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Objective: While treatment with antipsychotics and antiepileptics have been associated with an increased risk of diabetes mellitus (DM), lithium may have the opposite effect via inhibition of glycogen synthase kinase-3. The aim of this study was to investigate whether treatment of bipolar disorder with lithium, antipsychotics, or antiepileptics is associated with the risk of DM in a real-world clinical setting. Methods: Using nationwide registers, we identified all patients diagnosed with bipolar disorder in Danish Psychiatric Services from January 1, 1996, to January 1, 2019 (N = 30,451). The risk of developing DM was operationalized via hospital diagnoses and redeemed prescriptions for glucose-lowering drugs. For lithium, antipsychotics, valproate, and lamotrigine, we calculated hazard rate ratios (HRR) for developing DM via adjusted Cox proportional hazards models. Potential cumulative dose–response-like associations were examined using the log-rank test. Results: During follow-up (245,181 person-years), 2107 (6.9%) patients developed DM. Compared with non-users of the respective drugs, we found no clinically or statistically significant difference in the risk of developing DM among patients receiving lithium (n = 11,690; incidence rate of DM/1000 person-years (IR) = 8.87, 95% CI: 8.02–9.90; HRR = 0.94, 95% CI: 0.84–1.06) or lamotrigine (n = 11,785; IR = 7.58, 95% CI: 6.69–8.59; HRR = 0.89, 95% CI: 0.77–1.02), respectively. Conversely, for patients receiving valproate (n = 5171; IR = 12.68, 95% CI: 10.87–14.80; HRR = 1.34, 95% CI: 1.14–1.58) and antipsychotics (n = 22,719; IR = 12.00, 95% CI: 11.14–12.94; HRR = 1.65, 95% CI: 1.45–1.88), respectively, there was increased risk of developing DM. For antipsychotics, we observed a clear cumulative dose–response-like association with the risk of DM. Conclusions: Treatment with valproate and antipsychotics—but not with lithium and lamotrigine—was associated with increased risk of DM in a real-world cohort of patients with bipolar disorder.

Introduction Although clinical practice guidelines (CPG) identify first, second- and third-line mood stabilizer (MS) treatments, they rarely define clinical response to prophylaxis or the core issues to be considered. This project aimed to develop a template for describing how clinical response may be classified and a framework to assist decision-making and monitoring of response in day-to-day practice. Method A scoping exercise was undertaken followed by narrative synthesis of (a) qualitative and quantitative definitions of MS response applied in clinical and research practice and (b) potential confounders (eg, non-adherence; tolerability issues) of relevance to routine practice, for example, the concepts are applicable to individuals with bipolar disorder for whom sustained remission is a less realistic goal. Expert consensus was employed to develop a taxonomy of response and key concepts that inform clinical judgements about MS response. Results Five core constructs can be used to systematize clinical judgements regarding MS response and its monitoring: (a) quantitative, qualitative and/or patient-reported outcome measures (PROMS), (b) personalized assessment of the acceptable benefit-to-harm ratio of a proposed treatment, (c) adequacy of treatment exposure (dose, duration, therapeutic monitoring and adherence), (d) illness activity pre- and post-MS initiation, and (e) other potential confounders (co-prescription of MS; polypharmacy) or protective factors (eg, psychosocial factors). Conclusions This heuristic framework might be used as a teaching aid or by clinicians who wish to take a more systematic approach to developing shared criteria for judging MS response that better match patient expectations and preferences. Heuristic approaches also allow seamless introduction of new evidence.

The evidence for efficacy of many currently available treatments for bipolar disorder is based on studies of nonrefractory patients with bipolar disorder. Therefore, not surprisingly, most treatment recommendations and guidelines for the treatment of bipolar disorder and its many comorbidities depend heavily on data from placebo controlled randomized clinical trials (RCTs), but these RCTs provide little direction for the clinician as to what next steps might be optimal in non- or partial-responders and in those with ongoing medical and psychiatric comorbidities. Given this and the paucity of RCTs at later treatment junctures, we thought it appropriate to begin a discussion of the quality of the data that some experts in the field might consider using in choosing and sequencing drugs and their combination. We acknowledge that many other clinical investigators may prefer very different sequences, but thought the suggestions offered here might be useful to some clinicians in the field, might start discussions of other options in the literature, and, at the same time, provide a preliminary outline for a new round of much-needed clinical trials to better inform clinical practice. Given the very wide range of the quality of the data and clinical principles on which the current suggestions are based, only minimal references are included and a comprehensive review of the literature supporting each option would be outside the scope of this manuscript.

Bipolar disorder (BD) is associated with higher rates of sedentarism, metabolic syndrome, obesity and early onset cardiovascular disease leading to premature mortality. Moreover, BD is often associated with disability and deficits in general functioning associated with residual subsyndromal depressive symptoms and persistent neurocognitive impairments.

Objectives Lithium and quetiapine are known to be effective treatments for bipolar disorder. However, little information is available to inform prediction of response to these medications. Machine-learning methods can identify predictors of response by examining variables simultaneously. Further evaluation of models on a test sample can estimate how well these models would generalize to other samples. Methods Data (N = 482) were drawn from a randomized clinical trial of outpatients with bipolar I or II disorder who received adjunctive personalized treatment plus either lithium or quetiapine. Elastic net regularization (ENR) was used to generate models for lithium and quetiapine; these models were evaluated on a test set. Results Predictions from the lithium model explained 17.4% of the variance in actual observed scores of patients who received lithium in the test set, while predictions from the quetiapine model explained 32.1% of the variance of patients that received quetiapine. Of the baseline variables selected, those with the largest parameter estimates were: severity of mania; attention-deficit/hyperactivity disorder (ADHD) comorbidity; nonsuicidal self-injurious behavior; employment; and comorbidity with each of two anxiety disorders (social phobia/society anxiety and agoraphobia). Predictive accuracy of the ENR model outperformed the simple and basic theoretical models. Conclusion ENR is an effective approach for building optimal and generalizable models. Variables identified through this methodology can inform future research on predictors of response to lithium and quetiapine, as well as future modeling efforts of treatment choice in bipolar disorder.

INTRODUCTION: Depressive episodes are often prevalent among patients with bipolar disorder, but little is known regarding the differential patterns of development over time. We aimed to determine and characterize trajectories of depressive symptoms among adults with bipolar disorder during 6 months of systematic treatment.METHODS: The pragmatic clinical trial, Bipolar Clinical Health Outcomes Initiative in Comparative Effectiveness (CHOICE), randomized 482 outpatients with bipolar disorder to lithium or quetiapine. Depressive symptoms were rated at up to 9 visits using the Montgomery-Asberg Depression Rating Scale (MADRS). Growth mixture modeling was utilized to identify trajectories and multinomial regression analysis estimated associations with potential predictors.RESULTS: Four distinct trajectories of depressive symptoms were identified. The responding class (60.3%) with a rapid reduction and subsequent low level; the partial-responding class (18.4%) with an initial reduction followed by an increase during the remaining weeks; the fluctuating class (11.6%) with a fluctuation in depressive symptoms; and the non-responding class (9.7%) with sustained moderate-severe depressive symptoms. Bipolar type I predicted membership of the non-responding class and randomization to quetiapine predicted membership of either the responding or the non-responding class.CONCLUSION: Approximately 30% experienced a partial or fluctuating course, and almost 10% had a chronic course with moderate-severe depression during 6 months. Patients diagnosed with bipolar type 1 had higher risk of being categorized into a class with a worse outcome. While no differences in average overall outcomes occurred between the lithium and quetiapine groups, trajectory analysis revealed that the lithium group had more variable courses.

OBJECTIVES: Bipolar disorders (BD) are characterized by emotion and cognitive dysregulation. Mapping deficits in the neurocircuitry of cognitive-affective regulation allows for potential identification of intervention targets. The current study used functional MRI data in BD patients and healthy controls during performance on a task requiring cognitive and inhibitory control superimposed on affective images, assessing cognitive and affective interference. METHODS: Functional MRI data were collected from 39 BD patients and 36 healthy controls during performance on the Multi-Source Interference Task overlaid on images from the International Affective Picture System (MSIT-IAPS). Analyses examined patterns of activation in a priori regions implicated in cognitive and emotional processing. Functional connectivity to the anterior insula during task performance was also examined, given this region’s role in emotion-cognition integration. RESULTS: BD patients showed significantly less activation during cognitive interference trials in inferior parietal lobule, dorsomedial prefrontal cortex, anterior insula, mid-cingulate, and ventrolateral prefrontal cortex regardless of affective valence. BD patients showed deviations in functional connectivity with anterior insula in regions of the default mode and frontoparietal control networks during negatively valenced cognitive interference trials. CONCLUSIONS: Our findings show disruptions in cognitive regulation and inhibitory control in BD patients in the presence of irrelevant affective distractors. Results of this study suggest one pathway to dysregulation in BD is through inefficient integration of affective and cognitive information, and highlight the importance of developing interventions that target emotion-cognition integration in BD.

The DSM-IV includes subtypes, or illness specifiers, for major depressive episodes such as atypical and melancholic, which have been suggested to have predictive validity (1, 2). That is, depressive features may be informative about outcome or diagnosis (3). In particular, some investigators have reported that atypical depressive symptoms, most notably reversed neurovegetative symptoms, and melancholic features are more characteristic (and perhaps a hallmark) of bipolar disorder compared to major depressive disorder (MDD) (4-6). This literature makes the implicit, but important, assumption that depressive features are stable across episodes, an assumption rarely examined prospectively in large cohorts. In the only study to examine more than one depressive recurrence, Coryell and colleagues (7) found some stability for psychotic, agitated versus retarded, and ‘endogenous’ depression; this cohort included ~120 subjects with bipolar disorder. Smaller studies in MDD identified modest correlation for neurovegetative symptoms (8), groups of ‘endogenous’ or anxious symptoms (9, 10), melancholia (11), and suicidality (10). To our knowledge, no study has specifically examined stability of these symptoms in bipolar depression, and only one study considered more than one depressive episode. Beyond refining psychiatric nosology, understanding temporal stability may facilitate biological studies by clarifying ‘core’ symptoms of depression in mood disorders. It may also guide clinical practice if certain symptoms such as suicidality demonstrate stability from episode to episode. We therefore examined data from the multicenter Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) cohort study of bipolar disorder, utilizing the subset of individuals with up to three prospectively observed depressive episodes. We attempted to confirm the stability of neurovegetative symptoms and suicidality between episodes and explore the broader stability of mood symptoms.

Bipolar patients have markedly elevated rates of nicotine dependence (1, 2). Compared to only 12.8% in the general population, 35.3% of those with bipolar I disorder [odds ratio (OR) = 3.9] and 33.4% of those with bipolar II disorder (OR = 3.5) met criteria for nicotine dependence in the prior 12 months (2). Beyond the adverse health implications of smoking, bipolar patients who smoke are at higher risk of suicidal behavior and suicide attempts, independent of substance abuse and anxiety disorder comorbidity (3). Along with severity of depression and having made a prior suicide attempt, smoking was a robust predictor of suicidal behavior following a major depressive episode in bipolar disorder, even after controlling for other factors (4) and regardless of gender (5). Additionally, a study of adolescents with bipolar disorder found that cigarette smoking was independently associated with suicide attempts and substance use disorders (6, 7). It is unclear why smokers with bipolar disorder are more likely to make suicide attempts. Some have suggested that an aggression/impulsivity factor may predispose certain individuals with bipolar disorder to suicidal behavior, substance use disorders, and smoking (4, 8, 9). In a prospective study, hostility predicted suicide attempts in individuals with bipolar disorder, although the relationship between hostility and smoking was not examined (10). In this prospective, longitudinal study of suicidal ideation and behavior in a clinical sample of patients with bipolar disorder, we examined current cigarette smoking using a well-validated measure of suicidal ideation and behaviors at baseline and prospectively at nine-month follow-up, and employed a validated assessment of impulsivity. We hypothesized that smoking would be a significant predictor of suicidality at baseline and at nine-month follow-up.

Objective: Functional magnetic resonance imaging (fMRI) studies have documented abnormalities in the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex in bipolar disorder in the context of working memory tasks. It is increasingly recognized that DLPFC regions play a role in mood regulation and the integration of emotion and cognition. The purpose of the present study was to investigate with fMRI the interaction between acute sadness and working memory functioning in individuals with bipolar disorder. Methods: Nine depressed individuals with DSM-IV bipolar I disorder (BP-I) and 17 healthy control participants matched for age, gender, education, and IQ completed a 2-back working memory paradigm under no mood induction, neutral state, or acute sadness conditions while undergoing fMRI scanning. Functional MRI data were analyzed with SPM2 using a random-effects model. Results: Behaviorally, BP-I subjects performed equally well as control participants on the 2-back working memory paradigm. Compared to control participants, individuals with BP-I were characterized by more sadness-specific activation increases in the left DLPFC (BA 9/46) and left dorsal anterior cingulate (dACC). Conclusions: Our study documents sadness-specific abnormalities in the left DLPFC and dACC in bipolar disorder that suggest difficulties in the integration of emotion (sadness) and cognition. These preliminary findings require further corroboration with larger sample sizes of medication-free subjects.

Objectives: Individuals with bipolar disorder exhibit neuropsychological impairments when they are euthymic (neither depressed nor manic). One of the most consistently reported cognitive problems in euthymic individuals with bipolar disorder is impairment in verbal episodic memory. Recent findings suggest that episodic memory difficulties in these individuals are attributable to difficulties using organizational strategies during encoding. The purpose of the present study was (i) to investigate whether difficulties using organizational strategies in bipolar disorder are due to a failure in spontaneously initiating verbal organization strategies or are due to difficulties implementing such strategies, and (ii) to compare the characteristics of verbal organizational impairment in bipolar disorder with those observed in individuals with obsessive–compulsive disorder (OCD). Methods: Study participants were 20 individuals with bipolar I disorder (BP-I), 20 individuals with OCD, and 20 healthy control participants matched for age, gender, and education. Participants completed a verbal encoding paradigm that involved spontaneous and directed use of verbal organization strategies during encoding of word lists. Results: Compared with control subjects, both BP-I and OCD participants showed impaired verbal organization in the spontaneous encoding condition. In the directed encoding condition, OCD patients organized the word lists as well as control participants whereas BP-I participants exhibited lower verbal organization than both control and OCD participants. OCD and BP-I participants’ free recall performance did not differ from that of control participants in the spontaneous encoding condition. In the directed encoding condition, BP-I participants recalled fewer words than OCD or control participants. Conclusions: Episodic memory difficulties in OCD are associated with difficulties spontaneously initiating verbal organization strategies during encoding whereas the ability to implement verbal organization when instructed to do so is preserved. BP-I participants, on the other hand, exhibit difficulties in both spontaneously initiating verbal organization strategies and in the ability to implement such strategies when instructed to do so.

Objective: Despite promising new therapies, bipolar depression remains difficult to treat. Up to half of patients do not respond adequately to currently approved treatments. This study evaluated the efficacy of adjunctive inositol for bipolar depression. Methods: Seventeen participants with DSM-IV criteria for bipolar depression and a 17-item Hamilton Rating Scale for Depression (HRSD) ≥15 on proven therapeutic levels of lithium or valproate for >2 weeks were randomized to receive double-blind inositol or placebo for 6 weeks. At the end of double-blind treatment, subjects were eligible for an 8-week open-label trial of inositol. Results: Response was defined a priori as >50% reduction in the HRSD and a Clinical Global Impression of 1–2. Four of nine subjects (44%) on inositol and zero of eight subjects on placebo met response criteria (p = 0.053). There was no difference between groups in the average change score for the HRSD or Young Mania Rating Scale (YMRS). Response to inositol was highly variable. Of nine subjects randomized to inositol, two had >50% worsening in HRSD scores at the end of treatment, three had no change and four had >50% improvement. Those who had worsening in depressive symptoms on inositol had significantly higher scores at baseline on the YMRS total score and irritability, disruptive/aggressive behavior and unkempt appearance items. Conclusions: There was a trend for more subjects on inositol to show improvement in bipolar depression symptoms, but, on average, inositol was not more effective than placebo as an adjunct for bipolar depression. Baseline levels of anger or hostility may be predictive of clinical response to inositol.

Introduction: Because there is a high rate of partial response to standard thymoleptic medication, novel augmentation strategies for treatment-resistant bipolar disorder are needed. In an open trial, donepezil augmentation was associated with improvement in manic symptoms in 9 of 11 subjects. Method: We conducted a 6-week, double-blind, placebo-controlled trial of donepezil for treatment-resistant bipolar mania. Eligible subjects had a Young Mania Rating Scale (YMRS) score of at least 15 despite two or more weeks of proven therapeutic levels of lithium or valproate. Subjects who completed the trial were eligible for an 8-week open trial of donepezil. Subjects were started on donepezil 5 mg/day and were eligible for dose increase to 10 mg/day after 4 weeks. Results: Twelve subjects were enrolled. Eleven subjects received at least 1 week of study medication and were included in the analysis. No subjects in the donepezil group (0/6) and 60% (3/5) in the placebo group met response criteria of >30% reduction in YMRS score (Fisher's Exact p = 0.061). YMRS scores were higher at trial endpoint in the donepezil group 20.17 (3.66) compared with the placebo group [11.20 (4.60), Z = −2.476, p = 0.01]. There were no differences at trial endpoint in Hamilton Rating Scale for Depression (HAM-D) or Brief Psychiatric Rating Scale (BPRS) scores in either the intent-to-treat or the completer analyses. Conclusions: Donepezil does not appear to be an effective adjunctive treatment for refractory manic symptoms. The strength of the conclusion of this trial is limited by the possibility of a false-negative result due to the small sample.