A systematic review and meta-analysis of prospective transition from major depression to bipolar disorder

Age of onset of major depressive episode and association with lifetime psychiatric disorders, health-related quality of life and impact of gender: A cross sectional and retrospective cohort study

OBJECTIVE

To assess the long-term impact of the age of onset (AOO) of the first major depressive episode (MDE) according to 3 age groups and considering gender.

METHODS

Data were extracted from NESARC III, a representative U.S.

SAMPLE

We included 8053 participants with an MDE history in a cross-sectional and retrospective cohort study. We defined 3 AOO groups: childhood-onset (< 13 yo), adolescence-onset (13-18 yo), and adult-onset (> 18 yo). We compared sociodemographic characteristics, lifetime psychiatric disorders per DSM-5 criteria, and health-related quality of life (HRQOL) in each group and performed gender-stratified analyses.

RESULTS

Prevalence of childhood-onset MDE was 10.03 %, adolescence-onset was 14.12 %, and adult-onset was 75.85 %. Suicide attempts (AOR = 3.61; 95 % CI 2.90-4.50), anxiety disorders (AOR = 1.92; 95 % CI 1.62-2.27), and personality disorders (AOR = 3.08; 95 % CI 2.56-3.71) were more frequent in the childhood-onset than in the adult-onset one. Adolescence-onset group showed similar results. Physical Disability scale (p < 0.001) and Mental Disability scale (p < 0.001) were significantly lower in the childhood-onset group. Results were more nuanced in the adolescence-onset group. Women in childhood-onset and adolescence-onset groups had poorer outcomes than the adult-onset group. Differences were less pronounced in men.

LIMITATIONS

Recall and classification biases inherent to survey design.

CONCLUSION

Individuals, particularly women, who experienced their first MDE during childhood or adolescence exhibit higher lifetime psychiatric disorder prevalence and poorer HRQOL than those with adult-onset MDE. These findings highlight the importance of preventive measures, early diagnosis, and treatment of youth depression.

Factors associated with chronic depressive symptoms across adolescence and young adulthood: a UK birth cohort study

AIMS

Identifying children and/or adolescents who are at highest risk for developing chronic depression is of utmost importance, so that we can develop more effective and targeted interventions to attenuate the risk trajectory of depression. To address this, the objective of this study was to identify young people with persistent depressive symptoms across adolescence and young adulthood and examine the prospective associations between factors and persistent depressive symptoms in young people.

METHODS

We used data from 6711 participants in the Avon Longitudinal Study of Parents and Children. Depressive symptoms were assessed at 12.5, 13.5, 16, 17.5, 21 and 22 years with the Short Mood and Feelings Questionnaire, and we further examined the influence of multiple biological, psychological and social factors in explaining chronic depressive symptoms.

RESULTS

Using latent class growth analysis, we identified four trajectories of depressive symptoms: persistent high, persistent low, persistent moderate and increasing high. After applying several logistic regression models, we found that loneliness and feeling less connected at school were the most relevant factors for chronic course of depressive symptoms.

CONCLUSIONS

Our findings contribute with the identification of those children who are at highest risk for developing chronic depressive symptoms.

Antidepressant-associated diagnostic change from major depressive to bipolar disorder

BACKGROUND

Anticipating diagnostic change from major depressive (MDD) to bipolar disorder (BD) can support better prognosis and treatment, especially of depression but is challenging and reported research results are inconsistent. We therefore assessed clinical characteristics associated with diagnostic change from MDD to BD with antidepressant treatments.

METHODS

We compared characteristics of 3212 initially MDD patients who became (hypo)manic during antidepressant treatment to those with stable MDD diagnoses as well as with cases of stable, spontaneous BD, using standard bivariate and multivariate statistics.

RESULTS

Among MDD patients, 6.69% [CI: 5.85-7.61] changed to BD, mostly type II (BD2, 76.7%). BD-converters had higher rates of familial mood disorders (74.1% vs. 57.1%) or BD (33.7% vs. 21.0%) and 2.8-years younger onset than stable MDD patients. They also had more prior depressive recurrences/year, years-of-illness, mood-stabilizer treatment, divorces, fewer children, more suicide attempts and drug-abuse, and higher intake cyclothymia, YMRS and MDQ scores. Predictors independently associated with diagnostic conversion were: more familial BD, depressions/year, unemployment, cyclothymic temperament, suicidal ideation or acts, and fewer children. BD-converters vs. spontaneous BD cases had significantly more suicide attempts, BD2 diagnoses, and affected relatives. Converting to vs. spontaneous BD1 was associated with more ADHD, more suicidal ideation or behavior, MDI course, and younger onset; converting to vs. spontaneous BD2 had more episodes/year, unemployment, ADHD, substance abuse, suicidal ideation or attempts, and more relatives with BD.

CONCLUSIONS

Few (6.69%) initially MDD subjects converted to BD, most (76.7%) to BD2. Independent predictive associations with diagnostic change included: familial BD, more depressions/year, unemployment, cyclothymic temperament, suicidal behavior and fewer children. Notably, several characteristics were stronger among those changing to BD during antidepressant treatment vs. others with spontaneous BD.

The impact of family-genetic risk scores on social functioning in individuals affected with six major psychiatric and substance use disorders in a Swedish National Sample

To examine whether the level of genetic risk in psychiatric disorders impacts the social functioning of affected individuals, we examine the relationship between genetic risk factors for major depression (MD), anxiety disorders (AD), bipolar disorder (BD), non-affective psychosis (NAP), alcohol use disorder (AUD), and drug use disorder (DUD) in disordered individuals and five adverse social outcomes: unemployment, residence in areas of social deprivation, social welfare, early retirement, and divorce. We examine all cases with registration for these disorders from 1995 to 2015 in individuals born in Sweden. Genetic risk was assessed by the family genetic risk score (FGRS) and statistical estimates by Cox proportional hazard models. High genetic risk was significantly and modestly associated with poorer social outcomes in 23 of 30 analyses. Overall, genetic risk for MD, AD, AUD, and DUD impacted social functioning more strongly in affected individuals than did genetic risk for BD and NAP. Social welfare had the strongest associations with genetic risk, and residence in areas of high deprivation had the weakest. In individuals suffering from psychiatric and substance use disorders, high levels of genetic risk impact not only clinical features but also diverse measures of social functioning.

Beyond the Window of Risk? The Dutch Bipolar Offspring Study: 22-Year Follow-up

OBJECTIVE

Adolescent offspring of parents with bipolar disorder (BD) are at high risk to develop BD and other psychopathology, yet how this risk continues into middle adulthood remains unknown. This study aimed to determine the window of risk for BD and other psychopathology in offspring of parents with BD followed from adolescence into adulthood.

METHOD

This study reported on the 22-year follow-up assessment of the Dutch Bipolar Offspring Study, a fixed cohort study of 140 participants established in 1997. Offspring (n = 100; mean [SD] age = 38.28 [2.74] years) of parents with bipolar I disorder or bipolar II disorder were assessed at baseline and 1-, 5-, 12-, and 22-year follow-up.

RESULTS

No new BD onsets occurred since the 12-year follow-up (lifetime prevalence = 11%-13%; bipolar I disorder = 4%; bipolar II disorder = 7%). Lifetime prevalence of any mood disorder was 65%; for major depressive disorder, prevalence was 36%; and for recurrent mood episodes, prevalence was 37%. Prevalence of major depressive disorder more than doubled in the past decade. Point prevalence of any psychopathology peaked between 20 and 25 years (38%-46%), subsiding to 29% to 35% per year after age 30. Overall, 71% of offspring contacted mental health services since the last assessment.

CONCLUSION

The risk for homotypic transmission of BD in offspring of parents with BD is highest during adolescence. The heterotypic risk for mood disorder onset and recurrences continues over the life course. Severe mood disorders are often preceded by milder psychopathology, emphasizing the need for early identification and interventions. This study allows for better understanding of the onset and course of mood disorders and specific windows of risk in a familial high-risk population.

Combining predominant polarity and affective spectrum concepts in bipolar disorder: towards a novel theoretical and clinical perspective

This is an overview of recent advances on predominant polarity conceptualization in bipolar disorder (BD). Current evidence on its operationalized definitions, possible contextualization within the affective spectrum, along with its epidemiological impact, and treatment implications, are summarized. Predominant polarity identifies three subgroups of patients with BD according to their mood recurrencies: (i) those with depressive or (ii) manic predominance as well as (iii) patients without any preponderance ('nuclear' type). A predominant polarity can be identified in approximately half of patients, with similar rates for depressive and manic predominance. Different factors may influence the predominant polarity, including affective temperaments. More generally, affective disorders should be considered as existing on a spectrum ranging from depressive to manic features, also accounting for disorders with 'ultrapredominant' polarity, i.e., unipolar depression and mania. While mixed findings emerge on its utility in clinical practice, it is likely that the construct of predominant polarity, in place of conventional differentiation between BD-I and BD-II, may be useful to clarify the natural history of the disorder and select the most appropriate interventions. The conceptualization of predominant polarity seems to reconcile previous theoretical views of both BD and affective spectrum into a novel perspective. It may provide useful information to clinicians for the early identification of possible trajectories of BD and thus guide them when selecting interventions for maintenance treatment. However, further research is needed to clarify the specific role of predominant polarity as a key determinant of BD course, outcome, and treatment response.

Prior psychiatric morbidity and differential psychopharmacological treatment patterns: Exploring the heterogeneity of bipolar disorder in a nationwide study of 9594 patients

OBJECTIVES

Individuals with bipolar disorders (BD) have heterogenic pre-onset illness courses and responses to treatment. The pattern of illness preceding the diagnosis of BD may be a marker of future treatment response. Here, we examined associations between psychiatric morbidity preceding the diagnosis of BD and pharmacological treatment patterns in the 2 years following diagnosis.

METHODS

In this register-based study, we included all patients with a diagnosis of BD attending Danish Psychiatric Services between January 1, 2012 and December 31, 2016. We examined the association between a diagnosis of substance use disorder, psychosis (other than schizophrenia or schizoaffective disorder), unipolar depression, anxiety/OCD, PTSD, personality disorder, or ADHD preceding BD and pharmacological treatment patterns following the diagnosis of BD (lithium, valproate, lamotrigine, antidepressants, olanzapine, risperidone, and quetiapine) via multivariable Cox proportional hazards regression adjusted for age, sex, and year of BD diagnosis.

RESULTS

We included 9594 patients with a median age of 39 years, 58% of whom were female. Antidepressants, quetiapine, and lamotrigine were the most commonly used medications in BD and were all linked to prior depressive illness and female sex. Lithium was used among patients with less diagnostic heterogeneity preceding BD, while valproate was more likely to be used for patients with prior substance use disorder or ADHD.

CONCLUSION

The pharmacological treatment of BD is linked to psychiatric morbidity preceding its diagnosis. Assuming that these associations reflect well-informed clinical decisions, this knowledge may inform future clinical trials by taking participants' prior morbidity into account in treatment allocation.

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.

Multimodal integration of neuroimaging and genetic data for the diagnosis of mood disorders based on computer vision models

Mood disorders, particularly major depressive disorder (MDD) and bipolar disorder (BD), are often underdiagnosed, leading to substantial morbidity. Harnessing the potential of emerging methodologies, we propose a novel multimodal fusion approach that integrates patient-oriented brain structural magnetic resonance imaging (sMRI) scans with DNA whole-exome sequencing (WES) data. Multimodal data fusion aims to improve the detection of mood disorders by employing established deep-learning architectures for computer vision and machine-learning strategies. We analyzed brain imaging genetic data of 321 East Asian individuals, including 147 patients with MDD, 78 patients with BD, and 96 healthy controls. We developed and evaluated six fusion models by leveraging common computer vision models in image classification: Vision Transformer (ViT), Inception-V3, and ResNet50, in conjunction with advanced machine-learning techniques (XGBoost and LightGBM) known for high-dimensional data analysis. Model validation was performed using a 10-fold cross-validation. Our ViT ⊕ XGBoost fusion model with MRI scans, genomic Single Nucleotide polymorphism (SNP) data, and unweighted polygenic risk score (PRS) outperformed baseline models, achieving an incremental area under the curve (AUC) of 0.2162 (32.03% increase) and 0.0675 (+8.19%) and incremental accuracy of 0.1455 (+25.14%) and 0.0849 (+13.28%) compared to SNP-only and image-only baseline models, respectively. Our findings highlight the opportunity to refine mood disorder diagnostics by demonstrating the transformative potential of integrating diverse, yet complementary, data modalities and methodologies.

Based on white matter microstructure to early identify bipolar disorder from patients with depressive episode

OBJECTIVE

Because of similar clinical manifestations, bipolar disorder (BD) patients are often misdiagnosed as major depressive disorder (MDD). This study aimed to compare the difference between depressed patients later converting to BD and unipolar depression (UD) according to diffusion tensor imaging (DTI).

METHOD

Patients with MDD (562 participants) in depressive episode states and healthy controls (HCs) (145 participants) were recruited over 10 years. Demographic and magnetic resonance imaging (MRI) data were collected at the time of recruitment. All patients with MDD were followed up for 5 years and classified into the transfer to BD (tBD) group (83 participants) and UD group (160 participants) according to the follow-up results. DTI and functional magnetic resonance imaging at baseline were compared.

RESULTS

Common abnormalities were found in both tBD and UD groups, including left superior cerebellar peduncle (SCP.L), right anterior limb of the internal capsule (ALIC.R), right superior fronto-occipital fasciculus (SFOF.R), and right inferior fronto-occipital fasciculus (IFOF.R). The tBD showed more extensive abnormalities than the UD in the body of corpus callosum, fornix, left superior corona radiata, left posterior corona radiata, left superior longitudinal fasciculus, and left superior fronto-occipital fasciculus.

CONCLUSION

The study demonstrated the common and distinct abnormalities of tBD and UD when compared to HC. The tBD group showed more extensive disruptions of white matter integrity, which could be a potential biomarker for the early identification of BD.

Abnormal stability of spontaneous neuronal activity as a predictor of diagnosis conversion from major depressive disorder to bipolar disorder

OBJECTIVE

Bipolar disorder (BD) is often misdiagnosed as major depressive disorder (MDD) in the early stage, which may lead to inappropriate treatment. This study aimed to characterize the alterations of spontaneous neuronal activity in patients with depressive episodes whose diagnosis transferred from MDD to BD.

METHODS

532 patients with MDD and 132 healthy controls (HCs) were recruited over 10 years. During the follow-up period, 75 participants with MDD transferred to BD (tBD), and 157 participants remained with the diagnosis of unipolar depression (UD). After excluding participants with poor image quality and excessive head movement, 68 participants with the diagnosis of tBD, 150 participants with the diagnosis of UD, and 130 HCs were finally included in the analysis. The dynamic amplitude of low-frequency fluctuations (dALFF) of spontaneous neuronal activity was evaluated in tBD, UD and HC using functional magnetic resonance imaging at study inclusion. Receiver operating characteristic (ROC) analysis was performed to evaluate sensitivity and specificity of the conversion prediction from MDD to BD based on dALFF.

RESULTS

Compared to HC, tBD exhibited elevated dALFF at left premotor cortex (PMC_L), right lateral temporal cortex (LTC_R) and right early auditory cortex (EAC_R), and UD showed reduced dALFF at PMC_L, left paracentral lobule (PCL_L), bilateral medial prefrontal cortex (mPFC), right orbital frontal cortex (OFC_R), right dorsolateral prefrontal cortex (DLPFC_R), right posterior cingulate cortex (PCC_R) and elevated dALFF at LTC_R. Furthermore, tBD exhibited elevated dALFF at PMC_L, PCL_L, bilateral mPFC, bilateral OFC, DLPFC_R, PCC_R and LTC_R than UD. In addition, ROC analysis based on dALFF in differential areas obtained an area under the curve (AUC) of 72.7%.

CONCLUSIONS

The study demonstrated the temporal dynamic abnormalities of tBD and UD in the critical regions of the somatomotor network (SMN), default mode network (DMN), and central executive network (CEN). The differential abnormal patterns of temporal dynamics between the two diseases have the potential to predict the diagnosis transition from MDD to BD.

The Nature of the Familial Risk for Psychosis in Bipolar Disorder

BACKGROUND AND HYPOTHESIS

To clarify whether the familial liability to psychosis associated with bipolar disorder (BD) is nonspecific or has a greater effect on risk for psychosis in cases with prominent mood symptoms and/or a remitting course.

STUDY DESIGN

We examined, in 984 809 offspring raised in intact families in Sweden, born 1980-1996 and followed-up through 2018, by multivariable Cox proportional hazards regression, risk in offspring of parents with BD for 7 psychotic disorders: Psychotic MD (PMD), psychotic BD (PBD), schizoaffective disorder (SAD), acute psychoses, psychosis NOS, delusional disorder (DD) and schizophrenia (SZ). Diagnoses were obtained from national registers.

STUDY RESULTS

In the offspring of BD parents, the hazard ratios (HR) for these 7 disorders formed an inverted U-shaped curve, rising from 2.98 for PMD, to peak at 4.49 for PBD and 5.25 for SAD, and then declining to a HR of 3.48 for acute psychoses and 3.22 for psychosis NOS, to a low of 2.19 for DD and 2.33 for SZ. A similar pattern of risks was seen in offspring of mothers and fathers affected with BD and in offspring predicted from age at onset in their BD parent.

CONCLUSIONS

The BD-associated risk for psychosis impacts most strongly on mood disorders, moderately on episodic psychotic syndromes, and least on chronic psychotic disorders. These results support prior clinical studies suggesting a qualitative difference in the familial substrate for psychosis occurring in BD and SZ.

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.

From Unipolar to Bipolar: The Diagnostic Evolution in an Elderly Man

A pivotal concept in the field of mood disorders is the dichotomy between unipolar depression and bipolar disorder. Due to the unique treatment in older age bipolar disorder and the scarcity of research in this area, it is clinically important to raise the awareness of the diagnostic conversion of unipolar depression to bipolar disorder in the elderly population. We present a case of a 71-year-old Chinese man whose diagnosis was revised to bipolar disorder after 9 years of treatment for unipolar depression. Organic workup, including blood tests and brain imaging, was performed to rule out organic causes. This patient eventually responded well to the combined treatment of an antipsychotic and a mood stabilizer. This case report adds to the growing literature of challenges in identifying and managing bipolar disorder in the elderly. As unipolar depression and bipolar disorder have different disease courses and different treatment strategies, it is essential for clinicians to be aware of diagnostic conversion. Further research is needed to delineate bipolar disorder from unipolar depression in the elderly population.

Predicting diagnostic conversion from major depressive disorder to bipolar disorder: an EHR based study from Colombia

Bipolar Disorder (BD) is a severe and chronic disorder characterized by recurrent episodes of depression, mania, and/or hypomania. Most BD patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study leverages electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia to identify features predictive of the transition from Major Depressive Disorder (MDD) to BD. Analyzing EHR data from 13,607 patients diagnosed with MDD over 15 years, we identified 1,610 cases of conversion to BD. Using a multivariate Cox regression model, we identified severity of the initial MDD episode, the presence of psychosis and hospitalization at first episode, family history of mood or psychotic disorders, female gender to be predictive of the conversion to BD. Additionally, we observed associations with medication classes (prescriptions of mood stabilizers, antipsychotics, and antidepressants) and clinical features (delusions, suicide attempt, suicidal ideation, use of marijuana and alcohol use/abuse) derived from natural language processing (NLP) of clinical notes. Together, these risk factors predicted BD conversion within five years of the initial MDD diagnosis, with a recall of 72% and a precision of 38%. Our study confirms many previously identified risk factors identified through registry-based studies (such as female gender and psychotic depression at the index MDD episode), and identifies novel ones (specifically, suicidal ideation and suicide attempt extracted from clinical notes). These results simultaneously demonstrate the validity of using EHR data for predicting BD conversion as well as underscore its potential for the identification of novel risk factors and improving early diagnosis.

Examining the Relationships between the Incidence of Infectious Diseases and Mood Disorders: An Analysis of Data from the Global Burden of Disease Studies, 1990-2019

Mood disorders are among the commonest mental disorders worldwide. Epidemiological and clinical evidence suggests that there are close links between infectious diseases and mood disorders, but the strength and direction of these association remain largely unknown. Theoretical models have attempted to explain this link based on evolutionary or immune-related factors, but these have not been empirically verified. The current study examined cross-sectional and longitudinal associations between the incidence of infectious diseases and mood disorders, while correcting for climate and economic factors, based on data from the Global Burden of Disease Studies, 1990-2019. It was found that major depressive disorder was positively associated with lower respiratory infections, while bipolar disorder was positively associated with upper respiratory infections and negatively associated with enteric and tropical infections, both cross-sectionally and over a period of 30 years. These results suggest that a complex, bidirectional relationship exists between these disorders. This relationship may be mediated through the immune system as well as through the gut-brain and lung-brain axes. Understanding the mechanisms that link these groups of disorders could lead to advances in the prevention and treatment of both.

Transcranial alternating current stimulation for the treatment of major depressive disorder: from basic mechanisms toward clinical applications

Non-pharmacological treatment is essential for patients with major depressive disorder (MDD) that is medication resistant or who are unable to take medications. Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation method that manipulates neural oscillations. In recent years, tACS has attracted substantial attention for its potential as an MDD treatment. This review summarizes the latest advances in tACS treatment for MDD and outlines future directions for promoting its clinical application. We first introduce the neurophysiological mechanism of tACS and its novel developments. In particular, two well-validated tACS techniques have high application potential: high-definition tACS targeting local brain oscillations and bifocal tACS modulating interarea functional connectivity. Accordingly, we summarize the underlying mechanisms of tACS modulation for MDD. We sort out the local oscillation abnormalities within the reward network and the interarea oscillatory synchronizations among multiple MDD-related networks in MDD patients, which provide potential modulation targets of tACS interventions. Furthermore, we review the latest clinical studies on tACS treatment for MDD, which were based on different modulation mechanisms and reported alleviations in MDD symptoms. Finally, we discuss the main challenges of current tACS treatments for MDD and outline future directions to improve intervention target selection, tACS implementation, and clinical validations.

Privacy-Preserving Federated Model Predicting Bipolar Transition in Patients With Depression: Prediction Model Development Study

BACKGROUND

Mood disorder has emerged as a serious concern for public health; in particular, bipolar disorder has a less favorable prognosis than depression. Although prompt recognition of depression conversion to bipolar disorder is needed, early prediction is challenging due to overlapping symptoms. Recently, there have been attempts to develop a prediction model by using federated learning. Federated learning in medical fields is a method for training multi-institutional machine learning models without patient-level data sharing.

OBJECTIVE

This study aims to develop and validate a federated, differentially private multi-institutional bipolar transition prediction model.

METHODS

This retrospective study enrolled patients diagnosed with the first depressive episode at 5 tertiary hospitals in South Korea. We developed models for predicting bipolar transition by using data from 17,631 patients in 4 institutions. Further, we used data from 4541 patients for external validation from 1 institution. We created standardized pipelines to extract large-scale clinical features from the 4 institutions without any code modification. Moreover, we performed feature selection in a federated environment for computational efficiency and applied differential privacy to gradient updates. Finally, we compared the federated and the 4 local models developed with each hospital's data on internal and external validation data sets.

RESULTS

In the internal data set, 279 out of 17,631 patients showed bipolar disorder transition. In the external data set, 39 out of 4541 patients showed bipolar disorder transition. The average performance of the federated model in the internal test (area under the curve [AUC] 0.726) and external validation (AUC 0.719) data sets was higher than that of the other locally developed models (AUC 0.642-0.707 and AUC 0.642-0.699, respectively). In the federated model, classifications were driven by several predictors such as the Charlson index (low scores were associated with bipolar transition, which may be due to younger age), severe depression, anxiolytics, young age, and visiting months (the bipolar transition was associated with seasonality, especially during the spring and summer months).

CONCLUSIONS

We developed and validated a differentially private federated model by using distributed multi-institutional psychiatric data with standardized pipelines in a real-world environment. The federated model performed better than models using local data only.

Antidepressant-induced mania in panic disorder: a single-case study of clinical and functional connectivity characteristics

Background

Mental health issues, including panic disorder (PD), are prevalent and often co-occur with anxiety and bipolar disorders. While panic disorder is characterized by unexpected panic attacks, and its treatment often involves antidepressants, there is a 20-40% risk of inducing mania (antidepressant-induced mania) during treatment, making it crucial to understand mania risk factors. However, research on clinical and neurological characteristics of patients with anxiety disorders who develop mania is limited.

Methods

In this single case study, we conducted a larger prospective study on panic disorder, comparing baseline data between one patient who developed mania (PD-manic) and others who did not (PD-NM group). We enrolled 27 patients with panic disorder and 30 healthy controls (HCs) and examined alterations in amygdala-based brain connectivity using a seed-based whole-brain approach. We also performed exploratory comparisons with healthy controls using ROI-to-ROI analyses and conducted statistical inferences at a threshold of cluster-level family-wise error-corrected p < 0.05, with the cluster-forming threshold at the voxel level of uncorrected p < 0.001.

Results

The patient with PD-mania showed lower connectivity in brain regions related to the default mode network (left precuneous cortex, maximum z-value within the cluster = -6.99) and frontoparietal network (right middle frontal gyrus, maximum z-value within the cluster = -7.38; two regions in left supramarginal gyrus, maximum z-value within the cluster = -5.02 and -5.86), and higher in brain regions associated with visual processing network (right lingual gyrus, maximum z-value within the cluster = 7.86; right lateral occipital cortex, maximum z-value within the cluster = 8.09; right medial temporal gyrus, maximum z-value within the cluster = 8.16) in the patient with PD-mania compared to the PD-NM group. One significantly identified cluster, the left medial temporal gyrus (maximum z-value within the cluster = 5.82), presented higher resting-state functional connectivity with the right amygdala. Additionally, ROI-to-ROI analysis revealed that significant clusters between PD-manic and PD-NM groups differed from HCs in the PD-manic group but not in the PD-NM group.

Conclusion

Here, we demonstrate altered amygdala-DMN and amygdala-FPN connectivity in the PD-manic patient, as reported in bipolar disorder (hypo) manic episodes. Our study suggests that amygdala-based resting-state functional connectivity could serve as a potential biomarker for antidepressant-induced mania in panic disorder patients. Our findings provide an advance in understanding the neurological basis of antidepressant-induced mania, but further research with larger cohorts and more cases is necessary for a broader perspective on this issue.

Considerations when selecting an antidepressant: a narrative review for primary care providers treating adults with depression

Major depressive disorder (MDD) is a debilitating mental disorder that can be treated with a number of different antidepressant therapies, each with its own unique prescribing considerations. Complicating the selection of an appropriate antidepressant for adults with MDD is the heterogeneity of clinical profiles and depression subtypes. Additionally, patient comorbidities, preferences, and likelihood of adhering to treatment must all be considered when selecting an appropriate therapy. With the majority of prescriptions being written by primary care practitioners, it is appropriate to review the unique characteristics of all available antidepressants, including safety considerations. Prior to initiating antidepressant treatment and when patients do not respond adequately to initial therapy and/or exhibit any hypomanic or manic symptoms, bipolar disorder must be ruled out, and evaluation for psychiatric comorbidities must be considered as well. Patients with an inadequate response may then require a treatment switch to another drug with a different mechanism of action, combination, or augmentation strategy. In this narrative review, we propose that careful selection of the most appropriate antidepressant for adult patients with MDD based on their clinical profile and comorbidities is vital for initial treatment selection.Strategies must be considered for addressing partial and inadequate responses as well to help patients achieve full remission and sustained functional recovery. This review also highlights data for MDD clinical outcomes for which gaps in the literature have been identified, including the effects of antidepressants on functional outcomes, sleep disturbances, emotional and cognitive blunting, anxiety, and residual symptoms of depression.

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.

Risk of conversion to bipolar disorder in patients with late-onset major depression

To evaluate the impact of age at onset on late-life depression course and on risk of conversion to bipolar disorder (BD). A retrospective chart review of 100 elderly patients (age ≥ 65 years) diagnosed with a moderate-to-severe depressive episode and followed up for at least 18 months was conducted. Among patients affected by major depressive disorder ( N = 57), follow-up morbidity differences between those with typical onset depression (TOD) (&lt;60 years) and those with late-onset depression (LOD) (≥60 years) were investigated using Wilcoxon rank-sum test and Cox proportional hazard model. Patients belonging to the LOD group had a significantly lower percentage of follow-up time spent with depressive symptoms compared with patients with TOD ( r = 0.36; P = 0.006), but significantly more time spent with (hypo)manic episodes ( r = -0.31; P = 0.021). Moreover, LOD was significantly associated with a faster conversion to BD (hazard ratio = 3.05; P = 0.037). Depression first emerging in late life may represent an unstable condition with a high risk to convert to BD. Given the potential clinical implications, further studies on the course of LOD are required.

Understanding the development of bipolar disorder and borderline personality disorder in young people: a meta-review of systematic reviews

BACKGROUND

There is ongoing debate on the nosological position of bipolar disorder (BD) and borderline personality disorder (BPD). Identifying the unique and shared risks, developmental pathways, and symptoms in emerging BD and BPD could help the field refine aetiological hypotheses and improve the prediction of the onset of these disorders. This study aimed to: (a) systematically synthesise the available evidence from systematic reviews (SRs) and meta-analyses (MAs) concerning environmental, psychosocial, biological, and clinical factors leading to the emergence of BD and BPD; (b) identify the main differences and common features between the two disorders to characterise their complex interplay and, (c) highlight remaining evidence gaps.

METHODS

Data sources were; PubMed, PsychINFO, Embase, Cochrane, CINAHL, Medline, ISI Web of Science. Overlap of included SRs/MAs was assessed using the corrected covered area process. The methodological quality of each included SR and MA was assessed using the AMSTAR.

RESULTS

22 SRs and MAs involving 249 prospective studies met eligibility criteria. Results demonstrated that family history of psychopathology, affective instability, attention deficit hyperactivity disorder, anxiety disorders, depression, sleep disturbances, substance abuse, psychotic symptoms, suicidality, childhood adversity and temperament were common predisposing factors across both disorders. There are also distinct factors specific to emerging BD or BPD.

CONCLUSIONS

Prospective studies are required to increase our understanding of the development of BD and BPD onset and their complex interplay by concurrently examining multiple measures in BD and BPD at-risk populations.

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.

Predicting the emergence of full-threshold bipolar I, bipolar II and psychotic disorders in young people presenting to early intervention mental health services

BACKGROUND

Predictors of new-onset bipolar disorder (BD) or psychotic disorder (PD) have been proposed on the basis of retrospective or prospective studies of 'at-risk' cohorts. Few studies have compared concurrently or longitudinally factors associated with the onset of BD or PDs in youth presenting to early intervention services. We aimed to identify clinical predictors of the onset of full-threshold (FT) BD or PD in this population.

METHOD

Multi-state Markov modelling was used to assess the relationships between baseline characteristics and the likelihood of the onset of FT BD or PD in youth (aged 12-30) presenting to mental health services.

RESULTS

Of 2330 individuals assessed longitudinally, 4.3% (n = 100) met criteria for new-onset FT BD and 2.2% (n = 51) met criteria for a new-onset FT PD. The emergence of FT BD was associated with older age, lower social and occupational functioning, mania-like experiences (MLE), suicide attempts, reduced incidence of physical illness, childhood-onset depression, and childhood-onset anxiety. The emergence of a PD was associated with older age, male sex, psychosis-like experiences (PLE), suicide attempts, stimulant use, and childhood-onset depression.

CONCLUSIONS

Identifying risk factors for the onset of either BD or PDs in young people presenting to early intervention services is assisted not only by the increased focus on MLE and PLE, but also by recognising the predictive significance of poorer social function, childhood-onset anxiety and mood disorders, and suicide attempts prior to the time of entry to services. Secondary prevention may be enhanced by greater attention to those risk factors that are modifiable or shared by both illness trajectories.

Contributing factors to heterogeneity in the timing of the onset of major depressive episode: Results from a national study

INTRODUCTION

It remains unclear whether specific clinical factors contribute to heterogeneity in the timing of the onset of major depression.

METHODS

Using a nationally representative US adult sample, the second wave of the National Epidemiologic Survey on Alcohol and Related Conditions, we compared the characteristics of 5 different groups of patients defined by their age at onset: (i) before 18 years, (ii) between 18 and 34 years, (iii) between 35 and 44 years, (iv) between 45 and 59 years, and (v) 60 years or older. Specifically, we examined parental history of psychiatric disorders, history of childhood maltreatment experiences, sociodemographic characteristics, lifetime psychiatric disorders, and psychiatric disorders that occurred before the first major depressive episode (MDE).

RESULTS

Compared with first MDE occurring between 18 and 34 years, first MDE before 18 years was more strongly associated with childhood maltreatment and family history of psychiatric disorders, and less strongly linked to prior lifetime psychiatric disorders, whereas first MDE occurring at 60 years and older was more strongly associated with widowhood and a prior lifetime history of generalized anxiety disorder.

LIMITATIONS

Associations found cannot be interpzreted as causal relationships due to study design and the risk of recall bias.

CONCLUSION

Our results suggest substantial age differences in risk factors for first MDE. Improving early detection and treatment of major depression and other psychiatric disorders, and preventing childhood maltreatment may have broad benefits to reduce the burden of MDE at all ages.

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.

Practical Advice for Primary Care Clinicians on the Safe and Effective Use of Vortioxetine for Patients with Major Depressive Disorder (MDD)

Primary care clinicians have a vital role to play in the diagnosis and management of patients with major depressive disorder (MDD). This includes screening for MDD as well as identifying other possible psychiatric disorders including bipolar disorder and/or other comorbidities. Once MDD is confirmed, partnering with patients in the shared decision-making process while considering different treatment options and best management of MDD over the course of their illness is recommended. Vortioxetine has been approved for the treatment of adults with MDD since 2013, and subsequent US label updates indicate that vortioxetine may be particularly beneficial for specific populations of patients with MDD, including those with treatment-emergent sexual dysfunction and patients experiencing certain cognitive symptoms. Given these recent label updates, this prescribing guide for vortioxetine aims to provide clear and practical guidance for primary care clinicians on the safe and effective use of vortioxetine for the treatment of MDD, including how to identify appropriate patients for treatment.

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.

Bipolar Disorder: From Pathophysiology to Treatment

Bipolar disorder is a mental disorder that involves a manic or hypomanic state and a depressive state, and was once called manic-depressive disorder and was considered one of the two major mental disorders along with schizophrenia. Major depressive disorder, on the other hand, is a disorder in which only depressive states occur, and the two are sometimes referred to together as "mood disorders. This review will introduce the pathophysiology, diagnosis, epidemiology, and treatment of bipolar disorder, focusing on the current situation in Japan.

Factors causing a relapse of major depressive disorders following successful electroconvulsive therapy: A retrospective cohort study

BACKGROUND

Electroconvulsive therapy (ECT) is used to treat major depressive disorder (MDD). Relapse is often observed even after successful ECT, followed by adequate pharmaceutical treatment for MDD.

AIM

To investigate the diagnostic factors and treatment strategies associated with depression relapse.

METHODS

We analyzed the relationships between relapse, the diagnostic change from MDD to bipolar disorder (BP), and treatment after the initial ECT. We performed a 3-year retrospective study of the prognoses of 85 patients of the Shiga University of Medical Science Hospital. The relative risk of relapse of depressive symptoms was calculated based on the diagnostic change from MDD to BP. A receiver operating characteristic (ROC) curve was generated to evaluate the predictive accuracy of diagnostic changes from MDD to BP based on the duration between the first course of ECT and the relapse of depressive symptoms.

RESULTS

Eighty-five patients initially diagnosed with MDD and successfully treated with ECT were enrolled in the study. Compared with the MDD participants, more BP patients experienced relapses and required continuation and/or maintenance ECT to maintain remission (65.6% vs 15.1%, P < 0.001; relative risk = 4.35, 95%CI: 2.19-8.63, P < 0.001). Twenty-nine patients experienced relapses during the three-year follow-up. In 21 (72.4%, 21/29) patients with relapse, the diagnosis was changed from MDD to BP. The duration from the first course of ECT to relapse was shorter for the BP patients than for the MDD patients (9.63 ± 10.4 mo vs 3.38 ± 3.77 mo, P = 0.022); for most patients, the interval was less than one month. The relative risk of depressive symptoms based on diagnostic changes was 4.35 (95% confidence interval: 2.19–8.63, P < 0.001), and the area under the ROC curve for detecting diagnostic changes based on relapse duration was 0.756 (95%CI: 0.562-0.895, P = 0.007).

CONCLUSION

It may be beneficial to suspect BP and change the treatment strategy from MDD to BP for patients experiencing an early relapse.

[Early intervention in bipolar affective disorders: Why, when and how]

OBJECTIVES

Bipolar disorder (BD) is a chronic and severe psychiatric disease. There are often significant delays prior to diagnosis, and only 30 to 40 % of patients will experience complete remission. Since BD occurs most often at a young age, the disorder can seriously obstruct future socio-professional development and integration. Vulnerability-stress model of BD is considered to be the result of an interaction between vulnerability genes and environmental risk factors, which leads to the onset of the disorder most often in late adolescence or early adulthood. The clinical "staging" model of BD situates the subject in a clinical continuum of varying degrees of severity (at-risk status, first episode, full-blown BD). Given the demonstrated effectiveness of early intervention in the early stages of psychotic disorder, we posit that early intervention for early stages of BD (i.e. at-risk status and first episode mania or hypomania) would reduce the duration of untreated illness and optimize the chances of therapeutic response and recovery.

METHODS

We conducted a narrative review of the literature to gather updated data on: (1) features of early stages: risk factors, at-risk symptoms, clinical specificities of the first manic episode; (2) early screening: targeted populations and psychometric tools; (3) early treatment: settings and therapeutic approaches for the early stages of BD.

RESULTS

(1) Features of early stages: among genetic risk factors, we highlighted the diagnosis of BD in relatives and affective temperament including as cyclothymic, depressive, anxious and dysphoric. Regarding prenatal environmental risk, we identified peripartum factors such as maternal stress, smoking and viral infections, prematurity and cesarean delivery. Later in the neurodevelopmental course, stressful events and child psychiatric disorders are recognized as increasing the risk of developing BD in adolescence. At-risk symptoms could be classified as "distal" with early but aspecific expressions including anxiety, depression, sleep disturbance, decreased cognitive performance, and more specific "proximal" symptoms which correspond to subsyndromic hypomanic symptoms that increase in intensity as the first episode of BD approaches. Specific clinical expressions have been described to assess the risk of BD in individuals with depression. Irritability, mixed and psychotic features are often observed in the first manic episode. (2) Early screening: some individuals with higher risk need special attention for screening, such as children of people with BD. Indeed, it is shown that children with at least one parent with BD have around 50 % risk of developing BD during adolescence or early adulthood. Groups of individuals presenting other risk factors, experiencing an early stage of psychosis or depressive disorders should also be considered as targeted populations for BD screening. Three questionnaires have been validated to screen for the presence of at-risk symptoms of BD: the Hypomanic Personality Scale, the Child Behavior Checklist-Paediatric Bipolar Disorder, and the General Behavior Inventory. In parallel, ultra-high risk criteria for bipolar affective disorder ("bipolar at-risk") distinguishing three categories of at-risk states for BD have been developed. (3) Early treatment: clinical overlap between first psychotic and manic episode and the various trajectories of the at-risk status have led early intervention services (EIS) for psychosis to reach out for people with an early stage of BD. EIS offers complete biopsychosocial evaluations involving a psychiatric examination, semi-structured interviews, neuropsychological assessments and complementary biological and neuroimaging investigations. Key components of EIS are a youth-friendly approach, specialized and intensive care and client-centered case management model. Pharmaceutical treatments for at-risk individuals are essentially symptomatic, while guidelines recommend the use of a non-antipsychotic mood stabilizer as first-line monotherapy for the first manic or hypomanic episode. Non-pharmacological approaches including psychoeducation, psychotherapy and rehabilitation have proven efficacy and should be considered for both at-risk and first episode of BD.

CONCLUSIONS

EIS for psychosis might consider developing and implementing screening and treatment approaches for individuals experiencing an early stage of BD. Several opportunities for progress on early intervention in the early stages of BD can be drawn. Training first-line practitioners to identify at-risk subjects would be relevant to optimize screening of this population. Biomarkers including functional and structural imaging measures of specific cortical regions and inflammation proteins including IL-6 rates constitute promising leads for predicting the risk of transition to full-blown BD. From a therapeutic perspective, the use of neuroprotective agents such as folic acid has shown particularly encouraging results in delaying the emergence of BD. Large-scale studies and long-term follow-up are still needed to achieve consensus in the use of screening and treatment tools. The development of specific recommendations for the early stages of BD is warranted.

Risk factors for new-onset bipolar disorder in a community cohort: A five-year follow up study

The aim of this study was to assess the risk factors for new-onset Bipolar Disorder (BD) in a community sample of young adults. This is a prospective cohort study including a population-based sample of young adults aged between 18-24 years. The baseline took place from 2007 to 2009, and 1560 subjects were included. Five years after, 1244 individuals were re-evaluated (79.7% retention). Substance abuse/dependence was assessed using the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST), and mental disorders were assessed using the Mini International Neuropsychiatric Interview 5.0 (MINI) at both waves. The cumulative incidence of BD in five years was 4.6%. There was no significant association between sociodemographic factors and BD incidence. Tobacco, cannabis, cocaine/crack, other substances abuse/dependence increased the relative risk for BD. Depressive, anxiety, post-traumatic stress disorders, and the suicide risk increased the relative risk to BD. Depressive episode was the strongest risk factor for BD, followed by other mental disorders and substance abuse/dependence in a probabilistic community sample of young adults. Preventive actions in mental health directed at the non-clinical population are needed for early detection and better management of BD.

Emotion-Related Network Reorganization Following Fish Oil Supplementation in Depressed Bipolar Offspring: An fMRI Graph-Based Connectome Analysis

INTRODUCTION

Mood disorders are associated with fronto-limbic structural and functional abnormalities and deficits in omega-3 polyunsaturated fatty acids including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Emerging evidence also suggests that n-3 PUFA, which are enriched in fish oil, promote cortical plasticity and connectivity. The present study performed a graph-based connectome analysis to investigate the role of n-3 PUFA in emotion-related network organization in medication-free depressed adolescent bipolar offspring.

METHODS

At baseline patients (n = 53) were compared with healthy controls (n = 53), and patients were then randomized to 12-week double-blind treatment with placebo or fish oil. At baseline and endpoint, erythrocyte EPA+DHA levels were measured and fMRI scans (4 Tesla) were obtained while performing a continuous performance task with emotional and neutral distractors (CPT-END). Graph-based analysis was used to characterize topological properties of large-scale brain network organization.

RESULTS

Compared with healthy controls, patients exhibited lower erythrocyte EPA+DHA levels (p = 0.0001), lower network clustering coefficients (p = 0.029), global efficiency (p = 0.042), and lower node centrality and connectivity strengths in frontal-limbic regions (p<0.05). Compared with placebo, 12-week fish oil supplementation increased erythrocyte EPA+DHA levels (p<0.001), network clustering coefficient (p = 0.005), global (p = 0.047) and local (p = 0.023) efficiency, and node centralities mainly in temporal regions (p<0.05).

LIMITATIONS

The duration of fish oil supplementation was relatively short and the sample size was relatively small.

CONCLUSIONS

These findings provide preliminary evidence that abnormalities in emotion-related network organization observed in depressed high-risk youth may be amenable to modification through fish oil supplementation.

Preventive psychiatry: a blueprint for improving the mental health of young people

Preventive approaches have latterly gained traction for improving mental health in young people. In this paper, we first appraise the conceptual foundations of preventive psychiatry, encompassing the public health, Gordon's, US Institute of Medicine, World Health Organization, and good mental health frameworks, and neurodevelopmentally-sensitive clinical staging models. We then review the evidence supporting primary prevention of psychotic, bipolar and common mental disorders and promotion of good mental health as potential transformative strategies to reduce the incidence of these disorders in young people. Within indicated approaches, the clinical high-risk for psychosis paradigm has received the most empirical validation, while clinical high-risk states for bipolar and common mental disorders are increasingly becoming a focus of attention. Selective approaches have mostly targeted familial vulnerability and non-genetic risk exposures. Selective screening and psychological/psychoeducational interventions in vulnerable subgroups may improve anxiety/depressive symptoms, but their efficacy in reducing the incidence of psychotic/bipolar/common mental disorders is unproven. Selective physical exercise may reduce the incidence of anxiety disorders. Universal psychological/psychoeducational interventions may improve anxiety symptoms but not prevent depressive/anxiety disorders, while universal physical exercise may reduce the incidence of anxiety disorders. Universal public health approaches targeting school climate or social determinants (demographic, economic, neighbourhood, environmental, social/cultural) of mental disorders hold the greatest potential for reducing the risk profile of the population as a whole. The approach to promotion of good mental health is currently fragmented. We leverage the knowledge gained from the review to develop a blueprint for future research and practice of preventive psychiatry in young people: integrating universal and targeted frameworks; advancing multivariable, transdiagnostic, multi-endpoint epidemiological knowledge; synergically preventing common and infrequent mental disorders; preventing physical and mental health burden together; implementing stratified/personalized prognosis; establishing evidence-based preventive interventions; developing an ethical framework, improving prevention through education/training; consolidating the cost-effectiveness of preventive psychiatry; and decreasing inequalities. These goals can only be achieved through an urgent individual, societal, and global level response, which promotes a vigorous collaboration across scientific, health care, societal and governmental sectors for implementing preventive psychiatry, as much is at stake for young people with or at risk for emerging mental disorders.

Clinical characteristic of prodromal symptoms between bipolar I and II disorder among Chinese patients: a retrospective study

BACKGROUND

This study aimed to identify the clinical characteristic of prodromal symptoms in Chinese patients with bipolar disorder (BD), prior to the first affective episode. It further aimed to characterize the prodromal traits between bipolar disorder type I (BD-I) and type II (BD-II).

METHODS

120 individuals with BD-I (n = 92) and BD- II (n = 28) were recruited to the study. Semi-structured interviews were then administered to evaluate prodromal symptoms in patients, within 3 years of BD onset, by using the Bipolar Prodrome Symptom Scale-Retrospective (BPSS-R).

RESULTS

In the prodromal phase of the first depressive episode, patients with BD-II experienced more prodromal symptoms (p = 0.0028) compared to BD-I. Additionally, more frequent predictors were reported in patients with BD-II than BD-I including educational and occupational dysfunction (p = 0.0023), social isolation (p < 0.001), difficulty making decisions (p = 0.0012), oppositionality (p = 0.012), and suspiciousness/persecutory ideas (p = 0.017). There were also differences in the duration of the precursors. The duration of "weight loss or decrease in appetite" (p = 0.016) lasted longer in patients with BD-I, while "obsessions and compulsions" (p = 0.023) started earlier in patients with BD-II and occurred during the pre-depressive period. The prevalence and duration of each reported prodrome, preceding a first (hypo) manic episode, showed no difference between patients with BD-I and BD-II.

CONCLUSIONS

Specific affective, general, or psychotic symptoms occurred prior to both affective episodes. The characteristic of prodromal symptoms were key predictors for later episodes of BD including attenuated mania-like symptoms, subthreshold depressed mood, mood swings/lability, and anxiety. In the pre-depressive state, when compared to BD-II, BD-I presented with more prodromal symptoms in nonspecific dimensions, which indicated the substantial burden of BD-II. In conclusion, this study extends the understanding of the characteristics of prodromes of BD-I and BD-II.

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.

Atrophy of right inferior frontal orbital gyrus and frontoparietal functional connectivity abnormality in depressed suicide attempters

Although structural and functional brain abnormalities have been observed in depressed suicide attempters (DS), structural deficits and functional impairments together with their relationship in DS remain unclear. To clarify this issue, we aimed to examine the differences in gray matter (GM) alteration, corresponding functional connectivity (FC) change, and their relationship between DS and depressed non-suicide attempters (NDS). Sixty-eight DS, 119 NDS and 103 healthy controls were enrolled and subjected to magnetic resonance imaging scans. The patients were evaluated using the 17-item Hamilton Rating Scale for Depression (HRSD) and Nurses' Global Assessment of Suicide Risk (NGASR) scale. Both voxel-based morphometry and resting-state FC analyses were performed based on functional and structural imaging data. Compared with NDS, the DS group showed reduced GM volume in the right inferior frontal orbital gyrus (IFOG) and left caudate (CAU) but increased GM volume in the left calcarine fissure, weaker negative right IFOG-left rectus gyrus (REG) FC, and weaker positive right IFOG-left inferior parietal lobule (IPL) FC. In DS, the GM volume of the right IFOG and left CAU was negatively correlated with NGASR and HRSD scores, respectively; the right IFOG-left IPL FC was negatively correlated with cognitive factor scores; and the GM volume of the right IFOG was positively correlated with IFOG-REG and IFOG-IPL FC. Our findings indicate that structural deficit with its related functional alterations in brain circuits converged in right IFOG centralized pathways and may play a central role in suicidal behaviors in depression.

Clinical characteristics and sociodemographic features of psychotic major depression

BACKGROUND

Psychotic major depression (PMD) is a subtype of depression with a poor prognosis. Previous studies have failed to find many differences between patients with PMD and those with non-psychotic major depression (NMD) or schizophrenia (SZ). We compared sociodemographic factors (including season of conception) and clinical characteristics between patients with PMD, NMD, and schizophrenia. Our aim was to provide data to help inform clinical diagnoses and future etiology research.

METHODS

This study used data of all patients admitted to Shandong Mental Health Center from June 1, 2016 to December 31, 2017. We analyzed cases who had experienced an episode of PMD (International Classification of Diseases, Tenth Revision codes F32.3, F33.3), NMD (F32.0-2/9, F33.0-2/9), and SZ (F20-20.9). Data on sex, main discharge diagnosis, date of birth, ethnicity, family history of psychiatric diseases, marital status, age at first onset, education, allergy history, and presence of trigger events were collected. Odds ratios (OR) were calculated using logistic regression analyses. Missing values were filled using the k-nearest neighbor method.

RESULTS

PMD patients were more likely to have a family history of psychiatric diseases in their first-, second-, and third-degree relatives ([OR] 1.701, 95% confidence interval [CI] 1.019-2.804) and to have obtained a higher level of education (OR 1.451, 95% CI 1.168-1.808) compared with depression patients without psychotic features. Compared to PMD patients, schizophrenia patients had lower education (OR 0.604, 95% CI 0.492-0.741), were more often divorced (OR 3.087, 95% CI 1.168-10.096), had a younger age of onset (OR 0.934, 95% CI 0.914-0.954), less likely to have a history of allergies (OR 0.604, 95% CI 0.492-0.741), and less likely to have experienced a trigger event 1 year before first onset (OR 0.420, 95% CI 0.267-0.661). Season of conception, ethnicity, and sex did not differ significantly between PMD and NMD or schizophrenia and PMD.

CONCLUSIONS

PMD patients have more similarities with NMD patients than SZ patients in terms of demographic and clinical characteristics. The differences found between PMD and SZ, and PMD and NMD correlated with specificity of the diseases. Furthermore, allergy history should be considered in future epidemiological studies of psychotic disorders.

Circadian depression: A mood disorder phenotype

Major mood syndromes are among the most common and disabling mental disorders. However, a lack of clear delineation of their underlying pathophysiological mechanisms is a major barrier to prevention and optimised treatments. Dysfunction of the 24-h circadian system is a candidate mechanism that has genetic, behavioural, and neurobiological links to mood syndromes. Here, we outline evidence for a new clinical phenotype, which we have called 'circadian depression'. We propose that key clinical characteristics of circadian depression include disrupted 24-h sleep-wake cycles, reduced motor activity, low subjective energy, and weight gain. The illness course includes early age-of-onset, phenomena suggestive of bipolarity (defined by bidirectional associations between objective motor and subjective energy/mood states), poor response to conventional antidepressant medications, and concurrent cardiometabolic and inflammatory disturbances. Identifying this phenotype could be clinically valuable, as circadian-targeted strategies show promise for reducing depressive symptoms and stabilising illness course. Further investigation of underlying circadian disturbances in mood syndromes is needed to evaluate the clinical utility of this phenotype and guide the optimal use of circadian-targeted interventions.

Examining the relationship between gray matter volume and a continuous measure of bipolarity in unmedicated unipolar and bipolar depression

BACKGROUND

It has been argued that unipolar major depressive disorder (MDD) and bipolar disorder (BD) exist on a continuous spectrum, given their overlapping symptomatology and genetic diatheses. The Bipolarity Index (BI) is a scale that considers bipolarity as a continuous construct and was developed to assess confidence in bipolar diagnosis. Here we investigated whether BI scores correlate with gray matter volume (GMV) in a sample of unmedicated unipolar and bipolar depressed individuals.

METHODS

158 subjects (139 with MDD, 19 with BD) in a major depressive episode at time of scan were assigned BI scores. T1-weighted Magnetic Resonance Imaging scans were obtained and processed with Voxel-Based Morphometry using SPM12 (CAT12 toolbox) to assess GMV. Regression was performed at the voxel level to identify clusters of voxels whose GMV was associated with BI score, (p<0.001, family-wise error-corrected cluster-level p<0.05), with age, sex and total intracranial volume as covariates.

RESULTS

GMV was inversely correlated with BI score in four clusters located in left lateral occipital cortex, bilateral angular gyri and right frontal pole. Clusters were no longer significant after controlling for diagnosis. GMV was not correlated with BI score within the MDD cohort alone.

LIMITATIONS

Incomplete clinical data required use of a modified BI scale.

CONCLUSION

BI scores were inversely correlated with GMV in unmedicated subjects with MDD and BD, but these correlations appeared driven by categorical diagnosis. Future work will examine other imaging modalities and focus on elements of the BI scale most likely to be related to brain structure and function.

Predicting change in diagnosis from major depression to bipolar disorder after antidepressant initiation

We aimed to develop and validate classification models able to identify individuals at high risk for transition from a diagnosis of depressive disorder to one of bipolar disorder. This retrospective health records cohort study applied outpatient clinical data from psychiatry and nonpsychiatry practice networks affiliated with two large academic medical centers between March 2008 and December 2017. Participants included 67,807 individuals with a diagnosis of major depressive disorder or depressive disorder not otherwise specified and no prior diagnosis of bipolar disorder, who received at least one of the nine antidepressant medications. The main outcome was at least one diagnostic code reflective of a bipolar disorder diagnosis within 3 months of index antidepressant prescription. Logistic regression and random forests using diagnostic and procedure codes as well as sociodemographic features were used to predict this outcome, with discrimination and calibration assessed in a held-out test set and then a second academic medical center. Among 67,807 individuals who received at least one antidepressant medication, 925 (1.36%) subsequently received a diagnosis of bipolar disorder within 3 months. Models incorporating coded diagnoses and procedures yielded a mean area under the receiver operating characteristic curve of 0.76 (ranging from 0.73 to 0.80). Standard supervised machine learning methods enabled development of discriminative and transferable models to predict transition to bipolar disorder. With further validation, these scores may enable physicians to more precisely calibrate follow-up intensity for high-risk patients after antidepressant initiation.

Bipolar disorders

Bipolar disorders are a complex group of severe and chronic disorders that includes bipolar I disorder, defined by the presence of a syndromal, manic episode, and bipolar II disorder, defined by the presence of a syndromal, hypomanic episode and a major depressive episode. Bipolar disorders substantially reduce psychosocial functioning and are associated with a loss of approximately 10-20 potential years of life. The mortality gap between populations with bipolar disorders and the general population is principally a result of excess deaths from cardiovascular disease and suicide. Bipolar disorder has a high heritability (approximately 70%). Bipolar disorders share genetic risk alleles with other mental and medical disorders. Bipolar I has a closer genetic association with schizophrenia relative to bipolar II, which has a closer genetic association with major depressive disorder. Although the pathogenesis of bipolar disorders is unknown, implicated processes include disturbances in neuronal-glial plasticity, monoaminergic signalling, inflammatory homoeostasis, cellular metabolic pathways, and mitochondrial function. The high prevalence of childhood maltreatment in people with bipolar disorders and the association between childhood maltreatment and a more complex presentation of bipolar disorder (eg, one including suicidality) highlight the role of adverse environmental exposures on the presentation of bipolar disorders. Although mania defines bipolar I disorder, depressive episodes and symptoms dominate the longitudinal course of, and disproportionately account for morbidity and mortality in, bipolar disorders. Lithium is the gold standard mood-stabilising agent for the treatment of people with bipolar disorders, and has antimanic, antidepressant, and anti-suicide effects. Although antipsychotics are effective in treating mania, few antipsychotics have proven to be effective in bipolar depression. Divalproex and carbamazepine are effective in the treatment of acute mania and lamotrigine is effective at treating and preventing bipolar depression. Antidepressants are widely prescribed for bipolar disorders despite a paucity of compelling evidence for their short-term or long-term efficacy. Moreover, antidepressant prescription in bipolar disorder is associated, in many cases, with mood destabilisation, especially during maintenance treatment. Unfortunately, effective pharmacological treatments for bipolar disorders are not universally available, particularly in low-income and middle-income countries. Targeting medical and psychiatric comorbidity, integrating adjunctive psychosocial treatments, and involving caregivers have been shown to improve health outcomes for people with bipolar disorders. The aim of this Seminar, which is intended mainly for primary care physicians, is to provide an overview of diagnostic, pathogenetic, and treatment considerations in bipolar disorders. Towards the foregoing aim, we review and synthesise evidence on the epidemiology, mechanisms, screening, and treatment of bipolar disorders.

Polygenic Risk and Progression to Bipolar or Psychotic Disorders Among Individuals Diagnosed With Unipolar Depression in Early Life

OBJECTIVE

The authors investigated the associations between polygenic liability and progression to bipolar disorder or psychotic disorders among individuals diagnosed with unipolar depression in early life.

METHODS

A cohort comprising 16,949 individuals (69% female, 10-35 years old at the first depression diagnosis) from the iPSYCH Danish case-cohort study (iPSYCH2012) who were diagnosed with depression in Danish psychiatric hospitals from 1994 to 2016 was examined. Polygenic risk scores (PRSs) for major depression, bipolar disorder, and schizophrenia were generated using the most recent results from the Psychiatric Genomics Consortium. Hazard ratios for each disorder-specific PRS were estimated using Cox regressions with adjustment for the other two PRSs. Absolute risk of progression was estimated using the cumulative hazard.

RESULTS

Patients were followed for up to 21 years (median=7 years, interquartile range, 5-10 years). The absolute risks of progression to bipolar disorder and psychotic disorders were 7.3% and 13.8%, respectively. After mutual adjustment for the other PRSs, only the PRS for bipolar disorder predicted progression to bipolar disorder (adjusted hazard ratio for a one-standard-deviation increase in PRS=1.11, 95% CI=1.03, 1.21), and only the PRS for schizophrenia predicted progression to psychotic disorders (adjusted hazard ratio=1.10, 95% CI=1.04, 1.16). After adjusting for PRSs, parental history still strongly predicted progression to bipolar disorder (adjusted hazard ratio=5.02, 95% CI=3.53, 7.14) and psychotic disorders (adjusted hazard ratio=1.63, 95% CI=1.30, 2.06).

CONCLUSIONS

PRSs for bipolar disorder and schizophrenia are associated with risk for progression to bipolar disorder or psychotic disorders, respectively, among individuals diagnosed with depression; however, the effects are small compared with parental history, particularly for bipolar disorder.

Diagnostic conversion from unipolar depression to bipolar disorder, schizophrenia, or schizoaffective disorder: A nationwide prospective 15-year register study on 43 495 inpatients

OBJECTIVE

To examine temporal patterns and predictors for diagnostic conversion from unipolar depression (UD) to bipolar disorder (BD), schizophrenia, and schizoaffective disorder (SAD).

METHODS

A prospective nationwide register-based cohort (n = 43 495) of all first psychiatric hospitalizations due to UD during 1996-2011 was followed up to 15 years. We used cumulative incidence function (CIF) analyses and the Fine-Gray subdistribution model to define the cumulative incidence of the conversions and subdistribution hazard ratios (SHRs) for predictors.

RESULTS

The overall 15-year cumulative incidence of conversion was 11.1% (95% CI 10.7-11.6): 7.4% (95% CI 7.0-7.8) for BD, 2.5% (95% CI 2.3-2.7) for schizophrenia, and 1.3% (95% CI 1.1-1.4) for SAD. The highest crude incidence rate emerged during the first year. Psychotic depression predicted higher conversion risk to BD (SHR = 2.0, 95% CI 1.5-2.7), schizophrenia (SHR = 5.3, 95% CI 3.3-8.7), and SAD (SHR = 10.6, 95% CI 4.0-28.4) than mild depression. Female sex, greater overall disturbance, and comorbid personality disorder predicted conversion to BD, whereas young age and male sex to psychotic disorders.

CONCLUSIONS

Among patients with first hospitalization due to UD, approximately one in nine converts to another major psychiatric disorder during 15 years, with the highest risk occurring within the first year. Patients with psychotic depression are particularly vulnerable for conversion to other major psychiatric disorders. Conversion to psychotic disorders occurs earlier than to BD. Males are at higher risk for progression to psychotic disorders, whereas females, patients with recurrent depressive episodes, severe disturbance of overall functioning, and personality disorder are at higher risk for converting to BD.

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.