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.

Clinical distinctions in symptomatology and psychiatric comorbidities between misdiagnosed bipolar I and bipolar II disorder versus major depressive disorder.

BACKGROUND: To explore the demographic and clinical features of current depressive episode that discriminate patients diagnosed with major depressive disorder (MDD) from those with bipolar I (BP-I) and bipolar II (BP-II) disorder who were misdiagnosed as having MDD . METHODS: The Mini-International Neuropsychiatric Interview (MINI) assessment was performed to establish DSM-IV diagnoses of MDD, and BP-I and BP-II, previously being misdiagnosed as MDD. Demographics, depressive symptoms and psychiatric comorbidities were compared between 1463 patients with BP-I, BP-II and MDD from 8 psychiatric settings in mainland China. A multinomial logistic regression model was performed to assess clinical correlates of diagnoses. RESULTS: A total of 14.5% of the enrolled patients initially diagnosed with MDD were eventually diagnosed with BP. Broad illness characteristics including younger age, higher prevalence of recurrence, concurrent dysthymia, suicidal attempts, agitation, psychotic features and psychiatric comorbidities, as well as lower prevalence of insomnia, weight loss and somatic symptoms were featured by patients with BP-I and/or BP-I, compared to those with MDD. Comparisons between BP-I and BP-II versus MDD indicated distinct symptom profiles and comorbidity patterns with more differences being observed between BP-II and MDD, than between BP-I and MDD . CONCLUSION: The results provide evidence of clinically distinguishing characteristics between misdiagnosed BP-I and BP- II versus MDD. The findings have implications for guiding more accurate diagnoses of bipolar disorders.

Adults with both bipolar disorder and ADHD.

ADHD and bipolar disorder (BP) commonly coexist, and both share key symptoms, depending on affective state and emotional dysregulation. The overlap poses diagnostic challenges and may lead to underdiagnoses. Comorbid cases exhibit worsened symptom burden, increased psychiatric morbidity, admissions, and suicide attempts. Treating BP before ADHD is recommended. Stimulant use combined with mood stabilisers may be effective and relatively safe; however, this review finds that well-designed randomised controlled studies in the area is warranted.

Comparing Symptoms of Major Depression in Youth with Confirmed Versus Suspected Bipolar Disorder.

Background: While numerous studies have compared symptoms of major depressive episodes (MDEs) associated with bipolar disorder (BD; i.e., bipolar depression) versus major depressive disorder (MDD; i.e., unipolar depression), little is known about this topic in youth. We compared MDE symptoms in youth with BD with youth with suspected BD who have similar clinical and familial characteristics aside from having BD. Methods: MDE symptoms based on Kiddie Schedule for Affective Disorders and Schizophrenia for School Age Children (K-SADS) Depression Rating Scale items for the most severe past episode were compared in youth, ages 13-21 years, with BD (n = 208) versus suspected BD (n = 165). Diagnoses were confirmed via semistructured interviews. Symptoms with between-group differences (p < 0.05) in univariate analyses were evaluated in a multivariate forward stepwise regression. All analyses controlled for age and sex. Results: Youth with BD had significantly higher (more severe) ratings on depressed mood (p = 0.001, η2 = 0.05), irritability (p = 0.037, η2 = 0.02), anhedonia (p = 0.004, η2 = 0.04), negative self-image (p < 0.001, η2 = 0.07), hopelessness (p = 0.04, η2 = 0.02), fatigue (p = 0.001, η2 = 0.05), hypersomnia (p = 0.001, η2 = 0.05), suicidal ideation (p = 0.04, η2 = 0.02), and recurrent thoughts of death (p < 0.001, η2 = 0.05). In regression analyses, the only symptom that remained significant in the BD group was depressed mood (p = 0.002). Conclusions: These findings demonstrate greater severity of depressive symptoms in youth with BD versus MDD across mood, and cognitive and neurovegetative symptom domains. These differences are especially noteworthy given that the MDD group was highly similar to the BD group, aside from BD diagnosis. Present findings emphasize the need for novel treatment approaches to bipolar depression in youth, and for studies examining potential mechanisms underlying the increased severity of bipolar depression.

Adaption and validation of the Rwandese version of the Mood Disorder Questionnaire for the screening of bipolar disorder.

BACKGROUND: Bipolar disorder is challenging to diagnose. In Rwanda, a sub-Saharan country with a limited number of psychiatrists, the number of people with an undetected diagnosis of bipolar disorder could be high. Still, no screening tool for the disorder is available in the country. This study aimed to adapt and validate the Mood Disorder Questionnaire in the Rwandan population. METHODS: The Mood Disorder Questionnaire was translated into Kinyarwanda. The process involved back-translation, cross-cultural adaptation, field testing of the pre-final version, and final adjustments. A total of 331 patients with either bipolar disorder or unipolar major depression from two psychiatric outpatient hospitals were included. The statistical analysis included reliability and validity analyses and receiver operating characteristic curve (ROC) analysis. The optimal cut-off was chosen by maximizing Younden's index. RESULTS: The Rwandese version of The Mood Disorder Questionnaire had adequate internal consistency (Cronbach's alpha =0.91). The optimal threshold value was at least six positive items, which yielded excellent sensitivity (94.7%), and specificity (97.3%). The ROC area under the curve (AUC) was 0.99. CONCLUSION: The adapted tool showed good psychometric properties in terms of reliability and validity for the screening of bipolar disorder, with a recommended cutoff value of six items on the symptom checklist for a positive score and an exclusion of items 14 and 15. The tool has the potential to be a crucial instrument to identify otherwise undetected cases of bipolar disorder in Rwanda, improving access to mental health treatment, thus enhancing the living conditions of people with bipolar disorder.

AI algorithm combined with RNA editing-based blood biomarkers to discriminate bipolar from major depressive disorders in an external validation multicentric cohort.

Bipolar disorder (BD) is a leading cause of disability worldwide, as it can lead to cognitive and functional impairment and premature mortality. The first episode of BD is usually a depressive episode and is often misdiagnosed as major depressive disorder (MDD). Growing evidence indicates that peripheral immune activation and inflammation are involved in the pathophysiology of BD and MDD. Recently, by developing a panel of RNA editing-based blood biomarkers able to discriminate MDD from depressive BD, we have provided clinicians a new tool to reduce the misdiagnosis delay observed in patients suffering from BD. The present study aimed at validating the diagnostic value of this panel in an external independent multicentric Switzerland-based cohort of 143 patients suffering from moderate to major depression. The RNA-editing based blood biomarker (BMK) algorithm developped allowed to accurately discriminate MDD from depressive BD in an external cohort, with high accuracy, sensitivity and specificity values (82.5 %, 86.4 % and 80.8 %, respectively). These findings further confirm the important role of RNA editing in the physiopathology of mental disorders and emphasize the possible clinical usefulness of the biomarker panel for optimization treatment delay in patients suffering from BD.

Seasonal patterns in Chinese population: Validating the seasonal pattern assessment questionnaire and exploring associations with psychiatric diagnoses and biological rhythms.

Seasonal patterns (SP) exert a notable influence on the course and prognosis of patients with affective disorders, serving as a specifier in diagnosis. However, there is limited exploration of seasonality among psychotic patients, and the distinctions in seasonality among psychiatric patients remain unclear. In this study, we enrolled 198 psychiatric patients with anxiety and depressive disorders (A&D), bipolar disorder (BD), and schizophrenia (SZ), as well as healthy college students. Online questionnaires, including the Seasonal Pattern Assessment Questionnaire (SPAQ) for seasonality, the Morningness and Eveningness Questionnaire-5 (MEQ-5) for chronotypes, and the Pittsburgh Sleep Quality Index (PSQI), were administered. The validity and reliability of the Chinese version of the SPAQ were thoroughly analyzed, revealing a Cronbach's alpha of 0.896 with a two-factor structure. Results indicated that higher seasonality was correlated with poorer sleep quality and a more delayed chronotype (p < 0.05). Significant monthly variations were particularly evident in BD, specifically in mood, appetite, weight, social activities, and sleep dimensions (p < 0.001). In summary, the Chinese version of SPAQ is validated, demonstrating moderate correlations between seasonality, chronotype, and sleep quality. BD patients exhibited the strongest seasonality, while mood disorder patients displayed more delayed chronotypes than SZ.

Integrating Clinical Neuropsychology and Psychotic Spectrum Disorders: A Systematic Analysis of Cognitive Dynamics, Interventions, and Underlying Mechanisms.

Background and Objectives: The study aims to provide a comprehensive neuropsychological analysis of psychotic spectrum disorders, including schizophrenia, bipolar disorder, and depression. It focuses on the critical aspects of cognitive impairments, diagnostic tools, intervention efficacy, and the roles of genetic and environmental factors in these disorders. The paper emphasizes the diagnostic significance of neuropsychological tests in identifying cognitive deficiencies and their predictive value in the early management of psychosis. Materials and Methods: The study involved a systematic literature review following the PRISMA guidelines. The search was conducted in significant databases like Scopus, PsycINFO, PubMed, and Web of Science using keywords relevant to clinical neuropsychology and psychotic spectrum disorders. The inclusion criteria required articles to be in English, published between 2018 and 2023, and pertinent to clinical neuropsychology's application in these disorders. A total of 153 articles were identified, with 44 ultimately included for detailed analysis based on relevance and publication status after screening. Results: The review highlights several key findings, including the diagnostic and prognostic significance of mismatch negativity, neuroprogressive trajectories, cortical thinning in familial high-risk individuals, and distinct illness trajectories within psychosis subgroups. The studies evaluated underline the role of neuropsychological tests in diagnosing psychiatric disorders and emphasize early detection and the effectiveness of intervention strategies based on cognitive and neurobiological markers. Conclusions: The systematic review underscores the importance of investigating the neuropsychological components of psychotic spectrum disorders. It identifies significant cognitive impairments in attention, memory, and executive function, correlating with structural and functional brain abnormalities. The paper stresses the need for precise diagnoses and personalized treatment modalities, highlighting the complex interplay between genetic, environmental, and psychosocial factors. It calls for a deeper understanding of these neuropsychological processes to enhance diagnostic accuracy and therapeutic outcomes.

Perinatal photoperiod associations with bipolar disorder and depression: A systematic literature review and cross-sectional analysis of the UK Biobank database.

Season-of-birth associations with psychiatric disorders point to environmental (co-)aetiological factors such as natural photoperiod that, if clarified, may allow interventions toward prevention. We systematically reviewed the literature concerning season-of-birth and bipolar disorder and depression and explored associations between the perinatal natural photoperiod and these outcomes in a cross-sectional analysis of the UK Biobank database. We used mean daily photoperiod and relative photoperiod range (relative to the mean) in the 3rd trimester and, separately, in the first 3 months post birth as metrics. From review, increased risk of depression with late spring birth is compatible with increased odds of probable single episode-, probable recurrent-, and diagnosed depression (OR 2.85 95 %CI 1.6-5.08, OR 2.20 95 %CI 1.57-3.1, and OR 1.48 95 %CI 1.11-1.97, respectively) with increasing 3rd trimester relative photoperiod range for participants who experienced relatively non-extreme daily photoperiods. Risk of bipolar disorder with winter-spring birth contrasted with no consistent patterns of perinatal photoperiod metric associations with bipolar disorder in the UK Biobank. As natural photoperiod varies by both time-of-year and latitude, perinatal natural photoperiods (and a hypothesized mechanism of action via the circadian timing system and/or serotonergic circuitry associated with the dorsal raphe nucleus) may reconcile inconsistencies in season-of-birth associations. Further studies are warranted.

Developing a prediction model to identify people with severe mental illness without regular contact to their GP - a study based on data from the Danish national registers.

INTRODUCTION: People with severe mental illness (SMI) face a higher risk of premature mortality due to physical morbidity compared to the general population. Establishing regular contact with a general practitioner (GP) can mitigate this risk, yet barriers to healthcare access persist. Population initiatives to overcome these barriers require efficient identification of those persons in need. OBJECTIVE: To develop a predictive model to identify persons with SMI not attending a GP regularly. METHOD: For individuals with psychotic disorder, bipolar disorder, or severe depression between 2011 and 2016 (n = 48,804), GP contacts from 2016 to 2018 were retrieved. Two logistic regression models using demographic and clinical data from Danish national registers predicted severe mental illness without GP contact. Model 1 retained significant main effect variables, while Model 2 included significant bivariate interactions. Goodness-of-fit and discriminating ability were evaluated using Hosmer-Lemeshow (HL) test and area under the receiver operating characteristic curve (AUC), respectively, via cross-validation. RESULTS: The simple model retained 11 main effects, while the expanded model included 13 main effects and 10 bivariate interactions after backward elimination. HL tests were non-significant for both models (p = 0.50 for the simple model and p = 0.68 for the extended model). Their respective AUC values were 0.789 and 0.790. CONCLUSION: Leveraging Danish national register data, we developed two predictive models to identify SMI individuals without GP contact. The extended model had slightly better model performance than the simple model. Our study may help to identify persons with SMI not engaging with primary care which could enhance health and treatment outcomes in this group.

Cancer diagnosis after emergency presentations in people with mental health and substance use conditions: a national cohort study.

BACKGROUND: Cancer survival and mortality outcomes for people with mental health and substance use conditions (MHSUC) are worse than for people without MHSUC, which may be partly explained by poorer access to timely and appropriate healthcare, from screening and diagnosis through to treatment and follow-up. Access and quality of healthcare can be evaluated by comparing the proportion of people who receive a cancer diagnosis following an acute or emergency hospital admission (emergency presentation) across different population groups: those diagnosed with cancer following an emergency presentation have lower survival. METHODS: National mental health service use datasets (2002-2018) were linked to national cancer registry and hospitalisation data (2006-2018), to create a study population of people aged 15 years and older with one of four cancer diagnoses: lung, prostate, breast and colorectal. The exposure group included people with a history of mental health/addiction service contact within the five years before cancer diagnosis, with a subgroup of people with a diagnosis of bipolar disorder, schizophrenia or psychotic disorders. Marginal standardised rates were used to compare emergency presentations (hospital admission within 30 days of cancer diagnosis) in the exposure and comparison groups, adjusted for age, gender (for lung and colorectal cancers), ethnicity, area deprivation and stage at diagnosis. RESULTS: For all four cancers, the rates of emergency presentation in the fully adjusted models were significantly higher in people with a history of mental health/addiction service use than people without (lung cancer, RR 1.19, 95% CI 1.13, 1.24; prostate cancer RR 1.69, 95% CI 1.44, 1.93; breast cancer RR 1.42, 95% CI 1.14, 1.69; colorectal cancer 1.31, 95% CI 1.22, 1.39). Rates were substantially higher in those with a diagnosis of schizophrenia, bipolar disorder or psychotic disorders. CONCLUSIONS: Implementing pathways for earlier detection and diagnosis of cancers in people with MHSUC could reduce the rates of emergency presentation, with improved cancer survival outcomes. All health services, including cancer screening programmes, primary and secondary care, have a responsibility to ensure equitable access to healthcare for people with MHSUC.

[Multiple sclerosis and bipolar disorder: an overlap between soma and psyche]. / Multiple sclerose en bipolaire stoornis: overlap tussen soma en psyche.

This clinical vignette describes a 29-year-old woman who had her first neurological manifestations of multiple sclerosis (MS) on the same day as a second lifetime manic episode as part of a bipolar I disorder. The patient was stable for eight years before this episode. An MRI-scan conducted during admission showed multiple demyelinating lesions in the frontal cortex, which might have influenced the development and course of the manic episode. Her manic symptoms went into remission during the same time as her neurological symptoms. This clinical vignette with literature review is an illustration of the interesting, yet still unknown relationship between MS and affective disorders, where one might be influenced by the other but also have a common pathophysiology. This highlights that the dividing line between neurology and psychiatry, whose pathophysiology often takes place in the same organ, is often arbitrary.

Digital Tools to Facilitate the Detection and Treatment of Bipolar Disorder: Key Developments and Future Directions.

Bipolar disorder (BD) impacts over 40 million people around the world, often manifesting in early adulthood and substantially impacting the quality of life and functioning of individuals. Although early interventions are associated with a better prognosis, the early detection of BD is challenging given the high degree of similarity with other psychiatric conditions, including major depressive disorder, which corroborates the high rates of misdiagnosis. Further, BD has a chronic, relapsing course, and the majority of patients will go on to experience mood relapses despite pharmacological treatment. Digital technologies present promising results to augment early detection of symptoms and enhance BD treatment. In this editorial, we will discuss current findings on the use of digital technologies in the field of BD, while debating the challenges associated with their implementation in clinical practice and the future directions.

Study on exosomes for identifying bipolar disorder in early stage: A cross-sectional and validation study protocol.

BACKGROUND: The difficulty is remained to accurately distinguish bipolar disorder (BD) from major depressive disorder (MDD) in early stage, with a delayed diagnosis for 5-10 years. BD patients are often treated with antidepressants systematically due to being diagnosed with MDD, affecting the disease course and clinical outcomes. The current study aims to explore the role of plasma exosomes as biomarker to distinguish BD from MDD in early stage. METHODS: Two stages are included. The first stage is a cross-sectional study, comparing the concentrations of plasma exosome microRNA and related proteins among BD group, MDD group, and healthy controls (HC) group (n = 40 respectively), to identify target biomarkers preliminarily. The "Latent Class Analysis" and "Receiver Operating Characteristic" analysis will be performed to determine the optimal concentration range for each biomarker. The second stage is to validate target markers in subjects, coming from an ongoing study focusing on patients with a first depressive episode. All target biomarkers will be test in plasma samples reserved at the initial stage to detect whether the diagnosis indicated by biomarker level is consistent with the diagnosis by DSM-5. Furthermore, the correlation between specific biomarkers and the manic episode, suicidal ideation, and adverse reactions will also be observed. DISCUSSION: Exosome-derived microRNA and related proteins have potential in serving as a good medium for exploring mental disorders because it can pass through the blood-brain barrier bidirectionally and convey a large amount of information stably. Improving the early diagnosis of BD would help implement appropriate intervention strategy as early as possible and significantly reduce the burden of disease.

Evaluation of metabolomics-based urinary biomarker models for recognizing major depression disorder and bipolar disorder.

BACKGROUND: Major depressive disorder (MDD) and bipolar disorder (BD) are psychiatric disorders with overlapping symptoms, leading to high rates of misdiagnosis due to the lack of biomarkers for differentiation. This study aimed to identify metabolic biomarkers in urine samples for diagnosing MDD and BD, as well as to establish unbiased differential diagnostic models. METHODS: We utilized a metabolomics approach employing ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS) to analyze the metabolic profiles of urine samples from individuals with MDD (n = 50), BD (n = 12), and healthy controls (n = 50). The identification of urine metabolites was verified using MS data analysis tools and online metabolite databases. RESULTS: Two diagnostic panels consisting of a combination of metabolites and clinical indicators were identified-one for MDD and another for BD. The discriminative capacity of these panels was assessed using the area under the receiver operating characteristic (ROC) curve, yielding an area under the curve (AUC) of 0.9084 for MDD and an AUC value of 0.9017 for BD. CONCLUSIONS: High-resolution mass spectrometry-based assays show promise in identifying urinary biomarkers for depressive disorders. The combination of urine metabolites and clinical indicators is effective in differentiating healthy controls from individuals with MDD and BD. The metabolic pathway indicating oxidative stress is seen to significantly contribute to depressive disorders.