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.

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.

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.

Managing the Dual Diagnosis Dilemma of Bipolar Disorder and Substance Abuse in Clinical Settings.

OBJECTIVE: Drug addiction is a chronic mental disorder that significantly impacts all aspects of an individual's life, and substance use disorder in patients with bipolar disorder. The objective of this study is to assess the frequency of substance abuse among patients with bipolar spectrum disorder. METHOD: This cross-sectional study evaluated the frequency of bipolar spectrum disorder in patients taking methadone through various screening measures, including Mini Mental State Examination (MMSE), DSM IV criteria, Mood Disorders Questionnaire (MDQ), Goodwin and Ghaemi's criteria, and Akiskal classification for bipolar disorders. RESULTS: Out of the total 197 participants in the study, 77 were identified as individuals engaging in poly-substance abuse. The investigation assessed the frequency of bipolar spectrum disorder based on various diagnostic criteria: 24% according to DSM-IV criteria, 29.9% using MDQ, 29.9% based on Ghaemi and Goodwin's criteria, and the highest rate at 48.2% when applying Akiskal's classification. CONCLUSIONS: This study highlights the high frequency of bipolar disorder among individuals with substance use disorder, especially those with concomitant depression. Therefore, it is crucial to pay special attention to individuals with substance use disorder with co-existing bipolar disorder.

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.

Mapping prodromal symptoms in patients with bipolar disorder: A network perspective.

Bipolar disorder (BD) is a major mental disorder that significantly impairs behavior and social functioning. This study assessed the network structure of prodromal symptoms in patients with BD prior to their index mood episode. Semi-structured interviews were conducted with the Bipolar Prodrome Symptom Scale-Retrospective (BPSS-R) to examine patients' prodromal symptoms. Network analysis was conducted to elucidate inter-relations between prodromal symptoms. A total of 120 eligible patients participated in this study. Network analysis indicated that the observed model was stable. The edge Mania3-Depression9 ('Racing thoughts' - 'Thinking about suicide', edge weight = 14.919) showed the strongest positive connection in the model, followed by the edge Mania1-depression1 ('Extremely energetic/active' - 'Depressed mood', edge weight = 14.643). The only negative correlation in the model was for Mania7-depression2 ('Overly self-confident' - 'Tiredness or lack of energy', edge weight = -1.068). Nodes Mania3 ('Racing thoughts'), Depression9 ('Thinking about suicide'), Mania1 ('Extremely energetic/active'), and Depression1 ('Depressed mood') were the most central symptoms. Both depressive and manic or hypomanic symptoms appeared in the prodromal phase. Symptoms reflecting 'Racing thoughts', 'Thinking about suicide', 'Extremely energetic/active', and 'Depressed mood' should be thoroughly assessed and targeted as crucial prodromal symptoms in interventions to reduce the risk of BD episodes.

Comparative study of sleep and circadian rhythms in patients presenting unipolar or bipolar major depressive episodes.

Currently, there is a major challenge in distinguishing between unipolar and bipolar major depressive episode. A significant body of research has been dedicated to identifying biomarkers that can aid in this differentiation due to its crucial implications, particularly for therapeutic and prognostic purposes. Among the biomarkers of interest, markers related to sleep and circadian rhythms show promise and could potentially aid in making this distinction. Nevertheless, no study has simultaneously examined sleep-wake disorders, circadian rhythms, and seasonal patterns using both subjective and objective measures. This study aims to characterize and compare the sleep-wake and rhythm disorders including patients with unipolar major depressive episode (n = 72) and with bipolar major depressive episode (n = 43) using both subjective markers (using self-report questionnaires and sleep complaints) and objective markers (using actigraphy). Patients with unipolar major depressive episode seem to experience significantly poorer quality of sleep, more symptoms of insomnia and lower sleep efficiency compared to patients with bipolar major depressive episode. On the other hand, patients with bipolar major depressive episode exhibit significantly more symptoms of motor retardation and hypersomnia compared to patients with unipolar disorder. These results hold significant implications for identifying individuals with unipolar major depressive episode or bipolar major depressive episode using sleep and circadian markers, and for developing recommended and personalized therapeutic strategies.

[Psychopharmacotherapy of mixed affective states in bipolar disorder]. / Psikhofarmakoterapiya smeshannykh affektivnykh sostoyanii pri bipolyarnom rasstroistve.

On the example of a patient with a mixed affective episode within the framework of bipolar affective disorder, the clinical features of this psychopathological condition, the difficulties of diagnosis and selection of therapy in mixed states are presented. The use of the modern atypical antipsychotic ziprasidone in this category of patients is argued.

Heterogeneity of outcome measures in depression trials and the relevance of the content of outcome measures to patients: a systematic review.

Research waste occurs when randomised controlled trial (RCT) outcomes are heterogeneous or overlook domains that matter to patients (eg, relating to symptoms or functions). In this systematic review, we reviewed the outcome measures used in 450 RCTs of adult unipolar and bipolar depression registered between 2018 and 2022 and identified 388 different measures. 40% of the RCTs used the same measure (Hamilton Depression Rating Scale [HAMD]). Patients and clinicians matched each item within the 25 most frequently used measures with 80 previously identified domains of depression that matter to patients. Seven (9%) domains were not covered by the 25 most frequently used outcome measures (eg, mental pain and irritability). The HAMD covered a maximum of 47 (59%) of the 80 domains that matter to patients. An interim solution to facilitate evidence synthesis before a core outcome set is developed would be to use the most common measures and choose complementary scales to optimise domain coverage. TRANSLATIONS: For the French and Dutch translations of the abstract see Supplementary Materials section.

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.

Suspected geriatric onset of attention-deficit/hyperactivity disorder in a patient with comorbid bipolar disorder.

BACKGROUND: An increasing number of adults over 60 years old are presenting with requests for treatment of attention-deficit/hyperactivity disorder (ADHD). However, the prevalence of ADHD in older adults in geriatrics is unknown. Further, comorbid bipolar disorder and adult ADHD are likely underrecognized with many patients only receiving treatment for one of these conditions. The occurrence of bipolar disorder with geriatric onset ADHD is unknown. CASE PRESENTATION: A 64-year-old Hispanic woman with a psychiatric history of bipolar I disorder (diagnosed in early adulthood) was diagnosed with ADHD suspected of geriatric onset, and able to be successfully managed on concurrent mood stabilizers and psychostimulant medication. CONCLUSIONS: The findings of this case report emphasize the importance of appropriately recognizing and treating comorbid ADHD and bipolar disorder in any age group, including the geriatric population for which this occurrence appears to be very rare. Additionally, this case report demonstrates the safe utilization of psychostimulant medications in a geriatric patient with bipolar disorder without inducing a manic episode or other significant adverse reactions.

Olink proteomics analysis uncovers inflammatory proteins in patients with different states of bipolar disorder.

STUDY DESIGN: A prospective study. BACKGROUND: This study aims to investigate the relationship between different states of bipolar disorder (BD) and plasma inflammatory proteins, which may be used as their biomarkers. MATERIALS AND METHODS: We totally collected admission plasma from 16 healthy subjects and 32 BD patients, including 16 patients with BD manic episodes (BD-M) and 16 patients with BD depressive episodes (BD-D). Ten samples in each group were analyzed by proximity extension assays of 92 inflammation-related proteins, and all samples were verified by ELISA. Receiver-operating characteristic (ROC) curve analysis was performed to identify the diagnostic ability and cut-off values of potential biomarkers. RESULTS: Our findings showed that BD patients had significantly higher levels of IL6, MCP-1, TGF-α, IL8, and IL10-RB in comparison with healthy subjects, and their cut-off values were 0.531 pg/ml, 0.531 pg/ml, 0.469 pg/ml, 0.406 pg/ml, and 0.406 pg/ml, respectively. The levels of IL6, MCP-1, TGF-α, and IL8 in BD-M patients were significantly greater than in healthy individuals, and their cut-off values were 0.813 pg/ml, 0.688 pg/ml, 0.438 pg/ml, and 0.625 pg/ml, respectively. Moreover, we found cut-off values of 0.500 pg/mL and 0.688 ng/mL for TGF-α and ß-NGF, respectively, even though the levels in the BD-D group were much higher than in the control group. Furthermore, BD-M patients had significantly higher levels of IL6, FGF-19, IFN-γ, and IL-17C in comparison with BD-D patients. Likewise, 0.687 pg/ml, 0.500 pg/ml, 0.438 pg/ml, and 0.375 pg/ml were their cut-off values, respectively. Our findings also showed that the combination of these proteins had the highest diagnostic accuracy. CONCLUSIONS: Our findings showed that plasma inflammatory proteins were related to BD and its subtypes, which may be utilized as potential biomarkers of different stages of BD. Furthermore, we also found their cut-off values and their combinations to have the highest diagnostic accuracy, providing clinicians with a new method to rapidly differentiate BD and its subtypes and manage early targeted interventions.

MoodSensing: A smartphone app for digital phenotyping and assessment of bipolar disorder.

BACKGROUND: Daily life tracking has proven to be of great help in the assessment of patients with bipolar disorder. Although there are many smartphone apps for tracking bipolar disorder, most of them lack academic verification, privacy policy and long-term maintenance. METHODS: Our developed app, MoodSensing, aims to collect users' digital phenotyping for assessment of bipolar disorder. The data collection was approved by the Institutional Review Board. This study collaborated with professional clinicians to ensure that the app meets both clinical needs and user experience requirements. Based on the collected digital phenotyping, deep learning techniques were applied to forecast participants' weekly HAM-D and YMRS scale scores. RESULTS: In experiments, the data collected by our app can effectively predict the scale scores, reaching the mean absolute error of 0.84 and 0.22 on the scales. The statistical data also demonstrate the increase in user engagement. CONCLUSIONS: Our analysis reveals that the developed MoodSensing app can not only provide a good user experience, but also the recorded data have certain discriminability for clinical assessment. Our app also provides relevant policies to protect user privacy, and has been launched in the Apple Store and Google Play Store.

Task-state skin potential abnormalities can distinguish major depressive disorder and bipolar depression from healthy controls.

Early detection of bipolar depression (BPD) and major depressive disorder (MDD) has been challenging due to the lack of reliable and easily measurable biological markers. This study aimed to investigate the accuracy of discriminating patients with mood disorders from healthy controls based on task state skin potential characteristics and their correlation with individual indicators of oxidative stress. A total of 77 patients with BPD, 53 patients with MDD, and 79 healthy controls were recruited. A custom-made device, previously shown to be sufficiently accurate, was used to collect skin potential data during six emotion-inducing tasks involving video, pictorial, or textual stimuli. Blood indicators reflecting individual levels of oxidative stress were collected. A discriminant model based on the support vector machine (SVM) algorithm was constructed for discriminant analysis. MDD and BPD patients were found to have abnormal skin potential characteristics on most tasks. The accuracy of the SVM model built with SP features to discriminate MDD patients from healthy controls was 78% (sensitivity 78%, specificity 82%). The SVM model gave an accuracy of 59% (sensitivity 59%, specificity 79%) in classifying BPD patients, MDD patients, and healthy controls into three groups. Significant correlations were also found between oxidative stress indicators in the blood of patients and certain SP features. Patients with depression and bipolar depression have abnormalities in task-state skin potential that partially reflect the pathological mechanism of the illness, and the abnormalities are potential biological markers of affective disorders.