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.

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.

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.

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.

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.

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.

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.

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.

Bipolar symptoms, somatic burden and functioning in older-age bipolar disorder: A replication study from the global aging & geriatric experiments in bipolar disorder database (GAGE-BD) project.

OBJECTIVES: The Global Aging & Geriatric Experiments in Bipolar Disorder Database (GAGE-BD) project pools archival datasets on older age bipolar disorder (OABD). An initial Wave 1 (W1; n = 1369) analysis found both manic and depressive symptoms reduced among older patients. To replicate this finding, we gathered an independent Wave 2 (W2; n = 1232, mean ± standard deviation age 47.2 ± 13.5, 65% women, 49% aged over 50) dataset. DESIGN/METHODS: Using mixed models with random effects for cohort, we examined associations between BD symptoms, somatic burden and age and the contribution of these to functioning in W2 and the combined W1 + W2 sample (n = 2601). RESULTS: Compared to W1, the W2 sample was younger (p < 0.001), less educated (p < 0.001), more symptomatic (p < 0.001), lower functioning (p < 0.001) and had fewer somatic conditions (p < 0.001). In the full W2, older individuals had reduced manic symptom severity, but age was not associated with depression severity. Age was not associated with functioning in W2. More severe BD symptoms (mania p ≤ 0.001, depression p ≤ 0.001) were associated with worse functioning. Older age was significantly associated with higher somatic burden in the W2 and the W1 + W2 samples, but this burden was not associated with poorer functioning. CONCLUSIONS: In a large, independent sample, older age was associated with less severe mania and more somatic burden (consistent with previous findings), but there was no association of depression with age (different from previous findings). Similar to previous findings, worse BD symptom severity was associated with worse functioning, emphasizing the need for symptom relief in OABD to promote better functioning.

Antecedents of major depressive, bipolar, and psychotic disorders: A systematic review and meta-analysis of prospective studies.

Major depressive, bipolar, or psychotic disorders are preceded by earlier manifestations in behaviours and experiences. We present a synthesis of evidence on associations between person-level antecedents (behaviour, performance, psychopathology) in childhood, adolescence, or early adulthood and later onsets of major depressive disorder, bipolar disorder, or psychotic disorder based on prospective studies published up to September 16, 2022. We screened 11,342 records, identified 460 eligible publications, and extracted 570 risk ratios quantifying the relationships between 52 antecedents and onsets in 198 unique samples with prospective follow-up of 122,766 individuals from a mean age of 12.4 to a mean age of 24.8 for 1522,426 person years of follow-up. We completed meta-analyses of 12 antecedents with adequate data. Psychotic symptoms, depressive symptoms, anxiety, disruptive behaviors, affective lability, and sleep problems were transdiagnostic antecedents associated with onsets of depressive, bipolar, and psychotic disorders. Attention-deficit/hyperactivity and hypomanic symptoms specifically predicted bipolar disorder. While transdiagnostic and diagnosis-specific antecedents inform targeted prevention and help understand pathogenic mechanisms, extensive gaps in evidence indicate potential for improving early risk identification.

Identifying predictive factors for mood recurrence in early-onset major mood disorders: A 4-year, multicenter, prospective cohort study.

We investigate the predictive factors of the mood recurrence in patients with early-onset major mood disorders from a prospective observational cohort study from July 2015 to December 2019. A total of 495 patients were classified into three groups according to recurrence during the cohort observation period: recurrence group with (hypo)manic or mixed features (MMR), recurrence group with only depressive features (ODR), and no recurrence group (NR). As a result, the baseline diagnosis of bipolar disorder type 1 (BDI) and bipolar disorder type 2 (BDII), along with a familial history of BD, are strong predictors of the MMR. The discrepancies in wake-up times between weekdays and weekends, along with disrupted circadian rhythms, are identified as a notable predictor of ODR. Our findings confirm that we need to be aware of different predictors for each form of mood recurrences in patients with early-onset mood disorders. In clinical practice, we expect that information obtained from the initial assessment of patients with mood disorders, such as mood disorder type, family history of BD, regularity of wake-up time, and disruption of circadian rhythms, can help predict the risk of recurrence for each patient, allowing for early detection and timely intervention.

Increased circulating cell-free mitochondrial DNA in plasma of first-diagnosed drug-naïve bipolar disorder patients: A case-control and 4-week follow-up study.

BACKGROUND: The study of clinical biological indicators in bipolar disorder (BD) is important. In recent years, basic experiments have associated the pathophysiological mechanism of BD is related to mitochondrial dysfunction, but few clinical studies have confirmed this finding. OBJECT: The present study aimed to evaluate whether plasma circulating cell-free mitochondrial DNA (ccf-mtDNA) levels, which can represent the degree of mitochondrial damage in vivo, are altered in patients with BD in early onset and during treatment compared with controls. METHOD: A total of 75 first-diagnosed drug-naive patients with BD and 60 HCs were recruited and followed up for 1 month. The clinical symptoms were assessed using HAMD, HAMA, and YMRS, and ccf-mtDNA levels were measured by qPCR before and after drug treatment in BD. RESULT: (1) The plasma ccf-mtDNA levels in first-diagnosed drug-naive patients with BD increased compared with those in HCs (p = 0.001). (2) Drug treatment for 1 month can decrease the expression of ccf-mtDNA in BD (p < 0.001). (3) No significant correlation was observed between the changes in ccf-mtDNA levels and the improvement of clinical symptoms in BD after drug treatment. CONCLUSION: The plasma ccf-mtDNA level was increased in BD, and decreased after pharmacological treatment. These outcomes suggested that plasma ccf-mtDNA level is likely to be sensitive to the drug response in BD, and mitochondrial pathway is a potential target for further therapy.