Meta-analysis of the Interval between the Onset and Management of Bipolar Disorder

Person-level contributions of bipolar polygenic risk score to the prediction of new-onset bipolar disorder in at-risk offspring

BACKGROUND

Previous work indicates that polygenic risk scores (PRS) for bipolar disorder (BD) are elevated in adults and youth with BD, but whether BD-PRS can inform person-level diagnostic prediction is unknown. Here, we test whether BD-PRS improves performance of a previously published risk calculator (RC) for BD.

METHODS

156 parents with BD-I/II and their offspring ages 6-18 were recruited and evaluated with standardized diagnostic assessments every two years for >12 years. DNA was extracted from saliva samples, genotyping performed, and BD-PRS calculated based on a 2021 meta-analysis. Using a bootstrapped and cross-validated penalized Cox regression, we assessed whether BD-PRS (alone and interacting with clinical variables) improved RC performance.

RESULTS

Of 227 offspring, 38 developed BD during follow-up. The penalized regression selected BD-PRS and interactions between BD-PRS and parental age at mood disorder onset (AAO), depression, and anxiety. The resulting RC discriminated offspring who developed BD (vs. those that did not) with good accuracy (AUC = 0.81); removing BD-PRS and its interaction terms was associated with a significant decrement to the AUC (decrement = 0.07, p = 0.039). Further exploration of selected interaction terms indicated that all were significant (p-values<0.02), indicating that BD-PRS has a larger effect on the outcome in offspring with depression and anxiety, whose affected parent had a younger AAO.

CONCLUSIONS

The addition of BD-PRS to clinical/demographic predictors in the RC significantly improved its accuracy. BD-PRS predicted BD on the person-level, particularly in offspring of parents with earlier AAO who already had symptoms of anxiety and depression at intake.

Characterization of Bipolar Disorder I and II: Clinical Features, Comorbidities, and Pharmacological Pattern

Objective

Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition provides precise diagnostic criteria to differentiate between bipolar disorder (BD) type I and II; nevertheless, it can be challenging to come up with the right diagnosis. The aim of this study is to evaluate the sociodemographic differences, clinical features, comorbidities, and pharmacological pattern between patients with BD type I and II.

Methods

A total of 680 patients with BD type I and II were consecutively recruited to our psychiatry department. A semi-structured interview was used to collect several information.

Results

Patients with BD type I were mostly males, single, with a lower current age, and unemployed compared to patients with BD type II. Furthermore, patients with BD type I showed an earlier age at onset and a significant higher prevalence of psychotic and residual symptoms, a higher number of hospitalizations, and involuntary admissions. On the other hand, patients with BD type II were associated with a significant higher prevalence of lifetime suicide attempts, psychiatric comorbidities, and use of alcohol. Finally, antidepressant drugs were prescribed more often to patients with BD type II, while antipsychotics and mood stabilizers were mostly prescribed in patients with BD type I.

Conclusion

the differentiation of the 2 nosologic bipolar diagnosis is in line with the current scientific interest, confirming the existence of a markedly different profile between BD type I and II. This differentiation could reduce the heterogeneity of bipolar presentation in research, optimize clinical assessment, and increase the interest in developing more precise and individualized therapeutic strategies, also implementing psychosocial therapies.

The Impact on Anxiety Symptoms of an Immersive Virtual Reality Remediation Program in Bipolar Disorders: A Randomized Clinical Trial

Background: The objective of this work is to investigate the effectiveness of a cognitive remediation intervention on anxiety symptoms in people with bipolar disorder and the therapeutic effect on people whose anxiety symptoms were above the threshold for a screener and whose comorbidity could be identified as an anxiety disorder. Methods: The experimental intervention included 24 sessions (around 45 min each), two for each week over three months. The entire program was inspired by user-centered rehabilitation principles in a recovery-oriented perspective and an approach to bipolar disorder in an evolutionary and non-discriminating vision. The primary outcomes measure the score of the Zung Self-Rating Anxiety Scale (SAS), hypothesizing a higher decrease in the experimental group than in the control group. The survey has been conducted per the CONSORT guidelines for feasibility studies. Results: We evaluate a decrease in the overall SAS score from T0 to T1 to be higher in the experimental group compared to the control group, indicating an improvement in anxiety symptoms (p < 0.0001). Conclusions: The study suggests that virtual reality could have a role in treating anxiety symptoms and disorders in young adults with bipolar disorders or anxiety symptoms in people with hyperactivity and novelty-seeking behaviorsunder stress and high risk for bipolar disorder.

Adherence to clinical practice guidelines for using electroconvulsive therapy in elderly depressive patients

OBJECTIVES

Electroconvulsive therapy (ECT) is one of the most effective treatments in mood disorders, mainly in major depressive episode (MDE) in the context of either unipolar (MDD) or bipolar disorder (BD). However, ECT remains a neglected and underused treatment. Older people are at high risk patients for the development of adverse drug reactions. In this context, we sought to determine the duration of MDEs and the number of lines of treatment before the initiation of ECT in patients aged 65 years or over according to the presence or absence of first-line indications for using ECT from international guidelines.

METHODS

In this multicenter, retrospective study including patients aged 65 years or over with MDEs in MDD or BD who have been treated with ECT for MDEs, data on the duration of MDEs and the number of lines of treatment received before ECT were collected. The reasons for using ECT, specifically first-line indications (suicidality, urgency, presence of catatonic and psychotic features, previous ECT response, patient preference) were recorded. Statistical comparisons between groups used standard statistical tests.

RESULTS

We identified 335 patients. The mean duration of MDEs before ECT was about 9 months. It was significantly shorter in BD than in MDD- about 7 and 10 months, respectively. The co-occurrence of chronic medical disease increased the duration before ECT in the MDD group. The presence of first-line indications for using ECT from guidelines did not reduce the duration of MDEs before ECT, except where there was a previous response to ECT. The first-line indications reduced the number of lines of treatment before starting ECT.

CONCLUSION

Even if ECT seems to be a key treatment in the elderly population due to its efficacity and safety for MDEs, the delay before this treatment is still too long.

Improving Quality of Life in Bipolar Disorders with an Immersive Virtual Reality Remediation Training Randomized Controlled Trial (RCT)

Background: Health-related quality of life (H-QoL) is a critical measure in bipolar disorder (BD). Recent trials using virtual reality (VR) have shown potential in improving H-QoL. However, VR's effect on the H-QoL of people with BD needs to be further explored. Methods: This study involved a secondary analysis of a feasibility randomized controlled trial, focusing on "quality of life". Participants (aged 18-75) diagnosed with bipolar disorder were randomized into two groups. The experimental group used the CEREBRUM VR app, while the control group received the usual care. Quality of life was assessed using the Short-Form Health Survey (SF-12). Results: A total of 39 individuals in the experimental group and 25 in the control group represent the final samples. The results showed a greater improvement in the SF-12 total score in the experimental group (8.7%) compared to the control group (F = 66.851 p < 0.0001), specifically in the dimension of physical activity limitation, emotional impact, concentration, pain, calmness, energy levels, discouragement, and social activities. Conclusions: This study demonstrated an improvement in QoL for individuals with BD following a VR intervention. As a feasibility study, this secondary outcome needs to be confirmed by further phase III studies. If confirmed, VR could offer valuable rehabilitation tools and insights into the pathogenesis and treatment of BD.

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.

Exploring mood disorders and treatment options using human stem cells

Despite their global prevalence, the mechanisms for mood disorders like bipolar disorder and major depressive disorder remain largely misunderstood. Mood stabilizers and antidepressants, although useful and effective for some, do not have a high responsiveness rate across those with these conditions. One reason for low responsiveness to these drugs is patient heterogeneity, meaning there is diversity in patient characteristics relating to genetics, etiology, and environment affecting treatment. In the past two decades, novel induced pluripotent stem cell (iPSC) research and technology have enabled the use of human-derived brain cells as a new model to study human disease that can help account for patient variance. Human iPSC technology is an emerging tool to better understand the molecular mechanisms of these disorders as well as a platform to test novel treatments and existing pharmaceuticals. This literature review describes the use of iPSC technology to model bipolar and major depressive disorder, common medications used to treat these disorders, and novel patient-derived alternative treatment methods for non-responders stemming from past publications, as well as presenting new data derived from these models.

Neurophysiological profiles of patients with bipolar disorders as probed with transcranial magnetic stimulation: A systematic review

AIM

Bipolar disorder (BD) has a significant impact on global health, yet its neurophysiological basis remains poorly understood. Conventional treatments have limitations, highlighting the need for a better understanding of the neurophysiology of BD for early diagnosis and novel therapeutic strategies.

DESIGN

Employing a systematic review approach of the PRISMA guidelines, this study assessed the usefulness and validity of transcranial magnetic stimulation (TMS) neurophysiology in patients with BD.

METHODS

Databases searched included PubMed, MEDLINE, Embase, and PsycINFO, covering studies from January 1985 to January 2024.

RESULTS

Out of 6597 articles screened, nine studies met the inclusion criteria, providing neurophysiological insights into the pathophysiological basis of BD using TMS-electromyography and TMS-electroencephalography methods. Findings revealed significant neurophysiological impairments in patients with BD compared to healthy controls, specifically in cortical inhibition and excitability. In particular, short-interval cortical inhibition (SICI) was consistently diminished in BD across the studies, which suggests a fundamental impairment of cortical inhibitory function in BD. This systematic review corroborates the potential utility of TMS neurophysiology in elucidating the pathophysiological basis of BD. Specifically, the reduced cortical inhibition in the SICI paradigm observed in patients with BD suggests gamma-aminobutyric acid (GABA)-A receptor-mediated dysfunction, but results from other TMS paradigms have been inconsistent. Thus, complex neurophysiological processes may be involved in the pathological basis underlying BD. This study demonstrated that BD has a neural basis involving impaired GABAergic function, and it is highly expected that further research on TMS neurophysiology will further elucidate the pathophysiological basis of BD.

Response inhibition related neural oscillatory patterns show reliable early identification of bipolar from unipolar depression in a Go/No-Go task

BACKGROUND

Response inhibition is a key neurocognitive factor contributing to impulsivity in mood disorders. Here, we explored the common and differential alterations of neural circuits associated with response inhibition in bipolar disorder (BD) and unipolar disorder (UD) and whether the oscillatory signatures can be used as early biomarkers in BD.

METHODS

39 patients with BD, 36 patients with UD, 29 patients initially diagnosed with UD who later underwent diagnostic conversion to BD, and 36 healthy controls performed a Go/No-Go task during MEG scanning. We carried out time-frequency and connectivity analysis on MEG data. Further, we performed machine learning using oscillatory features as input to identify bipolar from unipolar depression at the early clinical stage.

RESULTS

Compared to healthy controls, patients had reduced rIFG-to-pre-SMA connectivity and delayed activity of rIFG. Among patients, lower beta power and higher peak frequency were observed in BD patients than in UD patients. These changes enabled accurate classification between BD and UD with an accuracy of approximately 80 %.

CONCLUSIONS

The inefficiency of the prefrontal control network is a shared mechanism in mood disorders, while the abnormal activity of rIFG is more specific to BD. Neuronal responses during response inhibition could serve as a diagnostic biomarker for BD in early stage.

Serum neuroactive metabolites of the tryptophan pathway in patients with acute phase of affective disorders

Background

Many studies showed disrupted tryptophan metabolism in patients with affective disorders. The aims of this study were to explore the differences in the metabolites of tryptophan pathway (TP) and the relationships between TP metabolites and clinical symptoms, therapeutic effect in patients with bipolar disorder with acute manic episode (BD-M), depressive episode (BD-D) and major depressive disorder (MDD).

Methods

Patients with BD-M (n=52) and BD-D (n=39), MDD (n=48) and healthy controls (HCs, n=49) were enrolled. The serum neuroactive metabolites levels of the TP were measured by liquid chromatography-tandem mass spectrometry. Hamilton Depression Scale-17 item (HAMD-17) and Young Mania Rating Scale (YMRS) were used to evaluate depressive and manic symptoms at baseline and after 8 weeks of antidepressants, mood stabilizers, some also received antipsychotic medication.

Results

The levels of tryptophan (TRP) and kynurenic acid (KYNA) were significantly lower and the ratios of tryptophan/kynurenine (TRP/KYN), 5-hydroxytryptamine/tryptophan (5-HT/TRP), quinolinic acid/kynurenic acid (QUIN/KYNA) were higher in BD-M, BD-D, MDD vs. HC. The levels of QUIN and the ratios of QUIN/KYNA were higher in BD-M than in BD-D, MDD, and HCs. The 5-hydroxyindoleacetic acid (5-HIAA) levels of patients with MDD were significantly higher than those in BD-M and BD-D. Binary logistic regression analysis showed the lower peripheral KYNA, the higher the QUIN level, and the higher the risk of BD-M; the lower peripheral KYNA and the higher KYN/TRP and 5-HT/TRP, the higher the risk of BD-D; and the lower the peripheral KYNA level and the higher the KYN/TRP and 5-HT/TRP, the higher the risk of MDD. Correlation analysis, showing a significant association between tryptophan metabolites and improvement of clinical symptoms, especially depression symptoms.

Conclusions

Patients with affective disorders had abnormal tryptophan metabolism, which involved in 5-HT and kynurenine pathway (KP) sub-pathway. Tryptophan metabolites might be potential biomarkers for affective disorders and some metabolites have been associated with remission of depressive symptoms.

Identifying prior signals of bipolar disorder using primary care electronic health records: a nested case-control study

BACKGROUND

Bipolar disorders are serious mental illnesses, yet evidence suggests that the diagnosis and treatment of bipolar disorder can be delayed by around 6 years.

AIM

To identify signals of undiagnosed bipolar disorder using routinely collected electronic health records.

DESIGN AND SETTING

A nested case-control study conducted using the UK Clinical Practice Research Datalink (CPRD) GOLD dataset, an anonymised electronic primary care patient database linked with hospital records. 'Cases' were adult patients with incident bipolar disorder diagnoses between 1 January 2010 and 31 July 2017.

METHOD

The patients with bipolar disorder (the bipolar disorder group) were matched by age, sex, and registered general practice to 20 'controls' without recorded bipolar disorder (the control group). Annual episode incidence rates were estimated and odds ratios from conditional logistic regression models were reported for recorded health events before the index (diagnosis) date.

RESULTS

There were 2366 patients with incident bipolar disorder diagnoses and 47 138 matched control patients (median age 40 years and 60.4% female: n = 1430/2366 with bipolar disorder and n = 28 471/47 138 without). Compared with the control group, the bipolar disorder group had a higher incidence of diagnosed depressive, psychotic, anxiety, and personality disorders and escalating self-harm up to 10 years before a bipolar disorder diagnosis. Sleep disturbance, substance misuse, and mood swings were more frequent among the bipolar disorder group than the control group. The bipolar disorder group had more frequent face-to-face consultations, and were more likely to miss multiple scheduled appointments and to be prescribed ≥3 different psychotropic medication classes in a given year.

CONCLUSION

Psychiatric diagnoses, psychotropic prescriptions, and health service use patterns might be signals of unreported bipolar disorder. Recognising these signals could prompt further investigation for undiagnosed significant psychopathology, leading to timely referral, assessment, and initiation of appropriate treatments.

Admixture Analysis of Age of Onset in Bipolar Disorder and Impact of Anxiety Comorbidity

BACKGROUND

 The present study aimed to examine clinical differences between subjects with early-onset (<21 years) and adult-onset (>30 years) bipolar I disorder, in particular, in relation to anxiety comorbidity.

METHOD

Subjects were selected from a cohort of 161 consecutive patients with bipolar disorder type I as diagnosed by the Structured Clinical Interview for DSM Disorder (SCID-I). Clinical characteristics and axis I comorbidity were compared between those whose illness first emerged before the age of 21 years (n=58) and those whose first episode occurred after the age of 30 years (n=27). Psychopathology was assessed using the 18-item version of the Brief Psychiatric Rating Scale (BPRS). The frequency of delusions, hallucinations, and formal thought disorders was evaluated with the SCID-I. Overall, social and occupational functioning was assessed by the Global Assessment of Functioning (GAF).

RESULTS

Most subjects with early-onset bipolar disorder were males, had panic disorder and substance abuse comorbidity, longer duration of illness, exhibited mood-incongruent delusions, and presented with a mixed episode at onset more frequently than the later adult-onset subjects. Mixed mania at the first episode of illness and lifetime panic disorder comorbidity predicted mixed polarity at the first hospitalization episode in the early-onset subjects.

CONCLUSIONS

Overall, early age at onset seems to delineate a distinct bipolar I disorder subtype characterized by a greater likelihood of mixed episodes, lifetime panic disorder comorbidity, and schizophrenia-like delusions.

Evaluation of a novel instrument for detecting bipolar disorders in China: The Rapid Mood Screener (RMS)

OBJECTIVE

Bipolar disorder is easily misdiagnosed with major depressive disorder (MDD). The Rapid Mood Screener (RMS) was developed to address this unmet clinical need. This study aims to translate and evaluated the reliability and validity of the RMS in Chinese adults with bipolar I/II disorder (BD-I/II).

METHODS

Brislin's translation and Delphi method were conducted to formulate the RMS-Chinses version (RMS-C). Patients with MDD (N = 99), BD-I (N = 77) and BD-II (N = 78) were included to assess the validity and reliability of RMS-C. The area under the curve (AUC) was computed to ascertain the ability of the Mood Disorder Questionnaire (MDQ) and RMS-C to distinguish BD-I and BD-II from MDD. The optimal cut-off scores for classification were also calculated by the maximum sensitivity and specificity.

RESULTS

The intraclass correlation coefficient of the RMS-C was 0.82 (95%CI, 0.71-0.89). The content validity index by six items were 0.71, 0.86, 1.00, 0.86, 1.00, and 1.00 in turn, and by scales was 0.90. The AUCs of the RMS-C in both BD-I/II, BD-I alone and BD-II alone were 0.83 (95 % CI, 0.78-0.89), 0.82 (95 % CI, 0.75-0.89) and 0.85 (95 % CI, 0.79-0.91), respectively, and were comparably to the MDQ. The optimal RMS-C values of the presence of BD-I and BD-II were >4 and 3, respectively.

CONCLUSION

The RMS-C is a valid, simple self-administer screening tool to help identify BD-I or BD-II in persons experiencing a depressive episode. Validating the impact of screening with the RMS-C on health outcomes and health economics is warranted.

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.

Young people at risk for developing bipolar disorder: Two-year findings from the multicenter prospective, naturalistic Early-BipoLife study

Early identification and intervention of individuals with an increased risk for bipolar disorder (BD) may improve the course of illness and prevent long‑term consequences. Early-BipoLife, a multicenter, prospective, naturalistic study, examined risk factors of BD beyond family history in participants aged 15-35 years. At baseline, positively screened help-seeking participants (screenBD at-risk) were recruited at Early Detection Centers and in- and outpatient depression and attention-deficit/hyperactivity disorder (ADHD) settings, references (Ref) drawn from a representative cohort. Participants reported sociodemographics and medical history and were repeatedly examined regarding psychopathology and the course of risk factors. N = 1,083 screenBD at-risk and n = 172 Ref were eligible for baseline assessment. Within the first two years, n = 31 screenBD at-risk (2.9 %) and none of Ref developed a manifest BD. The cumulative transition risk was 0.0028 at the end of multistep assessment, 0.0169 at 12 and 0.0317 at 24 months (p = 0.021). The transition rate with a BD family history was 6.0 %, 4.7 % in the Early Phase Inventory for bipolar disorders (EPIbipolar), 6.6 % in the Bipolar Prodrome Interview and Symptom Scale-Prospective (BPSS-FP) and 3.2 % with extended Bipolar At-Risk - BARS criteria). In comparison to help-seeking young patients from psychosis detection services, transition rates in screenBD at-risk participants were lower. The findings of Early-BipoLife underscore the importance of considering risk factors beyond family history in order to improved early detection and interventions to prevent/ameliorate related impairment in the course of BD. Large long-term cohort studies are crucial to understand the developmental pathways and long-term course of BD, especially in people at- risk.

Mitochondrial DNA oxidation, methylation, and copy number alterations in major and bipolar depression

Background

Mood disorders are common disabling psychiatric disorders caused by both genetic and environmental factors. Mitochondrial DNA (mtDNA) modifications and epigenetics are promising areas of research in depression since mitochondrial dysfunction has been associated with depression. In this study we aimed to investigate the mtDNA changes in depressive disorder (MDD) and bipolar disorder (BD).

Methods

Displacement loop methylation (D-loop-met), relative mtDNA copy number (mtDNA-cn) and mtDNA oxidation (mtDNA-oxi) were investigated in DNA samples of individuals with MDD (n = 34), BD (n = 23), and healthy controls (HC; n = 40) using the Real-Time Polymerase Chain Reaction (RT-PCR). Blood samples were obtained from a subset of individuals with MDD (n = 15) during a depressive episode (baseline) and after remission (8th week).

Results

The study groups exhibited significant differences in D-loop-met (p = 0.020), while relative mtDNA-cn and mtDNA-oxi showed comparable results. During the remission phase (8th week), there were lower levels of relative mtDNA-cn (Z = -2.783, p = 0.005) and D-loop-met (Z = -3.180, p = 0.001) compared to the acute MDD baseline, with no significant change in mtDNA-oxi levels (Z = -1.193, p = 0.233).

Conclusion

Our findings indicate significantly increased D-loop methylation in MDD compared to BD and HCs, suggesting distinct mtDNA modifications in these conditions. Moreover, the observed alterations in relative mtDNA-cn and D-loop-met during remission suggest a potential role of mtDNA alterations in the pathophysiology of MDD. Future studies may provide valuable insights into the dynamics of mtDNA modifications in both disorders and their response to treatment.

Bipolar affective disorder in India: A multi-site population-based cross-sectional study

Introduction

Bipolar Affective Disorder (BPAD) merits careful consideration within the medical and healthcare communities, researchers, and policymakers. This is due to its substantial disability burden, elevated prevalence of co-morbidities, heightened lifetime risk of suicidality, and a significant treatment gap. This article focuses on the lifetime and current prevalence, correlates, co-morbidities, associated disabilities, socio-economic impact, and treatment gap for BPAD in the adult population of the National Mental Health Survey (NMHS) 2016.

Materials and Methods

The NMHS 2016 was a nationally representative study conducted across 12 Indian states between 2014 and 2016. A multi-stage, stratified, random cluster sampling technique based on probability proportionate to size at each stage was used. The diagnosis of BPAD was based on Mini-International Neuropsychiatric Interview 6.0.0. Sheehan's Disability Scale was used to assess the disability.

Results

A total of 34,802 adults were interviewed. The overall weighted prevalence of BPAD was 0.3% [95% confidence interval (CI): 0.29-0.31] for current and 0.5% (95% CI: 0.49-0.51) for lifetime diagnosis. Male gender [odds ratio (OR) 1.56] and residence in urban metropolitans (OR 2.43) had a significantly higher risk of a lifetime diagnosis of BPAD. Substantial cross-sectional co-morbidities were noted as per MINI 6.0.0 with the diagnosis of current BPAD such as tobacco use disorder (33.3%), other substance use disorders (14.6%), and anxiety disorders (10.4%). Two-thirds of persons with current BPAD reported disability of varying severity at work (63%), social (59.3%), and family life (63%). The treatment gap for current BPAD was 70.4%.

Conclusion

Most individuals with current BPAD reported moderate-severe disability. There were substantial co-morbidities and a large treatment gap. These warrant concentrated efforts from policymakers in devising effective strategies.

Preliminary results from the Australian Genetics of Bipolar Disorder Study: A nation-wide cohort

OBJECTIVE

The Australian Genetics of Bipolar Disorder Study is a nation-wide cohort of adults living with bipolar disorder. The study aims to detect the relationships between genetic risk, symptom severity, and the lifetime prevalence of bipolar disorder, treatment response and medication side effects, and patterns and costs of health care usage.

METHODS

A total of 6682 participants (68.3% female; aged 44.8 ± 13.6 years [range = 18-90]) were recruited in three waves: a nation-wide media campaign, a mail-out based on prescriptions for lithium carbonate and through the Australian Genetics of Depression Study. Participants completed a self-report questionnaire. A total of 4706 (70%) participants provided a saliva sample and were genotyped and 5506 (82%) consented to record linkage of their Pharmaceutical and Medicare Benefits Schedule data.

RESULTS

Most participants were living with bipolar I disorder (n = 4068) while 1622 participants were living with bipolar II disorder and 992 with sub-threshold bipolar disorder. The mean age of bipolar disorder diagnosis was 32.7 ± 11.6 years but was younger in bipolar I (p = 2.0E-26) and females (p = 5.7E-23). Excluding depression with onset prior to bipolar disorder diagnosis, 64.5% of participants reported one or more co-occurring psychiatric disorders: most commonly generalised anxiety disorder (43.5%) and posttraumatic stress disorder (20.7%). Adverse drug reactions were common and resulted in discontinuation rates ranging from 33.4% for lithium to 63.0% for carbamazepine.

CONCLUSION

Our findings highlight the high rate of comorbidities and adverse drug reactions among adults living with bipolar disorder in the general Australian population. Future genomic analyses focus on identifying genetic variants influencing pharmacotherapy treatment response and side effects.

Help-seeking patterns and level of care for individuals with bipolar disorder in Rwanda

Most descriptive data on individuals with bipolar disorder originate from high-resource settings. Very little is known about the accessibility and service provision of intensive mental health care to persons living with bipolar disorder in low-resource settings. This information is needed to inform health systems and guide practitioners to improve standard treatment options and access to treatment. This cross-sectional study explored the level of care for outpatients with bipolar disorder and their help-seeking patterns at the two national referral hospitals in Rwanda. The study found that the majority, 93%, of outpatients with bipolar disorder in Rwanda were on prophylactic psychopharmacological treatment, but mainly first-generation antipsychotics and just 3% received lithium treatment. Furthermore, there was a lack of psychosocial intervention; consequently, 44% were not aware that they had bipolar disorder. Moreover, 1 in 5 participants utilized or had previously used traditional medicine. Awareness of own diagnostic status was not associated with educational level or use of traditional medicine. The study's sample size of 154 patients is relatively small, and the cross-sectional design does not provide causal inferences. The results demonstrate a considerable unmet need for improved mental health care services for individuals with bipolar disorder in Rwanda, including access to optimal medication and psychosocial interventions. Psychoeducation could be a possible starting point for improving the standard of care, informing the individual on their diagnosis and medication while empowering them to engage in their treatment plan. Trial registration: ClinicalTrials.gov NCT04671225. Registered on November 2020.

Polygenic prediction of bipolar disorder in a Latin American sample

To date, bipolar disorder (BD) genetic studies and polygenic risk scores (PRSs) for BD are based primarily on populations of European descent (EUR) and lack representation from other ancestries including Latin American (LAT). Here, we describe a new LAT cohort from the Mayo Clinic Bipolar Biobank (MCBB), a multisite collaboration with recruitment sites in the United States (EUR; 1,443 cases and 777 controls) and Mexico and Chile (LAT; 211 cases and 161 controls) and use the sample to explore the performance of a BD-PRS in a LAT population. Using results from the largest genome-wide association study of BD in EUR individuals, PRSice2 and LDpred2 were used to compute BD-PRSs in the LAT and EUR samples from the MCBB. PRSs explained up to 1.4% (PRSice) and 4% (LDpred2) of the phenotypic variance on the liability scale in the LAT sample compared to 3.8% (PRSice2) and 3.4% (LDpred2) in the EUR samples. Future larger studies should further explore the differential performance of different PRS approaches across ancestries. International multisite studies, such as this one, have the potential to address diversity-related limitations of prior genomic studies and ultimately contribute to the reduction of health disparities.

Suicidal risk and protective factors in major affective disorders: A prospective cohort study of 4307 participants

BACKGROUND

Suicidal behavior is strongly associated with major affective disorders, but there is a need to quantify and compare specific risk and protective factors in bipolar disorder (BD) and major depressive disorder (MDD).

METHODS

In 4307 extensively evaluated major affective-disorder participants with BD (n = 1425) or MDD (n = 2882) diagnosed by current international criteria, we compared characteristics among those with versus without suicidal acts from illness-onset through 8.24 years of follow-up.

RESULTS

Suicidal acts were identified in 11.4 % of participants; 25.9 % were violent and 6.92 % (0.79 % of all participants) were fatal. Associated risk factors included: diagnosis (BD > MDD), manic/psychotic features in first-episodes, family history of suicide or BD, separation/divorce, early abuse, young at illness-onset, female sex with BD, substance abuse, higher irritable, cyclothymic or dysthymic temperament ratings, greater long-term morbidity, and lower intake functional ratings. Protective factors included marriage, co-occurring anxiety disorder, higher ratings of hyperthymic temperament and depressive first episodes. Based on multivariable logistic regression, five factors remained significantly and independently associated with suicidal acts: BD diagnosis, more time depressed during prospective follow-up, younger at onset, lower functional status at intake, and women > men with BD.

LIMITATIONS

Reported findings may or may not apply consistently in other cultures and locations.

CONCLUSIONS

Suicidal acts including violent acts and suicides were more prevalent with BD than MDD. Of identified risk (n = 31) and protective factors (n = 4), several differed with diagnosis. Their clinical recognition should contribute to improved prediction and prevention of suicide in major affective disorders.

Bipolar II Disorder: Understudied and Underdiagnosed

Despite its inclusion as a distinct entity in APA's Diagnostic and Statistical Manual of Mental Disorders since 1994, bipolar II disorder remains a surprisingly neglected psychiatric condition. Understudied and underrecognized, bipolar II disorder is often misdiagnosed and misunderstood, even by experienced clinicians. As a result, patients typically experience symptoms for more than 10 years before receiving the correct diagnosis. Incorrect diagnosis leads to incorrect treatment, including overuse of monoaminergic antidepressant medications, with resultant declines in functioning and worse quality of life. Perhaps because of its underrecognition, treatment studies of bipolar II disorder are limited, and, too often, results of bipolar I disorder studies are applied to bipolar II disorder, with no direct evidence supporting this practice. Bipolar II disorder is an understudied and unmet treatment challenge in psychiatry. In this review, the authors provide a broad overview of bipolar II disorder, including differential diagnosis, course of illness, comorbid conditions, and suicide risk. The authors summarize treatment studies specific to bipolar II disorder, identifying gaps in the literature. This review reveals similarities between bipolar I and bipolar II disorders, including risks of suicide and predominance of depression over the course of illness, but also differences between the phenotypes in treatment response, for example, to antidepressant medications.

Early indicators of bipolar risk in preschool offspring of parents with bipolar disorder

BACKGROUND

Offspring of parents with bipolar disorder (BD-I/II) are at increased risk to develop the disorder. Previous work indicates that bipolar spectrum disorder (BPSD) is often preceded by mood/anxiety symptoms. In school-age offspring of parents with BD, we previously built a risk calculator to predict BPSD onset, which generates person-level risk scores. Here, we test whether preschool symptoms predict school-age BPSD risk.

METHODS

We assessed 113 offspring of parents with BD 1-3 times during preschool years (2-5 years old) and then approximately every 2 years for a mean of 10.6 years. We used penalized (lasso) regression with linear mixed models to assess relationships between preschool mood, anxiety, and behavioral symptoms (parent-reported) and school-age predictors of BPSD onset (i.e., risk score, subthreshold manic symptoms, and mood lability), adjusting for demographics and parental symptomatology. Finally, we conducted survival analyses to assess associations between preschool symptoms and school-age onset of BPSD and mood disorder.

RESULTS

Of 113 preschool offspring, 33 developed new-onset mood disorder, including 19 with new-onset BPSD. Preschool irritability, sleep problems, and parental factors were lasso-selected predictors of school-age risk scores. After accounting for demographic and parental factors, preschool symptoms were no longer significant. Lasso regressions to predict mood lability and subthreshold manic symptoms yielded similar predictors (irritability, sleep problems, and parental affective lability), but preschool symptoms remained predictive even after adjusting for parental factors (ps < .005). Exploratory analyses indicated that preschool irritability univariately predicted new-onset BPSD (p = .02) and mood disorder (p = .02).

CONCLUSIONS

These results provide initial prospective evidence that, as early as preschool, youth who will develop elevated risk scores, mood lability, and subthreshold manic symptoms are already showing symptomatology; these preschool symptoms also predict new-onset BPSD. While replication of findings in larger samples is warranted, results point to the need for earlier assessment of risk and development of early interventions.

Opportunities for digital health technology: identifying unmet needs for bipolar misdiagnosis and depression care management

Introduction

Digital health technologies (DHTs) driven by artificial intelligence applications, particularly those including predictive models derived with machine learning methods, have garnered substantial attention and financial investment in recent years. Yet, there is little evidence of widespread adoption and scant proof of gains in patient health outcomes. One factor of this paradox is the disconnect between DHT developers and digital health ecosystem stakeholders, which can result in developing technologies that are highly sophisticated but clinically irrelevant. Here, we aimed to uncover challenges faced by psychiatrists treating patients with major depressive disorder (MDD). Specifically, we focused on challenges psychiatrists raised about bipolar disorder (BD) misdiagnosis.

Methods

We conducted semi-structured interviews with 10 United States-based psychiatrists. We applied text and thematic analysis to the resulting interview transcripts.

Results

Three main themes emerged: (1) BD is often misdiagnosed, (2) information crucial to evaluating BD is often occluded from clinical observation, and (3) BD misdiagnosis has important treatment implications.

Discussion

Using upstream stakeholder engagement methods, we were able to identify a narrow, unforeseen, and clinically relevant problem. We propose an organizing framework for development of digital tools based upon clinician-identified unmet need.

Optimizing multi-domain hematologic biomarkers and clinical features for the differential diagnosis of unipolar depression and bipolar depression

There is a lack of objective features for the differential diagnosis of unipolar and bipolar depression, especially those that are readily available in practical settings. We investigated whether clinical features of disease course, biomarkers from complete blood count, and blood biochemical markers could accurately classify unipolar and bipolar depression using machine learning methods. This retrospective study included 1160 eligible patients (918 with unipolar depression and 242 with bipolar depression). Patient data were randomly split into training (85%) and open test (15%) sets 1000 times, and the average performance was reported. XGBoost achieved the optimal open-test performance using selected biomarkers and clinical features-AUC 0.889, sensitivity 0.831, specificity 0.839, and accuracy 0.863. The importance of features for differential diagnosis was measured using SHapley Additive exPlanations (SHAP) values. The most informative features include (1) clinical features of disease duration and age of onset, (2) biochemical markers of albumin, low density lipoprotein (LDL), and potassium, and (3) complete blood count-derived biomarkers of white blood cell count (WBC), platelet-to-lymphocyte ratio (PLR), and monocytes (MONO). Overall, onset features and hematologic biomarkers appear to be reliable information that can be readily obtained in clinical settings to facilitate the differential diagnosis of unipolar and bipolar depression.

Pharmacotherapy exposure as a marker of disease complexity in bipolar disorder: Associations with clinical & genetic risk factors

Individuals with bipolar disorder (BD) require chronic pharmacotherapy, typically including medication switches or polypharmacy due to persisting symptoms or intolerable side effects. Here, we quantified pharmacotherapy exposure (PE) of Mayo Clinic BD Biobank participants using the number of cross-sectional (at enrollment) and lifetime BD-specific medications and medication classes, to understand the relationship between PE and markers of disease severity or treatment failure, psychiatric comorbidities, and polygenic risk scores (PRS) for six major psychiatric disorders. Being female (p < 0.05), older (p < 0.01), having history of suicide attempts (p < 0.0001), and comorbid attention-deficit/hyperactivity disorder (p < 0.05) or generalized anxiety disorder (p < 0.05) were uniformly associated with higher PE. Lifetime exposure to unique medication classes among participants with BD-I was significantly lower than for those with schizoaffective disorder (estimate = -2.1, p < 0.0001) while significantly higher than for those with BD-II (estimate = 0.5, p < 0.01). Further, higher PRS for schizophrenia (SCZ) and anxiety resulted in greater lifetime medication counts (p < 0.01), both driven by antipsychotic (p < 0.001) and anxiolytic use (p < 0.05). Our results provide initial evidence of the utility of PE as a measure of disease complexity or treatment resistance, and that PE may be predicted by higher genetic risk for SCZ and anxiety.

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.

Effectiveness of internet delivered cognitive behaviour therapy provided as routine care for people in the depressed phase of bipolar disorder treated with Lithium

There is little research reporting the outcome of internet delivered cognitive behaviour therapy, (iCBT), which helps patients identify and modify unhelpful cognitions and behaviours, for the depressed phase of bipolar disorder as part of routine care. Demographic information, baseline scores and treatment outcomes were examined for patients of MindSpot Clinic, a national iCBT service who reported taking Lithium and their clinic records confirmed the diagnosis of bipolar disorder. Outcomes were completion rates, patient satisfaction and changes in measures of psychological distress, depression and anxiety measured by the Kessler-10 item (K-10), Patient Health Questionnaire 9 Item (PHQ-9), and Generalized Anxiety Disorder Scale 7 Item (GAD-7), compared to clinic benchmarks. Out of 21,745 people who completed a MindSpot assessment and enrolled in a MindSpot treatment course in a 7 year period, 83 reported taking Lithium and had a confirmed a diagnosis of bipolar disorder. Outcomes of reductions in symptoms were large on all measures (effect sizes > 1.0 on all measures, percentage change between 32.4% and 40%), and lesson completion and satisfaction with the course were also high. MindSpot treatments appear to be effective in treating anxiety and depression in people diagnosed with bipolar, and suggest that iCBT has the potential to overcome the under-use of evidence based psychological treatments of people with bipolar depression.

Persistent increase over time in oxidatively stress generated RNA and DNA damage in patients with newly diagnosed bipolar disorder and their unaffected first-degree relatives - An up to 5-year prospective study

OBJECTIVES

Increased oxidative stress generated nucleoside damage seems to play a crucial role in bipolar disorder (BD) pathophysiology. It may contribute to accelerated ageing and reduced life expectancy in patients with BD.

METHODS

In the five-year prospective "Bipolar Illness Onset study", we investigated repeated measurements of oxidative stress generated RNA and DNA damage in 357 patients with newly diagnosed/first-episode BD (880 visits), 132 of their unaffected first-degree relatives (236 visits) and 198 healthy age- and sex-matched control persons with no personal or first-degree family history of affective disorder (432 visits). Amongst patients with BD, we further investigated associations of oxidative stress generated RNA- and DNA damage with affective phases and measures of illness load.

RESULTS

Patients newly diagnosed with BD and their unaffected relatives had higher levels of oxidative stress generated RNA damage than healthy control individuals and these differences persisted over time, whereas DNA damage was less consistently elevated. Neither illness load nor affective phase impacted the levels in patients with BD.

CONCLUSIONS

Our findings support elevated oxidative stress generated RNA damage being a trait phenomenon in BD as indicated by persistent increase in RNA damage over time in patients newly diagnosed with BD and in their unaffected first-degree relatives compared with healthy control individuals. We did not detect state alterations in levels of oxidative stress.

Accuracy of the Arabic HCL - 32 and MDQ in detecting patients with bipolar disorder

BACKGROUND

Studies about the two most used and validated instruments for the early detection of Bipolar Disorder (BD), the 32 - item Hypomania Checklist (HCL - 32) and the Mood Disorder Questionnaire (MDQ), are scarce in non-Western countries. This study aimed to explore the reliability, factor structure, and criterion validity of their Arabic versions in a sample of Tunisian patients diagnosed with mood disorders.

METHODS

The sample included 59 patients with BD, 86 with unipolar Major Depressive Disorder (MDD) and 281 controls. Confirmatory factor analysis was applied to show that a single global score was an appropriate summary measure of the screeners in the sample. Receiver Operating Characteristic analysis was used to assess the capacity of the translated screeners to distinguish patients with BD from those with MDD and controls.

RESULTS

Reliability was good for both tools in all samples. The bifactor implementation of the most reported two-factor model had the best fit for both screeners. Both were able to distinguish patients diagnosed with BD from putatively healthy controls, and equally able to distinguish patients diagnosed with BD from patients with MDD.

CONCLUSION

Both screeners work best in excluding the presence of BD in patients with MDD, which is an advantage in deciding whether or not to prescribe an antidepressant.

Longer illness duration is associated with greater individual variability in functional brain activity in Schizophrenia, but not bipolar disorder

BACKGROUND

Individuals with schizophrenia exhibit greater inter-patient variability in functional brain activity during neurocognitive task performance. Some studies have shown associations of age and illness duration with brain function; however, the association of these variables with variability in brain function activity is not known. In order to better understand the progressive effects of age and illness duration across disorders, we examined the relationship with individual variability in brain activity.

METHODS

Neuroimaging and behavioural data were extracted from harmonized datasets collectively including 212 control participants, 107 individuals with bipolar disorder, and 232 individuals with schizophrenia (total n = 551). Functional activity in response to an N-back working memory task (2-back vs 1-back) was examined. Individual variability was quantified via the correlational distance of fMRI activity between participants; mean correlational distance of one participant in relation to all others was defined as a 'variability score'.

RESULTS

Greater individual variability was found in the schizophrenia group compared to the bipolar disorder and control groups (p = 1.52e-09). Individual variability was significantly associated with aging (p = 0.027), however, this relationship was not different across diagnostic groups. In contrast, in the schizophrenia sample only, a longer illness duration was associated with increased variability (p = 0.027).

CONCLUSION

An increase in variability was observed in the schizophrenia group related to illness duration, beyond the effects of normal aging, implying illness-related deterioration of cognitive networks. This has clinical implications for considering long-term trajectories in schizophrenia and progressive neural and cognitive decline which may be amiable to novel treatments.

A systematic review and meta-analysis of delayed help-seeking, delayed diagnosis and duration of untreated illness in bipolar disorders

OBJECTIVES

To examine the time delay between the age at onset of symptoms or episodes of bipolar disorders (BD) and the age at diagnosis of and/or receipt of clinical practice guideline recommended interventions for BD.

METHODS

Systematic search of five databases to identify publications from January 2000 to July 2022 that reported one or more of the following reliable and valid estimates of latency: delay in help seeking (DHS), delay in diagnosis (DD) and duration of untreated BD (DUB). Eligible studies were included in random effects meta-analyses and multivariate meta-regression was used to assess factors associated with each latency construct.

RESULTS

Screening of 1074 publications identified 59 eligible studies (reported in 66 publications) of >40,000 individuals that estimated DHS (8 studies), DD (20 studies) and/or DUB (45 studies). The median DHS, DD and DUB were 3.5 (IQR: 2.8, 8.48), 6.7 (IQR: 5.6, 8.9) and 5.9 years (IQR: 1.1, 8.2), respectively. Key factors associated with shorter DD included older age and residing outside North America; shorter DUB was associated with psychotic or manic onset and access to early intervention services.

CONCLUSIONS

Greater consensus on definitions of latency constructs and better-quality targeted research is required regarding DHS, DD and DUB. This review suggests that, while the peak age at onset of BD is 15-25, diagnosis and guideline recommended interventions (e.g., mood stabilizers) are likely to be delayed until age 25-35 years except for a minority of individuals with access to early intervention services.

Psychiatric polygenic risk scores: Child and adolescent psychiatrists' knowledge, attitudes, and experiences

Psychiatric polygenic risk scores (PRS) have potential utility in psychiatric care and prevention, but there are concerns about their implementation. We surveyed 960 US-based practicing child and adolescent psychiatrists' (CAP) about their experiences, perspectives, and potential uses of psychiatric PRS. While 23% of CAP reported that they had never heard of PRS, 10 % of respondents have had a patient/family bring PRS to them and 4% have generated PRS for patients. Though 25% stated they would request PRS if a patient/caregiver asked, 35% indicated that nothing would prompt them to request PRS. Most respondents (54%) believed psychiatric PRS are currently at least slightly useful and 87% believed they will be so in 5 years. More than 70% indicated they would take action in response to a child with a top fifth percentile psychiatric PRS but no diagnosis: 48% would increase monitoring of symptoms, 42% would evaluate for current symptoms, and 4% would prescribe medications. Yet, most respondents were concerned that high-PRS results could lead to overtreatment and negatively impact patients' emotional well-being. Findings indicate emerging use of psychiatric PRS within child and adolescent psychiatry in the US. It is critical to examine the ethical and clinical challenges that PRS may generate and begin efforts to promote their informed and responsible use.

Association between polarity of first episode and solar insolation in bipolar I disorder

OBJECTIVE

Circadian rhythm disruption is commonly observed in bipolar disorder (BD). Daylight is the most powerful signal to entrain the human circadian clock system. This exploratory study investigated if solar insolation at the onset location was associated with the polarity of the first episode of BD I. Solar insolation is the amount of electromagnetic energy from the Sun striking a surface area of the Earth.

METHODS

Data from 7488 patients with BD I were collected at 75 sites in 42 countries. The first episode occurred at 591 onset locations in 67 countries at a wide range of latitudes in both hemispheres. Solar insolation values were obtained for every onset location, and the ratio of the minimum mean monthly insolation to the maximum mean monthly insolation was calculated. This ratio is largest near the equator (with little change in solar insolation over the year), and smallest near the poles (where winter insolation is very small compared to summer insolation). This ratio also applies to tropical locations which may have a cloudy wet and clear dry season, rather than winter and summer.

RESULTS

The larger the change in solar insolation throughout the year (smaller the ratio between the minimum monthly and maximum monthly values), the greater the likelihood the first episode polarity was depression. Other associated variables were being female and increasing percentage of gross domestic product spent on country health expenditures. (All coefficients: P ≤ 0.001).

CONCLUSION

Increased awareness and research into circadian dysfunction throughout the course of BD is warranted.

Clinical and psychopathological correlates of duration of untreated illness (DUI) in affective spectrum disorders

Affective disorders represent psychopathological entities lying on a continuum, characterized by high prevalence and functional impairment. A delay in treatment initiation might increase the burden associated with affective spectrum disorders. The present study was aimed at analyzing the correlates of a long duration of untreated illness (DUI) in these conditions. We recruited subjects diagnosed with affective disorders, both in- and outpatients, and collected information concerning socio-demographic, clinical, and psychopathological characteristics. Long DUI was defined according to previous research criteria as >2 years for Bipolar Disorders or >1 year for Depressive Disorders. Bivariate analyses were performed to compare subjects with a long and short DUI (p<0.05). A logistic regression was operated to evaluate the correlates of long DUI. In the present sample (n=135), 34.1% (n=46) subjects showed a long DUI. This subgroup presented with more physical comorbidities (p=0.003), higher body mass index (BMI) (p<0.001), more frequent anxiety onset (p=0.018), younger onset age (p=0.042), and more severe depressive symptoms (Hamilton Depression Rating Scale item 1-depressed mood (p=0.032) and item 2-guilt feelings (p=0.018)). At the logistic regression, higher severity of depressed mood (OR 1.568), higher BMI (OR 1.264), and younger age at onset (OR 0.935) were associated with long DUI. The present study confirmed a possible role of DUI as a construct underpinning higher clinical severity in affective spectrum disorders, possibly linked to worse illness course and unfavorable outcomes. Intervention strategies targeting physical comorbidities and depressive symptoms severity may decrease disease burden in subjects with a long DUI.

Correlates of suicidality in young people with depressive disorders: A systematic review

OBJECTIVE

Depression is one of the most prevalent and disabling mental health conditions among young people worldwide. The health and economic burdens associated with depressive illness are substantial. Suicide and depression are closely intertwined, yet a diagnosis of depression itself lacks predictive specificity for suicidal behaviour. To better inform suicide prevention and early intervention strategies for young people, improved identification of modifiable intervention targets is needed. The objective of this review was to identify clinical, psychosocial and biological correlates of suicidality in young people diagnosed with a broad range of unipolar and bipolar depressive disorders.

METHOD

Systematic searches were conducted across MEDLINE, Embase and PsycINFO to identify studies of young people aged 15-25 years diagnosed with unipolar or bipolar depressive disorders. An assessment of suicidality was required for inclusion. Reporting followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 and Synthesis Without Meta-analysis guidelines.

RESULTS

We integrated findings from 71 studies including approximately 24,670 young people with clinically diagnosed depression. We identified 26 clinical, psychosocial and biological correlates of suicidality. Depression characteristics (type and severity), psychiatric comorbidity (particularly anxiety and substance use disorders) and neurological characteristics emerged as having the most evidence for being associated with suicidal outcomes. Our ability to pool data and conduct meaningful quantitative synthesis was hampered by substantial heterogeneity across studies and incomplete reporting; thus, meta-analysis was not possible.

CONCLUSION

Findings of this review reinforce the notion that suicidality is a complex phenomenon arising from the interplay of multiple contributing factors. Our findings question the utility of considering a diagnosis of depression as a specific risk factor for suicidality in young people. Suicidality itself is transdiagnostic; adoption of a transdiagnostic approach to investigating its aetiology and treatment is perhaps warranted. Future research investigating specific symptoms, or symptom networks, might help to further our understanding of suicidality among young people experiencing mental illness.

Eosinophils to Lymphocytes Ratio (ELR) as a Potential Inflammatory Biomarker in Patients with Dual Diagnosis of Bipolar and Alcohol Use Disorders: A Retrospective Cohort Study

Objective: It is well-established that Bipolar Disorder (BD) has comorbidity with Alcohol Use Disorder (AUD) and could present the same symptoms of an underlying diagnosis of BD, therefore delaying the proper relevant treatment. Recent studies show the occurrence of alterations in the circulating levels of inflammatory mediators in patients dealing with AUD as well as those with BD. The objective of this study is to get an assessment of whether patients with AUD and BD comorbidity [BD(+)] would present different ratios of the Complete Blood Count (CBC) in comparison with patients with AUD but without a BD comorbidity [BD(-)]. Methods: This is a retrospective study, conducted through a selection of patients files who were admitted to the psychiatric department at Hôtel-Dieu de France University Hospital in Beirut, Lebanon, between January of the year 2016 and May of the year 2021. Overall, 83 files of patients dealing with AUD were included in this study. Results: Patients with BD(+) showed a higher Eosinophils to Lymphocytes Ratio (ELR) in comparison to those with BD(-). The Receiver Operation Characteristic (ROC) analysis had an area under the curve at 0.719 with a p = .001. The cutoff value of ELR that best differentiates BD(-) from BD(+) was 0.087 (Sensitivity = 81.3%; Specificity = 63.6%). The logistic regression analysis showed that an ELR superior to 0.087 presented a statistically significant difference, exposing patients belonging to the BD(+) group (OR = 11.66; p < .001). Conclusions: Our data suggest that ELR may be a valuable, reproducible, easily accessible, and cost-effective inflammatory marker, pointing at the presence of a BD comorbidity with AUD.

Protocol for Rhapsody: a longitudinal observational study examining the feasibility of speech phenotyping for remote assessment of neurodegenerative and psychiatric disorders

INTRODUCTION

Neurodegenerative and psychiatric disorders (NPDs) confer a huge health burden, which is set to increase as populations age. New, remotely delivered diagnostic assessments that can detect early stage NPDs by profiling speech could enable earlier intervention and fewer missed diagnoses. The feasibility of collecting speech data remotely in those with NPDs should be established.

METHODS AND ANALYSIS

The present study will assess the feasibility of obtaining speech data, collected remotely using a smartphone app, from individuals across three NPD cohorts: neurodegenerative cognitive diseases (n=50), other neurodegenerative diseases (n=50) and affective disorders (n=50), in addition to matched controls (n=75). Participants will complete audio-recorded speech tasks and both general and cohort-specific symptom scales. The battery of speech tasks will serve several purposes, such as measuring various elements of executive control (eg, attention and short-term memory), as well as measures of voice quality. Participants will then remotely self-administer speech tasks and follow-up symptom scales over a 4-week period. The primary objective is to assess the feasibility of remote collection of continuous narrative speech across a wide range of NPDs using self-administered speech tasks. Additionally, the study evaluates if acoustic and linguistic patterns can predict diagnostic group, as measured by the sensitivity, specificity, Cohen's kappa and area under the receiver operating characteristic curve of the binary classifiers distinguishing each diagnostic group from each other. Acoustic features analysed include mel-frequency cepstrum coefficients, formant frequencies, intensity and loudness, whereas text-based features such as number of words, noun and pronoun rate and idea density will also be used.

ETHICS AND DISSEMINATION

The study received ethical approval from the Health Research Authority and Health and Care Research Wales (REC reference: 21/PR/0070). Results will be disseminated through open access publication in academic journals, relevant conferences and other publicly accessible channels. Results will be made available to participants on request.

TRIAL REGISTRATION NUMBER

NCT04939818.

A Mixed-Methods Analysis of Mobile ACT Responses From Two Cohorts

Background

Mobile transdiagnostic therapies offer a solution to the challenges of limited access to psychological care. However, it is unclear if individuals can actively synthesize and adopt concepts and skills via an app without clinician support.

Aims

The present study measured comprehension of and engagement with a mobile acceptance and commitment therapy (ACT) intervention in two independent cohorts. Authors hypothesized that participants would recognize that behaviors can be flexible in form and function and respond in an ACT process-aligned manner.

Methods

Mixed-methods analyses were performed on open-ended responses collected from initial participants (n = 49) in two parallel micro-randomized trials with: 1) first-generation college students (FGCSs) (n = 25) from a four-year public research university and 2) individuals diagnosed with bipolar disorder (BP) (n = 24). Twice each day over six weeks, participants responded to questions about mood and behavior, after which they had a 50-50 chance of receiving an ACT-based intervention. Participants identified current behavior and categorized behavior as values-based or avoidant. Interventions were selected randomly from 84 possible prompts, each targeting one ACT process: engagement with values, openness to internal experiences, or self-awareness. Participants were randomly assigned to either exploratory (10 FGCS, 9 BP) or confirmatory (15 FGCS, 15 BP) groups for analyses. Responses from the exploratory group were used to inductively derive a qualitative coding system. This system was used to code responses in the confirmatory group. Coded confirmatory data were used for final analyses.

Results

Over 50% of participants in both cohorts submitted a non-blank response 100% of the time. For over 50% of participants, intervention responses aligned with the target ACT process for at least 96% of the time (FGCS) and 91% of the time (BP), and current behavior was labeled as values-based 70% (FGCS) and 85% (BP) of the time. Participants labeled similar behaviors flexibly as either values-based or avoidant in different contexts. Dominant themes were needs-based behaviors, interpersonal and family relationships, education, and time as a cost.

Conclusions

Both cohorts were engaged with the app, as demonstrated by responses that aligned with ACT processes. This suggests that participants had some level of understanding that behavior can be flexible in form and function.

Change of Disease Spectrum Characteristics of Psychiatric Inpatients Before and After Lockdown Lifted During the COVID-19 Pandemic - Wuhan City, Hubei Province, China, 2021

What is already known about this topic?

The coronavirus disease 2019 (COVID-19) pandemic poses a significant threat to mental health globally and may change the proportion of hospitalized patients.

What is added by this report?

This report analyzed and compared the disease characteristics of psychiatric inpatients one year before and after Wuhan lifted lockdown during COVID-19. About 50% of the inpatients were diagnosed with bipolar disorder; females and adolescents had a higher prevalence of mental disorders.

What are the implications for public health practice?

More attention should be paid to the mental health of children, adolescents, and females.

A game changer for bipolar disorder diagnosis using RNA editing-based biomarkers

In clinical practice, differentiating Bipolar Disorder (BD) from unipolar depression is a challenge due to the depressive symptoms, which are the core presentations of both disorders. This misdiagnosis during depressive episodes results in a delay in proper treatment and a poor management of their condition. In a first step, using A-to-I RNA editome analysis, we discovered 646 variants (366 genes) differentially edited between depressed patients and healthy volunteers in a discovery cohort of 57 participants. After using stringent criteria and biological pathway analysis, candidate biomarkers from 8 genes were singled out and tested in a validation cohort of 410 participants. Combining the selected biomarkers with a machine learning approach achieved to discriminate depressed patients (n = 267) versus controls (n = 143) with an AUC of 0.930 (CI 95% [0.879-0.982]), a sensitivity of 84.0% and a specificity of 87.1%. In a second step by selecting among the depressed patients those with unipolar depression (n = 160) or BD (n = 95), we identified a combination of 6 biomarkers which allowed a differential diagnosis of bipolar disorder with an AUC of 0.935 and high specificity (Sp = 84.6%) and sensitivity (Se = 90.9%). The association of RNA editing variants modifications with depression subtypes and the use of artificial intelligence allowed developing a new tool to identify, among depressed patients, those suffering from BD. This test will help to reduce the misdiagnosis delay of bipolar patients, leading to an earlier implementation of a proper treatment.

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.

Process and Outcome Evaluations of Smartphone Apps for Bipolar Disorder: Scoping Review

Background

Mental health apps (MHAs) provide opportunities for accessible, immediate, and innovative approaches to better understand and support the treatment of mental health disorders, especially those with a high burden, such as bipolar disorder (BD). Many MHAs have been developed, but few have had their effectiveness evaluated.

Objective

This systematic scoping review explores current process and outcome measures of MHAs for BD with the aim to provide a comprehensive overview of current research. This will identify the best practice for evaluating MHAs for BD and inform future studies.

Methods

A systematic literature search of the health science databases PsycINFO, MEDLINE, Embase, EBSCO, Scopus, and Web of Science was undertaken up to January 2021 (with no start date) to narratively assess how studies had evaluated MHAs for BD.

Results

Of 4051 original search results, 12 articles were included. These 12 studies included 435 participants, and of these, 343 had BD type I or II. Moreover, 11 of the 12 studies provided the ages (mean 37 years) of the participants. One study did not report age data. The male to female ratio of the 343 participants was 137:206. The most widely employed validated outcome measure was the Young Mania Rating Scale, being used 8 times. The Hamilton Depression Rating Scale-17/Hamilton Depression Rating Scale was used thrice; the Altman Self-Rating Mania Scale, Quick Inventory of Depressive Symptomatology, and Functional Assessment Staging Test were used twice; and the Coping Inventory for Stressful Situations, EuroQoL 5-Dimension Health Questionnaire, Generalized Anxiety Disorder Scale-7, Inventory of Depressive Symptomatology, Mindfulness Attention Awareness Scale, Major Depression Index, Morisky-Green 8-item, Perceived Stress Scale, and World Health Organization Quality of Life-BREF were used once. Self-report measures were captured in 9 different studies, 6 of which used MONARCA. Mood and energy levels were the most commonly used self-report measures, being used 4 times each. Furthermore, 11 of the 12 studies discussed the various confounding factors and barriers to the use of MHAs for BD.

Conclusions

Reported low adherence rates, usability challenges, and privacy concerns act as barriers to the use of MHAs for BD. Moreover, as MHA evaluation is itself developing, guidance for clinicians in how to aid patient choices in mobile health needs to develop. These obstacles could be ameliorated by incorporating co-production and co-design using participatory patient approaches during the development and evaluation stages of MHAs for BD. Further, including qualitative aspects in trials that examine patient experience of both mental ill health and the MHA itself could result in a more patient-friendly fit-for-purpose MHA for BD.

Association between lifetime and recent stressful life events and the early course and psychopathology in patients with newly diagnosed bipolar disorder, first-degree unaffected relatives and healthy controls: Cross-sectional results from a prospective study

OBJECTIVE

There is an accumulation of stressful life events prior to the first mood episode, but the impact of previous severe life events on psychopathology in patients with bipolar disorder (BD) is not well studied. We aimed to examine the number of recent and lifetime life events in patients with newly diagnosed BD, their unaffected relatives (UR), and healthy controls (HC) as well as the impact of severe lifetime life events on the early course of BD.

METHODS

We compared the number of recent and lifetime life events in 398 patients with newly diagnosed BD, 109 UR, and 214 HC. We subsequently dichotomized the patients with BD by >2 lifetime life events to investigate the associations of severe lifetime life events with clinical characteristics and affective symptoms.

RESULTS

Patients with newly diagnosed BD reported significantly more life events in the last 12 months and lifetime before compared with UR and HC. Patients who reported >2 lifetime life events (n = 160) compared with patients with 0-2 life events (n = 238) had a significantly longer diagnostic delay (9.5 years ± 8.2 vs. 6.2 years ± 6.9), presented with more anxiety and depressive symptoms and had at least one previous suicide attempt (30.6% vs. 15.6%) and one previous admission (51.3% vs. 36.6%).

CONCLUSION

The experience of severe lifetime life events seems to impact the early course in BD in terms of longer diagnostic delay, more severe psychopathology including more admissions and a more than doubled risk for previous suicide attempts.

Research Status in Clinical Practice Regarding Pediatric and Adolescent Bipolar Disorders

Bipolar disorders (BDs) have high morbidity. The first onset of 27.7% of BDs occurs in children under 13 years and of 37.6% occurs in adolescents between 13 and 18 years. However, not all of the pediatric and adolescent patients with BD receive therapy in time. Therefore, studies about pediatric and adolescent patients with disorders have aroused increased attention in the scientific community. Pediatric and adolescent patients with BD present with a high prevalence rate (0.9-3.9%), and the pathogenic factors are mostly due to genetics and the environment; however, the pathological mechanisms remain unclear. Pediatric and adolescent patients with BD manifest differently from adults with BDs and the use of scales can be helpful for diagnosis and treatment evaluation. Pediatric and adolescent patients with BDs have been confirmed to have a high comorbidity rate with many other kinds of disorders. Both medication and psychological therapies have been shown to be safe and efficient methods for the treatment of BD. This review summarizes the research status related to the epidemiology, pathogenic factors, clinical manifestations, comorbidities, diagnostic and treatment scales, medications, and psychological therapies associated with BDs.

Clinical and demographic factors associated with delayed diagnosis of bipolar disorder: Data from Health Outcomes and Patient Evaluations in Bipolar Disorder (HOPE-BD) study

BACKGROUND

The diagnosis of Bipolar Disorder (BD) is frequently delayed. In this study, we aimed to examine the clinical and demographic factors associated with delayed diagnosis of BD, defined as the difference between the age at first mood episode (depressive, manic, or hypomanic) and the age at the correct diagnosis of BD, using data from a Canadian multicentre naturalistic study.

METHODS

The sample included 192 patients with Bipolar I Disorder (BD-I) and 127 with Bipolar II Disorder (BP-II) who participated in the Health Outcomes and Patient Evaluations in Bipolar Disorder (HOPE-BD) study. Sociodemographic characteristics and clinical features that had been previously associated with delayed diagnosis of BD were included in the analysis.

RESULTS

The median delay in diagnosis was 5.0 years in BD-I and 11.0 years in BD-II. Clinical factors such as earlier age of onset, lifetime suicide attempts and comorbid anxiety disorders were associated with a longer delay, whereas the presence of lifetime psychotic symptoms and psychiatric hospitalizations were associated with a shorter delay. Quantile regression analysis showed older age at which professional help was first sought and younger age of onset as predictors of increased delay in diagnosis of BD-I and BD-II. Depression as first episode predicted longer delay in diagnosis of BD-I but not BD-II.

CONCLUSION

Our findings identified the ongoing lag in identification of a BD diagnosis and the clinical markers most associated with this delay, highlighting the need for implementation of strategies for early identification and interventions in BD.

Changes in major psychiatric disorders in children and adolescents from 2001 to 2020: A retrospective single-center study

OBJECTIVE

This study aimed to determine the hospitalization rates, length of stay, age at the time of admission, and sex distribution for major psychiatric disorders in children and adolescents and provide a reference for early intervention for these diseases and distribution of medical resources in hospitals.

METHODS

We screened 4,423 patients in the child and adolescent wards of the Anhui Provincial Mental Health Center from 2001 to 2020, and examined the top four (81.1%) mental health disorders that accounted for the overall proportion of patients admitted, namely schizophrenia (SCZ) (45.7%), depressive disorder (DD) (14.5%), bipolar disorder (BD) (9.3%), and childhood emotional disorder (CED) (11.6%), and for each disorder, the percentage of hospitalization, length of stay, age at admission, and sex distribution were analyzed.

RESULTS

From 2001 to 2020, there was a significantly decreasing trend in the proportion of hospitalizations for SCZ (p < 0.001) and an increasing trend for depression and CED (p < 0.001). In terms of length of stay, SCZ was significantly longer than the other three disorders (p < 0.001), whereas there was no significant difference between DD, BD, and CED, and there was no significant trend in length of stay for any of the four disorders. The age at admission for CED was significantly lower than that for the other three disorders (p < 0.001). There was a decreasing trend in the age at admission for DD (p = 0.011) and an increasing trend for BD (p = 0.001). A significant increase in the number of female patients admitted for SCZ, DD, and CED was observed, while there was no significant change in the sex ratio for BD.

CONCLUSION

Although there is a significant downward trend in the percentage of hospitalizations for SCZ, it is still the most common psychiatric disorder in children and adolescents. We observed a significant increase in the percentage of hospitalizations for DD and CED. In addition, the proportion of female patients being hospitalized is on the rise, and this aspect requires continuous attention.

Characterisation of age and polarity at onset in bipolar disorder

BACKGROUND

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

AIMS

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

METHOD

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

RESULTS

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = -0.34 years, s.e. = 0.08), major depression (β = -0.34 years, s.e. = 0.08), schizophrenia (β = -0.39 years, s.e. = 0.08), and educational attainment (β = -0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

CONCLUSIONS

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Portable technologies for digital phenotyping of bipolar disorder: A systematic review

BACKGROUND

Bias-prone psychiatric interviews remain the mainstay of bipolar disorder (BD) assessment. The development of digital phenotyping promises to improve BD management. We present a systematic review of the evidence about the use of portable digital devices for the identification of BD, BD types and BD mood states and for symptom assessment.

METHODS

We searched Web of Knowledge^SM, Scopus ®, IEEE Xplore, and ACM Digital Library databases (until 5/1/2021) for articles evaluating the use of portable/wearable digital devices, such as smartphone apps, wearable sensors, audio and/or visual recordings, and multimodal tools. The protocol is registered in PROSPERO (CRD42020200086).

RESULTS

We included 62 studies (2325 BD; 724 healthy controls, HC): 27 using smartphone apps, either for recording self-assessments (n = 10) or for passively gathering metadata (n = 7) or both (n = 10); 15 using wearable sensors for physiological parameters; 17 analysing audio and/or video recordings; 3 using multiple technologies. Two thirds of the included studies applied artificial intelligence (AI)-based approaches. They achieved fair to excellent classification performances.

LIMITATIONS

The included studies had small sample sizes and marked heterogeneity. Evidence of overfitting emerged, limiting generalizability. The absence of clear guidelines about reporting classification performances, with no shared standard metrics, makes results hardly interpretable and comparable.

CONCLUSIONS

New technologies offer a noteworthy opportunity to BD digital phenotyping with objectivity and high granularity. AI-based models could deliver important support in clinical decision-making. Further research and cooperation between different stakeholders are needed for addressing methodological, ethical and socio-economic considerations.