A closer look at treatment resistant depression: is it due to a bipolar diathesis?

Brain-based graph-theoretical predictive modeling to map the trajectory of anhedonia, impulsivity, and hypomania from the human functional connectome

Clinical assessments often fail to discriminate between unipolar and bipolar depression and identify individuals who will develop future (hypo)manic episodes. To address this challenge, we developed a brain-based graph-theoretical predictive model (GPM) to prospectively map symptoms of anhedonia, impulsivity, and (hypo)mania. Individuals seeking treatment for mood disorders (n = 80) underwent an fMRI scan, including (i) resting-state and (ii) a reinforcement-learning (RL) task. Symptoms were assessed at baseline as well as at 3- and 6-month follow-ups. A whole-brain functional connectome was computed for each fMRI task, and the GPM was applied for symptom prediction using cross-validation. Prediction performance was evaluated by comparing the GPM to a corresponding null model. In addition, the GPM was compared to the connectome-based predictive modeling (CPM). Cross-sectionally, the GPM predicted anhedonia from the global efficiency (a graph theory metric that quantifies information transfer across the connectome) during the RL task, and impulsivity from the centrality (a metric that captures the importance of a region) of the left anterior cingulate cortex during resting-state. At 6-month follow-up, the GPM predicted (hypo)manic symptoms from the local efficiency of the left nucleus accumbens during the RL task and anhedonia from the centrality of the left caudate during resting-state. Notably, the GPM outperformed the CPM, and GPM derived from individuals with unipolar disorders predicted anhedonia and impulsivity symptoms for individuals with bipolar disorders. Importantly, the generalizability of cross-sectional models was demonstrated in an external validation sample. Taken together, across DSM mood diagnoses, efficiency and centrality of the reward circuit predicted symptoms of anhedonia, impulsivity, and (hypo)mania, cross-sectionally and prospectively. The GPM is an innovative modeling approach that may ultimately inform clinical prediction at the individual level.

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

OBJECTIVE

Drug addiction is a chronic mental disorder that significantly impacts all aspects of an individual's life, and substance use disorder in patients with bipolar disorder. The objective of this study is to assess the frequency of substance abuse among patients with bipolar spectrum disorder.

METHOD

This cross-sectional study evaluated the frequency of bipolar spectrum disorder in patients taking methadone through various screening measures, including Mini Mental State Examination (MMSE), DSM IV criteria, Mood Disorders Questionnaire (MDQ), Goodwin and Ghaemi's criteria, and Akiskal classification for bipolar disorders.

RESULTS

Out of the total 197 participants in the study, 77 were identified as individuals engaging in poly-substance abuse. The investigation assessed the frequency of bipolar spectrum disorder based on various diagnostic criteria: 24% according to DSM-IV criteria, 29.9% using MDQ, 29.9% based on Ghaemi and Goodwin's criteria, and the highest rate at 48.2% when applying Akiskal's classification.

CONCLUSIONS

This study highlights the high frequency of bipolar disorder among individuals with substance use disorder, especially those with concomitant depression. Therefore, it is crucial to pay special attention to individuals with substance use disorder with co-existing bipolar disorder.

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

BACKGROUND

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

AIM

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

DESIGN AND SETTING

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

METHOD

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

RESULTS

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

CONCLUSION

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

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.

Brain-based graph-theoretical predictive modeling to map the trajectory of transdiagnostic symptoms of anhedonia, impulsivity, and hypomania from the human functional connectome

Clinical assessments often fail to discriminate between unipolar and bipolar depression and identify individuals who will develop future (hypo)manic episodes. To address this challenge, we developed a brain-based graph-theoretical predictive model (GPM) to prospectively map symptoms of anhedonia, impulsivity, and (hypo)mania. Individuals seeking treatment for mood disorders (n = 80) underwent an fMRI scan, including (i) resting-state and (ii) a reinforcement-learning (RL) task. Symptoms were assessed at baseline as well as at 3- and 6-month follow-ups. A whole-brain functional connectome was computed for each fMRI task, and the GPM was applied for symptom prediction using cross-validation. Prediction performance was evaluated by comparing the GPM's mean square error (MSE) to that of a corresponding null model. In addition, the GPM was compared to the connectome-based predictive modeling (CPM). Cross-sectionally, the GPM predicted anhedonia from the global efficiency (a graph theory metric that quantifies information transfer across the connectome) during the RL task, and impulsivity from the centrality (a metric that captures the importance of a region for information spread) of the left anterior cingulate cortex during resting-state. At 6-month follow-up, the GPM predicted (hypo)manic symptoms from the local efficiency of the left nucleus accumbens during the RL task and anhedonia from the centrality of the left caudate during resting-state. Notably, the GPM outperformed the CPM, and GPM derived from individuals with unipolar disorders predicted anhedonia and impulsivity symptoms for individuals with bipolar disorders, highlighting transdiagnostic generalization. Taken together, across DSM mood diagnoses, efficiency and centrality of the reward circuit predicted symptoms of anhedonia, impulsivity, and (hypo)mania, cross-sectionally and prospectively. The GPM is an innovative modeling approach that may ultimately inform clinical prediction at the individual level. ClinicalTrials.gov identifier: NCT01976975.

Approach to Diagnosis and Management of Treatment-Resistant Depression

Major depressive disorder is a chronic and recurrent illness that affects 20% of adults during their lifetime and is one of the leading causes of suicide in the United States. A systematic measurement-based care approach is the essential first step in the diagnosis and management of treatment-resistant depression (TRD) by promptly identifying individuals with depression and avoiding delays in treatment initiation. As comorbidities may be associated with poorer outcomes to commonly used antidepressants and increase risk of drug-drug interactions, their recognition and treatment is an essential component of management of TRD.

Special Populations: Treatment-Resistant Depression in Children and Adolescents

Major depressive disorder is a substantial public health challenge impacting at least 3 million adolescents annually in the United States. Depressive symptoms do not improve in approximately 30% of adolescents who receive evidence-based treatments. Treatment-resistant depression in adolescents is broadly defined as a depressive disorder that does not respond to a 2-month course of an antidepressant medication at a dose equivalent of 40 mg of fluoxetine daily or 8 to 16 sessions of a cognitive behavioral or interpersonal therapy. This article reviews historical work, recent literature on classification, current evidence-based approaches, and emerging interventional research.

Treating bipolar depression with esketamine: Safety and effectiveness data from a naturalistic multicentric study on esketamine in bipolar versus unipolar treatment-resistant depression

BACKGROUND

Bipolar depression accounts for most of the disease duration in type I and type II bipolar disorder (BD), with few treatment options, often poorly tolerated. Many individuals do not respond to first-line therapeutic options, resulting in treatment-resistant bipolar depression (B-TRD). Esketamine, the S-enantiomer of ketamine, has recently been approved for treatment-resistant depression (TRD), but no data are available on its use in B-TRD.

OBJECTIVES

To compare the efficacy of esketamine in two samples of unipolar and bipolar TRD, providing preliminary indications of its effectiveness in B-TRD. Secondary outcomes included the evaluation of the safety and tolerability of esketamine in B-TRD, focusing on the average risk of an affective switch.

METHODS

Thirty-five B-TRD subjects treated with esketamine nasal spray were enrolled and compared with 35 TRD patients. Anamnestic data and psychometric assessments (Montgomery-Asberg Depression Rating Scale/MADRS, Hamilton-depression scale/HAM-D, Hamilton-anxiety scale/HAM-A) were collected at baseline (T0), at one month (T1), and three months (T2) follow up.

RESULTS

A significant reduction in depressive symptoms was found at T1 and T2 compared to T0, with no significant differences in response or remission rates between subjects with B-TRD and TRD. Esketamine showed a greater anxiolytic action in subjects with B-TRD than in those with TRD. Improvement in depressive symptoms was not associated with treatment-emergent affective switch.

CONCLUSIONS

Our results supported the effectiveness and tolerability of esketamine in a real-world population of subjects with B-TRD. The low risk of manic switch in B-TRD patients confirmed the safety of this treatment.

The roles of neuroinflammation and glutamatergic excitotoxicity in treatment-resistant depression

ABSTRACT

Major depressive disorder affects nearly 20% of people during their lifetime. A growing body of evidence supports the theory that neuroinflammation plays a prominent role in the neurobiology of depression, which implicates glutamate and gamma aminobutyric acid as key factors in the pathophysiology of the disease process. This article reviews the pathologic pathways of glutamate excess in the central nervous system and how they may be implicated in the underlying disorder of treatment-resistant depression and targeted for treatment.

Pharmacotherapies for Treatment-Resistant Depression: How Antipsychotics Fit in the Rapidly Evolving Therapeutic Landscape

One in three adults with major depressive disorder (MDD) do not experience clinically significant improvement after multiple sequential courses of antidepressants and have treatment-resistant depression (TRD). The presence of TRD contributes to the morbidity and excess mortality associated with MDD and has been linked to significantly increased health care expenses. In the absence of a consensus definition of TRD, this report takes a broad approach by considering inadequate response to one or more courses of antidepressants and focuses on atypical antipsychotics that are approved by the U.S. Food and Drug Administration for treatment of depression (aripiprazole, brexpiprazole, cariprazine, extended-release quetiapine, and olanzapine-fluoxetine combination). While multiple acute-phase studies have demonstrated the efficacy of these medications in improving depressive symptoms, clinically meaningful improvement (i.e., remission) remains limited, with significant concerns about side effects (including weight gain, metabolic dysfunction, extrapyramidal symptoms, and tardive dyskinesia), especially with long-term use. With the rapidly evolving landscape of antidepressant treatments over the past few years, which has witnessed approval of rapid-acting antidepressants (e.g., esketamine nasal spray and dextromethorphan-bupropion combination) and several more in the late-stage pipeline (e.g., zuranolone and psilocybin), it remains to be seen whether the use of atypical antipsychotics will go the way of the older and rarely prescribed antidepressants (such as tricyclics and monoamine oxidase inhibitors). Pragmatic clinical trials are needed to compare the effectiveness of atypical antipsychotics with TRD-specific pharmacotherapies and neuromodulation treatments and to identify the optimal sequencing of these varied approaches for patients with MDD. When using atypical antipsychotics, clinicians and patients are encouraged to use a shared decision-making approach by personalizing treatment selection based on anticipated side effects, tolerability, cost, and feasibility.

The Potential of Polygenic Risk Scores to Predict Antidepressant Treatment Response in Major Depression: A Systematic Review

BACKGROUND

Understanding the genetic underpinnings of antidepressant treatment response in unipolar major depressive disorder (MDD) can be useful in identifying patients at risk for poor treatment response or treatment resistant depression. A polygenic risk score (PRS) is a useful tool to explore genetic liability of a complex trait such as antidepressant treatment response. Here, we review studies that use PRSs to examine genetic overlap between any trait and antidepressant treatment response in unipolar MDD.

METHODS

A systematic search of literature was conducted in PubMed, Embase, and PsycINFO. Our search included studies examining associations between PRSs of psychiatric as well as non-psychiatric traits and antidepressant treatment response in patients with unipolar MDD. A quality assessment of the included studies was performed.

RESULTS

In total, eleven articles were included which contained PRSs for 30 traits. Studies varied in sample size and endpoints used for antidepressant treatment response. Overall, PRSs for attention-deficit hyperactivity disorder, the personality trait openness, coronary artery disease, obesity, and stroke have been associated with antidepressant treatment response in patients with unipolar MDD.

LIMITATIONS

The endpoints used by included studies differed significantly, therefore it was not possible to perform a meta-analysis.

CONCLUSIONS

Associations between a PRS and antidepressant treatment response have been reported for a number of traits in patients with unipolar MDD. PRSs could be informative to predict antidepressant treatment response in this population, given advances in the field. Most importantly, there is a need for larger study cohorts and the use of standardized outcome measures.

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.

Bipolar Disorder Treatments and Ovarian Cancer: A Systematic Review

OBJECTIVE

We reviewed literature on drugs for bipolar disorders (BD), utilized in ovarian cancer (OC).

METHOD

We adhered to the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) guidelines in completion of this systematic review.

RESULTS

We identified 73 papers. Thirty-two studies were finally included. BD is rarely diagnosed in OC patients. Limited finding from case reports is available. Drugs used to treat BD (mainly lithium and valproic acid) have been extensively studied in add-on to chemotherapy for treatment-resistant OC cells or in animal models, with promising results in vitro but not in vivo.

CONCLUSIONS

The clinical underestimation of BD in OC has leaded to the almost complete absence of evidences for a soundly based clinical guidance in this field. There is a urgent need for a systematic multi-disciplinary approach to OC.

A functional variant in the serotonin receptor 7 gene (HTR7), rs7905446, is associated with good response to SSRIs in bipolar and unipolar depression

Predicting antidepressant response has been a clinical challenge for mood disorder. Although several genome-wide association studies have suggested a number of genetic variants to be associated with antidepressant response, the sample sizes are small and the results are difficult to replicate. Previous animal studies have shown that knockout of the serotonin receptor 7 gene (HTR7) resulted in an antidepressant-like phenotype, suggesting it was important to antidepressant action. In this report, in the first stage, we used a cost-effective pooled-sequencing strategy to sequence the entire HTR7 gene and its regulatory regions to investigate the association of common variants in HTR7 and clinical response to four selective serotonin reuptake inhibitors (SSRIs: citalopram, paroxetine, fluoxetine and sertraline) in a retrospective cohort mainly consisting of subjects with bipolar disorder (n = 359). We found 80 single-nucleotide polymorphisms (SNPs) with false discovery rate < 0.05 associated with response to paroxetine. Among the significant SNPs, rs7905446 (T/G), which is located at the promoter region, also showed nominal significance (P < 0.05) in fluoxetine group. GG/TG genotypes for rs7905446 and female gender were associated with better response to two SSRIs (paroxetine and fluoxetine). In the second stage, we replicated this association in two independent prospective samples of SSRI-treated patients with major depressive disorder: the MARS (n = 253, P = 0.0169) and GENDEP studies (n = 432, P = 0.008). The GG/TG genotypes were consistently associated with response in all three samples. Functional study of rs7905446 showed greater activity of the G allele in regulating expression of HTR7. The G allele displayed higher luciferase activity in two neuronal-related cell lines, and estrogen treatment decreased the activity of only the G allele. Electrophoretic mobility shift assay suggested that the G allele interacted with CCAAT/enhancer-binding protein beta transcription factor (TF), while the T allele did not show any interaction with any TFs. Our results provided novel pharmacogenomic evidence to support the role of HTR7 in association with antidepressant response.

Evidence of new-onset depression among persons with migraine after discontinuing antidepressants

Antidepressants have been hypothesized to cause tardive dysphoria-the delayed development of negative emotional symptoms. We assessed the risk of tardive dysphoria in a cohort of persons with migraine taking anti-migraine antidepressants with no known diagnosis of any mood or anxiety disorder. We included all outpatient encounters in a university hospital system for migraine from January 2008 through October 2018, excluding subjects with prior psychiatric diagnoses. Kaplan-Meier survival curves and multivariable Cox proportional hazards analyses were conducted. 13,048 subjects were included; 1191 took an antidepressant; 402 discontinued an antidepressant. In multivariable analyses examining the first year after exposure, antidepressant use was not significantly associated with risk of a depression, any mood disorder (including depression, mania, and other mood disorders), or anxiety. Antidepressant discontinuation was significantly associated with increased risk of depression, but not any mood disorder or anxiety. Among persons with migraine with no known psychiatric diagnosis, antidepressants did not appear to be associated with indicators of tardive dysphoria. Antidepressant discontinuation, however, was associated with increased risk of a depression diagnosis.

The identification, assessment and management of difficult-to-treat depression: An international consensus statement

BACKGROUND

Many depressed patients are not able to achieve or sustain symptom remission despite serial treatment trials - often termed "treatment resistant depression". A broader, perhaps more empathic concept of "difficult-to-treat depression" (DTD) was considered.

METHODS

A consensus group discussed the definition, clinical recognition, assessment and management implications of the DTD heuristic.

RESULTS

The group proposed that DTD be defined as "depression that continues to cause significant burden despite usual treatment efforts". All depression management should include a thorough initial assessment. When DTD is recognized, a regular reassessment that employs a multi-dimensional framework to identify addressable barriers to successful treatment (including patient-, illness- and treatment-related factors) is advised, along with specific recommendations for addressing these factors. The emphasis of treatment, in the first instance, shifts from a goal of remission to optimal symptom control, daily psychosocial functional and quality of life, based on a patient-centred approach with shared decision-making to enhance the timely consideration of all treatment options (including pharmacotherapy, psychotherapy, neurostimulation, etc.) to optimize outcomes when sustained remission is elusive.

LIMITATIONS

The recommended definition and management of DTD is based largely on expert consensus. While DTD would seem to have clinical utility, its specificity and objectivity may be insufficient to define clinical populations for regulatory trial purposes, though DTD could define populations for service provision or phase 4 trials.

CONCLUSIONS

DTD provides a clinically useful conceptualization that implies a search for and remediation of specific patient-, illness- and treatment obstacles to optimizing outcomes of relevance to patients.

Critical Predictors for the Early Detection of Conversion From Unipolar Major Depressive Disorder to Bipolar Disorder: Nationwide Population-Based Retrospective Cohort Study

BACKGROUND

Unipolar major depressive disorder (MDD) and bipolar disorder are two major mood disorders. The two disorders have different treatment strategies and prognoses. However, bipolar disorder may begin with depression and could be diagnosed as MDD in the initial stage, which may later contribute to treatment failure. Previous studies indicated that a high proportion of patients diagnosed with MDD will develop bipolar disorder over time. This kind of hidden bipolar disorder may contribute to the treatment resistance observed in patients with MDD.

OBJECTIVE

In this population-based study, our aim was to investigate the rate and risk factors of a diagnostic change from unipolar MDD to bipolar disorder during a 10-year follow-up. Furthermore, a risk stratification model was developed for MDD-to-bipolar disorder conversion.

METHODS

We conducted a retrospective cohort study involving patients who were newly diagnosed with MDD between January 1, 2000, and December 31, 2004, by using the Taiwan National Health Insurance Research Database. All patients with depression were observed until (1) diagnosis of bipolar disorder by a psychiatrist, (2) death, or (3) December 31, 2013. All patients with depression were divided into the following two groups, according to whether bipolar disorder was diagnosed during the follow-up period: converted group and nonconverted group. Six groups of variables within the first 6 months of enrollment, including personal characteristics, physical comorbidities, psychiatric comorbidities, health care usage behaviors, disorder severity, and psychotropic use, were extracted and were included in a classification and regression tree (CART) analysis to generate a risk stratification model for MDD-to-bipolar disorder conversion.

RESULTS

Our study enrolled 2820 patients with MDD. During the follow-up period, 536 patients were diagnosed with bipolar disorder (conversion rate=19.0%). The CART method identified five variables (kinds of antipsychotics used within the first 6 months of enrollment, kinds of antidepressants used within the first 6 months of enrollment, total psychiatric outpatient visits, kinds of benzodiazepines used within one visit, and use of mood stabilizers) as significant predictors of the risk of bipolar disorder conversion. This risk CART was able to stratify patients into high-, medium-, and low-risk groups with regard to bipolar disorder conversion. In the high-risk group, 61.5%-100% of patients with depression eventually developed bipolar disorder. On the other hand, in the low-risk group, only 6.4%-14.3% of patients with depression developed bipolar disorder.

CONCLUSIONS

The CART method identified five variables as significant predictors of bipolar disorder conversion. In a simple two- to four-step process, these variables permit the identification of patients with low, intermediate, or high risk of bipolar disorder conversion. The developed model can be applied to routine clinical practice for the early diagnosis of bipolar disorder.

Cortisol levels in unmedicated patients with unipolar and bipolar major depression using hair and saliva specimens

Background

Differentiating between unipolar and bipolar depression can be clinically challenging, especially at first presentation. Patterns of cortisol secretion could aid diagnostic discrimination in affective disorders although there has been little comparative research to date. In this study, we investigated acute (saliva) and chronic (hair) cortisol levels concurrently in unmedicated unipolar and bipolar disorders by using conventional diagnostic criteria and self-report measures.

Methods

Patients with unipolar and bipolar major depression and healthy controls were recruited and assessed. Cortisol levels were extracted from saliva and hair specimens. Depressive features were investigated according to diagnostic groups and with a continuous self-report measure of bipolarity using the Hypomania Checklist (HCL-33).

Results

Whilst a trend towards a reduction in the total daily salivary cortisol output—area under the curve with respect to the ground (AUCg)—was detected in depressive disorders across diagnosis, the self-administrated bipolarity index suggested that an increase in bipolarity symptoms predicted lower cortisol levels using AUCg. Chronic cortisol measurement did not discriminate unipolar from bipolar depression.

Conclusion

Results suggested that whilst a low total daily salivary cortisol output (AUCg) might be associated with depressive symptoms, a self-reported measure of bipolarity predicts lower daily cortisol output.

May antidepressant drugs worsen the conditions they are supposed to treat? The clinical foundations of the oppositional model of tolerance

In recent years there has been a considerable debate on antidepressant drugs. Continued drug treatment with antidepressant medications may stimulate processes that run counter to the initial acute effects of a drug. The oppositional model of tolerance may explain loss of treatment efficacy during maintenance treatment and the fact that some side effects tend to occur only after a certain time. These processes may also direct the illness into a treatment-unresponsive course, including manifestations of bipolar disorder or paradoxical reactions. When drug treatment ends, oppositional processes no longer encounter resistance, resulting in potential onset of new withdrawal symptoms, persistent post-withdrawal disorders, hypomania, and resistance to treatment if it is reinstituted. In all these cases, antidepressant medications may constitute a form of iatrogenic comorbidity, which increases chronicity and vulnerability to depressive episodes. Antidepressant medications are essential drugs for the treatment of major depressive episodes. They are less likely, however, to provide protection for relapse prevention. Current prescription practices need to be reformulated in light of consideration of vulnerabilities and adverse effects of treatment. The oppositional model of tolerance provides a conceptual framework for weighing all these elements in the individual case. The model does not appear to apply to all patients who undergo treatment with AD, but only to a part of them. Studying the variables that are associated with such occurrence in certain patients and not in others would be one of the most important tasks of current therapeutic research. Current diagnostic systems in psychiatry do not consider the iatrogenic components of psychopathology, and can be applied to only patients who are drug free. They are suited for a patient who no longer exists: most of the cases that are seen in psychiatric clinical practice receive psychotropic drugs and such treatment is likely to affect prognosis and treatment choices.

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

BACKGROUND AND OBJECTIVES

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

METHODOLOGY

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

RESULTS

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

CONCLUSIONS

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

Neurocognitive Predictors of Clinical Improvement in Selective Serotonin Reuptake Inhibitor-Treated Adolescents with Major Depressive Disorder

OBJECTIVES

Numerous studies have suggested cognitive deficits as consistently associated with adolescent depression. No study to date, however, has assessed neurocognitive predictors of selective serotonin reuptake inhibitor (SSRI) treatment response in adolescents with depression. This study examined neurocognitive tasks at baseline as predictors of clinical improvement with SSRI treatment (fluoxetine) at week 6 and 12 in an adolescent population.

METHODS

Adolescents with depression were recruited from a child and adolescent psychiatry outpatient clinic at a university medical center. Twenty-four adolescents (mean age 14.8 years) with Major Depressive Disorder completed tasks of the Cambridge Neuropsychological Test Automated Battery, including visual memory, executive functioning, sustained attention, and impulsivity. Depression severity, measured by the Children's Depression Rating Scale-Revised (CDRS-R), was assessed at week 6 and 12 and clinical improvement was defined as percentage (%) change in CDRS-R from baseline.

RESULTS

Clinical improvement is noted at both week 6 (mean % change in CDRS-R [M] = 46.8, standard deviation [SD] = 51.9) and week 12 (M = 87.9, SD = 57.2). Results reveal that less difficulty in sustained attention (p = 0.02), lower impulsivity (p = 0.00), and better planning (p = 0.04) at baseline were predictors of greater clinical improvement at week 6. Lower impulsivity at baseline remained significantly predictive of clinical improvement at week 12 (p = 0.01).

CONCLUSION

Neurocognitive assessments could potentially help identify a subset of depressed adolescents who may not respond to conventional SSRI treatment and who may be better candidates for alternative or augmentation treatments.

Patterns of response to antidepressants in major depressive disorder: Drug resistance or worsening of depression are associated with a bipolar diathesis

Resistance and worsening of depression in response to antidepressants (ADs) are major clinical challenges. In a large international sample of patients with major depressive disorder (MDD), we aim to explore the possible associations between different patterns of response to ADs and bipolarity. A total of 2811 individuals with a major depressive episode (MDE) were enrolled in the BRIDGE-II-MIX study. This post-hoc analysis included only 1329 (47%) patients suffering from MDD. Patients with (TRD-MDD, n = 404) and without (NTRD-MDD, n = 925) history of resistance to AD treatment and with (n = 184) and without (n = 1145) previous AD-induced irritability and mood lability (AIM) were compared using Chi-square, t-Student's test and logistic regression models. TRD-MDD patients resulted significantly associated with higher rates of AIM, psychotic features, history of suicide attempts, emotional lability and impulsivity, comorbid borderline personality disorder and polipharmacological treatment, compared to NTRD-MDD group. In comparison to NAIM-MDD patients, subjects in the AIM-MDD group showed significantly higher rates of first-degree family history for BD, previous TRD, atypical features, mixed features, psychiatric comorbidities, lifetime suicide attempts and lower age at first psychiatric symptoms. In addition, patients with AIM presented more often almost all the hypomanic symptoms evaluated in this study. Among these latter symptoms, logistic regressions showed that distractibility, impulsivity and hypersexuality were significantly associated with AIM-MDD. In conclusion, in MDD patients, a lifetime history of resistance and/or irritability/mood lability in response to ADs was associated with the presence of mixed features and a possible underlying bipolar diathesis.

Lamotrigine augmentation in treatment-resistant unipolar depression: A comprehensive meta-analysis of efficacy and safety

OBJECTIVE

Augmentation strategies are commonly applied when an individual is unresponsive to antidepressant monotherapy. Lamotrigine is currently considered at best only as second line augmentation for treatment-resistant unipolar depression while its clinical efficacy and safety profiles remain inconclusive. We intended to assess the therapeutic effects and safety profiles of lamotrigine augmentation in patients with treatment-resistant unipolar depression by conducting a meta-analysis.

METHODS

MEDLINE, Embase, EBSCO, Cochrane, Web of Science, Scopus, Wanfang and Ariniti databases were searched. Coprimary outcomes, including changes in severity of depression and response rate, were measured in this study. Secondary outcomes were defined as the safety profile of the intervention, including reported discontinuation rate and adverse events.

RESULTS

Eight double-blinded randomized controlled trials with 677 patients overall were included. Significant improvements in Hamilton Rating Scale for Depression scores and response rates were shown in lamotrigine augmentation groups compared with control groups, of which the pooled result of six Chinese studies showed positive effects of Hamilton Rating Scale for Depression improvement while the pooled result of two non-Chinese studies was statistically non-significant. Patients with more severe illness and longer duration of illness were more effectively treated with lamotrigine augmentation. The magnitude of depression improvement after lamotrigine augmentation was higher in patients treated with selective serotonin reuptake inhibitors than those treated with serotonin-norepinephrine reuptake inhibitors. Lamotrigine augmentation is well-tolerated in terms of all-cause discontinuation rate and adverse events.

CONCLUSIONS

Lamotrigine augmentation may serve as a possible choice for patients with treatment-resistant unipolar depression and further trials are warranted to clarify the optimal dosage of lamotrigine augmentation together with the treatment duration and safety over time.

Sub-threshold bipolar disorder in medication-free young subjects with major depression: Clinical characteristics and antidepressant treatment response

BACKGROUND

This study, for the first time, compared illness and antidepressant response characteristics of young subjects with major depression (MDD) at low (LRMDD) or high-risk (HRMDD) for developing bipolar disorder with characteristics of young bipolar (BPD) subjects and healthy controls (HC).

METHODS

One hundred and six young (15-30 yr), medication-free subjects MDD subjects (HRMDD, N = 51; LRMDD, N = 55) were compared with 32 BPD (Type I: 14; Type II: 18) as well as 49 HC subjects. Baseline illness characteristics and frequency of comorbid conditions were examined using Analysis of Variance and Cochran-Armitage trend test. Additionally, in MDD subjects, the effect of open-label antidepressant treatment for up to 24 months with periodic assessments was compared between HRMDD and LRMDD groups for treatment response, remission and (hypo)mania switch while controlling for attrition.

RESULTS

Significant gradation from LRMDD to HRMDD to BPD groups was found for increasing occurrence of alcohol dependence (p = 0.006), comorbid PTSD (p = 0.006), borderline personality traits (p = 0.001), and occurrence of melancholic features (p < 0.005). Antidepressant treatment response was similar between the two groups except that for the 12-month period HRMDD showed a trend for a lower response. Switch to (hypo)mania was infrequent in both groups though the HRMDD showed a higher occurrence of spikes in (hypo)mania symptoms (>25% increase in YMRS scores)(p = 0.04).

CONCLUSION

Findings of the study indicate that a substantial proportion of young MDD subjects share BPD illness characteristics. These HRMDD subjects, if treated with antidepressants, need to be monitored for development of BPD.

TRIAL REGISTRATION

NCT01811147.

Bipolar features in major depressive disorder: Results from the Iranian mental health survey (IranMHS)

BACKGROUND

Past research suggests that individuals suffering from depressive disorders with bipolar features might have different clinical outcomes resembling bipolar disorders. The objectives of this study are to determine the prevalence of bipolar features among individuals meeting the criteria for 12-month major depressive disorder (MDD) in the Iranian population and to examine the demographic and clinical characteristics associated with these features.

METHODS

Data were drawn from the Iranian Mental Health Survey (IranMHS), a representative household survey of the Iranian population aged 15-64 years. The study sample consisted of all individuals with a 12-month MDD (n = 1014) ascertained by the Composite International Diagnostic Interview (CIDI 2.1) without a lifetime history of bipolar I or II disorders. Mood Disorder Questionnaire (MDQ) was used to screen for the lifetime history of bipolar features among participants with MDD.

RESULTS

Among participants meeting the 12-month MDD criteria, 22.1% (95% CI: 19.6-24.7) had a lifetime history of bipolar features. Compared with those without these features, participants with bipolar features had higher odds of endorsing suicidal ideations and suicide attempts, comorbid anxiety and substance use disorders, severe impairment, history of psychotic symptoms, some features of atypical depression and fewer depressive symptoms. Associations with comorbid anxiety disorders [Odds Ratio (OR) = 1.43; 95% confidence interval (CI): 1.00-2.03] and history of psychotic symptoms (OR = 2.63 95% CI: 1.81-3.81) persisted in multivariable models.

LIMITATION

Relying on self-reports of lifetime bipolar symptoms which is open to recall bias, and cross-sectional study design which limits interpretation of outcome and course of MDD are two major limitations of this study.

CONCLUSION

The presence of bipolar features is associated with a distinct demographic and clinical profile in MDD. Identifying these cases would enhance the homogeneity of the depressive disorder phenotype in general population surveys. Identifying MDD patients with these features has potential clinical implications.

Cluster analysis with MOODS-SR illustrates a potential bipolar disorder risk phenotype in young adults with remitted major depressive disorder

OBJECTIVES

Delays in the diagnosis and detection of bipolar disorder can lead to adverse consequences, including improper treatment and increased suicide risk. The Mood Spectrum Self-Report Measure (MOODS-SR) was designed to capture the full spectrum of lifetime mood symptomology with factor scores for depression and mania symptom constellations. The utility of the MOODS-SR as a tool to investigate homogeneous subgroups was examined, with particular focus on a possible bipolar risk subgroup. Moreover, potential patterns of differences in MOODS-SR subtypes were probed using cognitive vulnerabilities, neuropsychological functioning, and ventral striatum connectivity.

METHODS

K-mean cluster analysis based on factor scores of MOODS-SR was used to determine homogeneous subgroupings within a healthy and remitted depressed young adult sample (N = 86). Between-group comparisons (based on cluster subgroupings) were conducted on measures of cognitive vulnerabilities, neuropsychological functioning, and ventral striatum rs-fMRI connectivity.

RESULTS

Three groups of participants were identified: one with minimal symptomology, one with moderate primarily depressive symptomology, and one with more severe manic and depressive symptomology. Differences in impulsivity, neuroticism, conscientiousness, facial perception accuracy, and rs-fMRI connectivity exist between moderate and severe groups.

CONCLUSIONS

Within a sample of people with and without depression histories, a severe subgroup was identified with potentially increased risk of developing bipolar disorder through use of the MOODS-SR. This small subgroup had higher levels of lifetime depression and mania symptoms. Additionally, differences in traits, affective processing, and connectivity exist between those with a more prototypic unipolar subgrouping and those with potential risk for developing bipolar disorder.

Predictive modeling of treatment resistant depression using data from STAR*D and an independent clinical study

Identification of risk factors of treatment resistance may be useful to guide treatment selection, avoid inefficient trial-and-error, and improve major depressive disorder (MDD) care. We extended the work in predictive modeling of treatment resistant depression (TRD) via partition of the data from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) cohort into a training and a testing dataset. We also included data from a small yet completely independent cohort RIS-INT-93 as an external test dataset. We used features from enrollment and level 1 treatment (up to week 2 response only) of STAR*D to explore the feature space comprehensively and applied machine learning methods to model TRD outcome at level 2. For TRD defined using QIDS-C₁₆ remission criteria, multiple machine learning models were internally cross-validated in the STAR*D training dataset and externally validated in both the STAR*D testing dataset and RIS-INT-93 independent dataset with an area under the receiver operating characteristic curve (AUC) of 0.70–0.78 and 0.72–0.77, respectively. The upper bound for the AUC achievable with the full set of features could be as high as 0.78 in the STAR*D testing dataset. Model developed using top 30 features identified using feature selection technique (k-means clustering followed by χ² test) achieved an AUC of 0.77 in the STAR*D testing dataset. In addition, the model developed using overlapping features between STAR*D and RIS-INT-93, achieved an AUC of > 0.70 in both the STAR*D testing and RIS-INT-93 datasets. Among all the features explored in STAR*D and RIS-INT-93 datasets, the most important feature was early or initial treatment response or symptom severity at week 2. These results indicate that prediction of TRD prior to undergoing a second round of antidepressant treatment could be feasible even in the absence of biomarker data.

Diagnosis and Treatment of Cyclothymia: The "Primacy" of Temperament

Background: Contrary to DSM-5 definition based on recurrence of low grade hypomanic and depressive symptoms, cyclothymia is better defined in a neurodevelopmental perspective as an exaggeration of cyclothymic temperament. Emotional dysregulation with extreme mood instability and reactivity is the core features of the complex symptomatology.

Method: In the present article, we critically reviewed the literature on the diagnosis and treatment of cyclothymia, focusing on the temperamental and neurodevelopmental perspectives.

Results: Current epidemiological and clinical research showed the high prevalence and the validity of cyclothymia as a distinct form of bipolarity, frequently associated with multiple comorbidities with anxiety, impulse control, substance use, and so called “personality” disorders. Many patients receive correct diagnosis and treatments after many years of illness, when the superposition of complications reduces the possibility of complete remission. A therapeutic model combining the focus on symptomatic presentations with a temperamental perspective seems to represent an effective approach for cyclothymic patients with complex clinical presentations.

Conclusion: Cyclothymic mood instability is an understudied issue despite the evidence of its clinical relevance. Unresolved issues concern its diagnostic delimitation and the possible relationships with emotional dysregulation observed in other neurodevelopmental disorders. We need to confirm the specificity of the disorder and to improve its recognition in early phase of the life, especially in youth. Early recognition means avoiding unnecessary complications and establishing specific treatments and clinical management since the beginning.

Validation and Factor Analysis of the Japanese Version of the Highs Scale in Perinatal Women

Background: The Highs scale has been developed to evaluate hypomanic symptoms in the first postpartum week. However, it has not been elucidated whether this scale is also applicable to pregnant women. To address this issue, we confirmed the factor structure, reliability, and validity of the Japanese version of the Highs scale for pregnant and postpartum women. Methods: 418 women provided effective responses to both the Highs scale and the Edinburgh Postnatal Depression Scale (EPDS) during early pregnancy (before week 25), late pregnancy (around week 36), at 5 days and at 1 month after delivery. Subjects were randomly divided into two groups, and exploratory and confirmatory factor analyses were performed for each group. Cronbach's alpha was calculated and the correlation of the Highs scale with EPDS was analyzed. The correlation between the subscales was analyzed at four time points, and the correlation of subscales between the four time points was confirmed. Results: This scale was found to have the two-factor structure with elation and agitation subscales. The two subscales had reasonable internal consistency at all time points (Cronbach's alpha range: Factor 1, 0.696-0.758; Factor 2, 0.553-0.694). The overall scale had reasonable internal consistency at all time points (Cronbach's alpha range: 0.672-0.738). Based on the correlation analysis of the two subscales and EPDS, discriminative and convergent validity were indicated at all time points, confirming the construct validity of the Highs scale. Subscale scores showed a significant correlation with EPDS at all time points (r = 0.388, 0.384, 0.498, and 0.442, p < 0.01). Conclusions: The Japanese version of the Highs scale is reliable and valid, and can be applied for evaluating the hypomanic symptoms during pregnancy and postpartum period.

The Diagnosis and Management of Bipolar I and II Disorders: Clinical Practice Update

Bipolar disorders, including bipolar I disorder (BP-I) and bipolar II disorder (BP-II), are common, potentially disabling, and, in some cases, life-threatening conditions. Bipolar disorders are characterized by alternating episodes of mania or hypomania and depression, or mixtures of manic and depressive features. Bipolar disorders present many diagnostic and therapeutic challenges for busy clinicians. Adequate management of bipolar disorders requires pharmacotherapy and psychosocial interventions targeted to the specific phases of illness. Effective treatments are available for each illness phase, but mood episode relapses and incomplete responses to treatment are common, especially for the depressive phase. Mood symptoms, psychosocial functioning, and suicide risk must, therefore, be continually reevaluated, and, when necessary, the plan of care must be adjusted during long-term treatment. Many patients will require additional treatment of comorbid psychiatric and substance use disorders and management of a variety of commonly co-occurring chronic general medical conditions.

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.

Evaluation of the 13-item Hypomania Checklist and a brief 3-item manic features questionnaire in primary care

Aims and method The mean delay for bipolar disorder diagnosis is 10 years. Identification of patients with previous hypomania is challenging, sometimes resulting in misdiagnosis. The aims of this study were: (a) to estimate the proportion of primary care patients with depression currently taking antidepressants who have undiagnosed bipolar disorder and (b) to compare a brief 3-item manic features questionnaire with the Hypomania Checklist (HCL-13). The sample comprised patients with a recorded diagnosis of depression, either on long-term antidepressant therapy or with previous multiple courses of antidepressants. Results Of 149 participants assessed, 24 (16.1%) satisfied criteria for bipolar disorder. Areas under the curve (AUC) for the 3-item questionnaire and the HCL-13 were similar (0.79 and 0.72, respectively) but positive predictive values (PPV) were low. Clinical implications Bipolar disorder may be underdiagnosed in primary care. A 3-item questionnaire could be used by general practitioners to screen for bipolar disorder in their patients with depression.

Mixed-up about how to diagnose and treat mixed features in major depressive episodes

The classical point of view-that major depressive episodes (MDEs), no matter what additional symptoms are present, should be treated first line with antidepressants-is now giving way to new a notion. The idea is that MDEs mixed with a few symptoms of mania/hypomania should be viewed very differently in terms of their natural history, clinical outcome, and treatment, and perhaps certain antipsychotics should be given as first-line treatment rather than antidepressant monotherapy.

Guidelines for the recognition and management of mixed depression

A significant minority of people presenting with a major depressive episode (MDE) experience co-occurring subsyndromal hypo/manic symptoms. As this presentation may have important prognostic and treatment implications, the DSM-5 codified a new nosological entity, the "mixed features specifier," referring to individuals meeting threshold criteria for an MDE and subthreshold symptoms of (hypo)mania or to individuals with syndromal mania and subthreshold depressive symptoms. The mixed features specifier adds to a growing list of monikers that have been put forward to describe phenotypes characterized by the admixture of depressive and hypomanic symptoms (e.g., mixed depression, depression with mixed features, or depressive mixed states [DMX]). Current treatment guidelines, regulatory approvals, as well the current evidentiary base provide insufficient decision support to practitioners who provide care to individuals presenting with an MDE with mixed features. In addition, all existing psychotropic agents evaluated in mixed patients have largely been confined to patient populations meeting the DSM-IV definition of "mixed states" wherein the co-occurrence of threshold-level mania and threshold-level MDE was required. Toward the aim of assisting clinicians providing care to adults with MDE and mixed features, we have assembled a panel of experts on mood disorders to develop these guidelines on the recognition and treatment of mixed depression, based on the few studies that have focused specifically on DMX as well as decades of cumulated clinical experience.

Bupropion Maintenance Treatment in Refractory Bipolar Depression: A Case Report

BACKGROUND

The optimal duration of antidepressant treatment in bipolar depression appears to be controversial due to a lack of quality evidence, and guideline recommendations are either vague or contradictive. This is especially true for second line treatments such as bupropion that had not been subject to rigourous long term studies in Bipolar Disorder.

CASE PRESENTATION

We report the case of a 75 year old woman who presented with treatment refractory bipolar depression. Because of insufficient response to previous mood stabilizer treatment and refractory depressive symptoms, bupropion was added to venlafaxine and lamotrigine. From there onwards, the patient improved continuously without experiencing deterioration of depression or a switch into hypomania. Our patient being on antidepressants for allmost four years experienced an obvious benefit from longterm antidepressant administration.

CONCLUSION

Noradrenergic/dopaminergic mechanisms of action may play a more prominent role in bipolar depression, and may still be underused as a therapeutic strategy in the acute phase as well as in long-term maintenance in at least a subgroup of bipolar patients. There is still a lack of evidence from RCTs, but this case report further supports antidepressant long-term continuation and the usefulness of a noradrenergic/dopaminergic antidepressant in the acute and maintenance treatment of bipolar disorder.

Use of Stimulants in Bipolar Disorder

Several international guidelines indicate stimulants, including methylphenidate (MPH), amphetamines and derivatives, modafinil, and armodafinil among the second-third-line choices for bipolar depression. Efficacy of stimulants has been also reported for the management of residual depressive symptoms such as fatigue and sleepiness and for the management of affective, cognitive, and behavioral symptoms in children and adult bipolar patients with comorbid ADHD. Few case reports show positive results with MPH in the treatment of resistant mania. Finally, MPH might be an option in some bipolar forms observed in psychiatric presentations of frontotemporal dementia and traumatic brain injury. In spite of these preliminary observations, the use of stimulants in bipolar patients is still controversial. Potential of misuse and abuse and mood destabilization with induction of (hypo)manic switches, mixed states, and rapid cycling are the concerns most frequently reported. Our aims are to summarize available literature on this topic and discuss practical management implications.

Bipolar II disorder as a risk factor for postpartum depression

OBJECTIVES

There is evidence for a bipolar diathesis in postpartum depression (PPD) and women presenting with a first PPD frequently receive a diagnosis of bipolar type II disorder (BD-II). However formal evidence for an association between BD-II and PPD has not yet been reported. In the present study we tested a potential association between BD-II and PPD.

METHODS

Parous women with a diagnosis of bipolar type I disorder (BD-I) (n=93), BD-II (n=36) or major depressive disorder (MDD) (n=444) were considered in the present study. All women were retrospectively evaluated for history of PPD (DSM-IV criteria) and other clinical and socio-demographic features.

RESULTS

Women with a history of PDD (n=139, 24%) were younger, younger at illness onset and had more family history for BD compared to women without history of PPD (n=436, 75.9%). Half of BD-II women reported PPD (50%), compared to less than one-third of BD-I and MDD women (respectively 27.5% and 21.6%) (p=0.004).

LIMITATIONS

Limitations include the retrospective assessment of PPD and no available data about the timing of postpartum episodes, illness onset or psychiatric care before or after childbirth, and the number of postpartum episodes.

CONCLUSIONS

BD-II may confer a remarkable risk for PPD, which may be even higher than that of women affected by BD-I disorder. Careful monitoring of BD-II women during the pregnancy and postpartum period, as well as assessment of bipolar features in women with a PPD without a current diagnosis of BD are recommended.

Peripartum management of bipolar disorder: what do the latest guidelines recommend?

INTRODUCTION

Many women with bipolar disorder experience significant morbidity during pregnancy and the postpartum period. The use of evidence-based and up-to-date guidelines has the potential to improve maternal and neonatal care. We review the latest clinical practice guidelines to gather recommendations for the peripartum management of bipolar disorder. Areas covered: Three electronic databases, MEDLINE/PubMed, the Cochrane Library, and the National Guidelines Clearinghouse were searched using various combinations of the following terms: bipolar disorder, pregnancy, postpartum, peripartum, puerperal, antenatal, postnatal, and guidelines. All guidelines retrieved were published, revised, or reaffirmed during the period from November 2010-June 2016. Expert commentary: To date there are no exclusive guidelines for the peripartum management of bipolar disorder. Currently available guidelines do not provide sufficient guidance for clinicians to deliver optimal care to women before, during, and after pregnancy. The guidelines reflect the paucity of available literature on the peripartum management of bipolar disorder. Further research is urgently needed to strengthen the evidence supporting the guidelines recommendations.

Blood Transcriptomic Markers in Patients with Late-Onset Major Depressive Disorder

We investigated transcriptomic markers of late-onset major depressive disorder (LOD; onset age of first depressive episode ≥ 50 years) from the genes expressed in blood cells and identified state-dependent transcriptomic markers in these patients. We assessed the genes expressed in blood cells by microarray and found that the expression levels of 3,066 probes were state-dependently changed in the blood cells of patients with LOD. To select potential candidates from those probes, we assessed the genes expressed in the blood of an animal model of depression, ovariectomized female mice exposed to chronic ultra-mild stress, by microarray and cross-matched the differentially expressed genes between the patients and the model mice. We identified 14 differentially expressed genes that were similarly changed in both patients and the model mice. By assessing statistical significance using real-time quantitative PCR (RT-qPCR), the following 4 genes were selected as candidates: cell death-inducing DFFA-like effector c (CIDEC), ribonuclease 1 (RNASE1), solute carrier family 36 member-1 (SLC36A1), and serine/threonine/tyrosine interacting-like 1 (STYXL1). The discriminating ability of these 4 candidate genes was evaluated in an independent cohort that was validated. Among them, CIDEC showed the greatest discriminant validity (sensitivity 91.3% and specificity 87.5%). Thus, these 4 biomarkers should be helpful for properly diagnosing LOD.

Treatment response in relation to subthreshold bipolarity in patients with major depressive disorder receiving antidepressant monotherapy: a post hoc data analysis (KOMDD study)

BACKGROUND

The aim of this observational study was to determine whether subthreshold bipolarity affects treatment response and remission in patients with major depressive disorder receiving antidepressant (AD) monotherapy over a 6-month follow-up period.

METHODS

Seventy-eight patients with major depressive disorder were stratified into two subgroups according to the presence of subthreshold bipolarity, identified using the Korean version of the Mood Disorder Questionnaire (K-MDQ), which classifies patients as positive for a screening of bipolarity based on the cutoff for the total K-MDQ score (ie, 7 points). They received AD monotherapy such as escitalopram, sertraline, paroxetine, or tianeptine for 6 months. The Beck Depression Inventory (BDI), Hamilton Depression Rating Scale (HAMD), Hamilton Anxiety Scale, and Beck Scale for Suicide Ideation were applied at baseline, 1 week, 3 weeks, 2 months, 3 months, and 6 months.

RESULTS

The mean HAMD, BDI, and Beck Scale for Suicide Ideation scores were higher in the bipolarity group than in the nonbipolarity group at 3 weeks. The mean BDI score was also higher in the bipolarity group than in the nonbipolarity group at 6 months. Evaluation of the ratio of improvement for each scale revealed different patterns of percentage changes between the two groups over the 6-month follow-up period. Furthermore, the response and remission rates (as assessed using BDI and HAMD scores) were higher in the nonbipolarity group than in the bipolarity group, with the exception of HAMD scores at the 3-week follow-up time point.

CONCLUSION

The findings of this study showed that depressed patients with bipolarity had a worse response to AD monotherapy than did those without bipolarity.

A retrospective study of predictive factors for effective aripiprazole augmentation of antidepressant therapy in treatment-resistant depression

BACKGROUND

Several studies have evaluated the efficacy and tolerability of aripiprazole for augmentation of antidepressant therapy for treatment-resistant depression (TRD). Here, we investigated the efficacy of aripiprazole augmentation for TRD including both major depressive disorder and bipolar disorder and the clinical predictors of treatment efficacy in a Japanese population.

METHODS

Eighty-five depressed Japanese patients who underwent aripiprazole augmentation therapy after failing to respond satisfactorily to antidepressant monotherapy were included in the study. Treatment responses were evaluated based on Clinical Global Impression Improvement scores assessed 8 weeks after initiation of aripiprazole administration. We compared demographic and diagnostic variables, psychiatric medication variables, and clinical variables between remission and nonremission groups.

RESULTS

The aripiprazole augmentation remission rate was 36.5%. Multiple logistic regression analysis indicated that aripiprazole augmentation was significantly more effective for bipolar depression than for major depressive disorder, and both absence of comorbid anxiety disorders and current episode duration >3 months were significantly associated with the efficacy of aripiprazole augmentation.

CONCLUSION

Polarity of depression, comorbidity of anxiety disorders, and current episode duration may predict the efficacy of aripiprazole augmentation for TRD including both major depressive disorder and bipolar disorder. Among them, comorbidity of anxiety disorders was significantly related to the efficacy for TRD including only major depressive disorder. Additional studies are needed to examine the association between the efficacy of aripiprazole augmentation and bipolarity, and these findings should be validated further in a prospective study.

Prevalence and sociodemographic correlates of depressive and bipolar disorders in Catalonia (Spain) using DSM-5 criteria

BACKGROUND

This study aims to determine the prevalence and sociodemographic correlates of major depression disorders (MDD) and bipolar disorders (BPDs) in a population-based sample in Catalonia (NE Spain).

METHODS

Cross sectional study nested in the Regicor Survey. We used a population-based sample of participants 45 years and older (n = 5068). The Patient Health Questionnaire-9 (PHQ-9), and the Mini International Neuropsychiatric Interview (MINI) were used to apply DSM-5 criteria to diagnose MDD and BPDs.

RESULTS

The lifetime prevalence of Single MDD was 4.2% (95% CI = 3.7-4.8), while Recurrent MDD was 24.1% (95% CI = 22.9-25.3). Other depressive disorders were detected in 0.4% (95% CI = 0.2-0.5) of the sample. The lifetime prevalence of a bipolar disorder (BPD) was set to 3.0% (95% CI = 2.5-3.4), with 0.3% (95% CI = 0.2-0.5) BPD Type I, 0.9% (95% CI = 0.6-1.2) BPD type II, and 1.8% (95% CI = 1.4-2.1) other BPD. MDD was more frequent in women, unmarried people, and those with low education. BPD rates were higher in young and unmarried people.

LIMITATIONS

Only participants of 45 years and older were included in this study. The length of the depressive episodes was not recorded. Our results may be biased by a reluctance of patients with a mental illness to participate.

CONCLUSIONS

This is the first population-based study reporting DSM-5 estimated prevalences of depressive and bipolar disorders in our country. The prevalence of mood disorders is high in our community, with almost 25% of the population presenting with at least one depressive disorder throughout life.

Problems in the boundaries of bipolar disorders

Classical concepts of bipolarity (bipolar I and bipolar II) have sometimes been extended into a broader spectrum that includes a wide variety of conditions previously diagnosed as separate forms of psychopathology. Differential diagnosis remains important, particularly in personality disorders characterized by affective instability, and in behavior disorders affecting pre-pubertal children. In the absence of biological markers or other external sources of validity, as well as lack of evidence for response to pharmacological treatment when disorders are defined more broadly, the bipolar spectrum remains an unproven hypothesis.