Comparison of depressive episodes in bipolar disorder and in major depressive disorder within bipolar disorder pedigrees

Optimal risk and diagnosis assessment strategies in perinatal depression: A machine learning approach from the life-ON study cohort

This study aimed to assess the concordance of various psychometric scales in detecting Perinatal Depression (PND) risk and diagnosis. A cohort of 432 women was assessed at 10-15th and 23-25th gestational weeks, 33-40 days and 180-195 days after delivery using the Edinburgh Postnatal Depression Scale (EPDS), Visual Analogue Scale (VAS), Hamilton Depression Rating Scale (HDRS), Montgomery-Åsberg Depression Rating Scale (MADRS), and Mini International Neuropsychiatric Interview (MINI). Spearman's rank correlation coefficient was used to assess agreement across instruments, and multivariable classification models were developed to predict the values of a binary scale using the other scales. Moderate agreement was shown between the EPDS and VAS and between the HDRS and MADRS throughout the perinatal period. However, agreement between the EPDS and HDRS decreased postpartum. A well-performing model for the estimation of current depression risk (EPDS > 9) was obtained with the VAS and MADRS, and a less robust one for the estimation of current major depressive episode (MDE) diagnosis (MINI) with the VAS and HDRS. When the EPDS is not feasible, the VAS may be used for rapid and comprehensive postpartum screening with reliability. However, a thorough structured interview or clinical examination remains necessary to diagnose a MDE.

Identifying genetic differences between bipolar disorder and major depression through multiple GWAS

Background

Accurate diagnosis of bipolar disorder (BD) is difficult in clinical practice, with an average delay between symptom onset and diagnosis of about 7 years. A key reason is that the first manic episode is often preceded by a depressive one, making it difficult to distinguish BD from unipolar major depressive disorder (MDD).

Aims

Here, we use genome-wide association analyses (GWAS) to identify differential genetic factors and to develop predictors based on polygenic risk scores that may aid early differential diagnosis.

Methods

Based on individual genotypes from case-control cohorts of BD and MDD shared through the Psychiatric Genomics Consortium, we compile case-case-control cohorts, applying a careful merging and quality control procedure. In a resulting cohort of 51,149 individuals (15,532 BD cases, 12,920 MDD cases and 22,697 controls), we perform a variety of GWAS and polygenic risk scores (PRS) analyses.

Results

While our GWAS is not well-powered to identify genome-wide significant loci, we find significant SNP-heritability and demonstrate the ability of the resulting PRS to distinguish BD from MDD, including BD cases with depressive onset. We replicate our PRS findings, but not signals of individual loci in an independent Danish cohort (iPSYCH 2015 case-cohort study, N=25,966). We observe strong genetic correlation between our case-case GWAS and that of case-control BD.

Conclusions

We find that MDD and BD, including BD with a depressive onset, are genetically distinct. Further, our findings support the hypothesis that Controls - MDD - BD primarily lie on a continuum of genetic risk. Future studies with larger and richer samples will likely yield a better understanding of these findings and enable the development of better genetic predictors distinguishing BD and, importantly, BD with depressive onset from MDD.

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.

EEG alpha band characteristics in patients with a depressive episode within recurrent and bipolar depression

BACKGROUND

The search for biological markers for the differential diagnosis of recurrent depression and bipolar depression is an important undertaking in modern psychiatry. Electroencephalography (EEG) is one of the promising tools in addressing this challenge.

AIM

To identify differences in the quantitative characteristics of the electroencephalographic alpha band activity in patients with a depressive episode within the framework of recurrent depression and bipolar depression.

METHODS

Two groups of patients (all women) were formed: one consisting of subjects with recurrent depressive disorder and one with subjects experiencing a current mild/moderate episode (30 patients), and subjects with bipolar affective disorder or a current episode of mild or moderate depression (30 patients). The groups did not receive pharmacotherapy and did not differ in their socio-demographic parameters or total score on the Hamilton depression scale. A baseline electroencephalogram was recorded, and the quantitative characteristics of the alpha band activity were analyzed, including the absolute spectral power, interhemispheric coherence, and EEG activation.

RESULTS

The patients with recurrent depressive disorder demonstrated statistically significantly lower values of the average absolute spectral power of the alpha band (z=2.481; p=0.042), as well as less alpha attenuation from eyes closed to eyes open (z=2.573; p=0.035), as compared with the patients with bipolar affective disorder.

CONCLUSION

The presented quantitative characteristics of alpha activity are confirmation that patients with affective disorders of different origins also display distinctive electrophysiological features which can become promising biomarkers and could help separate bipolar depression from the recurrent type.

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.

Bipolar disorder in the International Classification of Diseases-Eleventh version: A review of the changes, their basis, and usefulness

The World Health Organization’s 11^th revision of the International Classification of Diseases (ICD-11) including the chapter on mental disorders has come into effect this year. This review focuses on the “Bipolar or Related Disorders” section of the ICD-11 draft. It describes the benchmarks for the new version, particularly the foremost principle of clinical utility. The alterations made to the diagnosis of bipolar disorder (BD) are evaluated on their scientific basis and clinical utility. The change in the diagnostic requirements for manic and hypomanic episodes has been much debated. Whether the current criteria have achieved an optimum balance between sensitivity and specificity is still not clear. The ICD-11 definition of depressive episodes is substantially different, but the lack of empirical support for the changes has meant that the reliability and utility of bipolar depression are relatively low. Unlike the Diagnostic and Statistical Manual of Mental Disorders, 5^th edition (DSM-5), the ICD-11 has retained the category of mixed episodes. Although the concept of mixed episodes in the ICD-11 is not perfect, it appears to be more inclusive than the DSM-5 approach. Additionally, there are some uncertainties about the guidelines for the subtypes of BD and cyclothymic disorder. The initial results on the reliability and clinical utility of BD are promising, but the newly created diagnostic categories also appear to have some limitations. Although further improvement and research are needed, the focus should now be on facing the challenges of implementation, dissemination, and education and training in the use of these guidelines.

Mindfulness based cognitive therapy (MBCT) reduces depression-related self-referential processing in patients with bipolar disorder: an exploratory task-based study

Negative self-referential processing has fruitfully been studied in unipolar depressed patients, but remarkably less in patients with bipolar disorder (BD). This exploratory study examines the relation between task-based self-referential processing and depressive symptoms in BD and their possible importance to the working mechanism of mindfulness-based cognitive therapy (MBCT) for BD. The study population consisted of a subsample of patients with BD (n = 49) participating in an RCT of MBCT for BD, who were assigned to MBCT + TAU (n = 23) or treatment as usual (TAU) (n = 26). Patients performed the self-referential encoding task (SRET), which measures (1) positive and (2) negative attributions to oneself as well as (3) negative self-referential memory bias, before and after MBCT + TAU or TAU. At baseline, all three SRET measures were significantly related to depressive symptoms in patients with BD. Moreover, repeated measures analyses of variance revealed that negative self-referential memory bias diminished over time in the MBCT + TAU group, compared with the TAU group. Given the preliminary nature of our findings, future research should explore the possibly mediating role of reducing negative self-referential memory bias in preventing and treating depressive symptoms in BD through MBCT.

Clinical research diagnostic criteria for bipolar illness (CRDC-BP): rationale and validity

BACKGROUND

In the 1970 s, scientific research on psychiatric nosology was summarized in Research Diagnostic Criteria (RDC), based solely on empirical data, an important source for the third revision of the official nomenclature of the American Psychiatric Association in 1980, the Diagnostic and Statistical Manual, Third Edition (DSM-III). The intervening years, especially with the fourth edition in 1994, saw a shift to a more overtly "pragmatic" approach to diagnostic definitions, which were constructed for many purposes, with research evidence being only one consideration. The latest editions have been criticized as failing to be useful for research. Biological and clinical research rests on the validity of diagnostic definitions that are supported by firm empirical foundations, but critics note that DSM criteria have failed to prioritize research data in favor of "pragmatic" considerations.

RESULTS

Based on prior work of the International Society for Bipolar Diagnostic Guidelines Task Force, we propose here Clinical Research Diagnostic Criteria for Bipolar Illness (CRDC-BP) for use in research studies, with the hope that these criteria may lead to further refinement of diagnostic definitions for other major mental illnesses in the future. New proposals are provided for mixed states, mood temperaments, and duration of episodes.

CONCLUSIONS

A new CRDC could provide guidance toward an empirically-based, scientific psychiatric nosology, and provide an alternative clinical diagnostic approach to the DSM system.

Psychotic symptoms in bipolar disorder and their impact on the illness: A systematic review

BACKGROUND

Lifetime psychotic symptoms are present in over half of the patients with bipolar disorder (BD) and can have an adverse effect on its course, outcome, and treatment. However, despite a considerable amount of research, the impact of psychotic symptoms on BD remains unclear, and there are very few systematic reviews on the subject.

AIM

To examine the extent of psychotic symptoms in BD and their impact on several aspects of the illness.

METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines were followed. An electronic literature search of six English-language databases and a manual search was undertaken to identify published articles on psychotic symptoms in BD from January 1940 to December 2021. Combinations of the relevant Medical Subject Headings terms were used to search for these studies. Articles were selected after a screening phase, followed by a review of the full texts of the articles. Assessment of the methodological quality of the studies and the risk of bias was conducted using standard tools.

RESULTS

This systematic review included 339 studies of patients with BD. Lifetime psychosis was found in more than a half to two-thirds of the patients, while current psychosis was found in a little less than half of them. Delusions were more common than hallucinations in all phases of BD. About a third of the patients reported first-rank symptoms or mood-incongruent psychotic symptoms, particularly during manic episodes. Psychotic symptoms were more frequent in bipolar type I compared to bipolar type II disorder and in mania or mixed episodes compared to bipolar depression. Although psychotic symptoms were not more severe in BD, the severity of the illness in psychotic BD was consistently greater. Psychosis was usually associated with poor insight and a higher frequency of agitation, anxiety, and hostility but not with psychiatric comorbidity. Psychosis was consistently linked with increased rates and the duration of hospitalizations, switching among patients with depression, and poorer outcomes with mood-incongruent symptoms. In contrast, psychosis was less likely to be accompanied by a rapid-cycling course, longer illness duration, and heightened suicidal risk. There was no significant impact of psychosis on the other parameters of course and outcome.

CONCLUSION

Though psychotic symptoms are very common in BD, they are not always associated with an adverse impact on BD and its course and outcome.

Ketamine and other glutamate receptor modulators for depression in adults with bipolar disorder

BACKGROUND

Glutamergic system dysfunction has been implicated in the pathophysiology of bipolar depression. This is an update of the 2015 Cochrane Review for the use of glutamate receptor modulators for depression in bipolar disorder.

OBJECTIVES

1. To assess the effects of ketamine and other glutamate receptor modulators in alleviating the acute symptoms of depression in people with bipolar disorder. 2. To review the acceptability of ketamine and other glutamate receptor modulators in people with bipolar disorder who are experiencing depressive symptoms.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL), Ovid MEDLINE, Embase and PsycINFO all years to July 2020.  We did not apply any restrictions to date, language or publication status.

SELECTION CRITERIA

RCTs comparing ketamine or other glutamate receptor modulators with other active psychotropic drugs or saline placebo in adults with bipolar depression.

DATA COLLECTION AND ANALYSIS

Two review authors independently selected studies for inclusion, assessed trial quality and extracted data. Primary outcomes were response rate and adverse events. Secondary outcomes included remission rate, depression severity change scores, suicidality, cognition, quality of life, and dropout rate. The GRADE framework was used to assess the certainty of the evidence.

MAIN RESULTS

Ten studies (647 participants) were included in this review (an additional five studies compared to the 2015 review). There were no additional studies added to the comparisons identified in the 2015 Cochrane review on ketamine, memantine and cytidine versus placebo. However, three new comparisons were found: ketamine versus midazolam, N-acetylcysteine versus placebo, and riluzole versus placebo. The glutamate receptor modulators studied were ketamine (three trials), memantine (two), cytidine (one), N-acetylcysteine (three), and riluzole (one). Eight of these studies were placebo-controlled and two-armed. In seven trials the glutamate receptor modulators had been used as add-on drugs to mood stabilisers. Only one trial compared ketamine with an active comparator, midazolam. The treatment period ranged from a single intravenous administration (all ketamine studies), to repeated administration for riluzole, memantine, cytidine, and N-acetylcysteine (with a follow-up of eight weeks, 8 to 12 weeks, 12 weeks, and 16 to 20 weeks, respectively). Six of the studies included sites in the USA, one in Taiwan, one in Denmark, one in Australia, and in one study the location was unclear. All participants had a primary diagnosis of bipolar disorder and were experiencing an acute bipolar depressive episode, diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders fourth edition (IV) or fourth edition text revision (IV-TR). Among all glutamate receptor modulators included in this review, only ketamine appeared to be more efficacious than placebo 24 hours after infusion for response rate (odds ratio (OR) 11.61, 95% confidence interval (CI) 1.25 to 107.74; P = 0.03; participants = 33; studies = 2; I² = 0%, low-certainty evidence). Ketamine seemed to be more effective in reducing depression rating scale scores (MD -11.81, 95% CI -20.01 to -3.61; P = 0.005; participants = 32; studies = 2; I² = 0%, very low-certainty evidence). There was no evidence of ketamine's efficacy in producing remission over placebo at 24 hours (OR 5.16, 95% CI 0.51 to 52.30; P = 0.72; participants = 33; studies = 2; I² = 0%, very low-certainty evidence). Evidence on response, remission or depression rating scale scores between ketamine and midazolam was uncertain at 24 hours due to very low-certainty evidence (OR 3.20, 95% CI 0.23 to 45.19). In the one trial assessing ketamine and midazolam, there were no dropouts due to adverse effects or for any reason (very low-certainty evidence). Placebo may have been more effective than N-acetylcysteine in reducing depression rating scale scores at three months, although this was based on very low-certainty evidence (MD 1.28, 95% CI 0.24 to 2.31; participants = 58; studies = 2). Very uncertain evidence found no difference in response at three months (OR 0.82, 95% CI 0.32 to 2.14; participants = 69; studies = 2; very low-certainty evidence). No data were available for remission or acceptability. Extremely limited data were available for riluzole vs placebo, finding only very-low certainty evidence of no difference in dropout rates (OR 2.00, 95% CI 0.31 to 12.84; P = 0.46; participants = 19; studies = 1; I² = 0%).

AUTHORS' CONCLUSIONS

It is difficult to draw reliable conclusions from this review due to the certainty of the evidence being low to very low, and the relatively small amount of data usable for analysis in bipolar disorder, which is considerably less than the information available for unipolar depression. Nevertheless, we found uncertain evidence in favour of a single intravenous dose of ketamine (as add-on therapy to mood stabilisers) over placebo in terms of response rate up to 24 hours, however ketamine did not show any better efficacy for remission in bipolar depression. Even though ketamine has the potential to have a rapid and transient antidepressant effect, the efficacy of a single intravenous dose may be limited. We did not find conclusive evidence on adverse events with ketamine, and there was insufficient evidence to draw meaningful conclusions for the remaining glutamate receptor modulators. However, ketamine's psychotomimetic effects (such as delusions or delirium) may have compromised study blinding in some studies, and so we cannot rule out the potential bias introduced by inadequate blinding procedures. To draw more robust conclusions, further methodologically sound RCTs (with adequate blinding) are needed to explore different modes of administration of ketamine, and to study different methods of sustaining antidepressant response, such as repeated administrations.

Discriminating bipolar depression from major depressive disorder with polygenic risk scores

BACKGROUND

Although accurate differentiation between bipolar disorder (BD) and unipolar major depressive disorder (MDD) has important prognostic and therapeutic implications, the distinction is often challenging based on clinical grounds alone. In this study, we tested whether psychiatric polygenic risk scores (PRSs) improve clinically based classification models of BD v. MDD diagnosis.

METHODS

Our sample included 843 BD and 930 MDD subjects similarly genotyped and phenotyped using the same standardized interview. We performed multivariate modeling and receiver operating characteristic analysis, testing the incremental effect of PRSs on a baseline model with clinical symptoms and features known to associate with BD compared with MDD status.

RESULTS

We found a strong association between a BD diagnosis and PRSs drawn from BD (R2 = 3.5%, p = 4.94 × 10-12) and schizophrenia (R2 = 3.2%, p = 5.71 × 10-11) genome-wide association meta-analyses. Individuals with top decile BD PRS had a significantly increased risk for BD v. MDD compared with those in the lowest decile (odds ratio 3.39, confidence interval 2.19-5.25). PRSs discriminated BD v. MDD to a degree comparable with many individual symptoms and clinical features previously shown to associate with BD. When compared with the full composite model with all symptoms and clinical features PRSs provided modestly improved discriminatory ability (ΔC = 0.011, p = 6.48 × 10-4).

CONCLUSIONS

Our study demonstrates that psychiatric PRSs provide modest independent discrimination between BD and MDD cases, suggesting that PRSs could ultimately have utility in subjects at the extremes of the distribution and/or subjects for whom clinical symptoms are poorly measured or yet to manifest.

Cluster Analysis of Care Pathways in Adults with Major Depressive Disorder with Acute Suicidal Ideation or Behavior in the USA

BACKGROUND AND OBJECTIVE

Suicidal ideation or behavior are core symptoms of major depressive disorder (MDD). This study aimed to understand heterogeneity among patients with MDD and acute suicidal ideation or behavior.

METHODS

Adults with a diagnosis of MDD on the same day or 6 months before a claim for suicidal ideation or behavior (index date) were identified in the MarketScan^® Databases (10/01/2014-04/30/2019). A mathematical algorithm was used to cluster patients on characteristics of care measured pre-index. Patient care pathways were described by cluster during the 12-month pre-index period and up to 12 months post-index.

RESULTS

Among 38,876 patients with MDD and acute suicidal ideation or behavior, three clusters were identified. Across clusters, pre-index exposure to mental healthcare was revealed as a key differentiator: Cluster 1 (N = 16,025) was least exposed, Cluster 2 (N = 5640) moderately exposed, and Cluster 3 (N = 17,211) most exposed. Patients whose MDD diagnosis was first observed during their index event comprised 86.0% and 72.8% of Clusters 1 and 2, respectively; in Cluster 3, all patients had an MDD diagnosis pre-index. Within 30 days post-index, in Clusters 1, 2, and 3, respectively, 79.3%, 85.2%, and 88.2% used mental health services, including outpatient visits for MDD. Within 12 months post-index, 61.5%, 91.5%, and 84.6% had one or more antidepressant claim, respectively. Per-patient index event costs averaged $5614, $6645, and $5853, respectively.

CONCLUSIONS

Patients with MDD and acute suicidal ideation or behavior least exposed to the healthcare system pre-index similarly received the least care post-index. An opportunity exists to optimize treatment and follow-up with mental health services.

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.

The association between self-reported physical activity and objective measures of physical activity in participants with newly diagnosed bipolar disorder, unaffected relatives, and healthy individuals

BACKGROUND

The association between the International Physical Activity Questionnaire Short Form (IPAQ-SF) and objective measures of physical activity has never been evaluated in participants with newly diagnosed bipolar disorder (BD). Our aim was to compare IPAQ-SF to objective measures in participants with newly diagnosed BD, their unaffected first-degree relatives (UR), and healthy control individuals (HC) in groups combined and stratified by group.

MATERIALS AND METHODS

Physical activity measurements were collected on 20 participants with newly diagnosed BD, 20 of their UR, and 20 HC using individually calibrated combined acceleration and heart rate sensing (Actiheart) for seven days. IPAQ-SF was self-completed at baseline. Correlation between measurements from the two methods was examined with Spearman rank correlation coefficient and agreement levels examined with modified Bland-Altman plots.

RESULTS

Physical activity energy expenditure (PAEE) from IPAQ-SF was weakly but significantly positively correlated with physical activity estimates measured using acceleration and heart rate in groups combined (Actiheart PAEE) (ρ= 0.301, p = 0.02). Correlations for each group were positive, but only in UR were it statistically significant (BD: p = 0.18, UR: p = 0.007, HC: p = 0.84). Self-reported PAEE and moderate-intensity were markedly underestimated [PAEE in all participants combined: 62.7 (Actiheart) vs. 24.3 kJ/day/kg (IPAQ-SF), p < 0.001], while vigorous-intensity was overestimated. Bland-Altman plots indicated proportional bias.

CONCLUSION

These results suggest that the use of the IPAQ-SF to monitor levels of physical activity in participants with newly diagnosed BD, in a psychiatric clinical setting, should be used with caution and consideration.

EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks:A review

Mental disorders represent critical public health challenges as they are leading contributors to the global burden of disease and intensely influence social and financial welfare of individuals. The present comprehensive review concentrate on the two mental disorders: Major depressive Disorder (MDD) and Bipolar Disorder (BD) with noteworthy publications during the last ten years. There is a big need nowadays for phenotypic characterization of psychiatric disorders with biomarkers. Electroencephalography (EEG) signals could offer a rich signature for MDD and BD and then they could improve understanding of pathophysiological mechanisms underling these mental disorders. In this review, we focus on the literature works adopting neural networks fed by EEG signals. Among those studies using EEG and neural networks, we have discussed a variety of EEG based protocols, biomarkers and public datasets for depression and bipolar disorder detection. We conclude with a discussion and valuable recommendations that will help to improve the reliability of developed models and for more accurate and more deterministic computational intelligence based systems in psychiatry. This review will prove to be a structured and valuable initial point for the researchers working on depression and bipolar disorders recognition by using EEG signals.

Daily mobility patterns in patients with bipolar disorder and healthy individuals

BACKGROUND

Alterations in energy and activity in bipolar disorder (BD) differ between affective states and compared with healthy control individuals (HC). Measurements of activity could discriminate between BD and HC and in the monitoring of affective states within BD. The aims were to investigate differences in 1) passively collected smartphone-based location data (location data) between BD and HC, and 2) location data in BD between affective states.

METHODS

Daily, patients with BD and HC completed smartphone-based self-assessments of mood for up to nine months. Location data reflecting mobility patterns, routine and location entropy was collected daily. A total of 46 patients with BD and 31 HC providing daily data was included.

RESULTS

A total of 4,859 observations of smartphone-based self-assessments of mood and mobility patterns were available from patients with BD and 1,747 observations from HC. Patients with BD had lower location entropy compared with HC (B= -0.14, 95% CI= -0.24; -0.034, p=0.009). Patients with BD during a depressive state were less mobile compared with a euthymic state. Patients with BD during an affective state had lower location entropy compared with a euthymic state (p<0.0001). The AUC of combined location data was rather high in classifying patients with BD compared with HC (AUC: 0.83).

LIMITATIONS

Individuals willing to use smartphones for daily self-monitoring may represent a more motivated group.

CONCLUSION

Alterations in location data reflecting mobility patterns may be a promising measure of illness and illness activity in patients with BD and may be used to monitor the effects of treatments.

EEG Frontal Asymmetry and Theta Power in Unipolar and Bipolar Depression

BACKGROUND

Distinguishing between unipolar and bipolar depression is of high clinical relevance. However, there is sparse research directly comparing these groups in terms of EEG activity.

METHOD

We investigated 87 participants' left and right EEG frontal alpha-1, alpha-2, and theta activity related to happy and sad face stimuli in unipolar (UD, n=33) and bipolar (BD, n=22) depressed participants, and controls without depression (HC, n=32).

RESULTS

Post-hoc analysis of an observed hemisphere x group interaction (p< .037) showed significant differences in alpha-1 asymmetry only for the comparison of UD and HC (p< .006). Further analysis of a significant emotion x group interaction (p= .001) revealed a differential impact of stimulus valence on theta power between the groups (p< .001). The valence dependent theta power of the BD differed from that of the UD (p< .0002) and the HC (p< .004). Alpha-1 asymmetry classified HC and both depressed groups with an accuracy of .69. Valence-related theta classified BD from UD with an accuracy of .83. Leave-one-out cross validation resulted in slightly reduced accuracy.

LIMITATIONS

Important limitations were the small sample size and that subjects were not medication-free.

CONCLUSIONS

Our results demonstrate the value of simple, task related EEG activity for differentiating not only healthy individuals from those with depression, but also individuals with unipolar depression from those with bipolar depression.

Differences in psychomotor activity and heart rate variability in patients with newly diagnosed bipolar disorder, unaffected relatives, and healthy individuals

BACKGROUND

Heart rate variability (HRV) and psychomotor activity have been found reduced in bipolar disorder (BD) but has never been investigated in newly diagnosed BD and unaffected relatives. The present study aimed to compare HRV and psychomotor activity between newly diagnosed patients with BD, their unaffected first-degree relatives (UR), and healthy control individuals (HC).

METHODS

20 newly diagnosed patients with BD, 20 of their UR, and 20 age- and sex-matched HC were included. Measurements of HRV for five minutes and heart rate and acceleration for seven days were conducted. Activity energy expenditure (AEE) was derived from the latter. Linear mixed effect regression models were conducted to compare the three groups.

RESULTS

HRV did not differ in any measure between the three groups of participants. Similarly, AEE (kJ/day/kg) did not differ between the three groups in neither daily means (BD: 63.6, UR: 64.1, HC: 62.1) nor when divided into quarter-daily intervals.

LIMITATIONS

The relatively small size of the study may affect the validity of the results.

CONCLUSION

Patients with newly diagnosed BD and UR do not present with decreased HRV or AEE. These results contrast prior findings from BD patients with more advanced stages of the disorder, suggesting that these outcomes progress with illness duration.

Prevalence of suicide attempt in individuals with major depressive disorder: a meta-analysis of observational surveys

BACKGROUND

Suicide attempt (SA), which is one of the strongest predictors of completed suicide, is common in major depressive disorder (MDD) but its prevalence across epidemiological studies has been mixed. The aim of this comprehensive meta-analysis was to examine the pooled prevalence of SA in individuals with MDD.

METHODS

A systematic literature search was conducted in PubMed, Embase, PsycINFO, Web of Science and Cochrane Library from their commencement date until 27 December 2017. Original studies containing data on prevalence of SA in individuals with MDD were analyzed.

RESULTS

In all, 65 studies with a total of 27 340 individuals with MDD were included. Using the random effects model, the pooled lifetime prevalence of SA was 31% [95% confidence interval (CI) 27-34%], 1-year prevalence was 8% (95% CI 3-14%) and 1-month prevalence was 24% (95% CI 15-34%). Subgroup analyses revealed that the lifetime prevalence of SA was significantly associated with the patient setting, study region and income level, while the 1-month prevalence of SA was associated with only the patient setting.

CONCLUSION

This meta-analysis confirmed that SA was common in individuals with MDD across the world. Careful screening and appropriate interventions should be implemented for SA in the MDD population.

Similarly in depression, nuances of gut microbiota: Evidences from a shotgun metagenomics sequencing study on major depressive disorder versus bipolar disorder with current major depressive episode patients

BACKGROUND

To probe the differences of gut microbiota among major depressive disorder (MDD), bipolar disorder with current major depressive episode (BPD) and health participants.

METHODS

Thirty one MDD patients, thirty BPD patients, and thirty healthy controls (HCs) were recruited. All the faecal samples were analyzed by shotgun metagenomics sequencing. Except for routine analyses of alpha diversity, we specially designed a new indicator, the G_m coefficient, to evaluate the inequality of relative abundances of microbiota for each participant.

RESULTS

The G_m coefficients are significant decreased in both MDD and BPD groups. The relative abundances of increased phyla Firmicutes and Actinobacteria and decreased Bacteroidetes were significantly in the MDD and BPD groups. At genus level, four of top five enriched genera (Bacteroides, Clostridium, Bifidobacterium, Oscillibacter and Streptococcus) were found increased significantly in the MDD and BPD groups compared with HCs. The genera Escherichia and Klebsiella showed significant changes in abundances only between the BPD and HC groups. At the species level, compared with BPD patients, MDD patients had a higher abundance of Prevotellaceae including Prevotella denticola F0289, Prevotella intermedia 17, Prevotella ruminicola, and Prevotella intermedia. Furthermore, the abundance of Fusobacteriaceae, Escherichia blattae DSM 4481 and Klebsiella oxytoca were significantly increased, whereas the Bifidobacterium longum subsp. infantis ATCC 15697 = JCM 1222 was significantly reduced in BPD group compared with MDD group.

CONCLUSIONS

Our study suggested that gut microbiota may be involved in the pathogenesis of both MDD and BPD patients, and the nuances of bacteria may have the potentiality of being the biomarkers of MDD and BPD.

Comparison of suicide attempts in individuals with major depressive disorder with and without history of subthreshold hypomania: A nationwide community sample of Korean adults✰,✰✰

BACKGROUND

Subthreshold hypomania is defined as a distinct period of elevated, expansive or irritable mood lasting for at least four days, but insufficient to fulfill the criteria of hypomania. This study aimed to investigate the association between suicidality and subthreshold hypomania in subjects with and without major depressive disorder (MDD).

METHODS

Face-to-face interviews were completed for 12,526 adults, randomly selected through a one-person-per-household method, using the Korean version of the Composite International Diagnostic Interview (K-CIDI) and a questionnaire relative to lifetime suicide attempts (LSA).

RESULTS

Of the 12,526 participants, 11,701 did not have MDD, and 825 were diagnosed with MDD. The MDD with subthreshold hypomania group (n = 72) revealed significantly higher rates of LSA and post-traumatic stress disorder (PTSD) than those without (n = 753). Compared to the no MDD without subthreshold hypomania group (n = 11,571), the no MDD with subthreshold hypomania group (n = 130) showed a significantly higher prevalence of suicidality and comorbid conditions. In multivariate logistic regression analyses of depressive symptoms, subthreshold hypomania was significantly associated with morning worsening of mood. The MDD with subthreshold hypomania group was significantly associated with LSA (AOR=16.82, 95% CI 9.81-28.83, p< 0.001), compared to the no MDD group without subthreshold hypomania. Compared to the MDD without subthreshold hypomania group, the MDD with subthreshold hypomania group revealed a significant association with LSA (AOR=2.08, 95% CI 1.20-3.62, p< 0.001).

CONCLUSIONS

A history of subthreshold hypomania doubled the risk of LSA in patients with MDD compared to those without subthreshold hypomania.

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.

The Use of Antidepressants in Bipolar Depression

Depression remains a significant debilitating and frequent phase of illness for patients with bipolar disorder. There are few FDA-approved medications for its treatment, only one of which includes a traditional antidepressant (olanzapine-fluoxetine combination), despite studies that demonstrate traditional antidepressants are one of the most commonly prescribed class of medications for bipolar patients in a depressive episode. While traditional antidepressants remain the primary option for treatment of unipolar depression, their use in bipolar depression has been controversial due to a limited efficacy evidence and the concern for potential harm. This chapter reviews the current data concerning the use of traditional antidepressants in bipolar disorder, and the current expert treatment guideline recommendations for their use.

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.

Deep brain stimulation for bipolar disorder-review and outlook

Research on deep brain stimulation (DBS) for treatment-resistant psychiatric disorders has established preliminary efficacy signals for treatment-resistant depression. There are only few studies on DBS that included patients suffering from bipolar disorder. This article gives an overview of these studies concerning DBS targets, antidepressant efficacy, and the occurrence of manic/hypomanic symptoms under stimulation. First, promising results show that all patients experienced significant improvement in depressive symptomatology. In a single case, hypomanic symptoms occurred, but they could be resolved by adjusting stimulation parameters. Furthermore, this article highlights important clinical differences between unipolar and bipolar depression that have to be considered throughout the course of treatment.

Differences in symptom expression between unipolar and bipolar spectrum depression: Results from a nationally representative sample using item response theory (IRT)

BACKGROUND

The inclusion of subsyndromal forms of bipolarity in the fifth edition of the DSM has major implications for the way in which we approach the diagnosis of individuals with depressive symptoms. The aim of the present study was to use methods based on item response theory (IRT) to examine whether, when equating for levels of depression severity, there are differences in the likelihood of reporting DSM-IV symptoms of major depressive episode (MDE) between subjects with and without a lifetime history of manic symptoms.

METHODS

We conducted these analyses using a large, nationally representative sample from the USA (n=34,653), the second wave of the National Epidemiologic Survey on Alcohol and Related Conditions.

RESULTS

The items sadness, appetite disturbance and psychomotor symptoms were better indicators of depression severity in participants without a lifetime history of manic symptoms, in a clinically meaningful way. DSM-IV symptoms of MDE were substantially less informative in participants with a lifetime history of manic symptoms than in those without such history.

LIMITATIONS

Clinical information on DSM-IV depressive and manic symptoms was based on retrospective self-report

CONCLUSIONS

The clinical presentation of depressive symptoms may substantially differ in individuals with and without a lifetime history of manic symptoms. These findings alert to the possibility of atypical symptomatic presentations among individuals with co-occurring symptoms or disorders and highlight the importance of continued research into specific pathophysiology differentiating unipolar and bipolar depression.

Towards person-centered neuroimaging markers for resilience and vulnerability in Bipolar Disorder

Improved clinical care for Bipolar Disorder (BD) relies on the identification of diagnostic markers that can reliably detect disease-related signals in clinically heterogeneous populations. At the very least, diagnostic markers should be able to differentiate patients with BD from healthy individuals and from individuals at familial risk for BD who either remain well or develop other psychopathology, most commonly Major Depressive Disorder (MDD). These issues are particularly pertinent to the development of translational applications of neuroimaging as they represent challenges for which clinical observation alone is insufficient. We therefore applied pattern classification to task-based functional magnetic resonance imaging (fMRI) data of the n-back working memory task, to test their predictive value in differentiating patients with BD (n=30) from healthy individuals (n=30) and from patients' relatives who were either diagnosed with MDD (n=30) or were free of any personal lifetime history of psychopathology (n=30). Diagnostic stability in these groups was confirmed with 4-year prospective follow-up. Task-based activation patterns from the fMRI data were analyzed with Gaussian Process Classifiers (GPC), a machine learning approach to detecting multivariate patterns in neuroimaging datasets. Consistent significant classification results were only obtained using data from the 3-back versus 0-back contrast. Using contrast, patients with BD were correctly classified compared to unrelated healthy individuals with an accuracy of 83.5%, sensitivity of 84.6% and specificity of 92.3%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their relatives with MDD, were respectively 73.1%, 53.9% and 94.5%. Classification accuracy, sensitivity and specificity when comparing patients with BD to their healthy relatives were respectively 81.8%, 72.7% and 90.9%. We show that significant individual classification can be achieved using whole brain pattern analysis of task-based working memory fMRI data. The high accuracy and specificity achieved by all three classifiers suggest that multivariate pattern recognition analyses can aid clinicians in the clinical care of BD in situations of true clinical uncertainty regarding the diagnosis and prognosis.

Are there subtypes of bipolar depression?

OBJECTIVE

To investigate for subtypes of bipolar depression using latent class analysis (LCA).

METHOD

Participants were recruited through a bipolar disorder (BD) clinic. LCA was undertaken using: (i) symptoms reported on the SCID-IV for the most severe lifetime depressive episode; (ii) lifetime illness features such as age at first depressive and hypo/manic episodes; and (iii) family history of BD and unipolar depression. To explore the validity of any demonstrated 'classes', clinical, demographic and treatment correlates were investigated.

RESULTS

A total of 243 BD subjects (170 with BD-I and 73 with BD-II) were included. For the combined sample, we found two robust LCA solutions, with two and three classes respectively. There were no consistent solutions when the BD-I and BD-II samples were considered separately. Subjects in class 2 of the three-class solution (characterised by anxiety, insomnia, reduced appetite/weight loss, irritability, psychomotor retardation, suicidal ideation, guilt, worthlessness and evening worsening) were significantly more likely to be in receipt of government financial support, suggesting a particularly malign pattern of symptoms.

CONCLUSION

Our study suggests the existence of two or three distinct classes of bipolar depression and a strong association with functional outcome.

Characteristics of depressive patients according to family history of affective illness: Findings from a French national cohort

BACKGROUND

Literature is scarce about the characteristics of mood disorder patients with a family history (FH) of affective illness. The aim of the current study was to compare the prominent features of depressive patients with a FH of mania (FHM), those of depressive patients with a FH of depression (FHD), and those of depressive patients with no FH of affective illness (FHO).

METHODS

As part of the EPIDEP National Multisite French Study of 493 consecutive DSM-IV major depressive patients evaluated in at least two semi-structured interviews 1 month apart, 45 (9.1%) were classified as FHM, 210 (42.6%) as FHD, and 238 (48.3%) as FHO.

RESULTS

The main characteristics of FHM patients were a cyclothymic temperament, the presence of mixed features and diurnal variations of mood during depression, early sexual behaviour, a high number of mood episodes and hypomanic switches, high rates of suicide attempts and rapid cycling; diagnosis of bipolar disorder was more frequent in this group as well as comorbid obsessive compulsive disorder, posttraumatic stress disorder, bulimia, attention deficit/hyperactivity disorder and impulse control disorders. The FHD patients had more depressive temperament, generalized anxiety disorder, and anorexia nervosa. Compared to FHO, FHM and FHD showed an earlier age at onset, more comorbid anxiety disorders, as well as more psychotic features.

LIMITATIONS

The following are the limitations of this study: retrospective design, recall bias, and preferential enrolment of bipolar patients with a depressive predominant polarity.

CONCLUSIONS

In light of genetic studies conducted in affective disorder patients, our findings may support the hypothesis of genetic risks factors common to affective disorders and dimensions of temperament, that may extend to comorbid conditions specifically associated with bipolar or unipolar illness.

State-related differences in the level of psychomotor activity in patients with bipolar disorder - Continuous heart rate and movement monitoring

Measuring changes in psychomotor activity is a potential tool in the monitoring of the course of affective states in bipolar disorder. Previous studies have been cross-sectional and only some have used objective measures. The aim was to investigate state-related differences in objectively-measured psychomotor activity in bipolar disorder. During a 12 weeks study, repeated measurements of heart rate and movement monitoring over several days were collected during different affective states from 19 outpatients with bipolar disorder. Outcomes included activity energy expenditure (AEE) and trunk acceleration (ACC). Symptoms were clinically assessed using Hamilton Depression Rating Scale (HDRS-17) and Young Mania Rating Scale (YMRS). Compared to patients in a euthymic state, patients in a manic state had significantly higher AEE. Compared to patients in a depressive state, patients in a manic state had significantly higher ACC and AEE. There was a significant diurnal variation in ACC and AEE between affective states. Finally, there was a significant correlation between the severity of manic symptoms and ACC and AEE, respectively. This first study measuring psychomotor activity during different affective states using a combined heart rate and movement sensor supports that psychomotor activity is a core symptom in bipolar disorder that is altered during affective states.

Suicide attempts in bipolar disorders: comprehensive review of 101 reports

OBJECTIVE

Assess reported risk of suicide attempts by patients with bipolar disorder (BD).

METHOD

Systematic searching yielded 101 reports from 22 countries (79 937 subjects). We analyzed for risk (%) and incidence rates (%/year) of attempts, comparing sex and diagnostic types, including by meta-analysis.

RESULTS

Attempt risk averaged 31.1% [CI: 27.9-34.3] of subjects, or 4.24 [3.78-4.70]%/year. In BD-I (43 studies) and BD-II subjects (30 studies), risks (29.9%, 31.4%) and incidence rates (4.01, 4.11%/year) were similar and not different by meta-analysis. Among women vs. men, risks (33.7% vs. 25.5%) and incidence (4.50 vs. 3.21%/year) were greater (also supported by meta-analysis: RR = 1.35 [CI: 1.25-1.45], P < 0.0001). Neither measure was related to reporting year, % women/study, or to onset or current age. Risks were greater with longer exposure, whereas incidence rates decreased with longer time at risk, possibly through 'dilution' by longer exposure.

CONCLUSION

This systematic update of international experience underscores high risks of suicide attempts among patients with BD (BD-I = BD-II; women > men). Future studies should routinely include exposure times and incidence rates by diagnostic type and sex for those who attempt suicide or not.

Discriminating Between Bipolar Disorder and Major Depressive Disorder

Rates of misdiagnosis between major depressive disorder and bipolar disorder have been reported to be substantial, and the consequence of such misdiagnosis is likely to be a delay in achieving effective control of symptoms, in some cases spanning many years. Particularly in the midst of a depressive episode, or early in the illness course, it may be challenging to distinguish the 2 mood disorders purely on the basis of cross-sectional features. To date, no useful biological markers have been reliably shown to distinguish between bipolar disorder and major depressive disorder.

Neuropsychological and social cognitive function in young people at genetic risk of bipolar disorder

BACKGROUND

Impairments in key neuropsychological domains (e.g. working memory, attention) and social cognitive deficits have been implicated as intermediate (endo) phenotypes for bipolar disorder (BD), and should therefore be evident in unaffected relatives.

METHOD

Neurocognitive and social cognitive ability was examined in 99 young people (age range 16-30 years) with a biological parent or sibling diagnosed with the disorder [thus deemed to be at risk (AR) of developing BD], compared with 78 healthy control (HC) subjects, and 52 people with a confirmed diagnosis of BD.

RESULTS

Only verbal intelligence and affective response inhibition were significantly impaired in AR relative to HC participants; the BD participants showed significant deficits in attention tasks compared with HCs. Neither AR nor BD patients showed impairments in general intellectual ability, working memory, visuospatial or language ability, relative to HC participants. Analysis of BD-I and BD-II cases separately revealed deficits in attention and immediate memory in BD-I patients (only), relative to HCs. Only the BD (but not AR) participants showed impaired emotion recognition, relative to HCs.

CONCLUSIONS

Selective cognitive deficits in the capacity to inhibit negative affective information, and general verbal ability may be intermediate markers of risk for BD; however, the extent and severity of impairment in this sample was less pronounced than has been reported in previous studies of older family members and BD cases. These findings highlight distinctions in the cognitive profiles of AR and BD participants, and provide limited support for progressive cognitive decline in association with illness development in BD.

Delayed sleep phase: An important circadian subtype of sleep disturbance in bipolar disorders

BACKGROUND

Theoretical models of Bipolar Disorder (BD) highlight that sleep disturbances may be a marker of underlying circadian dysregulation. However, few studies of sleep in BD have reported on the most prevalent circadian sleep abnormality, namely Delayed Sleep Phase (DSP).

METHODS

A cross-sectional study of 404 adults with BD who met published clinical criteria for insomnia, hypersomnia or DSP, and who had previously participated in a study of sleep in BD using a comprehensive structured interview assessment.

RESULTS

About 10% of BD cases with a sleep problem met criteria for a DSP profile. The DSP group was younger and had a higher mean Body Mass Index (BMI) than the other groups. Also, DSP cases were significantly more likely to be prescribed mood stabilizers and antidepressant than insomnia cases. An exploratory analysis of selected symptom item ratings indicated that DSP was significantly more likely to be associated with impaired energy and activity levels.

LIMITATIONS

The cross-sectional design precludes examination of longitudinal changes. DSP is identified by sleep profile, not by diagnostic criteria or objective sleep records such as actigraphy. The study uses data from a previous study to identify and examine the DSP group.

CONCLUSIONS

The DSP group identified in this study can be differentiated from hypersomnia and insomnia groups on the basis of clinical and demographic features. The association of DSP with younger age, higher BMI and impaired energy and activity also suggest that this clinical profile may be a good proxy for underlying circadian dysregulation.

Multimodal Neuroimaging-Informed Clinical Applications in Neuropsychiatric Disorders

Recent advances in neuroimaging data acquisition and analysis hold the promise to enhance the ability to make diagnostic and prognostic predictions and perform treatment planning in neuropsychiatric disorders. Prior research using a variety of types of neuroimaging techniques has confirmed that neuropsychiatric disorders are associated with dysfunction in anatomical and functional brain circuits. We first discuss current challenges associated with the identification of reliable neuroimaging markers for diagnosis and prognosis in mood disorders and for neurosurgical treatment planning for deep brain stimulation (DBS). We then present data on the use of neuroimaging for the diagnosis and prognosis of mood disorders and for DBS treatment planning. We demonstrate how multivariate analyses of functional activation and connectivity parameters can be used to differentiate patients with bipolar disorder from those with major depressive disorder and non-affective psychosis. We also present data on connectivity parameters that mediate acute treatment response in affective and non-affective psychosis. We then focus on precision mapping of functional connectivity in native space. We describe the benefits of integrating anatomical fiber reconstruction with brain functional parameters and cortical surface measures to derive anatomically informed connectivity metrics within the morphological context of each individual brain. We discuss how this approach may be particularly promising in psychiatry, given the clinical and etiological heterogeneity of the disorders, and particularly in treatment response prediction and planning. Precision mapping of connectivity is essential for DBS. In DBS, treatment electrodes are inserted into positions near key gray matter nodes within the circuits considered relevant to disease expression. However, targeting white matter tracts that underpin connectivity within these circuits may increase treatment efficacy and tolerability therefore relevant for effective treatment. We demonstrate how this approach can be validated in the treatment of Parkinson's disease by identifying connectivity patterns that can be used as biomarkers for treatment planning and thus refine the traditional approach of DBS planning that uses only gray matter landmarks. Finally, we describe how this approach could be used in planning DBS treatment of psychiatric disorders.

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.

Could glutamate spectroscopy differentiate bipolar depression from unipolar?

BACKGROUND

Accurate differentiation of bipolar and unipolar depression is a key clinical challenge. A biological measure that could differentiate bipolar and unipolar depression might supplement clinical assessment. Magnetic Resonance Spectroscopy measurements of total glutamate and glutamine (Glx) in anterior cingulate cortex are one potential measure. The objective of this study was to assess the potential performance of this measure.

METHODS

Meta-analysis of data from eleven studies where anterior cingulate Glx of depressed patients has been compared to that of healthy controls was performed. Effect sizes for bipolar and unipolar depression were calculated as Standardised Mean Differences. The best estimate of test classification performance on the basis of observed effects was calculated.

RESULTS

People with unipolar depression had on average lower levels of Glx than healthy controls (effect size -1.05; 95% CI -058 to -1.53). People with bipolar depression tended towards higher Glx than healthy controls (effect size 0.40; 95% CI -0.04 to 0.85). This yielded a difference in Glx between unipolar and bipolar depression of effect size 1.46 (95% CI 0.80-2.11). Based on this difference, a test differentiating bipolar from unipolar depression by whether Glx was higher or lower than the average in healthy population would have sensitivity 0.66 and specificity 0.85.

LIMITATIONS

There is an absence of studies directly comparing unipolar and bipolar depressed patients.

CONCLUSIONS

On available data, measurement of anterior cingulate Glx is a promising potential tool for differentiation of bipolar and unipolar depression. This potential effect requires direct validation within mixed clinical cohorts.

Dwelling quietly in the rich club: brain network determinants of slow cortical fluctuations

For more than a century, cerebral cartography has been driven by investigations of structural and morphological properties of the brain across spatial scales and the temporal/functional phenomena that emerge from these underlying features. The next era of brain mapping will be driven by studies that consider both of these components of brain organization simultaneously--elucidating their interactions and dependencies. Using this guiding principle, we explored the origin of slowly fluctuating patterns of synchronization within the topological core of brain regions known as the rich club, implicated in the regulation of mood and introspection. We find that a constellation of densely interconnected regions that constitute the rich club (including the anterior insula, amygdala and precuneus) play a central role in promoting a stable, dynamical core of spontaneous activity in the primate cortex. The slow timescales are well matched to the regulation of internal visceral states, corresponding to the somatic correlates of mood and anxiety. In contrast, the topology of the surrounding 'feeder' cortical regions shows unstable, rapidly fluctuating dynamics likely to be crucial for fast perceptual processes. We discuss these findings in relation to psychiatric disorders and the future of connectomics.

Hamilton depression rating scale and montgomery-asberg depression rating scale in depressed and bipolar I patients: psychometric properties in a Brazilian sample

Background

The Hamilton Depression Rating Scale (HAM-D) and the Montgomery–Asberg Depression Scale (MADRS) are used worldwide and considered standard scales for evaluating depressive symptoms. This paper aims to investigate the psychometric proprieties (reliability and validity) of these scales in a Brazilian sample, and to compare responses in bipolar and unipolar patients.

Methods

The sample comprised 91 patients with either bipolar I or major depressive disorder from a psychiatric institute at São Paulo, Brazil. Participants were recruited and treated by clinicians through the Structured Interview for DSM-IV criteria, and had previously been interviewed by a trained, blind tester.

Results

Both scales indicated good reliability properties; however, the MADRS reliability statistics were higher than those of the HAM-D for detecting initial symptoms of unipolar depression. Correlation between the tests was moderate. Despite demonstrating adequate validity, neither test achieved the levels of sensitivity and specificity required for identification of a cutoff score to differentiate bipolar I and unipolar patients.

Conclusions

Both scales demonstrate adequate reliability and validity for assessing depressive symptoms in the Brazilian sample, and are good options to complement psychiatric diagnosis, but are not appropriate for distinguishing between the two affective disorder types.

Clinical and psychometric validation of the psychotic depression assessment scale

BACKGROUND

Recent studies have indicated that the 11-item Psychotic Depression Assessment Scale (PDAS), consisting of the 6-item melancholia subscale (HAM-D6) of the Hamilton Depression Rating Scale and 5 psychosis items from the Brief Psychiatric Rating Scale (BPRS), is a valid measure for the severity of psychotic depression. The aim of this study was to subject the PDAS, and its depression (HAM-D6) and psychosis (BPRS5) subscales to further validation.

METHODS

Patients diagnosed with psychotic depression at Danish psychiatric hospitals participated in semi-structured interviews. Video recordings of these interviews were assessed by two experienced psychiatrists (global severity rating of psychotic depression, depressive symptoms and psychotic symptoms) and by two young physicians (rating on 27 symptom items, including the 11 PDAS items). The clinical validity and responsiveness of the PDAS and its subscales was investigated by Spearman correlation analysis of the global severity ratings and the PDAS, HAM-D6, and BPRS5 total scores. The unidimensionality of the scales was tested by item response theory analysis (Mokken).

RESULTS

Ratings from 39 participants with unipolar psychotic depression and nine participants with bipolar psychotic depression were included in the analysis. The Spearman correlation analysis indicated that the PDAS, HAM-D6 and BPRS5 were clinically valid (correlation coefficients from 0.78 to 0.85, p<0.001) and responsive (correlation coefficients from 0.72 to 0.86, p<0.001) measures of psychotic depression. According to the Mokken analysis, all three scales were unidimensional.

CONCLUSIONS

The clinical validity, responsiveness and unidimensionality of the PDAS and its subscales were confirmed in an independent sample of patients with psychotic depression.

Long term course of bipolar I disorder in India: using retrospective life chart method

BACKGROUND

There are grounds to believe that the course of bipolar disorder may be different in tropical countries such as India when compared to temperate nations. There is a dearth of literature about the course of bipolar I disorder from India.

METHODS

This study was conducted in a multispecialty teaching hospital in southern India. Patients with a DSM-IV TR diagnosis of bipolar I disorder, confirmed using SCID-I, with a minimum duration of illness of 3 years were assessed. Information was gathered on demographic and clinical variables, and the life course of episodes was charted using the National Institute of Mental Health - Life Chart Methodology Clinician Retrospective Chart (NIMH-LCM-CRC).

RESULTS

A total of 150 patients with bipolar disorder were included. The mean age at onset of illness was 24.8 (± 8.2) years. Mania was the first episode in a majority (85%) of the cases, and was the most frequent episode in the course of the illness, followed by depression. Patients spent an average of 11.1% of the illness duration in a mood episode, most commonly a manic episode. The median duration of manic or depressive episode was 2 months. Median time to recurrence after the first episode was 21 months (inter-quartile range of 10-60 months), and was shorter for women than men.

LIMITATIONS

The hospital based sample from a particular region limits generalizability. Recall bias may be present in this retrospective information based study. Medical illness, personality disorders, other Axis I psychiatric disorders (apart from substance use disorder) and influence of adherence to treatment on the course of the disorder were not assessed systematically.

CONCLUSIONS

Bipolar I disorder among Indian patients has a course characterized by predominantly manic episodes, which is in line with previous reports from tropical countries and substantially different from that of temperate regions.

A randomized, double-blind, placebo-controlled trial of pregnenolone for bipolar depression

Depression in bipolar disorder (BPD) is challenging to treat. Therefore, additional medication options are needed. In the current report, the effect of the neurosteroid pregnenolone on depressive symptoms in BPD was examined. Adults (n=80) with BPD, depressed mood state, were randomized to pregnenolone (titrated to 500 mg/day) or placebo, as add-on therapy, for 12 weeks. Outcome measures included the 17-item Hamilton Rating Scale for Depression (HRSD), Inventory of Depressive Symptomatology-Self-Report (IDS-SR), Hamilton Rating Scale for Anxiety (HRSA), and Young Mania Rating Scale (YMRS). Serum neurosteroid levels were assessed at baseline and week 12. Data were analyzed using a mixed model ANCOVA with a between factor of treatment assignment, a within factor (repeated) of visit, and the baseline value, as well as age and gender, as covariates. In participants with at least one postbaseline visit (n=73), a significant treatment by week interaction for the HRSD (F(5,288)=2.61, p=0.025), but not IDS-SR, was observed. Depression remission rates were greater in the pregnenolone group (61%) compared with the placebo group (37%), as assessed by the IDS-SR (χ(2)(1)=3.99, p=0.046), but not the HRSD. Large baseline-to-exit changes in neurosteroid levels were observed in the pregnenolone group but not in the placebo group. In the pregnenolone group, baseline-to-exit change in the HRSA correlated negatively with changes in allopregnanolone (r(22)=-0.43, p=0.036) and pregNANolone (r(22)=-0.48, p=0.019) levels. Pregnenolone was well tolerated. The results suggest that pregnenolone may improve depressive symptoms in patients with BPD and can be safely administered.

Excess mortality in bipolar disorders

Bipolar disorder is associated with high mortality, and people with this disorder on average may die 10-20 years earlier than the general population. This excess and premature mortality continues to occur despite a large and expanding selection of treatment options dating back to lithium and now including anticonvulsants, antipsychotics, and evidence-based psychotherapies. This review summarizes recent findings on mortality in bipolar disorder, with an emphasis on the role of suicide (accounting for about 15% of deaths in this population) and cardiovascular disease (accounting for about 35-40% of deaths). Recent care models and treatments incorporating active outreach, integrated mental and physical health care, and an emphasis on patient self-management have shown promise in reducing excess mortality in this population.

Bipolar I and II versus unipolar depression: clinical differences and impulsivity/aggression traits

OBJECTIVE

To investigate distinguishing features between bipolar I, II and unipolar depression, and impulsivity/aggression traits in particular.

METHODS

Six hundred and eighty-five (n=685) patients in a major depressive episode with lifetime Unipolar (UP) depression (n=455), Bipolar I (BP-I) disorder (n=151), and Bipolar II (BP-II) (n=79) disorder were compared in terms of their socio-demographic and clinical characteristics.

RESULTS

Compared to unipolar patients, BP-I and BP-II depressed patients were significantly younger at onset of their first depressive episode, and were more likely to experience their first depressive episode before/at age of 15. They also had more previous affective episodes, more first- and second-degree relatives with history of mania, more current psychotic and subsyndromal manic symptoms, and received psychopharmacological and psychotherapy treatment at an earlier age. Furthermore, BP-I and BP-II depressed patients had higher lifetime impulsivity, aggression, and hostility scores. With regard to bipolar subtypes, BP-I patients had more trait-impulsivity and lifetime aggression than BP-II patients whereas the latter had more hostility than BP-I patients. As for co-morbid disorders, Cluster A and B Personality Disorders, alcohol and substance abuse/dependence and anxiety disorders were more prevalent in BP-I and BP-II than in unipolar patients. Whereas the three groups did not differ on other socio-demographic variables, BP-I patients were significantly more often unemployed that UP patients.

CONCLUSION

Our findings comport with major previous findings on differences between bipolar and unipolar depression. As for trait characteristics, bipolar I and II depressed patients had more life-time impulsivity and aggression/hostility than unipolar patients. In addition, bipolar I and II patients also differed on these trait characteristics.

Bipolar polygenic loading and bipolar spectrum features in major depressive disorder

OBJECTIVES

Family and genetic studies indicate overlapping liability for major depressive disorder and bipolar disorder. The purpose of the present study was to determine whether this shared genetic liability influences clinical presentation.

METHODS

A polygenic risk score for bipolar disorder, derived from a large genome-wide association meta-analysis, was generated for each subject of European-American ancestry (n = 1,274) in the Sequential Treatment Alternatives to Relieve Depression study (STAR*D) outpatient major depressive disorder cohort. A hypothesis-driven approach was used to test for association between bipolar disorder risk score and features of depression associated with bipolar disorder in the literature. Follow-up analyses were performed in two additional cohorts.

RESULTS

A generalized linear mixed model including seven features hypothesized to be associated with bipolar spectrum illness was significantly associated with bipolar polygenic risk score [F = 2.07, degrees of freedom (df) = 7, p = 0.04]. Features included early onset, suicide attempt, recurrent depression, atypical depression, subclinical mania, subclinical psychosis, and severity. Post-hoc univariate analyses demonstrated that the major contributors to this omnibus association were onset of illness at age ≤ 18 years [odds ratio (OR) = 1.2, p = 0.003], history of suicide attempt (OR = 1.21, p = 0.03), and presence of at least one manic symptom (OR = 1.16, p = 0.02). The maximal variance in these traits explained by polygenic score ranged from 0.8% to 1.1%. However, analyses in two replication cohorts testing a five-feature model did not support this association.

CONCLUSIONS

Bipolar genetic loading appeared to be associated with bipolar-like presentation in major depressive disorder in the primary analysis. However, the results were at most inconclusive because of lack of replication. Replication efforts were challenged by different ascertainment and assessment strategies in the different cohorts. The methodological approach described here may prove useful in applying genetic data to clarify psychiatric nosology in future studies.

Rejection sensitivity and pain in bipolar versus unipolar depression

OBJECTIVES

Recent neuroimaging studies support the contention that depression, pain distress, and rejection distress share the same neurobiological circuits. In two recently published studies we confirmed the hypothesis that the perception of increased pain during both treatment-refractory depression (predominantly unipolar) and difficult-to-treat bipolar depression was related to increased state rejection sensitivity (i.e., rejection sensitivity when depressed). In the present study, we aimed to compare the correlates of pain and rejection sensitivity in individuals with bipolar versus unipolar depression and test the hypothesis that bipolar disorder may be distinguished from unipolar depression both by an increased perception of pain and heightened rejection sensitivity during depression.

METHODS

We analyzed data from 113 bipolar and 146 unipolar depressed patients presenting to the Black Dog Institute, Sydney, Australia. The patients all met DSM-IV criteria for bipolar disorder or unipolar depression (major depressive disorder).

RESULTS

Bipolar disorder predicted a major increase in state rejection sensitivity when depressed (p = 0.001), whereas trait rejection sensitivity (i.e., a long-standing pattern of rejection sensitivity) was not predicted by polarity. A major increase in the experience of headaches (p = 0.007), chest pain (p < 0.001), and body aches and pains (p = 0.02) during depression was predicted by a major increase in state rejection sensitivity for both bipolar and unipolar depression.

CONCLUSIONS

State, but not trait, rejection sensitivity is significantly predicted by bipolar depression, suggesting that this might be considered as a state marker for bipolar depression and taken into account in the clinical differentiation of bipolar and unipolar depression.

Actigraphic assessment of motor activity in acutely admitted inpatients with bipolar disorder

Introduction

Mania is associated with increased activity, whereas psychomotor retardation is often found in bipolar depression. Actigraphy is a promising tool for monitoring phase shifts and changes following treatment in bipolar disorder. The aim of this study was to compare recordings of motor activity in mania, bipolar depression and healthy controls, using linear and nonlinear analytical methods.

Materials and Methods

Recordings from 18 acutely hospitalized inpatients with mania were compared to 12 recordings from bipolar depression inpatients and 28 healthy controls. 24-hour actigraphy recordings and 64-minute periods of continuous motor activity in the morning and evening were analyzed. Mean activity and several measures of variability and complexity were calculated.

Results

Patients with depression had a lower mean activity level compared to controls, but higher variability shown by increased standard deviation (SD) and root mean square successive difference (RMSSD) over 24 hours and in the active morning period. The patients with mania had lower first lag autocorrelation compared to controls, and Fourier analysis showed higher variance in the high frequency part of the spectrum corresponding to the period from 2–8 minutes. Both patient groups had a higher RMSSD/SD ratio compared to controls. In patients with mania we found an increased complexity of time series in the active morning period, compared to patients with depression. The findings in the patients with mania are similar to previous findings in patients with schizophrenia and healthy individuals treated with a glutamatergic antagonist.

Conclusion

We have found distinctly different activity patterns in hospitalized patients with bipolar disorder in episodes of mania and depression, assessed by actigraphy and analyzed with linear and nonlinear mathematical methods, as well as clear differences between the patients and healthy comparison subjects.

Clinical differences between unipolar and bipolar depression: interest of BDRS (Bipolar Depression Rating Scale)

OBJECTIVES

It is currently assumed that there are no important differences between the clinical presentations of unipolar and bipolar depression. Failure to distinguish bipolar from unipolar depression may lead to inappropriate treatment and poorer outcomes. We hereby compare unipolar and bipolar depressed subjects, in order to identify distinctive clinical specificities of bipolar depression.

METHODS

Two independent samples of depressed patients (unipolar and bipolar) were recruited, with 55 patients in one sample, and 49 in the other. In both samples, unipolar and bipolar patients were compared on a broad range of parameters, including sociodemographic characteristics, comorbidities, Montgomery and Asberg Depression Scale (MADRS; assessing depression severity), CORE (assessing psychomotor disturbance) and Bipolar Depression Rating Scale (assessing specific bipolar depression symptoms).

RESULTS

Results were similar in both samples. MADRS scores were similar in bipolar and unipolar subjects (median score 33 vs 34; p=0.74). On the CORE, there was a trend to higher scores among the bipolar subjects. BDRS scores were higher in bipolar than in unipolar subjects (median score 33 vs 27; p<0.001). The difference was particularly marked on the "mixed" subscale of the BDRS. We tested the ability of the mixed subscale of the BDRS to distinguish bipolar from unipolar depression, using different cut off points: a cut off point of 3 can predict bipolar depression, with a sensibility of 62% and a specificity of 82%.

CONCLUSIONS

Presence of mixed symptoms during a depressive episode is in favour of bipolar depression. The BDRS scale should be integrated in a probabilistic approach to distinguish bipolar from unipolar depression.