Changing the bipolar illness trajectory

Pharmacological Strategies for Bipolar Disorders in Acute Phases and Chronic Management with a Special Focus on Lithium, Valproic Acid, and Atypical Antipsychotics

Bipolar disorders (BDs) are a heterogeneous group of severe affective disorders generally described by the alternation of (hypo)manic, depressive, and mixed phases, with euthymic intervals of variable duration. BDs are burdened with high psychiatric and physical comorbidity, increased suicide risk and reduced life expectancy. In addition, BDs can progress into complicated forms (e.g., mixed states, rapid/irregular cycling), which are more difficult to treat and often require personalized pharmacological combinations. Mood stabilizers, particularly Lithium and Valproic acid (VPA), still represent the cornerstones of both acute and chronic pharmacotherapies of BDs. Lithium is the gold standard in BD-I and BDII with typical features, while VPA seems more effective for atypical forms (e.g., mixed-prevalence and rapid-cycling). However, despite appropriate mood stabilization, many patients show residual symptoms, and more than a half recur within 1-2 years, highlighting the need of additional strategies. Among these, the association of atypical antipsychotics (AAPs) with mood stabilizers is recurrent in the treatment of acute phases, but it is also being growingly explored in the maintenance pharmacotherapy. These combinations are clinically more aggressive and often needed in the acute phases, whereas simplifying pharmacotherapies to mood stabilizers only is preferable in the long-term, whenever possible. When mood stabilizers are not enough for maintenance treatment, Quetiapine and, less consistently, Aripiprazole have been proposed as the most advisable adjunctive strategies, for their safety and tolerability profiles. However, in view of the increased risk of serious adverse effects, a careful patient-centered balance between costs and benefits is mandatory.

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.

Consensus on nomenclature for clinical staging models in bipolar disorder: A narrative review from the International Society for Bipolar Disorders (ISBD) Staging Task Force

OBJECTIVES

Clinical staging is widely used in medicine to map disease progression, inform prognosis, and guide treatment decisions; in psychiatry, however, staging remains a hypothetical construct. To facilitate future research in bipolar disorders (BD), a well-defined nomenclature is needed, especially since diagnosis is often imprecise with blurred boundaries, and a full understanding of pathophysiology is lacking.

METHODS

Under the auspices of the International Society of Bipolar Disorders, a Task Force of international experts was convened to review, discuss, and integrate findings from the scientific literature relevant to the development of a consensus staging model and standardize a terminology that could be used to advance future research including staging of BD and related disorders.

RESULTS

Consensus opinion and areas of uncertainty or difference were identified in regard to terms referring to staging as it may apply to BD, to at-risk status and subthreshold stages, and to various clinical stages of BD as it is currently diagnosed.

CONCLUSION

The use of a standardized nomenclature about the clinical stages of BD will facilitate communication about research on clinical and pathological components of this heterogeneous group of disorders. The concepts presented are based on current evidence, but the template provided allows for further refinements as etiological advances come to light.

Pluripotential Risk and Clinical Staging: Theoretical Considerations and Preliminary Data From a Transdiagnostic Risk Identification Approach

Most psychiatric disorders develop during adolescence and young adulthood and are preceded by a phase during which attenuated or episodic symptoms and functional decline are apparent. The introduction of the ultra-high risk (UHR) criteria two decades ago created a new framework for identification of risk and for pre-emptive psychiatry, focusing on first episode psychosis as an outcome. Research in this paradigm demonstrated the comorbid, diffuse nature of emerging psychopathology and a high degree of developmental heterotopy, suggesting the need to adopt a broader, more agnostic approach to risk identification. Guided by the principles of clinical staging, we introduce the concept of a pluripotent at-risk mental state. The clinical high at risk mental state (CHARMS) approach broadens identification of risk beyond psychosis, encompassing multiple exit syndromes such as mania, severe depression, and personality disorder. It does not diagnostically differentiate the early stages of psychopathology, but adopts a "pluripotent" approach, allowing for overlapping and heterotypic trajectories and enabling the identification of both transdiagnostic and specific risk factors. As CHARMS is developed within the framework of clinical staging, clinical utility is maximized by acknowledging the dimensional nature of clinical phenotypes, while retaining thresholds for introducing specific interventions. Preliminary data from our ongoing CHARMS cohort study (N = 114) show that 34% of young people who completed the 12-month follow-up assessment (N = 78) transitioned from Stage 1b (attenuated syndrome) to Stage 2 (full disorder). While not without limitations, this broader risk identification approach might ultimately allow reliable, transdiagnostic identification of young people in the early stages of severe mental illness, presenting further opportunities for targeted early intervention and prevention strategies.

Bullying and psychotic symptoms in youth with bipolar disorder

BACKGROUND

Childhood trauma is associated with psychosis in adults with bipolar disorder (BD). Although bullying represents a widespread form of childhood trauma, no studies thus far have investigated the association of bullying and psychosis in pediatric bipolar disorder (PBD). We aim to examine the association between psychosis in PBD with bullying victimization.

METHODS

We included 64 children and adolescents (age± mean= 12±3.43) outpatients with BD spectrum disorders. Psychiatric diagnoses were assessed with the semi- structured interview Schedule for Affective Disorders and Schizophrenia for School Age Children-Present and Lifetime (KSADS-PL) version with additional depression and manic symptom items derived from the Washington University in St. Louis Kiddie Schedule for Affective Disorders (WASH-U-KSADS). Bullying, demographic, and clinical variables were assessed during the clinical interview.

RESULTS

A lifetime history of psychotic symptoms was associated with bullying (p = 0.002), suicidal behavior (p = 0.006), low socioeconomic status (p = 0.04), and severity of PBD (p = 0.02). Only bullying (OR = 7.3; 95%CI = 2-32) and suicidal behavior (OR = 7.6; 95%CI = 1.5-47.8) remained significant after adjustment for confounders. In a supplementary analysis, we developed a model using supervised machine learning to identify the most relevant variables that differentiated participants with psychotic symptoms, which included bullying, Clinical Global Impression-Severity scale (CGI-S), and suicidal behavior (accuracy = 75%, [p = 0.03]; sensitivity = 77.91%; specificity = 69.05%; area under the curve [AUC] = 0.86).

LIMITATIONS

Small sample, cross-sectional design, and generalizability of findings beyond the outpatient clinical sample.

CONCLUSIONS

Findings underscore the importance of assessing bullying in PBD participants. Future longitudinal studies with larger samples are needed to replicate our findings and determine causality.

Machine learning and big data analytics in bipolar disorder: A position paper from the International Society for Bipolar Disorders Big Data Task Force

OBJECTIVES

The International Society for Bipolar Disorders Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learning and big data analytics strategies for BD.

METHOD

A task force was convened to examine and integrate findings from the scientific literature related to machine learning and big data based studies to clarify terminology and to describe challenges and potential applications in the field of BD. We also systematically searched PubMed, Embase, and Web of Science for articles published up to January 2019 that used machine learning in BD.

RESULTS

The results suggested that big data analytics has the potential to provide risk calculators to aid in treatment decisions and predict clinical prognosis, including suicidality, for individual patients. This approach can advance diagnosis by enabling discovery of more relevant data-driven phenotypes, as well as by predicting transition to the disorder in high-risk unaffected subjects. We also discuss the most frequent challenges that big data analytics applications can face, such as heterogeneity, lack of external validation and replication of some studies, cost and non-stationary distribution of the data, and lack of appropriate funding.

CONCLUSION

Machine learning-based studies, including atheoretical data-driven big data approaches, provide an opportunity to more accurately detect those who are at risk, parse-relevant phenotypes as well as inform treatment selection and prognosis. However, several methodological challenges need to be addressed in order to translate research findings to clinical settings.

Clinical differences between patients with pediatric bipolar disorder with and without a parental history of bipolar disorder

Pediatric Bipolar Disorder (PBD) is a highly heritable condition responsible for 18% of all pediatric mental health hospitalizations. Despite the heritability of this disorder, few studies have assessed potential differences in the clinical manifestation of PBD among patients with a clear parental history of BD. Additionally, while recent studies suggest that attentional deficits are a potential endophenotypic marker of PBD, it is unclear whether heritability is a relevant contributor to these symptoms. In order to address this gap, the present study assessed 61 youth with PBD (6-17 years old), corresponding to 27 offspring of BD patients, and 31 PBD patients without a parental history of the disorder. All standardized assessments, including the K-SADS-PL-W were performed by trained child and adolescent psychiatrists. We performed a logistic multivariate model using the variables of ADHD, rapid cycling, and lifetime psychosis. Rates of ADHD comorbidity were significantly higher among PBD patients who had a parent with BD. Furthermore, PBD patients who had a parent with BD showed a trend toward significance of earlier symptom onset. PBD offspring did not show increased rates of suicide attempts, rapid cycling, or psychosis. Given these findings, it appears that PBD patients who have a parent with BD may represent a distinct endophenotype of the disorder. Future longitudinal and larger studies are required to confirm our findings.

Canadian Network for Mood and Anxiety Treatments (CANMAT) and International Society for Bipolar Disorders (ISBD) 2018 guidelines for the management of patients with bipolar disorder

The Canadian Network for Mood and Anxiety Treatments (CANMAT) previously published treatment guidelines for bipolar disorder in 2005, along with international commentaries and subsequent updates in 2007, 2009, and 2013. The last two updates were published in collaboration with the International Society for Bipolar Disorders (ISBD). These 2018 CANMAT and ISBD Bipolar Treatment Guidelines represent the significant advances in the field since the last full edition was published in 2005, including updates to diagnosis and management as well as new research into pharmacological and psychological treatments. These advances have been translated into clear and easy to use recommendations for first, second, and third- line treatments, with consideration given to levels of evidence for efficacy, clinical support based on experience, and consensus ratings of safety, tolerability, and treatment-emergent switch risk. New to these guidelines, hierarchical rankings were created for first and second- line treatments recommended for acute mania, acute depression, and maintenance treatment in bipolar I disorder. Created by considering the impact of each treatment across all phases of illness, this hierarchy will further assist clinicians in making evidence-based treatment decisions. Lithium, quetiapine, divalproex, asenapine, aripiprazole, paliperidone, risperidone, and cariprazine alone or in combination are recommended as first-line treatments for acute mania. First-line options for bipolar I depression include quetiapine, lurasidone plus lithium or divalproex, lithium, lamotrigine, lurasidone, or adjunctive lamotrigine. While medications that have been shown to be effective for the acute phase should generally be continued for the maintenance phase in bipolar I disorder, there are some exceptions (such as with antidepressants); and available data suggest that lithium, quetiapine, divalproex, lamotrigine, asenapine, and aripiprazole monotherapy or combination treatments should be considered first-line for those initiating or switching treatment during the maintenance phase. In addition to addressing issues in bipolar I disorder, these guidelines also provide an overview of, and recommendations for, clinical management of bipolar II disorder, as well as advice on specific populations, such as women at various stages of the reproductive cycle, children and adolescents, and older adults. There are also discussions on the impact of specific psychiatric and medical comorbidities such as substance use, anxiety, and metabolic disorders. Finally, an overview of issues related to safety and monitoring is provided. The CANMAT and ISBD groups hope that these guidelines become a valuable tool for practitioners across the globe.