A diagnosis of bipolar spectrum disorder predicts diagnostic conversion from unipolar depression to bipolar disorder: a 5-year retrospective study

Relationship between cognitive function and functional outcomes in remitted major depression

BACKGROUND

Few studies have focused on functional impairment in depressed patients during symptomatic remission. The exact relationship between cognitive performance and functional outcomes of patients with Major depressive disorder (MDD) remains unclear.

METHODS

Participants diagnosed with MDD were included and interviewed at both baseline and follow-up. Cognitive function was assessed during acute episodes using the Cambridge Neuropsychological Test Automated Battery (CANTAB), which targeted attention (Rapid Visual Processing - RVP), visual memory (Pattern Recognition Memory - PRM), and executive function (Intra-Extra Dimensional Set Shift - IED). The 17-item Hamilton Depression Scale (HAMD) was used for symptom assessment. Participants were divided into two groups based on their SDSS (Social Disability Screening Schedule) scores, and the differences between their demographic information, HAMD scores, and baseline CANTAB test results were compared. Logistic regression analysis was used to identify cognitive predictors of social function during symptomatic remission.

RESULTS

According to the SDSS score at follow-up, 103 patients were divided into the normal social function group (n = 81,78.6%) and the poor social function group (n = 22, 21.4%) during clinical remission. Participants with poorer social function performed worse in the visual memory (PRM) and executive function tests (IED) at the baseline. Logistic regression analysis suggested that performance on the PRM (95%CI = 0.31-0.93, p = 0.030) and IED (95%CI = 1.01-1.13, p = 0.014) tests, instead of less severe symptoms, significantly contributed to functional outcomes.

CONCLUSION

Better performance in visual memory and executive function during acute episodes may predict better social functional outcomes in individuals with MDD. A potential early intervention to improve social function in individuals with MDD could include the treatments for executive function and visual memory.

Predictors of diagnostic conversion from major depression to bipolar disorder: a Swedish national longitudinal study

BACKGROUND

It is clinically important to predict the conversion of major depression (MD) to bipolar disorder (BD). Therefore, we sought to identify related conversion rates and risk factors.

METHODS

This cohort study included the Swedish population born from 1941 onward. Data were collected from Swedish population-based registers. Potential risk factors, including family genetic risk scores (FGRS), which were calculated based on the phenotypes of relatives in the extended family and not molecular data, and demographic/clinical characteristics from these registers were retrieved. Those with first MD registrations from 2006 were followed up until 2018. The conversion rate to BD and related risk factors were analyzed using Cox proportional hazards models. Additional analyses were performed for late converters and with stratification by sex.

RESULTS

The cumulative incidence of conversion was 5.84% [95% confidence interval (95% CI) 5.72-5.96] for 13 years. In the multivariable analysis, the strongest risk factors for conversion were high FGRS of BD [hazard ratio (HR) = 2.73, 95% CI 2.43-3.08], inpatient treatment settings (HR = 2.64, 95% CI 2.44-2.84), and psychotic depression (HR = 2.58, 95% CI 2.14-3.11). For late converters, the first registration of MD during the teenage years was a stronger risk factor when compared with the baseline model. When the interactions between risk factors and sex were significant, stratification by sex revealed that they were more predictive in females.

CONCLUSIONS

Family history of BD, inpatient treatment, and psychotic symptoms were the strongest predictors of conversion from MD to BD.

Evidence of functional abnormalities in the default mode network in bipolar depression: A coordinate-based activation likelihood estimation meta-analysis

BACKGROUND

The default mode network (DMN) is thought to be involved in the pathophysiology of bipolar depression (BD). However, the findings of prior studies on DMN alterations in BD are inconsistent. Thus, this study aimed to systematically investigate functional abnormalities of the DMN in BD patients.

METHODS

We systematically searched PubMed, Ovid, and Web of Science for functional neuroimaging studies on regional homogeneity, amplitude of low frequency fluctuations (ALFF), and functional connectivity of the DMN in BD patients published before March 18, 2022. The stereotactic coordinates of the reported altered brain regions were extracted and incorporated into a brain map using the coordinate-based activation likelihood estimation approach.

RESULTS

A total of 43 original research studies were included in the meta-analysis. BD patients showed specific changes in the DMN including decreased ALFF/fractional ALFF in the left cingulate gyrus (CG) and bilateral precuneus (PCUN); increased functional connectivity (FC) in the left CG, left posterior CG, left PCUN, bilateral medial frontal gyrus, and bilateral superior frontal gyrus; and decreased FC in the left CG, left PCUN, left inferior parietal lobule, and left postcentral gyrus.

LIMITATIONS

Conclusions are limited by the small number of studies, additional meta-analyses are needed to obtain more data in BD subgroup.

CONCLUSION

This meta-analysis supports specific changes in DMN activity and FC in BD patients, which may be powerful biomarkers for the diagnosis of BD. The CG and PCUN were the most affected regions and are thus potential targets for clinical interventions to delay BD progression.

Factors associated with onset-age in major affective disorders

BACKGROUND

Research findings on factors associated with onset-age (OA) with bipolar (BD) and major depressive disorders (MDD) have been inconsistent, but often indicate greater morbidity following early OA.

METHODS

We considered factors associated with OA in 1033 carefully evaluated, systematically followed mood disorder subjects with DSM-5 BD (n = 505) or MDD (n = 528), comparing rates of descriptive and clinical characteristics following early (age <18), intermediate (18-40), or later onset (≥40 years), as well as regressing selected measures versus OA. Exposure time (years ill) was matched among these subgroups.

RESULTS

As hypothesized, many features were associated with early OA: familial psychiatric illness, including BD, greater maternal age, early sexual abuse, nondepressive first episodes, co-occurring ADHD, suicide attempts and violent suicidal behavior, abuse of alcohol or drugs, smoking, and unemployment. Other features increased consistently with later OA: %-time-depressed (in BD and MDD, women and men), as well as depressions/year and intake ratings of depression, educational levels, co-occurring medical disorders, rates of marriage and number of children.

CONCLUSIONS

OA averaged 7.5 years earlier in BD versus MDD (30.7 vs. 38.2). Some OA-associated measures may reflect maturation. Associations with family history and suicidal risk with earlier OA were expected; increases of time-depressed in both BD and MDD with later OA were not. We conclude that associations of OA with later morbidity are complex and not unidirectional but may be clinically useful.

Bipolar disorder diagnosis with cubic bipolar fuzzy information using TOPSIS and ELECTRE-I

Bipolar disorder ([Formula: see text] ) is a neurodegenerative disease that consists of two main manifestations: mania and depression. In the clinical diagnosis of [Formula: see text], there are two primary components. First and foremost is itself [Formula: see text] which is often wrongly diagnosed as unipolar depression in clinical finding. This is so because in clinical diagnosis the first factor is often neglected due to its approach towards positivity. As a result, the element of bipolarity dies down, and the condition worsens. The second disadvantage is that [Formula: see text] is frequently misdiagnosed due to comparable indications and symptoms. To overcome these diagnosis issues, a cubic bipolar fuzzy set (CBFS) which comprises both bipolar fuzzy set (BFS) and interval-valued bipolar fuzzy set (IVBFS) is very helpful for clinical diagnosis of [Formula: see text] . A CBFS has the ability to handle bipolarity with suitable closed intervals to express positive and negative grades to build a solid numerical demonstrating interaction to analyze this disorder effectively. For these objectives, the algorithms of technique for the order of preference by similarity to positive ideal solution (TOPSIS) and elimination and choice translating reality (ELECTRE-I) for multi-criteria decision-making (MCDM) based on CBF information are developed. The application of proposed algorithms is presented for clinical diagnosis of [Formula: see text] . In order to discuss efficiency and validity of the proposed MCDM approaches, we apply the authenticity test for ranking of feasible alternatives and optimal decision by TOPSIS and ELECTRE-I. The comparison analysis of proposed MCDM approaches with existing techniques is also given.

Dynamical regional activity in putamen distinguishes bipolar type I depression and unipolar depression

OBJECTIVES

Intrinsic human brain activity is time-varying and dynamic. However, there is still a lack of knowledge about the dynamic regional activity differences between unipolar depression (UD) and bipolar type I depression (BD-I), and whether their differential pattern can help to distinguish these two patient groups who are prone to misdiagnosis in clinical practice.

METHOD

In this study, we used the dynamical fractional amplitude of low-frequency fluctuations (dfALFF) to examine the resting-state dynamical regional activity in 40 BD-I, 42 UD, and 44 healthy controls (HCs). Analysis of covariance was applied to explore the shared and distinct dfALFF pattern among three groups, and machine-learning methods were conducted to classify BD-I from UD by using the detected distinct dfALFF pattern.

RESULTS

Compared with HCs, both BD-I and UD exhibited decreased dfALFF temporal variability in the left inferior temporal gyrus. The BD-I showed significantly decreased dfALFF temporal variability in the left putamen compared to UD. By using the dfALFF variability pattern of the left putamen as features, we achieved the 75.61% accuracy and 0.756 area under curve in classifying BD-I from UD.

LIMITATIONS

The small sample size of the current study may limit the generalizability of the findings.

CONCLUSIONS

The current study demonstrated that the dfALFF temporal variability pattern in the putamen may show a promise as future diagnostic aids for BD-I and UD.

A Predictive Model of Risk Factors for Conversion From Major Depressive Disorder to Bipolar Disorder Based on Clinical Characteristics and Circadian Rhythm Gene Polymorphisms

BACKGROUND

Bipolar disorder (BD) is easy to be misdiagnosed as major depressive disorder (MDD), which may contribute to a delay in treatment and affect prognosis. Circadian rhythm dysfunction is significantly associated with conversion from MDD to BD. So far, there has been no study that has revealed a relationship between circadian rhythm gene polymorphism and MDD-to-BD conversion. Furthermore, the prediction of MDD-to-BD conversion has not been made by integrating multidimensional data. The study combined clinical and genetic factors to establish a predictive model through machine learning (ML) for MDD-to-BD conversion.

METHOD

By following up for 5 years, 70 patients with MDD and 68 patients with BD were included in this study at last. Single nucleotide polymorphisms (SNPs) of the circadian rhythm genes were selected for detection. The R software was used to operate feature screening and establish a predictive model. The predictive model was established by logistic regression, which was performed by four evaluation methods.

RESULTS

It was found that age of onset was a risk factor for MDD-to-BD conversion. The younger the age of onset, the higher the risk of BD. Furthermore, suicide attempts and the number of hospitalizations were associated with MDD-to-BD conversion. Eleven circadian rhythm gene polymorphisms were associated with MDD-to-BD conversion by feature screening. These factors were used to establish two models, and 4 evaluation methods proved that the model with clinical characteristics and SNPs had the better predictive ability.

CONCLUSION

The risk factors for MDD-to-BD conversion have been found, and a predictive model has been established, with a specific guiding significance for clinical diagnosis.

Affective lability as a prospective predictor of subsequent bipolar disorder diagnosis: a systematic review

Objectives

The early pathogenesis and precursors of Bipolar Disorder (BD) are poorly understood. There is some cross-sectional and retrospective evidence of affective lability as a predictor of BD, but this is subject to recall biases. The present review synthesises the prospective evidence examining affective lability and the subsequent development of BD at follow-up.

Methods

The authors performed a systematic search of PubMed, PsycInfo and Embase (1960–June 2020) and conducted hand searches to identify studies assessing affective lability (according to a conceptually-inclusive definition) at baseline assessment in individuals without a BD diagnosis, and a longitudinal follow-up assessment of bipolar (spectrum) disorders. Results are reported according to the PRISMA guidelines, and the synthesis without meta-analysis (SWiM) reporting guidelines were used to strengthen the narrative synthesis. The Newcastle–Ottawa Scale was used to assess risk of bias (ROB).

Results

11 articles describing 10 studies were included. Being identified as having affective lability at baseline was associated with an increased rate of bipolar diagnoses at follow-up; this association was statistically significant in six of eight studies assessing BD type I/II at follow-up and in all four studies assessing for bipolar spectrum disorder (BSD) criteria. Most studies received a ‘fair’ or ‘poor’ ROB grade.

Conclusions

Despite a paucity of studies, an overall association between prospectively-identified affective lability and a later diagnosis of BD or BSD is apparent with relative consistency between studies. This association and further longitudinal studies could inform future clinical screening of those who may be at risk of BD, with the potential to improve diagnostic accuracy and facilitate early intervention.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40345-021-00237-1.

Diagnostic conversion to bipolar disorder in unipolar depressed patients in Hong Kong: A 20-year follow-up study

BACKGROUND

Bipolar (BP) disorder, especially BP depression is common and yet remains enigmatic until the emergence of mania. The rates and risk factors of conversion from unipolar (UP) depression to BP disorder reported vary.

OBJECTIVE

To study the long-term conversion rate from UP depression to BP disorder of an inpatient sample and identify the associated risk factors.

METHODS

This is a retrospective longitudinal study conducted in 2017 based on review of medical records of patients admitted to a regional hospital in Hong Kong with diagnosis of major depressive disorder during the period from 1988 to 2000.

RESULTS

A total of 19.5% of subjects had diagnostic shift from UP depression to BP disorder at follow-up, with a mean conversion time of 10.8 years and about 1% shift annually in the first 10 years. Risk factors include family history of mental illness, young age at onset, repeated admissions, psychotic symptoms and use of electroconvulsive therapy. More unconverted UP subjects (9.0%) committed suicide than those converted to BP (3.5%).

LIMITATIONS

The study is limited by its retrospective design.

CONCLUSIONS

Conversion from UP depression to BP disorder is dictated by its biological characteristics and clinical severity. Vigilance should be held in the first decade after onset when most conversion takes place.

Clinical characteristics of treatment-resistant depression in adults in Hungary: Real-world evidence from a 7-year-long retrospective data analysis

Purpose

Treatment-resistant depression (TRD) is associated with a poor quality of life and high economic burden. This observational retrospective epidemiological study aimed to estimate the proportion of patients with TRD within a cohort of patients with major depressive disorder (MDD) in Hungary and examine the mortality and comorbidities of patients with and without TRD.

Patients and methods

This study included patients with MDD who experienced onset of a new depressive episode between 01 January 2009 and 31 August 2015, using data from a nationwide, longitudinal database.

Results

Overall, 99,531 patients were included in the MDD cohort, of which 8,268 (8.3%) also met the criteria for TRD. The overall survival of non-TRD patients was longer than in TRD patients; the risk of mortality for TRD patients was significantly higher than of non-TRD patients (HR [CI] 1.381 [1.212–1.571]; p<0.001). Patients with TRD had a significantly higher probability of having “Neurotic, stress-related and somatoform disordersˮ, autoimmune conditions, cardio- or cerebrovascular diseases, thyroid gland diseases and self-harming behaviour not resulting in death than non-TRD patients (for all comparisons, p values were less than 0.005).

Discussion

To our best knowledge, this is the first study to assess the frequency of TRD in Hungary. In a cohort of Hungarian MDD patients, we have found that the proportion of TRD (~8.3%) is comparable to those reported in previous studies with similar methodology from other countries. The majority of our other main findings (e.g. more frequent self-harming behaviour, increased risk of “Neurotic, stress-related and somatoform disordersˮ and higher overall mortality in TRD subjects) are also in line with previous results from other countries. Taking the substantial proportion of patients with TRD into consideration, a more comprehensive and targeted treatment strategy would be required for these individuals.

Risk Calculators in Bipolar Disorder: A Systematic Review

INTRODUCTION

Early recognition of bipolar disorder improves the prognosis and decreases the burden of the disease. However, there is a significant delay in diagnosis. Multiple risk factors for bipolar disorder have been identified and a population at high-risk for the disorder has been more precisely defined. These advances have allowed the development of risk calculators to predict individual risk of conversion to bipolar disorder. This review aims to identify the risk calculators for bipolar disorder and assess their clinical applicability.

METHODS

A systematic review of original studies on the development of risk calculators in bipolar disorder was performed. The studies' quality was evaluated with the Newcastle-Ottawa Quality Assessment Form for Cohort Studies and according to recommendations of the Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis Initiative.

RESULTS

Three studies met the inclusion criteria; one developed a risk calculator of conversion from major depressive episode to bipolar disorder; one of conversion to new-onset bipolar spectrum disorders in offspring of parents with bipolar disorder; and the last one of conversion in youths with bipolar disorder not-otherwise-specified.

CONCLUSIONS

The calculators reviewed in this article present good discrimination power for bipolar disorder, although future replication and validation of the models is needed.

Lifetime cocaine use is a potential predictor for conversion from major depressive disorder to bipolar disorder: A prospective study

AIM

We aimed to identify whether lifetime cocaine use is a risk factor for conversion from major depressive disorder (MDD) to bipolar disorder (BD) in an outpatient sample of adults.

METHODS

This prospective cohort study included 585 subjects aged 18 to 60 years who had been diagnosed with MDD as assessed by the Mini International Neuropsychiatric Interview (MINI-Plus) at baseline (2012-2015). Subjects were reassessed a mean of 3 years later (2017-2018) for potential conversion to BD as assessed by the MINI-Plus. Lifetime cocaine use was assessed using the Alcohol, Smoking, and Substance Involvement Screening Test.

RESULTS

In the second wave, we had 117 (20%) losses, and 468 patients were reassessed. The rate of conversion from MDD to BD in 3 years was 12.4% (n = 58). A logistic regression analysis showed that the risk for conversion from MDD to BD was 3.41-fold higher (95% confidence interval, 1.11-10.43) in subjects who reported lifetime cocaine use at baseline as compared to individuals who did not report lifetime cocaine use at baseline, after adjusting for demographic and clinical confounders.

CONCLUSION

These findings showed that lifetime cocaine use is a potential predictor of conversion to BD in an MDD cohort. Further studies are needed to assess the possible underlying mechanisms linking exposure to cocaine with BD conversion.

Youth Mental Health Tracker: protocol to establish a longitudinal cohort and research database for young people attending Australian mental health services

INTRODUCTION

Mental disorders are a leading cause of long-term disability worldwide. Much of the burden of mental ill-health is mediated by early onset, comorbidities with physical health conditions and chronicity of the illnesses. This study aims to track the early period of mental disorders among young people presenting to Australian mental health services to facilitate more streamlined transdiagnostic processes, highly personalised and measurement-based care, secondary prevention and enhanced long-term outcomes.

METHODS AND ANALYSIS

Recruitment to this large-scale, multisite, prospective, transdiagnostic, longitudinal clinical cohort study ('Youth Mental Health Tracker') will be offered to all young people between the ages of 12 and 30 years presenting to participating services with proficiency in English and no history of intellectual disability. Young people will be tracked over 3 years with standardised assessments at baseline and 3, 6, 12, 24 and 36 months. Assessments will include self-report and clinician-administered measures, covering five key domains including: (1) social and occupational function; (2) self-harm, suicidal thoughts and behaviour; (3) alcohol or other substance misuse; (4) physical health; and (5) illness type, clinical stage and trajectory. Data collection will be facilitated by the use of health information technology. The data will be used to: (1) determine prospectively the course of multidimensional functional outcomes, based on the differential impact of demographics, medication, psychological interventions and other key potentially modifiable moderator variables and (2) map pathophysiological mechanisms and clinical illness trajectories to determine transition rates of young people to more severe illness forms.

ETHICS AND DISSEMINATION

The study has been reviewed and approved by the Human Research Ethics Committee of the Sydney Local Health District (2019/ETH00469). All data will be non-identifiable, and research findings will be disseminated through peer-reviewed journals and scientific conference presentations.

Diagnostic Stability in Bipolar Disorder: A Narrative Review

LEARNING OBJECTIVES

After participating in this activity, learners should be better able to:• Evaluate diagnostic stability in bipolar disorder• Analyze the factors contributing to diagnostic stability OBJECTIVE: Diagnostic stability is the degree to which a diagnosis remains unchanged during follow-up. It is an important measure of predictive validity in bipolar disorder (BD). In this study, we review the literature concerning diagnostic stability in BD, analyze the factors contributing to diagnostic stability, and describe the implications of diagnostic boundaries and diagnostic delay.

METHODS

A comprehensive literature search of MEDLINE and EMBASE databases was conducted, including all studies published from 1980 to 2016, to evaluate the diagnostic stability of BD. Thirty-seven articles were included: 6 focusing mainly on BD, 18 on psychotic disorders, 10 on depression, and 3 on diagnostic stability in psychiatric disorders in general. Data analysis was performed in standardized fashion using a predefined form.

RESULTS

Despite a high variability of the methodological approaches taken, an acceptable degree of diagnostic stability was found. The most common criteria for evaluating diagnostic stability were prospective consistency and retrospective consistency. The mean prospective and retrospective consistencies were 77.4% and 67.6%, respectively. A large majority of studies were performed in Europe or in North America (67.5%), compared to 21.6% in Asia and only 10.8% in Africa, Oceania, and South America. Extreme ages, female gender, psychotic symptoms, changes to treatment, substance abuse, and family history of affective disorder have been related to diagnostic instability.

CONCLUSIONS

Several factors appear to have a negative impact on the diagnostic stability, but the evidence is insufficient to draw any robust conclusions. Nevertheless, despite variable prospective and retrospective consistencies, the overall diagnostic stability is good. Standardized methods need to be used to obtain more accurate assessments of stability.

Right care, first time: a highly personalised and measurement-based care model to manage youth mental health

Mood and psychotic syndromes most often emerge during adolescence and young adulthood, a period characterised by major physical and social change. Consequently, the effects of adolescent-onset mood and psychotic syndromes can have long term consequences. A key clinical challenge for youth mental health is to develop and test new systems that align with current evidence for comorbid presentations and underlying neurobiology, and are useful for predicting outcomes and guiding decisions regarding the provision of appropriate and effective care. Our highly personalised and measurement-based care model includes three core concepts: ▶ A multidimensional assessment and outcomes framework that includes: social and occupational function; self-harm, suicidal thoughts and behaviour; alcohol or other substance misuse; physical health; and illness trajectory. ▶ Clinical stage. ▶ Three common illness subtypes (psychosis, anxious depression, bipolar spectrum) based on proposed pathophysiological mechanisms (neurodevelopmental, hyperarousal, circadian). The model explicitly aims to prevent progression to more complex and severe forms of illness and is better aligned to contemporary models of the patterns of emergence of psychopathology. Inherent within this highly personalised approach is the incorporation of other evidence-based processes, including real-time measurement-based care as well as utilisation of multidisciplinary teams of health professionals. Data-driven local system modelling and personalised health information technologies provide crucial infrastructure support to these processes for better access to, and higher quality, mental health care for young people. CHAPTER 1: MULTIDIMENSIONAL OUTCOMES IN YOUTH MENTAL HEALTH CARE: WHAT MATTERS AND WHY?: Mood and psychotic syndromes present one of the most serious public health challenges that we face in the 21st century. Factors including prevalence, age of onset, and chronicity contribute to substantial burden and secondary risks such as alcohol or other substance misuse. Mood and psychotic syndromes most often emerge during adolescence and young adulthood, a period characterised by major physical and social change; thus, effects can have long term consequences. We propose five key domains which make up a multidimensional outcomes framework that aims to address the specific needs of young people presenting to health services with emerging mental illness. These include social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness type, stage and trajectory. Impairment and concurrent morbidity are well established in young people by the time they present for mental health care. Despite this, services and health professionals tend to focus on only one aspect of the presentation - illness type, stage and trajectory - and are often at odds with the preferences of young people and their families. There is a need to address the disconnect between mental health, physical health and social services and interventions, to ensure that youth mental health care focuses on the outcomes that matter to young people. CHAPTER 2: COMBINING CLINICAL STAGE AND PATHOPHYSIOLOGICAL MECHANISMS TO UNDERSTAND ILLNESS TRAJECTORIES IN YOUNG PEOPLE WITH EMERGING MOOD AND PSYCHOTIC SYNDROMES: Traditional diagnostic classification systems for mental disorders map poorly onto the early stages of illness experienced by young people, and purport categorical distinctions that are not readily supported by research into genetic, environmental and neurobiological risk factors. Consequently, a key clinical challenge in youth mental health is to develop and test new classification systems that align with current evidence on comorbid presentations, are consistent with current understanding of underlying neurobiology, and provide utility for predicting outcomes and guiding decisions regarding the provision of appropriate and effective care. This chapter outlines a transdiagnostic framework for classifying common adolescent-onset mood and psychotic syndromes, combining two independent but complementary dimensions: clinical staging, and three proposed pathophysiological mechanisms. Clinical staging reflects the progression of mental disorders and is in line with the concept used in general medicine, where more advanced stages are associated with a poorer prognosis and a need for more intensive interventions with a higher risk-to-benefit ratio. The three proposed pathophysiological mechanisms are neurodevelopmental abnormalities, hyperarousal and circadian dysfunction, which, over time, have illness trajectories (or pathways) to psychosis, anxious depression and bipolar spectrum disorders, respectively. The transdiagnostic framework has been evaluated in young people presenting to youth mental health clinics of the University of Sydney's Brain and Mind Centre, alongside a range of clinical and objective measures. Our research to date provides support for this framework, and we are now exploring its application to the development of more personalised models of care. CHAPTER 3: A COMPREHENSIVE ASSESSMENT FRAMEWORK FOR YOUTH MENTAL HEALTH: GUIDING HIGHLY PERSONALISED AND MEASUREMENT-BASED CARE USING MULTIDIMENSIONAL AND OBJECTIVE MEASURES: There is an urgent need for improved care for young people with mental health problems, in particular those with subthreshold mental disorders that are not sufficiently severe to meet traditional diagnostic criteria. New comprehensive assessment frameworks are needed to capture the biopsychosocial profile of a young person to drive highly personalised and measurement-based mental health care. We present a range of multidimensional measures involving five key domains: social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness type, stage and trajectory. Objective measures include: neuropsychological function; sleep-wake behaviours and circadian rhythms; metabolic and immune markers; and brain structure and function. The recommended multidimensional measures facilitate the development of a comprehensive clinical picture. The objective measures help to further develop informative and novel insights into underlying pathophysiological mechanisms and illness trajectories to guide personalised care plans. A panel of specific multidimensional and objective measures are recommended as standard clinical practice, while others are recommended secondarily to provide deeper insights with the aim of revealing alternative clinical paths for targeted interventions and treatments matched to the clinical stage and proposed pathophysiological mechanisms of the young person. CHAPTER 4: PERSONALISING CARE OPTIONS IN YOUTH MENTAL HEALTH: USING MULTIDIMENSIONAL ASSESSMENT, CLINICAL STAGE, PATHOPHYSIOLOGICAL MECHANISMS, AND INDIVIDUAL ILLNESS TRAJECTORIES TO GUIDE TREATMENT SELECTION: New models of mental health care for young people require that interventions be matched to illness type, clinical stage, underlying pathophysiological mechanisms and individual illness trajectories. Narrow syndrome-focused classifications often direct clinical attention away from other key factors such as functional impairment, self-harm and suicidality, alcohol or other substance misuse, and poor physical health. By contrast, we outline a treatment selection guide for early intervention for adolescent-onset mood and psychotic syndromes (ie, active treatments and indicated and more specific secondary prevention strategies). This guide is based on experiences with the Brain and Mind Centre's highly personalised and measurement-based care model to manage youth mental health. The model incorporates three complementary core concepts: ▶A multidimensional assessment and outcomes framework including: social and occupational function; self-harm, suicidal thoughts and behaviours; alcohol or other substance misuse; physical health; and illness trajectory. ▶Clinical stage. ▶Three common illness subtypes (psychosis, anxious depression, bipolar spectrum) based on three underlying pathophysiological mechanisms (neurodevelopmental, hyperarousal, circadian). These core concepts are not mutually exclusive and together may facilitate improved outcomes through a clinical stage-appropriate and transdiagnostic framework that helps guide decisions regarding the provision of appropriate and effective care options. Given its emphasis on adolescent-onset mood and psychotic syndromes, the Brain and Mind Centre's model of care also respects a fundamental developmental perspective - categorising childhood problems (eg, anxiety and neurodevelopmental difficulties) as risk factors and respecting the fact that young people are in a period of major biological and social transition. Based on these factors, a range of social, psychological and pharmacological interventions are recommended, with an emphasis on balancing the personal benefit-to-cost ratio. CHAPTER 5: A SERVICE DELIVERY MODEL TO SUPPORT HIGHLY PERSONALISED AND MEASUREMENT-BASED CARE IN YOUTH MENTAL HEALTH: Over the past decade, we have seen a growing focus on creating mental health service delivery models that better meet the unique needs of young Australians. Recent policy directives from the Australian Government recommend the adoption of stepped-care services to improve the appropriateness of care, determined by severity of need. Here, we propose that a highly personalised approach enhances stepped-care models by incorporating clinical staging and a young person's current and multidimensional needs. It explicitly aims to prevent progression to more complex and severe forms of illness and is better aligned to contemporary models of the patterns of emergence of psychopathology. Inherent within a highly personalised approach is the incorporation of other evidence-based processes, including real-time measurement-based care and use of multidisciplinary teams of health professionals. Data-driven local system modelling and personalised health information technologies provide crucial infrastructure support to these processes for better access to, and higher quality of, mental health care for young people.

Altered Patterns of the Fractional Amplitude of Low-Frequency Fluctuation in Drug-Naive First-Episode Unipolar and Bipolar Depression

Background: An early and correct diagnosis is crucial for treatment of unipolar depression (UD) and bipolar disorder (BD). The fractional amplitude of low-frequency fluctuations (fALFFs) has been widely used in the study of neuropsychiatric diseases, as it can detect spontaneous brain activities. This study was conducted to survey changes of fALFF within various frequency bands of the UD and BD patients, as well as to explore the effects on changes in fALFF on cognitive function. Methods: In total, 58 drug-naive first-episode patients, including 32 UD and 26 BD, were enrolled in the study. The fALFF values were calculated under slow-5 band (0.01-0.027 Hz) and slow-4 band (0.027-0.073 Hz) among UD patients, BD patients, and healthy control (HC). Additionally, we conducted correlation analyses to examine the association between altered fALFF values and cognitive function. Results: Under the slow-5 band, compared to the HC group, the UD group showed increased fALFF values in the right cerebellum posterior lobe, whereas the BD group showed increased fALFF values in the left middle temporal gyrus (MTG). Under the slow-4 band, in comparison to HC, the UD group showed increased fALFF values in the left superior temporal gyrus, whereas the right inferior parietal lobule (IPL) and BD group showed increased fALFF values in the bilateral postcentral gyrus. Notably, compared to BD, the UD group showed increased fALFF values in the right IPL under the slow-4 band. Furthermore, altered fALFF values in the left MTG and the right IPL were significantly positively correlated with Verbal Fluency Test scores. Conclusions: This current study indicated that there were changes in brain activities in the early UD and BD groups, and changes were related to executive function. The fALFF values can serve as potential biomarker to diagnose and differentiate UD and BD patients.

Common and distinct neural activities in frontoparietal network in first-episode bipolar disorder and major depressive disorder: Preliminary findings from a follow-up resting state fMRI study

BACKGROUND

It is difficult to distinguish bipolar disorder (BD) from major depressive disorder (MDD), especially with the initial depressive episode. In this study, we compared neural activities of BD and MDD patients during the first-episode (FE) to investigate common and distinct neural activities and further explore predictive indicators in the two diseases.

METHODS

FE-MDD patients were performed resting state functional magnetic resonance imaging and followed up after scanning. After follow-up, FE-MDD patients were regrouped into FE-BD and FE-MDD patients. The study included 24 FE-BD patients, 28 FE-MDD patients, and 30 age- and sex-matched healthy controls (HC) to investigate neural activities with regional homogeneity (ReHo) analysis among the 3 groups.

RESULTS

Compared to HC, FE-BD patients displayed significantly higher ReHo values in the superior frontal gyrus, the medial superior frontal gyrus within right-side cerebral hemisphere than FE-MDD patients and HC. Compared to HC, FE-BD and FE-MDD patients displayed significant decreased ReHo values in the paracentral lobule, the precuneus and the median cingulate and paracingulate gyrus within bilateral cerebral hemisphere, and the postcentral gyrus and the precentral gyrus within the right-side. FE-BD displayed significant lower ReHo values than FE-MDD patients in these regions.

LIMITATIONS

The potential effects of medicine, age, course of disease and handedness on results could not be ignored.

CONCLUSIONS

Abnormal neural activities of frontoparietal network may provide common and distinct markers to affective disorders and scientific basis for further prediction researches of affective disorders.

Bipolar spectrum disorder: What evidence for pharmacological treatment? A systematic review

BACKGROUND AND OBJECTIVES

Bipolar spectrum disorder (BSD) is an extended concept of bipolar disorder (BD) that includes conditions that do not fulfill the criteria. There is no recommendation today about its treatment. We reviewed relevant literature focusing on pharmacological treatments, looking for high-strength evidence leading to guidelines.

METHODOLOGY

A literature search was conducted using MedLine / PubMed database and Google Scholar up to September 2018. Search words were related to BSD and pharmacological treatment.

RESULTS

The literature search yielded 621 articles. Out of these, 35 articles met our selection criteria. There was limited high quality data. Only one randomized control trial (RCT) and one randomized open label trial were found. Most studies used different definition of BSD.

CONCLUSIONS

There is a considerable lack of data and no evidence supporting efficacy of pharmacological treatment for BSD. There is a need for a consensus on the definition of BSD and more evidence studies to evaluate drug's effectiveness in this condition.

Bipolar fuzzy soft mappings with application to bipolar disorders

Bipolar disorder is a neurological disorder that consists of two main factors, i.e. mania and depression. There are two main drawbacks in clinical diagnosis of the bipolar disorder. First, bipolar disorder is mostly wrongly diagnosed as unipolar depression in clinical diagnosis. This is, because in clinical diagnosis, the first factor is often neglected due to its approach toward positivity. Consequently, the element of bipolarity vanishes and the disease becomes worse. Second, the types of bipolar disorder are mostly misdiagnosed due to similar symptoms. To overcome these problems, the bipolar fuzzy soft set (BFS-set) and bipolar fuzzy soft mappings (BFS-mappings) are useful to tackle bipolarity and to construct a strong mathematical modeling process to diagnose this disease correctly. This technique is extensive but simple as compared to existing medical diagnosis methods. A chart (relation between different types and symptoms of bipolar disorder) is provided which contains different ranges over the interval [Formula: see text]. A process of BFS-mappings is also provided to obtain correct diagnosis and to suggest the best treatment. Lastly, a generalized BFS-mapping is introduced which is helpful to keep patient’s improvement record. The case study indicates the reliability, efficiency and capability of the achieved theoretical results. Further, it reveals that the connection of soft set with bipolar fuzzy set is fruitful to construct a connection between symptoms which minimize the complexity of the case study.

Abnormal resting-state cerebral-limbic functional connectivity in bipolar depression and unipolar depression

Background

Distinctive patterns of functional connectivity (FC) abnormalities in neural circuitry has been reported in patients with bipolar depression (BD) and unipolar depression (UD). However, it is unclear that whether this distinct functional connectivity patterns are diagnosis specific between BD and UD. This study aimed to compare patterns of functional connectivity among BD, UD and healthy controls (HC) and determine the distinct functional connectivity patterns which can differentiate BD from UD.

Method

Totally 23 BD, 22 UD, and 24 HC were recruited to undergo resting-state fMRI scanning. FC between each pair of brain regions was calculated and compared among the three groups, the associations of FC with depressive symptom were also analyzed.

Results

Both patient groups showed significantly decreased cerebral-limbic FC located between the default mode network [posterior cingulated gyrus (PCG) and precuneus] and limbic regions (hippocampus, amygdala and thalamus) than HC. Moreover, the BD group exhibited more decreased FC mainly in the cortical regions (middle temporal gyrus, PCG, medial superior frontal gyrus, inferior occipital gyrus and superior temporal gyrus), but the UD group is more associated with limbic alterations. These decreased FCs were negatively correlated with HAMD scores in both BD and UD patients.

Conclusions

BD and UD patients demonstrate different patterns of abnormal cerebral-limbic FC, reflected by decreased FC within cerebral cortex and limbic regions in BD and UD, respectively. The distinct FC abnormal pattern of the cerebral-limbic circuit might be applied as biomarkers to differentiate these two depressive patient groups.

Discussion on Patients with Bipolar Disorder and Depressive Episode by Ratio Low Frequency Amplitude Combined with Grey Matter Volume Analysis

In order to explore the brain functional and structural imaging results of patients with bipolar disorder and depressive episode without taking medicine, and to further explore the disease mechanism of bipolar disorder by combining with clinical symptoms and cognitive function (neuropsychological test), DPABI (Data Processing and Analysis (Resting-State) For Brain Image) software is used to pre-process fMRI (functional magnetic resonance imaging) data and calculate fALFF (ratio low frequency fluctuation amplitude) index. In addition, SPM8 is applied for grey matter volume analysis based on voxel morphology. Pearson correlation model is used to analyze the relationship between functional and morphological changes and clinical symptoms and cognitive tests. DPABI software and SPSS 22.0 software are used to analyze the data. The results show that corresponding abnormal brain areas are found in both functional and structural aspects of patients with bipolar disorder and depression, involving LCSPT emotional circuits. More importantly, the superior frontal gyrus shows significant abnormalities in both functional and structural analysis.

Differentiation of Transformed Bipolar Disorder From Unipolar Depression by Resting-State Functional Connectivity Within Reward Circuit

Previous studies have found that neural functional abnormalities detected by functional magnetic resonance imaging (fMRI) in brain regions implicated in reward processing during reward tasks show promise to distinguish bipolar from unipolar depression (UD), but little is known regarding resting-state functional connectivity (rsFC) within the reward circuit. In this study, we investigated neurobiomarkers for early recognition of bipolar disorder (BD) by retrospectively comparing rsFC within the reward circuit between UD and depressed BD. Sixty-six depressed patients were enrolled, none of whom had ever experienced any manic/hypomanic episodes before baseline. Simultaneously, 40 matched healthy controls (HC) were also recruited. Neuroimaging data of each participant were obtained from resting-state fMRI scans. Some patients began to manifest bipolar disorder (tBD) during the follow-up period. All patients were retrospectively divided into two groups (33 tBD and 33 UD) according to the presence or absence of mania/hypomania in the follow-up. rsFC between key regions of the reward circuit was calculated and compared among groups. Results showed decreased rsFC between the left ventral tegmental area (VTA) and left ventral striatum (VS) in the tBD group compared with the UD group, which showed good accuracy in predicting diagnosis (tBD vs. UD) according to receiver operating characteristic (ROC) analysis. No significant different rsFC was found within the reward circuit between any patient group and HC. Our preliminary findings indicated that bipolar disorder, in early depressive stages before onset of mania/hypomania attacks, already differs from UD in the reward circuit of VTA-VS functional synchronicity at the resting state.

Decreased Functional Connectivity in Insular Subregions in Depressive Episodes of Bipolar Disorder and Major Depressive Disorder

Objective: Clinically, it is very difficult to distinguish between major depressive disorder (MDD) and bipolar disorder (BD) in the period of depression. Increasing evidence shows that the insula plays an important role in depression. We aimed to compare the resting-state functional connectivity (rsFC) of insular subregions in patients with MDD and BD in depressive episodes (BDD), who had never experienced manic or hypomanic episodes when they were scanned to identify biomarkers for the identification of two diseases. Methods: We recruited 21 BDD patients, 40 MDD patients and 70 healthy controls (HC). Resting-state functional magnetic resonance imaging (rs-fMRI) was performed. BDD patients had never had manic or hypomanic episodes when they were scanned, and the diagnoses were determined by follow-up. We divided the insula into three parts including the ventral anterior insular cortex (v-AIN), dorsal anterior insular cortex (d-AIN), and posterior insula (PI). The insular-based rsFC was compared among the three groups, and an analysis of the correlation between the rsFC value and Hamilton depression and anxiety scales was carried out. Results: BDD and MDD patients demonstrated decreased rsFC from the v-AIN to the left superior/middle frontal gyrus compared with the HC group. Versus MDD and HC groups, BDD patients exhibited decreased rsFC from the v-AIN to the area in the left orbital frontal gyrus and left superior temporal gyrus (included temporal pole), from the PI to the right lateral postcentral gyrus and from all three insular subregions to the somatosensory and motor cortex. Meanwhile, a correlation between the rsFC value of the PI-right lateral postcentral gyrus and anxiety score was observed in patients. Conclusion: Our findings show BDD and MDD patients have similar decreases in insular connectivity in the dorsal lateral frontal regions, and BDD patients have specific decreased insular connectivity, especially in the somatosensory and motor cortex, which may be used as imaging evidence for clinical identification.

The Staging of Major Mood Disorders: Clinical and Neurobiological Correlates

OBJECTIVE

Staging of psychiatric disorders is gaining momentum and the purpose of this review is to examine whether major mood disorders can be defined according to stages.

METHODS

In April 2018 the PubMed electronic data base was scrutinized by a combination of various search terms like "major depressive disorder and staging," "bipolar disorder and neuroprogression," etc. To incorporate the latest findings the search was limited to the last 10 years. Both original and review articles were examined by reading the abstracts, and papers which were found to be particularly applicable were read in full and their reference lists were also consulted.

RESULTS

A significant increase occurred in the number of papers published on the topic of staging of mood disorders. Staging formats were found for both major mood disorders, with the caveat that many more articles were discovered for bipolar disorder. Current evidence points to allostatic load and neuroprogression as the basis for staging of mood disorders.

CONCLUSION

Principal affective illnesses may be characterized by distinct stages, for instance early, intermediate and late. These phases inform the management so that clinicians should incorporate the staging schema into everyday practice and implement treatment strategies according to the phase of the illness.

Common and distinct abnormal frontal-limbic system structural and functional patterns in patients with major depression and bipolar disorder

Major depressive disorder (MDD) and bipolar disorder (BD) are common severe affective diseases. Although previous neuroimaging studies have investigated brain abnormalities in MDD or BD, the structural and functional differences between these two disorders remain unclear. In this study, we adopted a multimodal approach, combining voxel-based morphometry (VBM) and functional connectivity (FC), to study the common and distinct structural and functional alterations in unmedicated MDD and BD patients. The VBM analysis revealed that both the MDD and BD patients showed decreased gray matter volume (GMV) in the left anterior cingulate cortex (ACC_L) and right hippocampus (HIP_R) compared with the healthy controls, and the MDD patients showed decreased GMV in the left superior frontal gyrus (SFG_L) and ACC_L compared with the BD patients. Furthermore, we took these clusters as seed regions to analyze the abnormal resting-state functional connectivity (RSFC) in the patients. We found that both the MDD and BD groups had decreased RSFC between the ACC_L and the left orbitofrontal cortex (OFC_L) and that the MDD group had decreased RSFC between the SFG_L and the HIP_L, compared with the healthy controls. Our results revealed that the MDD and BD patients were more similar than different in GMV and RSFC. These findings indicate that investigating the frontal-limbic system could be useful for understanding the underlying mechanisms of these two disorders.

•

Both MDD and BD patients had reduced GMV in the ACC_L and HIP_R compared with HC.

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MDD patients had decreased GMV in the ACC_L and SFG_L compared with BD patients.

•

Both BD and MDD patients had decreased ACC-OFC RSFC compared with HC.

•

The MDD and BD patients were more similar than different in GMV and RSFC.

A morphometric signature of depressive symptoms in unmedicated patients with mood disorders

OBJECTIVE

A growing literature indicates that unipolar depression and bipolar depression are associated with alterations in grey matter volume. However, it is unclear to what degree these patterns of morphometric change reflect symptom dimensions. Here, we aimed to predict depressive symptoms and hypomanic symptoms based on patterns of grey matter volume using machine learning.

METHOD

We used machine learning methods combined with voxel-based morphometry to predict depressive and self-reported hypomanic symptoms from grey matter volume in a sample of 47 individuals with unmedicated unipolar and bipolar depression.

RESULTS

We were able to predict depressive severity from grey matter volume in the anteroventral bilateral insula in both unipolar depression and bipolar depression. Self-reported hypomanic symptoms did not predict grey matter loss with a significant degree of accuracy.

DISCUSSION

The results of this study suggest that patterns of grey matter volume alteration in the insula are associated with depressive symptom severity across unipolar and bipolar depression. Studies using other modalities and exploring other brain regions with a larger sample are warranted to identify other systems that may be associated with depressive and hypomanic symptoms across affective disorders.

A YinYang bipolar fuzzy cognitive TOPSIS method to bipolar disorder diagnosis

BACKGROUND AND OBJECTIVE

Bipolar disorder is often mis-diagnosed as unipolar depression in the clinical diagnosis. The main reason is that, different from other diseases, bipolarity is the norm rather than exception in bipolar disorder diagnosis. YinYang bipolar fuzzy set captures bipolarity and has been successfully used to construct a unified inference mathematical modeling method to bipolar disorder clinical diagnosis. Nevertheless, symptoms and their interrelationships are not considered in the existing method, circumventing its ability to describe complexity of bipolar disorder. Thus, in this paper, a YinYang bipolar fuzzy multi-criteria group decision making method to bipolar disorder clinical diagnosis is developed.

METHODS

Comparing with the existing method, the new one is more comprehensive. The merits of the new method are listed as follows: First of all, multi-criteria group decision making method is introduced into bipolar disorder diagnosis for considering different symptoms and multiple doctors' opinions. Secondly, the discreet diagnosis principle is adopted by the revised TOPSIS method. Last but not the least, YinYang bipolar fuzzy cognitive map is provided for the understanding of interrelations among symptoms.

RESULTS

The illustrated case demonstrates the feasibility, validity, and necessity of the theoretical results obtained. Moreover, the comparison analysis demonstrates that the diagnosis result is more accurate, when interrelations about symptoms are considered in the proposed method.

CONCLUSIONS

In a conclusion, the main contribution of this paper is to provide a comprehensive mathematical approach to improve the accuracy of bipolar disorder clinical diagnosis, in which both bipolarity and complexity are considered.

Incidence, prevalence and clinical correlates of antidepressant-emergent mania in bipolar depression: a systematic review and meta-analysis

BACKGROUND

Treatment-emergent mania (TEM) represents a common phenomenon inconsistently reported across primary studies, warranting further assessment.

METHODS

A systematic review and meta-analysis following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) and Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidelines were conducted. Major electronic databases were searched from inception to May 2017 to assess the incidence and prevalence rates and clinical features associated with manic switch among bipolar depressed patients receiving antidepressants, using meta-regression and subgroup analysis.

RESULTS

Overall, 10 098 depressed patients with bipolar disorder (BD) across 51 studies/arms were included in the quantitative analysis. The cumulative incidence of cases (TEM⁺ ) among 4767 patients with BD over 15 retrospective studies was 30.9% (95% confidence interval [CI] 19.6-45.0%, I²  = 97.9%). The cumulative incidence of TEM⁺ among 1929 patients with BD over 12 prospective open studies was 14.4% (95% CI 7.4-26.1%, I²  = 93.7%). The cumulative incidence of TEM⁺ among 1316 patients with BD over 20 randomized controlled trials (RCTs) was 11.8% (95% CI 8.4-16.34%, I²  = 73.46%). The pooled prevalence of TEM⁺ among 2086 patients with BD over four cross-sectional studies was 30.9% (95% CI 18.1-47.4%, I²  = 95.6%). Overall, concurrent lithium therapy predicted the lowest TEM rates. Inconsistent operational definitions of TEM were recorded, and the lack of information about age, sex, co-occurring anxiety, and other clinically relevant moderators precluded further stratification of the results.

CONCLUSIONS

Rates of TEM vary primarily depending on study setting, which is concordant with the high degree of heterogeneity of the included records. Forthcoming RCT studies should adopt consistent operational definitions of TEM and broaden the number of moderators, in order to contribute most effectively to the identification of clear-cut sub-phenotypes of BD and patient-tailored pharmacotherapy.

The World Federation of Societies of Biological Psychiatry (WFSBP) Guidelines for the Biological Treatment of Bipolar Disorders: Acute and long-term treatment of mixed states in bipolar disorder

OBJECTIVES

Although clinically highly relevant, the recognition and treatment of bipolar mixed states has played only an underpart in recent guidelines. This WFSBP guideline has been developed to supply a systematic overview of all scientific evidence pertaining to the acute and long-term treatment of bipolar mixed states in adults.

METHODS

Material used for these guidelines is based on a systematic literature search using various data bases. Their scientific rigour was categorised into six levels of evidence (A-F), and different grades of recommendation to ensure practicability were assigned. We examined data pertaining to the acute treatment of manic and depressive symptoms in bipolar mixed patients, as well as data pertaining to the prevention of mixed recurrences after an index episode of any type, or recurrence of any type after a mixed index episode.

RESULTS

Manic symptoms in bipolar mixed states appeared responsive to treatment with several atypical antipsychotics, the best evidence resting with olanzapine. For depressive symptoms, addition of ziprasidone to treatment as usual may be beneficial; however, the evidence base is much more limited than for the treatment of manic symptoms. Besides olanzapine and quetiapine, valproate and lithium should also be considered for recurrence prevention.

LIMITATIONS

The concept of mixed states changed over time, and recently became much more comprehensive with the release of DSM-5. As a consequence, studies in bipolar mixed patients targeted slightly different bipolar subpopulations. In addition, trial designs in acute and maintenance treatment also advanced in recent years in response to regulatory demands.

CONCLUSIONS

Current treatment recommendations are still based on limited evidence, and there is a clear demand for confirmative studies adopting the DSM-5 specifier with mixed features concept.

Application of machine learning classification for structural brain MRI in mood disorders: Critical review from a clinical perspective

Mood disorders are a highly prevalent group of mental disorders causing substantial socioeconomic burden. There are various methodological approaches for identifying the underlying mechanisms of the etiology, symptomatology, and therapeutics of mood disorders; however, neuroimaging studies have provided the most direct evidence for mood disorder neural substrates by visualizing the brains of living individuals. The prefrontal cortex, hippocampus, amygdala, thalamus, ventral striatum, and corpus callosum are associated with depression and bipolar disorder. Identifying the distinct and common contributions of these anatomical regions to depression and bipolar disorder have broadened and deepened our understanding of mood disorders. However, the extent to which neuroimaging research findings contribute to clinical practice in the real-world setting is unclear. As traditional or non-machine learning MRI studies have analyzed group-level differences, it is not possible to directly translate findings from research to clinical practice; the knowledge gained pertains to the disorder, but not to individuals. On the other hand, a machine learning approach makes it possible to provide individual-level classifications. For the past two decades, many studies have reported on the classification accuracy of machine learning-based neuroimaging studies from the perspective of diagnosis and treatment response. However, for the application of a machine learning-based brain MRI approach in real world clinical settings, several major issues should be considered. Secondary changes due to illness duration and medication, clinical subtypes and heterogeneity, comorbidities, and cost-effectiveness restrict the generalization of the current machine learning findings. Sophisticated classification of clinical and diagnostic subtypes is needed. Additionally, as the approach is inevitably limited by sample size, multi-site participation and data-sharing are needed in the future.

Characteristics of depression among offspring at high and low familial risk of bipolar disorder

OBJECTIVES

Having a parent with bipolar disorder (BP) is a very strong risk factor for developing BP. Similarly, depression among youth is a clinical risk factor for subsequent BP. We evaluated whether mood symptomatology in depressed youth is different between those at high and low familial risk to develop BP.

METHODS

The most severe major depressive episode in BP offspring (N=61) and community control offspring (N=20) was evaluated using expanded depression and mania rating scales derived from the Schedule for Affective Disorders and Schizophrenia for Children Present Version. The results were adjusted for any between-group significant demographic differences and for multiple comparisons.

RESULTS

The severity of depressive symptoms and the percentage of offspring with severe depressive symptoms, especially atypical depressive features, were significantly higher in the depressed offspring of BP parents compared to the depressed controls (P_s <.05). The depressive symptoms were helpful to identify a high-risk group (e.g., odds ratio [OR] for hypersomnia: 22.4, 95% confidence interval [CI]: 1.3-404, P=.04). In addition, there were significantly more depressed offspring of BP parents with subsyndromal manic symptoms than controls (52.5% vs 20%, OR: 4.2, 95% CI: 1.2-14.7, P<.01).

CONCLUSIONS

Depressed BP offspring had more severe depression including atypical depressive symptoms, and were more likely to have subsyndromal mixed manic symptoms than depressed control offspring. Prospective studies to evaluate whether these youth are at high risk to develop BP are warranted. If replicated, the results of this study have important clinical (e.g., treatment of depression in depressed offspring of BP parents) and research implications.

Using Clinical Characteristics to Identify Which Patients With Major Depressive Disorder Have a Higher Genetic Load for Three Psychiatric Disorders

BACKGROUND

Limited successes of gene finding for major depressive disorder (MDD) may be partly due to phenotypic heterogeneity. We tested whether the genetic load for MDD, bipolar disorder, and schizophrenia (SCZ) is increased in phenotypically more homogenous MDD patients identified by specific clinical characteristics.

METHODS

Patients (n = 1539) with a DSM-IV MDD diagnosis and control subjects (n = 1792) were from two large cohort studies (Netherlands Study of Depression and Anxiety and Netherlands Twin Register). Genomic profile risk scores (GPRSs) for MDD, bipolar disorder, and SCZ were based on meta-analysis results of the Psychiatric Genomics Consortium. Regression analyses (adjusted for year of birth, sex, three principal components) examined the association between GPRSs with characteristics and GPRSs with MDD subgroups stratified according to the most relevant characteristics. The proportion of liability variance explained by GPRSs for each MDD subgroup was estimated.

RESULTS

GPRS-MDD explained 1.0% (p = 4.19e^-09) of MDD variance, and 1.5% (p = 4.23e^-09) for MDD endorsing nine DSM symptoms. GPRS-bipolar disorder explained 0.6% (p = 2.97e^-05) of MDD variance and 1.1% (p = 1.30e^-05) for MDD with age at onset <18 years. GPRS-SCZ explained 2.0% (p = 6.15e^-16) of MDD variance, 2.6% (p = 2.88e^-10) for MDD with higher symptom severity, and 2.3% (p = 2.26e^-13) for MDD endorsing nine DSM symptoms. An independent sample replicated the same pattern of stronger associations between cases with more DSM symptoms, as compared to overall MDD, and GPRS-SCZ.

CONCLUSIONS

MDD patients with early age at onset and higher symptom severity have an increased genetic risk for three major psychiatric disorders, suggesting that it is useful to create phenotypically more homogenous groups when searching for genes associated with MDD.

Functional alterations of fronto-limbic circuit and default mode network systems in first-episode, drug-naïve patients with major depressive disorder: A meta-analysis of resting-state fMRI data

BACKGROUND

The neurobiological mechanisms of depression are increasingly being explored through resting-state brain imaging studies. However, resting-state fMRI findings have varied, perhaps because of differences between study populations, which included the disorder course and medication use. The aim of our study was to integrate studies of resting-state fMRI and explore the alterations of abnormal brain activity in first-episode, drug-naïve patients with major depressive disorder.

METHODS

Relevant imaging reports in English were searched, retrieved, selected and subjected to analysis by activation likelihood estimation, a coordinate-based meta-analysis technique (final sample, 31 studies). Coordinates extracted from the original reports were assigned to two categories based on effect directionality.

RESULTS

Compared with healthy controls, the first-episode, medication-naïve major depressive disorder patients showed decreased brain activity in the dorsolateral prefrontal cortex, superior temporal gyrus, posterior precuneus, and posterior cingulate, as well as in visual areas within the occipital lobe, lingual gyrus, and fusiform gyrus, and increased activity in the putamen and anterior precuneus.

LIMITATIONS

Not every study that has reported relevant data met the inclusion criteria.

CONCLUSION

Resting-state functional alterations were located mainly in the fronto-limbic system, including the dorsolateral prefrontal cortex and putamen, and in the default mode network, namely the precuneus and superior/middle temporal gyrus. Abnormal functional alterations of the fronto-limbic circuit and default mode network may be characteristic of first-episode, drug-naïve major depressive disorder patients.

Geographical and temporal variations in the prevalence of mental disorders in suicide: Systematic review and meta-analysis

BACKGROUND

In contrast to the previous studies reporting that most suicides occur among people with mental disorders, recent studies have reported various rates of mental disorders in suicide in different geographical regions. We aimed to comprehensively investigate the factors influencing the variation in the prevalence of mental disorders reported among suicide victims.

METHOD

The authors searched Embase, Medline, Web of Science, and the Cochrane Library to identify psychological autopsy studies reporting the prevalence of any mental disorders among suicide victims. A meta-regression analysis was conducted to identify the potential effects of geographical regions, the year of publication, measurements of personality disorder, measurements of comorbidity, and the ratio of females on the prevalence of mental disorders in addition to examining the heterogeneity across studies.

RESULTS

From 4475 potentially relevant studies, 48 studies met eligibility criteria, with 6626 suicide victims. The studies from East Asia had a significantly lower mean prevalence (69.6% [95% CI=56.8 to 80.0]) than those in North America (88.2% [95% CI=79.7-93.5]) and South Asia (90.4% [95% CI=71.8-97.2]). The prevalence of any mental disorder decreased according to the year of publication (coefficients=-0.0715, p<0.001).

LIMITATIONS

Substantial heterogeneities were identified within all subgroup analyses.

CONCLUSIONS

The prevalence of mental disorders among suicide cases seemed relatively low in the East Asia region, and recently published studies tended to report a lower prevalence of mental disorders. The link between the risk factors and suicide in the absence of a mental disorder should be examined in different geographical and sociocultural contexts.

Attention-deficit hyperactivity disorder, its pharmacotherapy, and the risk of developing bipolar disorder: A nationwide population-based study in Taiwan

In this study, we aimed to evaluate the relationship between attention-deficit/hyperactivity disorder (ADHD) during childhood and subsequent diagnoses of bipolar disorder (BD), as well as to determine whether the pharmacotherapy for ADHD (methylphenidate and atomoxetine) influence the risks of developing BD. A nationwide cohort of patients newly diagnosed with ADHD (n = 144,920) and age- and gender-matching controls (n = 144,920) were found in Taiwan's National Health Insurance database from January 2000 to December 2011. Both patients and controls were observed until December 31, 2011. To determine the effect that the duration of methylphenidate and atomoxetine exposure had on BD, the difference in the risk of developing BD was compared among non-users, short-term users (≤ 365 days), and long-term users (>365 days). In comparison to the control group, the ADHD group showed a significantly increased risk of developing BD (ADHD: 2.1% vs.

CONTROLS

0.4%; aHR: 7.85, 95% CI: 7.09-8.70), and had a younger mean age at the time of first diagnosis (ADHD: 12.0 years vs.

CONTROLS

18.8 years). Compared to ADHD patients that had never taken methylphenidate, patients with long-term use of methylphenidate were less likely to be diagnosed with BD (aOR: 0.72, 95% CI: 0.65-0.80). However, the duration of exposure to atomoxetine did not have a significant relationship to a BD diagnosis. The results suggested that a previous diagnosis of ADHD was a powerful indicator of BD, particularly juvenile-onset BD. Nevertheless, the exact mechanisms of the relationships among ADHD, its pharmacotherapy, and BD require further clarification in the future.

Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders

OBJECTIVES

To provide guidance for the management of mood disorders, based on scientific evidence supplemented by expert clinical consensus and formulate recommendations to maximise clinical salience and utility.

METHODS

Articles and information sourced from search engines including PubMed and EMBASE, MEDLINE, PsycINFO and Google Scholar were supplemented by literature known to the mood disorders committee (MDC) (e.g., books, book chapters and government reports) and from published depression and bipolar disorder guidelines. Information was reviewed and discussed by members of the MDC and findings were then formulated into consensus-based recommendations and clinical guidance. The guidelines were subjected to rigorous successive consultation and external review involving: expert and clinical advisors, the public, key stakeholders, professional bodies and specialist groups with interest in mood disorders.

RESULTS

The Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders (Mood Disorders CPG) provide up-to-date guidance and advice regarding the management of mood disorders that is informed by evidence and clinical experience. The Mood Disorders CPG is intended for clinical use by psychiatrists, psychologists, physicians and others with an interest in mental health care.

CONCLUSIONS

The Mood Disorder CPG is the first Clinical Practice Guideline to address both depressive and bipolar disorders. It provides up-to-date recommendations and guidance within an evidence-based framework, supplemented by expert clinical consensus.

MOOD DISORDERS COMMITTEE

Professor Gin Malhi (Chair), Professor Darryl Bassett, Professor Philip Boyce, Professor Richard Bryant, Professor Paul Fitzgerald, Dr Kristina Fritz, Professor Malcolm Hopwood, Dr Bill Lyndon, Professor Roger Mulder, Professor Greg Murray, Professor Richard Porter and Associate Professor Ajeet Singh.

INTERNATIONAL EXPERT ADVISORS

Professor Carlo Altamura, Dr Francesco Colom, Professor Mark George, Professor Guy Goodwin, Professor Roger McIntyre, Dr Roger Ng, Professor John O'Brien, Professor Harold Sackeim, Professor Jan Scott, Dr Nobuhiro Sugiyama, Professor Eduard Vieta, Professor Lakshmi Yatham.

AUSTRALIAN AND NEW ZEALAND EXPERT ADVISORS

Professor Marie-Paule Austin, Professor Michael Berk, Dr Yulisha Byrow, Professor Helen Christensen, Dr Nick De Felice, A/Professor Seetal Dodd, A/Professor Megan Galbally, Dr Josh Geffen, Professor Philip Hazell, A/Professor David Horgan, A/Professor Felice Jacka, Professor Gordon Johnson, Professor Anthony Jorm, Dr Jon-Paul Khoo, Professor Jayashri Kulkarni, Dr Cameron Lacey, Dr Noeline Latt, Professor Florence Levy, A/Professor Andrew Lewis, Professor Colleen Loo, Dr Thomas Mayze, Dr Linton Meagher, Professor Philip Mitchell, Professor Daniel O'Connor, Dr Nick O'Connor, Dr Tim Outhred, Dr Mark Rowe, Dr Narelle Shadbolt, Dr Martien Snellen, Professor John Tiller, Dr Bill Watkins, Dr Raymond Wu.

Disturbances in Hypothalamic-Pituitary-Adrenal Axis and Immunological Activity Differentiating between Unipolar and Bipolar Depressive Episodes

INTRODUCTION

Differentiating bipolar depression (BD) from unipolar depression (UD) is difficult in clinical practice and, consequently, accurate recognition of BD can take as long as nine years. Research has therefore focused on the discriminatory capacities of biomarkers, such as markers of the hypothalamic-pituitary-adrenal (HPA) axis or immunological activity. However, no previous study included assessments of both systems, which is problematic as they may influence each other. Therefore, this study aimed to explore whether cortisol indicators and inflammatory markers were a) independently associated with and/or b) showed effect modification in relation to a lifetime (hypo)manic episode in a large sample of depressed patients.

METHODS

Data were derived from the Netherlands Study of Depression and Anxiety and comprised 764 patients with a DSM-IV depressive disorder at baseline, of which 124 (16.2%) had a lifetime (hypo)manic episode at the 2-year assessment, or a more recent episode at the 4-year or 6-year assessment. Baseline cortisol awakening response, evening cortisol and diurnal cortisol slope were considered as cortisol indicators, while baseline C-reactive Protein (CRP), Interleukin-6 (IL-6), and Tumor Necrosis Factor Alpha (TNF-α) were included as inflammatory markers.

RESULTS

In depressed men and women, none of the cortisol indicators and inflammatory markers were (independently) associated with a (hypo)manic episode. However, effect modification was found of diurnal cortisol slope and CRP in relation to a (hypo)manic episode. Further analyses showed that depressed men with high levels of diurnal cortisol slope and CRP had an increased odds (OR=10.99, p=.001) of having a (hypo)manic episode. No significant differences were found in women.

CONCLUSION

Our findings suggest that the combination of high diurnal cortisol slope and high CRP may differentiate between UD and BD. This stresses the importance of considering HPA-axis and immunological activity simultaneously, but more research is needed to unravel their interrelatedness.