

Development and multi-site external validation of a generalizable risk prediction model for bipolar disorder

Bipolar disorder is a leading contributor to disability, premature mortality, and suicide. Early identification of risk for bipolar disorder using generalizable predictive models trained on diverse cohorts around the United States could improve targeted assessment of high risk individuals, reduce misdiagnosis, and improve the allocation of limited mental health resources. This observational case-control study intended to develop and validate generalizable predictive models of bipolar disorder as part of the multisite, multinational PsycheMERGE Network across diverse and large biobanks with linked electronic health records (EHRs) from three academic medical centers: in the Northeast (Massachusetts General Brigham), the Mid-Atlantic (Geisinger) and the Mid-South (Vanderbilt University Medical Center). Predictive models were developed and valid with multiple algorithms at each study site: random forests, gradient boosting machines, penalized regression, including stacked ensemble learning algorithms combining them. Predictors were limited to widely available EHR-based features agnostic to a common data model including demographics, diagnostic codes, and medications. The main study outcome was bipolar disorder diagnosis as defined by the International Cohort Collection for Bipolar Disorder, 2015. In total, the study included records for 3,529,569 patients including 12,533 cases (0.3%) of bipolar disorder. After internal and external validation, algorithms demonstrated optimal performance in their respective development sites. The stacked ensemble achieved the best combination of overall discrimination (AUC = 0.82-0.87) and calibration performance with positive predictive values above 5% in the highest risk quantiles at all three study sites. In conclusion, generalizable predictive models of risk for bipolar disorder can be feasibly developed across diverse sites to enable precision medicine. Comparison of a range of machine learning methods indicated that an ensemble approach provides the best performance overall but required local retraining. These models will be disseminated via the PsycheMERGE Network website.

Diagnosis of bipolar and major depressive disorders: The appropriateness of MINI compared to the clinical interview in a sample of patients with mood disorders in tertiary mental health care

OBJECTIVE

The Mini International Neuropsychiatric Interview (MINI) is one of the most used instruments for the assessment of Mental Disorders, playing an essential role in psychiatric research and in clinical and hospital practice. Despite this, the accuracy of the MINI, when used by a psychiatrist, is poorly studied, particularly in relation to Bipolar Disorder (BD). The early diagnosis of BD and Major Depressive Disorder (MDD) is extremely important, as it provides an opportunity for intervention that can reduce the impact on the patient's daily life and functionality. As such, this study assesses the suitability of MINI for diagnosing BD or MDD in a sample of patients with mood disorders.

METHOD

Agreement between the MINI and the clinical interview was assessed in a sample of 347 outpatients by calculating Cohen's kappa, sensitivity, specificity, positive predictive value, negative predictive value, and the area under the curve (AUC).

RESULTS

The sample consisted of 347 patients with mood disorders. 279 were women (80.40%), 105 (30.3%) were diagnosed with MDD and 242 (69.7%) with BD from the assessment performed in the clinical interview. In the MINI assessment, 97 individuals (28%) were classified with a diagnosis of MDD and 250 (72%) with BD. We found a sensitivity of 87.2% and specificity of 62.8% for the MINI in the diagnosis of BD and a Cohen's kappa between the MINI and the clinical interview of 0.51. The AUC was 0.75.

CONCLUSIONS

MINI has greater sensitivity (87.2%) for the diagnosis of BD and greater specificity (87.2%) for the diagnosis of MDD. In addition, the moderate Cohen kappa (0.51) and AUC (0.75) values between the MINI and the clinical interview are acceptable when considering most available psychiatric diagnostic tools.

Preventive interventions for individuals at risk of developing bipolar disorder: A systematic review and meta-analysis

BACKGROUND

This systematic review and meta-analysis aimed to explore whether early interventions can reduce affective symptoms and have long-term benefits among individuals at risk of bipolar disorder (BD).

METHODS

The PubMed, Embase, and Web of Science databases were searched. The primary outcome was continuous symptom scores before and after treatment. Random effects meta-analyses were conducted for each outcome arm studied and pooled mean difference estimates were calculated.

RESULTS

The search identified 10 controlled studies involving 425 participants and 6 single-arm studies involving 90 participants. For controlled trials, meta-analysis showed that the interventions led to greater reduction in clinical global score than placebo (standardized mean differences (SMD) = -0.96, 95 % CI:-1.32, -0.60), and supported a long-term longitudinal effect for pharmacotherapy (SMD = -0.42, 95 % CI: -0.79, -0.05). For single-arm trials, both pharmacotherapy and psychotherapy showed efficacy for depressive symptoms, while pharmacotherapy only showed efficacy for hypomania symptoms (effect size (ES) = -9.16, 95 % CI:-11.29, -7.04). Discontinuation of pharmacotherapy due to adverse effects did not show a difference.

LIMITATIONS

The primary limitations are the small number of RCTs and the influence of medication dosage.

CONCLUSIONS

Based on the limited available data, early interventions show efficacy for individuals at risk of BD. Psychological therapy might be more beneficial for depressive symptoms and have long-term benefits for hypomania. Pharmacotherapy may be appropriate in situations of severe hypomanic symptoms and the poor functioning. Large, well-designed, double-blind -controlled trials are needed to make solid conclusions about the efficacy of early interventions.

Towards a youth mental health paradigm: a perspective and roadmap

Most mental disorders have a typical onset between 12 and 25 years of age, highlighting the importance of this period for the pathogenesis, diagnosis, and treatment of mental ill-health. This perspective addresses interactions between risk and protective factors and brain development as key pillars accounting for the emergence of psychopathology in youth. Moreover, we propose that novel approaches towards early diagnosis and interventions are required that reflect the evolution of emerging psychopathology, the importance of novel service models, and knowledge exchange between science and practitioners. Taken together, we propose a transformative early intervention paradigm for research and clinical care that could significantly enhance mental health in young people and initiate a shift towards the prevention of severe mental disorders.

Course of subthreshold manic symptoms and related risk factors in the general population: A three-year follow-up study

OBJECTIVES

Subthreshold manic symptoms (subM) are a risk factor for the onset and recurrence of bipolar disorder (BD). Individuals with subM may benefit from preventive interventions, however, their development is hampered by a lack of knowledge on subM prevalence and subsequent course. This study examines subM characteristics, course, and risk factors for an unfavourable course.

METHODS

In a Dutch representative, population-based sample aged 18-64 (N = 4618), we assessed subM, defined as the occurrence of manic core symptoms (elation/irritability), without meeting full DSM-IV criteria for BD I or II in the past 3 years. Comparison groups had either no manic symptoms (noM) or hypomania/mania in the context of BD (mBD) in the past 3 years. Furthermore, we differentiated a mild and moderate type of subM, based on the number of manic symptoms. A subsequent three-year course was assessed prospectively.

RESULTS

SubM had a three-year prevalence of 4.9%. Its prevalence, characteristics, and course were in between noM and mBD, and there were few differences between mild and moderate subM. Over the 3-year follow-up, 25.0% of individuals with subM had persistent subM and another 6.1% transitioned to mBD. Eleven significant risk factors for this unfavourable course were found. The most important were a history of depression/dysthymia (OR 3.75, p ≤ 0.001), living alone (OR 2.61, p ≤ 0.01) and elevated neuroticism score (OR 1.21, p ≤ 0.001).

CONCLUSIONS

This study supports the validity and clinical relevance of subM as a BD prodrome. It demonstrates that subM symptoms often persist or increase during follow-up and identifies 11 risk factors that are associated with an unfavourable course.

Development and Multi-Site External Validation of a Generalizable Risk Prediction Model for Bipolar Disorder

Bipolar disorder is a leading contributor to disability, premature mortality, and suicide. Early identification of risk for bipolar disorder using generalizable predictive models trained on diverse cohorts around the United States could improve targeted assessment of high risk individuals, reduce misdiagnosis, and improve the allocation of limited mental health resources. This observational case-control study intended to develop and validate generalizable predictive models of bipolar disorder as part of the multisite, multinational PsycheMERGE Consortium across diverse and large biobanks with linked electronic health records (EHRs) from three academic medical centers: in the Northeast (Massachusetts General Brigham), the Mid-Atlantic (Geisinger) and the Mid-South (Vanderbilt University Medical Center). Predictive models were developed and validated with multiple algorithms at each study site: random forests, gradient boosting machines, penalized regression, including stacked ensemble learning algorithms combining them. Predictors were limited to widely available EHR-based features agnostic to a common data model including demographics, diagnostic codes, and medications. The main study outcome was bipolar disorder diagnosis as defined by the International Cohort Collection for Bipolar Disorder, 2015. In total, the study included records for 3,529,569 patients including 12,533 cases (0.3%) of bipolar disorder. After internal and external validation, algorithms demonstrated optimal performance in their respective development sites. The stacked ensemble achieved the best combination of overall discrimination (AUC = 0.82 - 0.87) and calibration performance with positive predictive values above 5% in the highest risk quantiles at all three study sites. In conclusion, generalizable predictive models of risk for bipolar disorder can be feasibly developed across diverse sites to enable precision medicine. Comparison of a range of machine learning methods indicated that an ensemble approach provides the best performance overall but required local retraining. These models will be disseminated via the PsycheMERGE Consortium website.

A systematic review of interventions in the early course of bipolar disorder I or II: a report of the International Society for Bipolar Disorders Taskforce on early intervention

BACKGROUND

Given the likelihood of progressive illness in bipolar disorder (BD), it is important to understand the benefits and risks of interventions administered early in illness course. We conducted a systematic review of the effectiveness of interventions in the early course of BD I or II.

METHODS

We completed a systematic search on MEDLINE, PsycINFO, EMBASE, the Cochrane Central Register of Controlled Trials, CINAHL and Google Scholar from 1/1/1979 till 14/9/2022. We included controlled trials examining intervention effects on symptomatic, course, functional and tolerability outcomes of patients in the 'early course' of BD I or II. We classified patients to be in early course if they (a) were seeking help for the first time for a manic episode, (b) had a lifetime history of up to 3 manic episodes, or (c) had up to 6 lifetime mood episodes. Evidence quality was assessed using the GRADE approach.

RESULTS

From 4135 unique publications we included 25 reports representing 2212 participants in 16 randomized studies, and 17,714 participants from nine non-randomized studies. Available evidence suggested that in early illness course, lithium use was associated with lower recurrence risk compared with other mood stabilizers. Mood stabilizers were also associated with better global functioning, compared with the use of antipsychotics in the medium term. While summative findings regarding psychological therapies were limited by heterogeneity, family-focused and cognitive-behavioral interventions were associated with reduced recurrence risk or improved symptomatic outcomes. There was some evidence that the same pharmacological interventions were more efficacious in preventing recurrences when utilized in earlier rather than later illness course.

CONCLUSIONS AND RECOMMENDATIONS

While there are promising initial findings, there is a need for more adequately powered trials to examine the efficacy and tolerability of interventions in youth and adults in early illness course. Specifically, there is a compelling need to compare the relative benefits of lithium with other pharmacological agents in preventing recurrences. In addition to symptomatic outcomes, there should be a greater focus on functional impact and tolerability. Effective pharmacological and psychological interventions should be offered to those in early course of BD, balancing potential risks using shared decision-making approaches.

Bipolar disorder treatment according to illness trajectory: a systematic review of clinical trials

The current bipolar disorder treatment guidelines focus mainly on the prevention of recurrence and stabilization of acute mood episodes while neglecting outcomes related to the longitudinal course of illness. We systematically reviewed studies that assess the impact of disease progression in the treatment of patients with bipolar disorder. We searched PubMed, Embase, and Web of Science for clinical trials that moderated treatment effects by number of previous episodes, disease length, or a clinical staging model. We retrieved 6,156 potential abstracts. After deduplication, 5,376 were screened and eight studies met inclusion criteria. Seven trials moderated results by number of prior episodes, and one of those also used a measure of disease length. One trial used a clinical staging model and yielded informing results. Only three studies evaluated pharmacological interventions, the other five assessing psychotherapeutic modalities. Most of the studies were post-hoc analysis of clinical trials not primarily aimed at studying variables associated with illness trajectory. Overall, a loss of efficacy was found according to clinical progression, which supports early intervention. Tailored recommendations according to disease stages cannot be made. Furthermore, we identified methodological weaknesses and strengths in this subfield of research, suggesting the use of clinical staging models for future studies.

Reliability and Validity of the Bipolar Prodrome Symptom Interview and Scale-Full Prospective in Its Turkish Translation

Editors' Note: The Editors would like to address issues related to the acceptance of this manuscript. The original manuscript referenced the study tool as the Bipolar Prodrome Symptom Interview Scale-Prospective (BPSS-P). After the manuscript's initial acceptance, the authors requested a revision of the tool name to Bipolar Prodrome Symptom Interview Scale-Full Perspective (BPSS-FP). When this request was made, the original acceptance was rescinded, and the authors were asked to formally revise and resubmit the manuscript with an explanation for the change. This revision and subsequent review led to the final acceptance of the manuscript. The authors have assured us that the tool used in the manuscript was the BPSS-FP (version 5) as opposed to abbreviated forms of this tool that are also used in research (e.g., Bipolar Prodrome Symptom Scale-Abbreviated Screen for Patients (BPSS-AS-P). Background: No scale exists to assess patients at-risk for bipolar disorder (BD) in Turkey. We aimed to assess the psychometric properties of the Turkish version of the Bipolar Prodrome Symptom Interview and Scale-Full Prospective (BPSS-FP). Method: Psychiatric service users aged 11-18 years old were interviewed using the BPSS-FP translated into Turkish and the Kiddie Schedule for Affective Disorders and Schizophrenia. Youth with major depressive disorder (MDD, n = 63), bipolar-spectrum disorder (n = 47), and healthy controls (n = 122) were included. Cronbach's alpha was calculated to assess internal consistency. The Young Mania Rating Scale (YMRS) and Children's Depression Rating Scale-Revised (CDRS-R) were administered to test convergent/discriminant validity. Discriminant validity was further tested using one-way ANOVA and "receiver operating characteristic" (ROC) curves. Inter-rater reliability was tested using correlation coefficients. Findings: Across 232 youth, Cronbach's alpha values were 0.932 for the BPSS-FP total score, 0.878 for the Mania Symptom Index, 0.887 for the Depression Symptom Index, and 0.797 for the General Symptom Index. Correlation coefficients for inter-rater reliability were high for the Mania Symptom Index (r = 0.989), Depression Symptom Index (r = 0.973), and General Symptom Index (r = 0.981). There were high correlations between the BPSS-FP Mania Symptom Index subscore and YMRS (r = 0.732), and the BPSS-FP Depression Symptom Index subscore and CDRS-R (r = 0.754), whereas cross-polarity correlations were non-significant. ROC analysis cut-off value was ≥21 for the BPSS-FP Mania Symptom Index between patients with BD and MDD (specificity = 85.7%, sensitivity = 78.7%). Conclusion: The Turkish version of the BPSS-FP has good psychometric properties and can be used in research. Longitudinal studies are needed to confirm the predictive value of the BPSS-FP.

Psychosocial Treatments for Bipolar Disorder in Children and Adolescents

Evidence suggests that adjunctive psychosocial intervention for the treatment of pediatric bipolar spectrum disorders (BPSDs) is effective, feasible, and highly accepted as both an acute and maintenance treatment for youth with BPSD diagnoses as well as a preventive treatment for high-risk youth who are either asymptomatic or exhibit subsyndromal mood symptoms. Here, we provide a comprehensive review of all known evidence-based interventions, including detailed descriptions of treatment targets and core components, results of clinical trials, and updated research on mediators and moderators of treatment efficacy. Treatments are presented systematically according to level of empirical support (i.e., well established, probably efficacious, possibly efficacious, experimental, or questionable); upcoming and ongoing trials are included when possible. In line with a staging approach, preventive interventions are presented separately. Recommendations for best practices based on age, stage, and additional evidence-based child and family factors shown to affect treatment outcomes are provided. Expected final online publication date for the Annual Review of Clinical Psychology, Volume 18 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Alterations in blood proteins in the prodromal stage of bipolar II disorders

Although early intervention may help prevent the progression of bipolar disorder, there are some controversies over early pharmacological intervention. In this study, we recruited 40 subjects in the prodromal stage of BD-II (BP), according to bipolar at-risk state criteria. We compared the expression of their plasma proteins with that of 48 BD-II and 75 healthy control (HC) to identify markers that could be detected in a high-risk state. The multiple reaction monitoring method was used to measure target peptide levels with high accuracy. A total of 26 significant peptides were identified through analysis of variance with multiple comparisons, of which 19 were differentially expressed in the BP group when compared to the BD-II and HC groups. Two proteins were overexpressed in the BP group; and were related to pro-inflammation and impaired neurotransmission. The other under-expressed peptides in the BP group were related to blood coagulation, immune reactions, lipid metabolism, and the synaptic plasticity. In this study, significant markers observed in the BP group have been reported in patients with psychiatric disorders. Overall, the results suggest that the pathophysiological changes included in BD-II had already occurred with BP, thus justifying early pharmacological treatment to prevent disease progression.

Transitioning to bipolar disorder: A systematic review of prospective high-risk studies

PURPOSE OF REVIEW

Bipolar disorder is a highly heritable condition, which can progress from an asymptomatic period in at-risk individuals to a potentially debilitating illness. Identifying individuals who are at a high risk of developing bipolar disorder may provide an opportunity for early intervention to improve outcomes. The main objective of this systematic review is to provide an overview of prospective studies that evaluated the incidence and predictors of transitioning to bipolar disorder among high-risk individuals.

RECENT FINDINGS

Twenty-three publications from 16 cohorts were included in the final review. Most studies focused on familial high-risk groups, while others either used clinical or a combination of clinical and genetic risk factors. The follow-up length was from 1 to 21 years and the rate of conversion to bipolar disorder was between 8 and 25% among different studies. Overall, the results suggest that a combination of genetic and clinical risk factors; namely, subthreshold (hypo)manic symptoms and elevated depressive symptoms, may be required to optimally predict conversion to bipolar disorder.

SUMMARY

The concept of high-risk for bipolar disorder is still in its infancy. Further discussions are needed to work towards an expert consensus on the high-risk criteria for bipolar disorder, taking into account both clinical and genetic risk factors.

Alterations in the Plasma Lipidome of Adult Women With Bipolar Disorder: A Mass Spectrometry-Based Lipidomics Research

Lipidomics has become a pivotal tool in biomarker discovery for the diagnosis of psychiatric illnesses. However, the composition and quantitative analysis of peripheral lipids in female patients with bipolar disorder (BD) have been poorly addressed. In this study, plasma samples from 24 female patients with BD and 30 healthy controls (HCs) were analyzed by comprehensive lipid profiling and quantitative validation based on liquid chromatography-mass spectrometry. Clinical characteristics and a correlation between the level of lipid molecules and clinical symptoms were also observed. We found that the quantitative alterations in several lipid classes, including acylcarnitine, lysophosphatidylethanolamine, GM2, sphingomyelin, GD2, triglyceride, monogalactosyldiacylglycerol, phosphatidylinositol phosphate, phosphatidylinositol 4,5-bisphosphate, phosphatidylethanolamine, phosphatidylserine, and lysophosphatidylinositol, were remarkably upregulated or downregulated in patients with BD and were positively or negatively correlated with the severity of psychotic, affective, or mania symptoms. Meanwhile, the composition of different carbon chain lengths and degrees of fatty acid saturation for these lipid classes in BD were also different from those of HCs. Moreover, 55 lipid molecules with significant differences and correlations with the clinical parameters were observed. Finally, a plasma biomarker set comprising nine lipids was identified, and an area under the curve of 0.994 was obtained between patients with BD and the HCs. In conclusion, this study provides a further understanding of abnormal lipid metabolism in the plasma and suggests that specific lipid species can be used as complementary biomarkers for the diagnosis of BD in women.