Bipolar disorders following initial depression: modeling predictive clinical factors

Major challenges in youth psychopathology: treatment-resistant depression. A narrative review

Major depressive disorder (MDD) represents a major health issue in adolescents and young adults, leading to high levels of disability and profoundly impacting overall functioning. The clinical presentation of MDD in this vulnerable age group may slightly differ from what can be observed in adult populations, and psychopharmacological strategies do not always lead to optimal response. Resistance to antidepressant treatment has a prevalence estimated around 40% in youths suffering from MDD and is associated with higher comorbidity rates and suicidality. Several factors, encompassing biological, environmental, and clinical features, may contribute to the emergence of treatment-resistant depression (TRD) in adolescents and young adults. Furthermore, TRD may underpin the presence of an unrecognized bipolar diathesis, increasing the overall complexity of the clinical picture and posing major differential diagnosis challenges in the clinical practice. After summarizing current evidence on epidemiological and clinical correlates of TRD in adolescents and young adults, the present review also provides an overview of possible treatment strategies, including novel fast-acting antidepressants. Despite these pharmacological agents are promising in this population, their usage is expected to rely on risk-benefit ratio and to be considered in the context of integrated models of care.

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.

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.

Explainable machine-learning algorithms to differentiate bipolar disorder from major depressive disorder using self-reported symptoms, vital signs, and blood-based markers

BACKGROUND AND OBJECTIVE

Caused by shared genetic risk factors and similar neuropsychological symptoms, bipolar disorder (BD) and major depressive disorder (MDD) are at high risk of misdiagnosis, which is associated with ineffective treatment and worsening of outcomes. We aimed to develop a machine learning (ML)-based diagnostic system, based on electronic medical records (EMR) data, to mimic the clinical reasoning of human physicians to differentiate MDD and BD (especially BD depressive episodes) patients about to be admitted to a hospital and, hence, reduce the misdiagnosis of BD as MDD on admission. In addition, we examined to what extent our ML model could be made interpretable by quantifying and visualizing the features that drive the predictions.

METHODS

By identifying 16,311 patients admitted to a hospital located in western China between 2009 and 2018 with a recorded main diagnosis of MDD or BD, we established three sub-cohorts with different combinations of features for both the MDD-BD cohort and the MDD-BD depressive episodes cohort, respectively. Four different ML algorithms (logistic regression, extreme gradient boosting (XGBoost), random forest, and support vector machine) and four train-test splits were used to train and validate diagnostic models, and explainable methods (SHAP and Break Down) were utilized to analyze the contribution of each of the features at both population-level and individual-level, including feature importance, feature interaction, and feature effect on prediction decision for a specific subject.

RESULTS

The XGBoost algorithm provided the best test performance (AUC: 0.838 (0.810-0.867), PPV: 0.810 and NPV: 0.834) for separating patients with BD from those with MDD. Core predictors included symptoms (mood-up, exciting, bad sleep, loss of interest, talking, mood-down, provoke), along with age, job, myocardial enzyme markers (creatine kinase, hydroxybutyrate dehydrogenase), diabetes-associated marker (glucose), bone function marker (alkaline phosphatase), non-enzymatic antioxidant (uric acid), markers of immune/inflammation (white blood cell count, lymphocyte count, basophil percentage, monocyte count), cardiovascular function marker (low density lipoprotein), renal marker (total protein), liver biochemistry marker (indirect bilirubin), and vital signs like pulse. For separating patients with BD depressive episodes from those with MDD, the test AUC was 0.777 (0.732-0.822), with PPV 0.576 and NPV 0.899. Additional validation in models built with self-reported symptoms removed from the feature set, showed test AUC of 0.701 (0.666-0.736) for differentiating BD and MDD, and AUC of 0.564 (0.515-0.614) for detecting patients in BD depressive episodes from MDD patients. Validation in the datasets without removing the patients with comorbidity showed an AUC of 0.826 (0.806-0.846).

CONCLUSION

The diagnostic system accurately identified patients with BD in various clinical scenarios, and differences in patterns of peripheral markers between BD and MDD could enrich our understanding of potential underlying pathophysiological mechanisms of them.

Differentiation between bipolar disorder and major depressive disorder in adolescents: from clinical to biological biomarkers

Background

Mood disorders are very common among adolescents and include mainly bipolar disorder (BD) and major depressive disorder (MDD), with overlapping depressive symptoms that pose a significant challenge to realizing a rapid and accurate differential diagnosis in clinical practice. Misdiagnosis of BD as MDD can lead to inappropriate treatment and detrimental outcomes, including a poorer ultimate clinical and functional prognosis and even an increased risk of suicide. Therefore, it is of great significance for clinical management to identify clinical symptoms or features and biological markers that can accurately distinguish BD from MDD. With the aid of bibliometric analysis, we explore, visualize, and conclude the important directions of differential diagnostic studies of BD and MDD in adolescents.

Materials and methods

A literature search was performed for studies on differential diagnostic studies of BD and MDD among adolescents in the Web of Science Core Collection database. All studies considered for this article were published between 2004 and 2023. Bibliometric analysis and visualization were performed using the VOSviewer and CiteSpace software.

Results

In total, 148 publications were retrieved. The number of publications on differential diagnostic studies of BD and MDD among adolescents has been generally increasing since 2012, with the United States being an emerging hub with a growing influence in the field. Boris Birmaher is the top author in terms of the number of publications, and the Journal of Affective Disorders is the most published journal in the field. Co-occurrence analysis of keywords showed that clinical characteristics, genetic factors, and neuroimaging are current research hotspots. Ultimately, we comprehensively sorted out the current state of research in this area and proposed possible research directions in future.

Conclusion

This is the first-ever study of bibliometric and visual analyses of differential diagnostic studies of BD and MDD in adolescents to reveal the current research status and important directions in the field. Our research and analysis results might provide some practical sources for academic scholars and clinical practice.

Celecoxib for Mood Disorders: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

The effects of celecoxib on a broad spectrum of mood disorders and on inflammatory parameters have not yet been comprehensively evaluated. The aim of this study was to systematically summarize the available knowledge on this topic. Data from both preclinical and clinical studies were analyzed, considering the efficacy and safety of celecoxib in the treatment of mood disorders, as well as the correlation of inflammatory parameters with the effect of celecoxib treatment. Forty-four studies were included. We found evidence supporting the antidepressant efficacy of celecoxib in a dose of 400 mg/day used for 6 weeks as an add-on treatment in major depression (SMD = -1.12 [95%Cl: -1.71,-0.52], p = 0.0002) and mania (SMD = -0.82 [95% CI:-1.62,-0.01], p = 0.05). The antidepressant efficacy of celecoxib in the above dosage used as sole treatment was also confirmed in depressed patients with somatic comorbidity (SMD = -1.35 [95% CI:-1.95,-0.75], p < 0.0001). We found no conclusive evidence for the effectiveness of celecoxib in bipolar depression. Celecoxib at a dose of 400 mg/d used for up to 12 weeks appeared to be a safe treatment in patients with mood disorders. Although an association between celecoxib response and inflammatory parameters has been found in preclinical studies, this has not been confirmed in clinical trials. Further studies are needed to evaluate the efficacy of celecoxib in bipolar depression, as well as long-term studies evaluating the safety and efficacy of celecoxib in recurrent mood disorders, studies involving treatment-resistant populations, and assessing the association of celecoxib treatment with inflammatory markers.

Gray matter alterations in adolescent major depressive disorder and adolescent bipolar disorder

BACKGROUND

Gray matter volume (GMV) alterations in several emotion-related brain areas are implicated in mood disorders, but findings have been inconsistent in adolescents with major depressive disorder (MDD) or bipolar disorder (BD).

METHODS

We conducted a comprehensive meta-analysis of 35 region-of-interest (ROI) and 18 whole-brain voxel-based morphometry (VBM) MRI studies in adolescent MDD and adolescent BD, and indirectly compared the results in the two groups. The effects of age, sex, and other demographic and clinical scale scores were explored using meta-regression analysis.

RESULTS

In the ROI meta-analysis, right putamen volume was decreased in adolescents with MDD, while bilateral amygdala volume was decreased in adolescents with BD compared to healthy controls (HC). In the whole-brain VBM meta-analysis, GMV was increased in right middle frontal gyrus and decreased in left caudate in adolescents with MDD compared to HC, while in adolescents with BD, GMV was increased in left superior frontal gyrus and decreased in limbic regions compared with HC. MDD vs BD comparison revealed volume alteration in the prefrontal-limbic system.

LIMITATION

Different clinical features limit the comparability of the samples, and small sample size and insufficient clinical details precluded subgroup analysis or meta-regression analyses of these variables.

CONCLUSIONS

Distinct patterns of GMV alterations in adolescent MDD and adolescent BD could help to differentiate these two populations and provide potential diagnostic biomarkers.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

A physically active lifestyle is associated with lower long-term incidence of bipolar disorder in a population-based, large-scale study

Background

Physical activity has been proposed to be beneficial for the symptomatic control of bipolar disorder, but the duration of the effects, sex-specific mechanisms, and impact of exercise intensity are not known.

Method

With an observational study design, we followed skiers and age and sex-matched non-skiers from the general population to investigate if participation in a long-distance cross-country ski race (Vasaloppet) was associated with a lower risk of getting diagnosed with bipolar disorder. Using the Swedish population and patient registries, skiers in Vasaloppet and age and sex-matched non-skiers from the general population were analyzed for any diagnosis of bipolar disorder after participation in the race. Additionally, we used finishing time of the ski race as a proxy for intensity levels to investigate if exercise intensity impacts the risk of bipolar disorder among the physically active skiers.

Results

Previous participation in a long distance ski race (n = 197,685, median age 36 years, 38% women) was associated with a lower incidence of newly diagnosed bipolar compared to an age and sex-matched general population (n = 197,684) during the up to 21 years follow-up (adjusted hazard ratio, HR = 0.48). The finishing time of the race did not significantly impact the risk of bipolar disorder in men. Among women, high performance (measured as the finishing time to complete the race, a proxy for higher exercise dose) was associated with an increased risk of bipolar disorder compared to slower skiing women (HR = 2.07).

Conclusions

Our results confirm that a physically active lifestyle is associated with a lower risk of developing bipolar disorder. Yet, to elucidate the direction of causality in this relationship requires complementary study designs. And the influence of physical performance level on the risk of bipolar disorder warrants further examinations among women.

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.

Peripheral non-enzymatic antioxidants as biomarkers for mood disorders: Evidence from a machine learning prediction model

BACKGROUND

Oxidative stress is related to the pathogenesis of mood disorders, and the level of oxidative stress may differ between bipolar disorder (BD) and major depressive disorder (MDD). This study aimed to detect the differences in non-enzymatic antioxidant levels between BD and MDD and assess the predictive values of non-enzymatic antioxidants in mood disorders by applying a machine learning model.

METHODS

Peripheral uric acid (UA), albumin (ALB), and total bilirubin (TBIL) were measured in 1,188 participants (discover cohort: 157 with BD and 544 with MDD; validation cohort: 119 with BD and 95 with MDD; 273 healthy controls). An extreme gradient boosting (XGBoost) model and a logistic regression model were used to assess the predictive effect.

RESULTS

All three indices differed between patients with mood disorders and healthy controls; in addition, the levels of UA in patients with BD were higher than those of patients with MDD. After treatment, UA levels increased in the MDD group, while they decreased in the BD group. Finally, we entered age, sex, UA, ALB, and TBIL into the XGBoost model. The area under the curve (AUC) of the XGBoost model for distinguishing between BD and MDD reached 0.849 (accuracy = 0.808, 95% CI = 0.719-0.878) and for distinguishing between BD with depression episode (BD-D) and MDD was 0.899 (accuracy = 0.891, 95% CI = 0.856-0.919). The models were validated in the validation cohort. The most important feature distinguishing between BD and MDD was UA.

CONCLUSION

Peripheral non-enzymatic antioxidants, especially the UA, might be a potential biomarker capable of distinguishing between BD and MDD.

Duration of untreated illness and bipolar disorder: time for a new definition? Results from a cross-sectional study

BACKGROUND

We primarily aimed to explore the associations between duration of untreated illness (DUI), treatment response, and functioning in a cohort of patients with bipolar disorder (BD).

METHODS

261 participants with BD were recruited. DUI was defined as months from the first affective episode to the start of a mood-stabilizer. The functioning assessment short test (FAST) scores and treatment response scores for lithium, valproate, or lamotrigine according to the Alda Scale Total Score (TS) were compared between patients with short (<24 months) or long DUI. Differences in FAST scores among good (GR; TS≥7), poor (PR; TS=2-6), or non-responders (NR; TS<2) to each mood-stabilizer were analyzed. Linear regression was computed using the FAST global score as the dependent variable.

RESULTS

DUI and FAST scores showed no statistically significant correlation. Patients with a longer DUI showed poorer response to lithium (Z=-3.196; p<0.001), but not to valproate or lamotrigine. Response to lithium (β=-1.814; p<0.001), number of hospitalizations (β=0.237; p<0.001), and illness duration (β=0.160; p=0.028) were associated with FAST total scores. GR to lithium was associated with better global functioning compared to PR or NR [H=27.631; p<0.001].

LIMITATIONS

The retrospective design could expose our data to a recall bias. Also, only few patients were on valproate or lamotrigine treatment.

CONCLUSIONS

Poor functioning in BD could be the result of multiple affective relapses, rather than a direct effect of DUI. A timely diagnosis with subsequent effective prophylactic treatment, such as lithium, may prevent poor functional outcomes in real-world patients with BD.

Individuals with bipolar disorder have a higher level of uric acid than major depressive disorder: a case-control study

At present, no well-established biomarkers were ever found to distinguish unipolar depression and bipolar disorder (BD). This study aimed to provide a clearer comparison of UA levels between BD and major depressive disorder. Peripheral UA of 119 patients with BD in acute stage (AS) and 77 in remission stage (RS), and 95 patients with UD in AS and 61 in RS were measured, so were 180 healthy controls. UA levels in BD group were higher than UD and HC groups regardless of the AS or RS, while differences in UA levels between UD group and HC group were not significant. Differences in UA levels of BD-M (bipolar mania/hypomania) were higher than BD-D (bipolar depression) subgroups, and UA levels of BD-M and BD-D subgroups were higher than UD and HC groups. The comparison of number of participants with hyperuricemia among groups confirmed the above results. There were no significant differences in UA levels of between drug-use and drug-free/naïve subgroups. UA could distinguish BD and UD significantly both in acute and remission stage. The study suggests patients with BD had a higher level of UA than UD, especially in mania episode. UA may be a potential biomarker to distinguish BD from UD.

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.

Insula activity in resting-state differentiates bipolar from unipolar depression: a systematic review and meta-analysis

Symptomatic overlap of depressive episodes in bipolar disorder (BD) and major depressive disorder (MDD) is a major diagnostic and therapeutic problem. Mania in medical history remains the only reliable distinguishing marker which is problematic given that episodes of depression compared to episodes of mania are more frequent and predominantly present at the beginning of BD. Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive, task-free, and well-tolerated method that may provide diagnostic markers acquired from spontaneous neural activity. Previous rs-fMRI studies focused on differentiating BD from MDD depression were inconsistent in their findings due to low sample power, heterogeneity of compared samples, and diversity of analytical methods. This meta-analysis investigated resting-state activity differences in BD and MDD depression using activation likelihood estimation. PubMed, Web of Science, Scopus and Google Scholar databases were searched for whole-brain rs-fMRI studies which compared MDD and BD currently depressed patients between Jan 2000 and August 2020. Ten studies were included, representing 234 BD and 296 MDD patients. The meta-analysis found increased activity in the left insula and adjacent area in MDD compared to BD. The finding suggests that the insula is involved in neural activity patterns during resting-state that can be potentially used as a biomarker differentiating both disorders.

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.

Rate of diagnostic conversion to bipolar disorder in adults with unipolar depression and psychopharmacological treatment in the republic of Korea: A nationwide register-based study

BACKGROUND

Patients with bipolar disorder (BD) and depressive episodes are usually diagnosed with major depressive disorder (MDD). It is clinically important to estimate diagnostic conversion rate from MDD to BD and identify factors characterizing MDD patients at highest risk. We investigated conversion rate from depression to BD, stratified by age and sex, and associated psychopharmacological treatment patterns.

METHODS

Data were extracted from the National Health Insurance to include 817,759 patients 18 years or older with new-onset antidepressant-treated depression between 2011 and 2015. We estimated rate of conversion from unipolar depression to BD stratified by age and sex during follow-up (357,343 person-years) and investigated the related medication patterns.

RESULTS

During follow-up (median, 155 days; range, 2-1,442 days), 19,179 patients had diagnostic conversion to BD. Conversion rate was highest for patients aged 18-29 years; it gradually decreased with age until 60-69 years. Overall conversion rate to BD was 58.48 per 1,000 person-years for males and 50.97 per 1,000 person-years for females. For patients aged 18-39 years, the rate was higher for females. Patients with conversion to BD were prescribed more antidepressants. When the diagnosis changed to BD, 51% of patients were prescribed additional antipsychotics and/or mood stabilizers.

LIMITATIONS

The limited follow-up period may have underestimated conversion rate to BD. Data were restricted to participants with pharmaceutically treated depression.

CONCLUSIONS

The rate of diagnostic conversion from depression to BD differed by sex and age and was highest for females aged 18-29 years. Diagnostic conversion was accompanied by relevant prescription changes.

Predictive factors of diagnostic conversion from major depressive disorder to bipolar disorder in young adults ages 19-34: A nationwide population study in South Korea

BACKGROUND

Predicting patients who convert to bipolar disorder is important for deciding appropriate treatment for young adults with major depressive disorder (MDD). We focused on the predictive factors of bipolar conversion in a large population of young adults.

METHODS

A nationwide, population-based electronic medical records database from the Health Insurance Review & Assessment service of South was used to investigate adjusted hazard ratio (HR) of each potential predictor of the bipolar converter group compared to the non-converter group using Cox regression analysis including age of onset, medication use, clinical features, comorbid disorders, admission, self-harm, and negative life events in childhood.

RESULTS

Among 291,721 subjects who were initially diagnosed with MDD in young adults, 12,376 subjects experienced diagnostic conversion to bipolar disorder. The cumulative incidence was 6.46% during the average 3.26 years of follow-up. Among the predictive factors during diagnosis of MDD, antipsychotic use (HR 3.12, 95%CI, 2.99-3.26, p < 0.0001) and mood stabilizers (HR 2.45, 95%CI, 2.35-2.55, p < 0.0001) showed the strongest association with diagnostic conversion to bipolar disorder. In addition, female sex, younger age of onset, mood stabilizer use, recurrent depression, psychotic symptoms, and admission to a psychiatric ward during diagnosis of MDD were also associated with diagnostic conversion to bipolar disorder.

CONCLUSION

In young adults with MDD, antipsychotic and mood stabilizer use during diagnosis of MDD were the strongest predictive factors with diagnostic conversion to bipolar disorder during follow-up. If young adults with MDD need antipsychotics or mood stabilizer, patients should be carefully evaluated for possibility of bipolar disorder.

Bipolar depression: a major unsolved challenge

Depression in bipolar disorder (BD) patients presents major clinical challenges. As the predominant psychopathology even in treated BD, depression is associated not only with excess morbidity, but also mortality from co-occurring general-medical disorders and high suicide risk. In BD, risks for medical disorders including diabetes or metabolic syndrome, and cardiovascular disorders, and associated mortality rates are several-times above those for the general population or with other psychiatric disorders. The SMR for suicide with BD reaches 20-times above general-population rates, and exceeds rates with other major psychiatric disorders. In BD, suicide is strongly associated with mixed (agitated-dysphoric) and depressive phases, time depressed, and hospitalization. Lithium may reduce suicide risk in BD; clozapine and ketamine require further testing. Treatment of bipolar depression is far less well investigated than unipolar depression, particularly for long-term prophylaxis. Short-term efficacy of antidepressants for bipolar depression remains controversial and they risk clinical worsening, especially in mixed states and with rapid-cycling. Evidence of efficacy of lithium and anticonvulsants for bipolar depression is very limited; lamotrigine has long-term benefit, but valproate and carbamazepine are inadequately tested and carry high teratogenic risks. Evidence is emerging of short-term efficacy of several modern antipsychotics (including cariprazine, lurasidone, olanzapine-fluoxetine, and quetiapine) for bipolar depression, including with mixed features, though they risk adverse metabolic and neurological effects.

Theory of mind in remitted bipolar disorder: Interpersonal accuracy in recognition of dynamic nonverbal signals

A relatively unexplored aspect in bipolar disorder (BD) is the ability to accurately judge other´s nonverbal behavior. To explore this aspect of social cognition in this population is particularly meaningful, as it may have an influence in their social and interpersonal functioning. The aim of this research was to study interpersonal accuracy (IPA) in remitted BDs, that is, the specific skills that fall under the general term Theory of Mind (ToM). Study participants included 119 remitted individuals with BD (70 BD I and 49 BD II), and they were compared with a group of 39 persons diagnosed with unipolar depression (UD) and 119 control participants. The MiniPONS was used to test the whole spectrum of nonverbal cues as facial expressions, body language and voice. Results indicated a superiority of the control group with statistically significant differences both in the performance in the MiniPONS (number of right answers) and in each of the areas evaluated by this test. BD groups, in recognition of the meaning of gestures in face, body and voice intonation, performed significantly worse than controls. ANCOVA analysis controlling the effect of age shows that control group performed significantly better compared to clinical groups, and there were no differences between UD and BD groups. The results indicate a deficit in IPA and suggest that better comprehension of deficiencies in interpersonal accuracy in BD may help to develop new training programs to improve in these patients the understanding of others, which might have a positive impact in their psychosocial functionality, and thus lead to the objective of functional rehabilitation.

Suicidal risk factors in major affective disorders

BACKGROUND

Rates and risk factors for suicidal behaviour require updating and comparisons among mood disorders.AimsTo identify factors associated with suicidal risk in major mood disorders.

METHOD

We considered risk factors before, during and after intake assessments of 3284 adults with/without suicidal acts, overall and with bipolar disorder (BD) versus major depressive disorder (MDD), using bivariate comparisons, multivariable regression modelling and receiver operating characteristic (ROC) analysis.

RESULTS

Suicidal prevalence was greater in BD versus MDD: ideation, 29.2 versus 17.3%; attempts, 18.8 versus 4.78%; suicide, 1.73 versus 0.48%; attempts/suicide ratio indicated similar lethality, 10.9 versus 9.96. Suicidal acts were associated with familial BD or suicide, being divorced/unmarried, fewer children, early abuse/trauma, unemployment, younger onset, longer illness, more dysthymic or cyclothymic temperament, attention-deficit hyperactivity disorder (ADHD), substance misuse, mixed features, hospital admission, percentage time unwell, less antidepressants and more antipsychotics and mood stabilisers. Logistic regression found five independent factors: hospital admission, more depression at intake, BD diagnosis, onset age ≤25 years and mixed features. These factors were more associated with suicidal acts in BD than MDD: percentage time depressed/ill, alcohol misuse, >4 pre-intake depressions, more dysthymic/cyclothymic temperament and prior abuse/trauma. ADHD and total years ill were similar in BD and MDD; other factors were more associated with MDD. By ROC analysis, area under the curve was 71.3%, with optimal sensitivity (76%) and specificity (55%) with any two factors.

CONCLUSIONS

Suicidal risks were high in mood disorders: ideation was highest with BD type II, attempts and suicides (especially violent) with BD type I. Several risk factors for suicidal acts differed between BD versus MDD patients.Declaration of interestNo author or immediate family member has financial relationships with commercial entities that might appear to represent potential conflicts of interest with the information presented.

Serum uric acid as a predictor of bipolarity in individuals with a major depressive episode

OBJECTIVES

There are no well-established biomarkers to predict the risk of conversion to bipolar disorder (BD) in patients with depression. Given the putative role of purinergic neurotransmission dysfunction in BD, the purpose of our study was to evaluate if higher serum uric acid (UA) levels could predict BD conversion in depressed inpatients.

METHODS

We reviewed retrospectively the records of subjects hospitalized between June 2007 and June 2010 with a diagnosis of major depressive disorder (MDD) who had undergone routine UA levels testing at admission. At an approximate 10-year follow-up we identified subjects with a subsequent diagnosis of BD. We compared UA levels between the BD-converter and non-BD converter groups, performed Receiver operating characteristic curve analysis to evaluate the prognostic accuracy of serum UA levels and calculated the clinical utility index (CUI) as a risk biomarker for conversion to BD.

RESULTS

The study included 250 subjects (55 "BD-converters" and 195 "No BD-converters"). "BD-converters" had significantly higher plasma UA levels compared to "No BD-converters" in their index hospitalization irrespective of gender (males: 403.84 ± 91.76 vs 270.81 ± 53.58 µmol/L; U = 94.5, P < 0.001 and females 302.19 ± 52.64 vs 202.69 ± 48.93 µmol/L; t = 10.75, P < 0.001). Serum UA levels showed a very good to excellent accuracy for predicting conversion to BD in inpatients with MDD (area under the curve [AUC]: 0.90; 95% CI: 0.86, 0.94) and had a good to excellent CUI- and a moderate to good CUI+ grading for discriminating BD-converter cases from non-BD converters.

CONCLUSIONS

Our study suggests that depressed patients with higher levels of serum UA are at greater risk of a subsequent manic or hypomanic episode. The purinergic system could prove a promising path for the search of biomarkers in BD.

The implications of hypersomnia in the context of major depression: Results from a large, international, observational study

According to the DSM-5, "reduction in the need for sleep" is the only sleep-related criteria for mixed features in depressive episodes. We aimed at studying the prevalence, clinical correlates and the role of hypersomnia in a sample of acutely depressed patients. Secondarily, we factors significantly increasing the odds of hypersomnia were studied. We conducted a post-hoc analysis of the BRIDGE-II-Mix study. Variables were compared between patients with hypersomnia (SLEEP+) and with insomnia (SLEEP-) with standard bivariate tests. A stepwise backward logistic regression model was performed with SLEEP+ as dependent variable. A total of 2514 subjects were dichotomized into SLEEP+ (n = 423, 16.8%) and SLEEP- (n = 2091, 83.2%). SLEEP+ had significant higher rates of obese BMI (p < 0.001), BD diagnosis (p = 0.027), severe BD (p < 0.001), lifetime suicide attempts (p < 0.001), lower age at first depression (p = 0.004) than SLEEP-. Also, SLEEP+ had significantly poorer response to antidepressants (AD) such as (hypo)manic switches, AD resistance, affective lability, or irritability (all 0<0.005). Moreover, SLEEP+ had significantly higher rates of mixed-state specifiers than SLEEP- (all 0 < 0.006). A significant contribution to hypersomnia in our regression model was driven by metabolic-related features, such as "current bulimia" (OR = 4.21) and "overweight/obese BMI (OR = 1.42)". Globally, hypersomnia is associated with poor outcome in acute depression. Hypersomnia is strongly associated with mixed features and bipolarity. Metabolic aspects could influence the expression of hypersomnia, worsening the overall clinical outcome. Along with commonly used screening tools, detection of hypersomnia has potential, costless discriminative validity in the differential diagnosis unipolar and bipolar depression.

Clinical features of differential diagnosis between unipolar and bipolar depression in a drug-free sample of young adults

INTRODUCTION

Subjects with bipolar disorder suffering of a depressive episode are frequently misdiagnosed as unipolar depression, being important studies assessing the differential diagnosis between bipolar and unipolar depression.

OBJECTIVE

To assess the sociodemographic and clinical features of drug-free young adults in a depressive episode of bipolar or unipolar disorder in order to identify factors that may differentiate these psychiatric conditions.

METHODS

This is a cross-sectional study with 241 young adults aged between 18 and 29 years who were evaluated using the Structured Clinical Interview for DSM-IV (SCID). The sample comprised patients with BD (n = 89) and major depressive disorder (n = 152), experiencing a depressive episode and not using psychoactive drugs or illicit psychoactive substances.

RESULTS

The characteristics associated with bipolar depression were being male (p < 0.001), with a family history of BD (p = 0.013), a higher frequency of childhood traumatic experiences (p = 0.001), younger age of onset of mood disorder (p = 0.004), many previous depressive episodes (p = 0.027), greater severity of depressive symptoms (p < 0.001) and day/night reversal (p = 0.013). Those with unipolar depression showed a higher frequency of biological rhythm disturbances (p < 0.001), and diurnal preference (p = 0.028).

LIMITATIONS

The sample has not included subjects with severe suicide risk, a possible important marker in differentiate unipolar from bipolar depression.

CONCLUSION

Some clinical aspects may contribute to an early differential diagnosis of both bipolar and unipolar depression even in the initial stages of the disease.

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.

Differential clinical characteristics and possible predictors of bipolarity in a sample of unipolar and bipolar inpatients

Major affective conditions including both unipolar (UD) and bipolar disorders (BD) are associated with significant disability throughout the life course. We aimed to investigate the most relevant socio-demographic/clinical differences between UD and BD subjects. Our sample included 180 inpatients, of which 82 (45.5%) participants were diagnosed with UD and 98 (54.5%) with BD. Relative to UD patients, BD individuals were more likely to report prior psychoactive medications, lifetime psychotic symptoms, nicotine abuse, a reduced ability to provide to their needs, gambling behavior, and fewer nonsuicidal self-harm episodes. Moreover, BD patients were more likely to report severe side effects related to medications, a younger age at illness onset and first hospitalization, higher illness episodes, and longer illness duration in years than UD subjects. In a multivariate logistic analysis accounting for age, gender, and socio-demographic characteristics, a significant positive contribution to bipolarity was found only for higher lifetime psychotic symptoms (β = 1.178; p ≤ .05) and number of illness episodes (β = .155; p ≤ .05). The present findings suggest that specific clinical factors may be used in order to better distinguish between UD and BD subgroups. Further studies are required to replicate these findings in larger samples.

Depressive residual symptoms are associated with illness course characteristics in a sample of outpatients with bipolar disorder

Rates of 50-70% of residual symptoms referring to subsyndromal manifestations between episodes that do not meet the required criteria for episode definition were reported in bipolar disorder (BD). However, the specific role of these symptoms on the course of BD patients is poorly understood; thus, we aimed to investigate factors associated with depressive residual symptoms. Overall, 255 currently euthymic BD outpatients on maintenance treatment, including 95 (37.2%) males and 160 (62.8%) females, were consecutively recruited at the Section of Psychiatry, Department of Neuroscience, University of Genoa (Italy) and underwent detailed structured interviews, comprehensive clinical interviews, and clinical record reviews for assessment/collection of relevant information concerning the course of illness and clinical status including cross-referral of all available information. After categorizing subjects according to the presence/absence of residual symptoms, groups were compared along clinical variables and variables associated with residual symptoms were analyzed using multivariate analyses. Subjects with residual symptoms were less likely to report substance abuse (χ²₍₂₎ = 11.937, p ≤ 0.005) and lifetime psychotic symptoms (χ²₍₂₎ = 10.577, p = 0.005), and more likely to report higher illness episodes, longer duration of illness (t₂₅₃ = 67.282, p ≤ 0.001; t₂₅₃ = 10.755, p ≤ 0.001), and longer duration of current illness episode (t₂₅₃ = 7.707, p ≤ 0.001) than those without residual symptoms. After multivariate analyses, a significant positive contribution to residual symptoms was given only by duration of current illness episode (β = 0.003; p ≤ 0.05), and lifetime psychotic symptoms (β = 1.094; p ≤ 0.005). Clinicians have to pay attention to minimize residual symptoms that may significantly impact on the course of BD and achievement of full remission between episodes.

Characteristics of depressive and bipolar disorder patients with mixed features

OBJECTIVE

To assess differences between subjects with vs. without mixed features in major affective disorders.

METHODS

In 3099 out-patient subjects with DSM-5 major depressive disorder (MDD, n = 1921) or bipolar disorders (BD, n = 1178), we compared those with (Mx) vs. without (Non-Mx) mixed features (agitated-irritable depression or dysphoric [hypo]mania) in an index episode.

RESULTS

Prevalence of Mx averaged 21.9% [CI: 20.5-23.4] overall, ranking: BD-II > BD-I > MDD, and in BD depression ≥ [hypo]mania > MDD. Mx subjects were significantly more likely than Non-Mx cases to (i) have other mixed episodes, (ii) have higher irritable and agitated ratings, (iii) have more substance abuse, (iv) switch into mixed episodes, (v) have more suicide attempts and higher suicidal ratings, (vi) change diagnosis from depression to BD, (vii) have higher hypomania scores when depressed or depression scores when [hypo]manic, (viii) be unmarried or separated with fewer children and siblings, (ix) be diagnosed more with BD than MDD, (x) be unemployed, (xi) have BD, suicide and divorce among first-degree relatives, (xii) be female, (xiii) be younger at illness-onset. Both BD and MDD Mx subjects also received antidepressants less, but antipsychotics and mood-stabilizers more, alone and in combination with antidepressants.

CONCLUSIONS

Mood disorder subjects with agitated-irritable depression or dysphoric [hypo]mania differed from those without such mixed features, including having a less favorable clinical course and repeated mixed episodes. They may represent a distinct and prevalent, syndromal clinical subtype with prognostic and therapeutic significance.

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.

Clinical predictors of conversion to bipolar disorder in a prospective longitudinal familial high-risk sample: focus on depressive features

BACKGROUND

Identifying clinical features that predict conversion to bipolar disorder (BD) in those at high familial risk (HR) would assist in identifying a more focused population for early intervention.

METHOD

In total 287 participants aged 12-30 (163 HR with a first-degree relative with BD and 124 controls (CONs)) were followed annually for a median of 5 years. We used the baseline presence of DSM-IV depressive, anxiety, behavioural and substance use disorders, as well as a constellation of specific depressive symptoms (as identified by the Probabilistic Approach to Bipolar Depression) to predict the subsequent development of hypo/manic episodes.

RESULTS

At baseline, HR participants were significantly more likely to report ⩾4 Probabilistic features (40.4%) when depressed than CONs (6.7%; p < .05). Nineteen HR subjects later developed either threshold (n = 8; 4.9%) or subthreshold (n = 11; 6.7%) hypo/mania. The presence of ⩾4 Probabilistic features was associated with a seven-fold increase in the risk of 'conversion' to threshold BD (hazard ratio = 6.9, p < .05) above and beyond the fourteen-fold increase in risk related to major depressive episodes (MDEs) per se (hazard ratio = 13.9, p < .05). Individual depressive features predicting conversion were psychomotor retardation and ⩾5 MDEs. Behavioural disorders only predicted conversion to subthreshold BD (hazard ratio = 5.23, p < .01), while anxiety and substance disorders did not predict either threshold or subthreshold hypo/mania.

CONCLUSIONS

This study suggests that specific depressive characteristics substantially increase the risk of young people at familial risk of BD going on to develop future hypo/manic episodes and may identify a more targeted HR population for the development of early intervention programs.

Number of illness episodes as predictor of residual symptoms in major depressive disorder

Notwithstanding major depressive disorder (MDD) is a recurring and chronic condition, relatively few variables have consistently been shown to predict its course. Residual depressive symptoms may be associated with disability and functional impairment but few studies evaluated clinical correlates associated with these symptoms and their impact on functioning after adjustment for potential confounders. Therefore, our study aimed to investigate factors associated with residual depressive symptoms and their impact on the course of MDD. The sample consisted of 210 consecutive MDD euthymic outpatients (67.6% females; mean age = 52.1 ± 15.5), admitted to the Section of Psychiatry, University of Genoa (Italy). Residuals depressive symptoms were significantly associated with female gender; use of short half-life benzodiazepines; longer duration of the current depressive episode; higher number of illness episodes; and higher duration of illness. Conversely, prior treatment with first-generation antipsychotics, later age of illness onset and first hospitalization were less frequently observed among patients with residual symptoms. After multivariate analyses, only duration of current illness episodes (ß = 0.003; p = <0.005) and substance abuse (ß = 0.042; p = <0.05) remained significantly associated with residual symptoms. Our findings indicate that residual depressive symptoms conferred a pernicious illness course in this specific cohort of MDD patients. Future trials mainly targeting these burdensome symptoms are warranted.

Is recurrence in major depressive disorder related to bipolarity and mixed features? Results from the BRIDGE-II-Mix study

BACKGROUND

Current classifications separate Bipolar (BD) from Major Depressive Disorder (MDD) based on polarity rather than recurrence. We aimed to determine bipolar/mixed feature frequency in a large MDD multinational sample with (High-Rec) and without (Low-Rec) >3 recurrences, comparing the two subsamples.

METHODS

We measured frequency of bipolarity/hypomanic features during current depressive episodes (MDEs) in 2347 MDD patients from the BRIDGE-II-mix database, comparing High-Rec with Low-Rec. We used Bonferroni-corrected Student's t-test for continuous, and chi-squared test, for categorical variables. Logistic regression estimated the size of the association between clinical characteristics and High-Rec MDD.

RESULTS

Compared to Low-Rec (n = 1084, 46.2%), High-Rec patients (n = 1263, 53.8%) were older, with earlier depressive onset, had more family history of BD, more atypical features, suicide attempts, hospitalisations, and treatment resistance and (hypo)manic switches when treated with antidepressants, higher comorbidity with borderline personality disorder, and more hypomanic symptoms during current MDE, resulting in higher rates of mixed depression according to both DSM-5 and research-based diagnostic (RBDC) criteria. Logistic regression showed age at first symptoms < 30 years, current MDE duration ≤ 1 month, hypomania/mania among first-degree relatives, past suicide attempts, treatment-resistance, antidepressant-induced swings, and atypical, mixed, or psychotic features during MDE to associate with High-Rec.

LIMITATIONS

Number of MDEs for defining recurrence was arbitrary; cross-sectionality did not allow assessment of conversion from MDD to BD.

CONCLUSIONS

High-Rec MDD differed from Low-Rec group for several clinical/epidemiological variables, including bipolar/mixed features. Bipolarity specifier and RBDC were more sensitive than DSM-5 criteria in detecting bipolar and mixed features in MDD.

Association of suicidal risk with ratings of affective temperaments

BACKGROUND

Ratings of particular temperament-types with the TEMPS-A autoquestionnaire have been associated with suicidal risk, and combinations of such ratings may enhance the association. However, the predictive value of scores for individual temperaments and combinations remains to be quantified.

METHOD

We evaluated associations of TEMPS-A ratings for anxious (anx), cyclothymic (cyc), dysthymic (dys), hyperthymic (hyp) and irritable (irr) temperaments, with a history of suicidal acts or reported suicidal ideation in 882 patients with bipolar (BD; n = 509), major depressive (MDD; n = 268) or anxiety (ANX; n = 105) disorders.

RESULTS

With BD, scores for cyc and irr were highest and anx lowest; with MDD, dys scored highest, hyp lowest; anx was highest with ANX and MDD. Women (n = 497) had higher anx and cyc scores than men; scores for irr and hyp decreased with age. Scores for dys, anx, and cyc, were higher, and hyp lower, with greater HDRS₂₁ depression ratings. Among 347 suicidal subjects (112 with attempts), cyc, dys, and irr scores were higher, hyp lower. Pooled score [cyc+ dys+ irr - hyp] best distinguished subjects with suicide attempts versus nonsuicidal subjects, including in Receiver-Operating Characteristic (ROC) analysis (AUC for acts = 70.1% [64.9- 75.3]). Multivariable modeling associated suicidal acts with TEMPS-A [cyc+ dys+ irr - hyp] composite-score, depression severity, BD or MDD diagnosis, and older at illness-onset.

CONCLUSIONS

Subjects with suicidal acts or ideation were best distinguished by composite TEMPS-A score [cyc+ dys+ irr - hyp]. These factors should help to identify those at suicidal risk.

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.

Topological Properties of Brain Structural Networks Represent Early Predictive Characteristics for the Occurrence of Bipolar Disorder in Patients With Major Depressive Disorder: A 7-Year Prospective Longitudinal Study

Bipolar disorder (BD) and major depressive disorder (MDD) are associated with different brain functional and structural abnormalities, but BD is hard to distinguish from MDD until the first manic or hypomanic episode. The aim of this study was to examine whether the topological properties of the brain structural network could be used to differentiate BD from MDD patients before their first manic/hypomanic episode. Diffusion tensor images were collected from 80 MDD patients and 53 healthy controls (HCs); 78 patients completed the follow-up study lasting 7 years. Among them, 12 patients were converted to BD and 64 patients remained MDD. Topological properties of the brain structural networks at baseline were compared among patients who converted to BD, patients who did not develop BD, and HCs. Patients who converted to BD displayed reduced nodal local efficiency in the left inferior frontal gyrus(IFG) compared with HCs and patients who did not convert to BD. There was no significant difference in the nodal global efficiency among the three groups. The findings suggest that the nodal local efficiency in the left IFG could serve as a potential biomarker to predict the conversion of MDD to BD before the occurrence of the first manic or hypomanic episode.

Differential failure to deactivate the default mode network in unipolar and bipolar depression

OBJECTIVES

Neuroimaging studies have revealed evidence of brain functional abnormalities in bipolar depressive disorder (BDD) and major depressive disorder (MDD). However, few studies to date have compared these two mood disorders directly.

METHODS

Matched groups of 26 BDD type I patients, 26 MDD patients and 26 healthy controls underwent functional magnetic resonance imaging (fMRI) while performing the n-back working memory task. A whole-brain ANOVA was used to compare the three groups and clusters of significant difference were examined further using region-of-interest (ROI) analysis.

RESULTS

The whole-brain ANOVA revealed a single cluster of significant difference in the medial frontal cortex. The BDD and MDD patients both showed failure to deactivate in this area compared to the controls. The BDD patients showed significantly greater failure of deactivation than the MDD patients, which was not accounted for by differences in severity or chronicity of illness between them.

CONCLUSIONS

Failure of deactivation, considered to reflect default mode network dysfunction, is present to a greater extent in bipolar than unipolar depression. The study of this network may be useful in the search for brain markers that distinguish the two disorders.

Is a delay in the diagnosis of bipolar disorder inevitable?

OBJECTIVE

A diagnosis of bipolar disorder (BD) is often preceded by an initial diagnosis of depression, creating a delay in the accurate diagnosis and treatment of BD. Although previous research has focused on predictors of a diagnosis change from depression to BD, the research on this delay in diagnosis is sparse. Therefore, the present study examined the time taken to make a BD diagnosis following an initial diagnosis of major depressive disorder in order to further understand the patient characteristics and psychological factors that may explain this delay.

METHOD

A total of 382 patients underwent a clinical evaluation by a psychiatrist and completed a series of questionnaires.

RESULTS

Ninety patients were initially diagnosed with depression with a later diagnosis of BD, with a mean delay in diagnostic conversion of 8.74 years. These patients who were later diagnosed with BD were, on average, diagnosed with depression at a younger age, experienced more manic symptoms, and had a more open personality style and better coping skills. Cox regressions showed that depressed patients with diagnoses that eventually converted to BD had been diagnosed with depression earlier and that this was related to a longer delay to conversion and greater likelihood of dysfunctional attitudes.

CONCLUSION

The findings from the present study suggested that an earlier diagnosis of depression is related to experiencing a longer delay in conversion to BD. The clinical implications of this are briefly discussed, with a view to reducing the seemingly inevitable delay in the diagnosis of BD.

Rate and predictors of conversion from unipolar to bipolar disorder: A systematic review and meta-analysis

OBJECTIVES

For the first time to present a systematic review and meta-analysis of the conversion rate and predictors of conversion from unipolar disorder to bipolar disorder.

METHODS

A systematic literature search up to October 2016 was performed. For the meta-analysis, we only included studies that used survival analysis to estimate the conversion rate.

RESULTS

A total of 31 studies were identified, among which 11 used survival analyses, including two register-based studies. The yearly rate of conversion to bipolar disorder decreased with time from 3.9% in the first year after study entry with a diagnosis of unipolar disorder to 3.1% in years 1-2, 1.0% in years 2-5 and 0.8% in years 5-10. A total of eight risk factors were evaluated comprising gender, age at onset of unipolar disorder, number of depressive episodes, treatment resistance to antidepressants, family history of bipolar disorder, the prevalence of psychotic depression, the prevalence of chronic depression, and severity of depression. It was not possible to identify risk factors that were consistently or mainly confirmed to predict conversion across studies.

CONCLUSIONS

The conversion rate from unipolar to bipolar disorder decreases with time. It was not possible to identify predictors of conversion that were consistently or mainly confirmed across studies, which may be due to variations in methodology across studies.

The Andalusian Bipolar Family (ABiF) Study: Protocol and sample description

INTRODUCTION

Here, we present the first description of the Andalusian Bipolar Family (ABiF) Study. This longitudinal investigation of families from Andalusia, Spain commenced in 1997 with the aim of elucidating the molecular genetic causes of bipolar affective disorder. The cohort has since contributed to a number of key genetic findings, as reported in international journals. However, insight into the genetic underpinnings of the disorder in these families remains limited.

METHOD

In the initial 1997-2003 study phase, 100 multiplex bipolar disorder and other mood disorder families were recruited. The ongoing second phase of the project commenced in 2013, and involves follow-up of a subgroup of the originally recruited families. The aim of the follow-up investigation is to generate: i) longitudinal clinical data; ii) results from detailed neuropsychological assessments; and iii) a more extensive collection of biomaterials for future molecular biological studies.

RESULTS

The ABiF Study will thus generate a valuable resource for future investigations into the aetiology of bipolar affective disorder; in particular the causes of high disease loading within multiply affected families.

DISCUSSION

We discuss the value of this approach in terms of new technologies for the identification of high-penetrance genetic factors. These new technologies include exome and whole genome sequencing, and the use of induced pluripotent stem cells or model organisms to determine functional consequences.

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

OBJECTIVE

Some people with major depressive disorder (MDD) may be at a pre-onset stage for bipolar disorder (BD), where early identification or prevention efforts may be feasible. We aimed to identify rates and characteristics predictive of transition to BD in prospective follow-up studies of people with MDD.

METHODS

Using a systematic search strategy, we identified studies with a diagnostic ascertainment of MDD and BD of an adequate standard, and where the minimum length of follow-up was 6 months. We examined the incidence and point prevalence of BD and the pooled odds ratios (OR) for baseline predictors.

RESULTS

From 5554 unique publications, 56 were included. Nearly a quarter of adults (22.5%) and adolescents with MDD followed up for a mean length of 12-18 years developed BD, with the greatest risk of transition being in the first 5 years. The meta-analysis identified that transition from MDD to BD was predicted by family history of BD (OR = 2.89, 95% CI: 2.01-4.14, N = 7), earlier age of onset of depression (g = -0.33, SE = 0.05, N = 6) and presence of psychotic symptoms (OR = 4.76, 95% CI: 1.79-12.66, N = 5).

CONCLUSIONS

Participants with the identified risk factors merit closer observation and may benefit from prevention efforts, especially if outcomes broader than BD are considered.

Diagnostic Conversion to Bipolar Disorder in Unipolar Depressed Patients Participating in Trials on Antidepressants

Objective

In unipolar depressed patients participating in trials on antidepressants, we investigated if illness characteristics at baseline could predict conversion to bipolar disorder.

Method

A long-term register-based follow-up study of 290 unipolar depressed patients with a mean age of 50.8 years (SD = 11.9) participating in three randomized trials on antidepressants conducted in the period 1985–1994. The independent effects of explanatory variables were examined by applying Cox regression analyses.

Results

The overall risk of conversion was 20.7%, with a mean follow-up time of 15.2 years per patient. The risk of conversion was associated with an increasing number of previous depressive episodes at baseline, [HR 1.18, 95% CI (1.10–1.26)]. No association with gender, age, age at first depressive episode, duration of baseline episode, subtype of depression or any of the investigated HAM-D subscales included was found.

Limitations

The patients were followed-up through the Danish Psychiatric Central Research Register, which resulted in inherent limitations such as possible misclassification of outcome.

Conclusion

In a sample of middle-aged hospitalized unipolar depressed patients participating in trials on antidepressants, the risk of conversion was associated with the number of previous depressive episodes. Therefore, this study emphasizes that unipolar depressed patients experiencing a relatively high number of recurrences should be followed more closely, or at least be informed about the possible increased risk of conversion.

Rates and predictors of remission, recurrence and conversion to bipolar disorder after the first lifetime episode of depression--a prospective 5-year follow-up study

BACKGROUND

In depression, non-remission, recurrence of depressive episodes after remission and conversion to bipolar disorder are crucial determinants of poor outcome. The present study aimed to determine the cumulative incidences and clinical predictors of these long-term outcomes after the first lifetime episode of depression.

METHOD

A total of 301 in- or out-patients aged 18-70 years with a validated diagnosis of a single depressive episode were assessed from 2005 to 2007. At 5 years of follow-up, 262 patients were reassessed by means of the life chart method and diagnostic interviews from 2011 to 2013. Cumulative incidences and the influence of clinical variables on the rates of remission, recurrence and conversion to bipolar disorder, respectively, were estimated by survival analysis techniques.

RESULTS

Within 5 years, 83.3% obtained remission, 31.5% experienced recurrence of depression and 8.6% converted to bipolar disorder (6.3% within the first 2 years). Non-remission increased with younger age, co-morbid anxiety and suicidal ideations. Recurrence increased with severity and treatment resistance of the first depression, and conversion to bipolar disorder with treatment resistance, a family history of affective disorder and co-morbid alcohol or drug abuse.

CONCLUSIONS

The identified clinical characteristics of the first lifetime episode of depression should guide patients and clinicians for long-term individualized tailored treatment.

Comparative analysis of affective temperament in patients with difficult-to-treat and easy-to-treat major depression and bipolar disorder: Possible application in clinical settings

BACKGROUND

Difficult-to-treat major depressive disorder (MDD-DT), which involves antidepressant refractoriness or antidepressant-related adverse psychiatric effects, is bipolar in nature; therefore, it may share common temperamental features with bipolar disorder. To examine this hypothesis, affective temperament was compared between MDD-DT, easy-to-treat major depressive disorder (MDD-ET), and bipolar disorder.

METHODS

Affective temperament was measured in 320 patients (69, 56, and 195 with MDD-ET, MDD-DT, and bipolar disorder, respectively) using the self-rated questionnaire version of the Temperament Evaluation of Memphis, Pisa, Paris, and San Diego (TEMPS-A), with between-group differences examined using multiple logistic regression analysis controlling for confounders. Optimal cut-off points for TEMPS-A scores to discriminate between diagnostic groups were determined using receiver-operating characteristic analysis.

RESULTS

Of the five temperamental domains, the mode for cyclothymic temperament score was highest, followed by those of bipolar disorder, MDD-DT, and MDD-ET. The cyclothymic temperament score discriminated significantly between bipolar disorder and MDD-DT (odds ratio [OR]: 1.12, 95% confidence interval [CI]: 1.04-1.20, p=0.0022), MDD-DT and MDD-ET (OR: 1.15, 95% CI: 1.01-1.31, p=0.0334), and bipolar and major depressive disorders (OR: 1.17, 95% CI: 1.07-1.28, p=0.0003). Optimal cut-off points for the cyclothymic temperament scores to discriminate between bipolar disorder and major depressive disorder and MDD-DT and MDD-ET were 9 (sensitivity: 64.6%, specificity: 76.0%) and 6 (66.1%, 62.3%), respectively.

CONCLUSIONS

MDD-DT has a quantitatively stronger bipolar temperamental feature, cyclothymic temperament, relative to that of MDD-ET. Cut-off points determined in this study could be clinically helpful. Because of our study design, longitudinal changes in temperamental scores during treatment cannot be fully excluded.

Symptom characteristics of depressive episodes prior to the onset of mania or hypomania

OBJECTIVE

Depressive episodes are typically the initial presentation of bipolar disorder. The evidence as to whether depressive episodes occurring in persons who later convert to bipolar disorder are symptomatically distinct from episodes of unipolar depression remains controversial. As there are crucial differences in the therapeutic management, symptom profiles indicating subsequent bipolar conversion may aid in appropriate treatment.

METHOD

A representative community sample of originally N = 3021 adolescents and young adults aged 14-24 years at baseline was assessed up to four times over 10 years. Assessment of symptoms was conducted by clinically trained interviewers using the standardized M-CIDI. Symptom profiles of depressive episodes were compared via logistic regression between subjects that subsequently developed (hypo-)manic episodes (n = 35) or remained unipolar depressive (n = 659).

RESULTS

Initial depression amongst prospective converters was characterized by significantly increased suicidality (odds ratio, OR = 2.31), higher rates of feelings of worthlessness and excessive guilt (OR = 2.52), complete loss of pleasure (OR = 2.53) and diurnal variation (OR = 4.30). No differences were found for hyperphagia, hypersomnia and psychomotor alterations.

CONCLUSION

Findings suggest that the symptom profile of initial depressive episodes may be useful in the identification of subjects with an elevated risk for the subsequent conversion to bipolar disorder.

The role of comorbidities in duration of untreated illness for bipolar spectrum disorders

BACKGROUND

Growing interest has been given to the construct of Duration of untreated illness (DUI) on the outcome of bipolar disorder (BD), due to its potentially modifiable nature. The aim of this study was to identify possible clinical correlates of DUI in a sample of BD patients.

METHOD

119 BD spectrum patients included. DUI rate was calculated and dichotomized into short DUI and long DUI subgroups, cut-off 24 months. These subgroups were compared for socio-demographic and clinical variables. Significant results were included into direct logistic regressions to assess their impact on the likelihood of presenting with long DUI.

RESULTS

Mean DUI±SD was 75.6±98.3 months. Short DUI subgroup comprised 56 (47.1%), long DUI 60 (52.9%) patients. Age at onset of BD was lower in the long DUI subgroup (p=0.021), illness duration longer (p=0.011). Long DUI subgroup showed significantly more comorbidity with Axis I (p=0.002) and personality disorders (p=0.017), less interepisodic recovery (p<0.001) and less Manic Predominant Polarity (p=0.009). Direct logistic regression as a full model was significant, correctly classifying 76.7% of cases. A unique statistically significant contribution was made by: Manic Predominant Polarity, Personality Disorder Comorbidity, and Total Changes in Medications.

LIMITATIONS

Partial retrospective data, cross sectional study.

CONCLUSIONS

DUI was longer than 24 months in half of the sample. Psychotic /Manic onset contributed to a quick diagnostic classification. Personality disorders in depressed patients could delay a correct diagnosis of BD, factors associated with an increased likelihood of BD must be considered. More research on personality disorder comorbidities is needed.

Mortality and secular trend in the incidence of bipolar disorder

BACKGROUND

The world-wide interest in bipolar disorder is illustrated by an exponential increase in publications on the disorder registered in Pubmed since 1990. This inspired an investigation of the epidemiology of bipolar disorder.

METHODS

This was a register-based cohort study. All first-ever diagnoses of bipolar disorder (International Classification of Diseases-10: F31) were identified in the nationwide Danish Psychiatric Central Research Register between 1995 and 2012. Causes of death were obtained from The Danish Register of Causes of Death. Age- and gender standardized incidence rates, standardized mortality ratio (SMR) and Kaplan-Meier survival estimates were calculated.

RESULTS

We identified 15,334 incident cases of bipolar disorder. The incidence rate increased from 18.5/100,000 person-years (PY) in 1995 to 28.4/100,000 PY in 2012. The mean age at time of diagnosis decreased significantly from 54.5 years in 1995 to 42.4 years in 2012 (p<0.001). The mean time from first affective diagnosis to diagnosis of bipolar disorder was 7.9 years (SD 9.1). The SMR was 1.7 (95%-CI 1.2-2.1). Causes of death were mainly natural; 9% died from suicide.

LIMITATIONS

Only patients in psychiatric care were included. The outpatient registry opened in 1995. Patients treated solely in outpatient units are not recorded previously. Systematic studies validating all the clinical diagnoses of the registry do not exist.

CONCLUSIONS

The incidence of bipolar disorder has increased in the last 10 years. The SMR was significantly increased. Half of the patients were known to have another affective disorder. This should be considered in future decisions regarding the healthcare organization.

Distinguishing bipolar from unipolar depression: the importance of clinical symptoms and illness features

BACKGROUND

Distinguishing bipolar disorder (BP) from major depressive disorder (MDD) has important relevance for prognosis and treatment. Prior studies have identified clinical features that differ between these two diseases but have been limited by heterogeneity and lack of replication. We sought to identify depression-related features that distinguish BP from MDD in large samples with replication.

METHOD

Using a large, opportunistically ascertained collection of subjects with BP and MDD we selected 34 depression-related clinical features to test across the diagnostic categories in an initial discovery dataset consisting of 1228 subjects (386 BPI, 158 BPII and 684 MDD). Features significantly associated with BP were tested in an independent sample of 1000 BPI cases and 1000 MDD cases for classifying ability in receiver operating characteristic (ROC) analysis.

RESULTS

Seven clinical features showed significant association with BPI compared with MDD: delusions, psychomotor retardation, incapacitation, greater number of mixed symptoms, greater number of episodes, shorter episode length, and a history of experiencing a high after depression treatment. ROC analyses of a model including these seven factors showed significant evidence for discrimination between BPI and MDD in an independent dataset (area under the curve = 0.83). Only two features (number of mixed symptoms, and feeling high after an antidepressant) showed an association with BPII versus MDD.

CONCLUSIONS

Our study suggests that clinical features distinguishing depression in BPI versus MDD have important classification potential for clinical practice, and should also be incorporated as 'baseline' features in the evaluation of novel diagnostic biomarkers.