Abstracts: Bipolar Disorders

Citrome L, Ketter TA, Cucchiaro J, Loebel A.

J Affect Disord 2014; 155:20–7

Background: Prior to recent FDA approval of lurasidone for treatment of bipolar depression there were only two approved treatments for this condition (quetiapine and olanzapine-fluoxetine combination), and these were as likely to provide therapeutic benefit as adverse effects. We assessed the efficacy, safety, and tolerability of lurasidone for major depressive episodes associated with bipolar I disorder, using number needed to treat (NNT, for benefits), number needed to harm (NNH, for harms), and likelihood of being helped or harmed (LHH, ratio of NNH to NNT, for trade-offs between benefits versus harms). Methods: Data were collected from two 6-week multicenter, randomized, double-blind, placebo-controlled, flexibly dosed acute bipolar I depression studies, one using lurasidone monotherapy at 20–60 mg/d or 80–120 mg/d, and the other using lurasidone 20–120mg/d adjunctive to lithium or valproate. The NNT or NNH was calculated for lurasidone versus placebo for the following dichotomous outcomes: response (≥50% reduction from baseline on Montgomery Asberg Depression Rating Scale [MADRS] total score); remission (final MADRS total score ≤12); discontinuation due to an adverse event (AE); weight gain ≥7% from baseline; incidence of spontaneously reported AEs; and incidence of total cholesterol ≥240 mg/dl, low-density lipoprotein cholesterol ≥160 mg/dl, fasting triglycerides ≥200 mg/dl, and glucose ≥126 mg/dl postbaseline. Results: NNT versus placebo for response was 5 for lurasidone monotherapy (both dose ranges) and 7 for adjunctive therapy. NNT versus placebo for remission for lurasidone monotherapy was 6 for 20–60 mg/d and 7 for 80–120 mg/d and 7 for adjunctive lurasidone. NNH versus placebo for discontinuation due to an AE for lurasidone monotherapy was 642 for 20–60 mg/d and −181 for 80–120 mg/d, and for adjunctive lurasidone was −54 (negative NNH denotes an advantage for lurasidone). Lurasidone was not associated with any clinically meaningful mean weight or metabolic changes compared with placebo; NNH versus placebo for weight gain ≥7% was 29 for 20–60 mg/d and 5550 for 80–120 mg/d and 42 for adjunctive lurasidone. The three most frequently occurring AEs with the largest difference in incidence for lurasidone versus placebo were nausea, akathisia, and somnolence, with NNH values for lurasidone versus placebo ranging from 11 (nausea with lurasidone monotherapy 80–120 mg/d) to 130 (somnolence with lurasidone monotherapy 20–60 mg/d). LHH was substantially and consistently >1 (indicating benefit being more likely than harm) when contrasting response or remission versus AEs or weight gain. Limitations: Additional studies, including longer-term and open-label, “real world” data are needed to confirm the results reported here. Conclusions: NNT, NNH, and LHH help quantify relative benefits (efficacy) and harms (side effects), thus placing lurasidone findings in research studies into clinical perspective. Lurasidone, compared with other treatments approved for bipolar depression, yielded comparable benefits (all had single-digit NNT versus placebo for response or remission), and less risk of harm (double-digit or greater NNHs with lurasidone compared with single-digit NNHs for sedation with quetiapine and for ≥7% weight gain with olanzapine-fluoxetine combination), and thus a substantially more favorable LHH (> or >>1) with lurasidone monotherapy and adjunctive therapy, compared with quetiapine and olanzapine-fluoxetine combination (LHH < or ∼ 1).

Reprinted with permission from Elsevier.

Miklowitz DJ, Schneck CD, George EL, Taylor D.O., Sugar CA, Birmaher B, Kowatch RA, DelBello MP, Axelson DA.

Am J Psychiatry 2014; 171:658–667

Objective: Previous studies have found that family-focused treatment is an effective adjunct to pharmacotherapy in stabilizing symptoms in adult bipolar disorder. The authors examined whether pharmacotherapy and family-focused treatment for adolescents with bipolar disorder was more effective than pharmacotherapy and brief psychoeducation (enhanced care) in decreasing time to recovery from a mood episode, increasing time to recurrence, and reducing symptom severity over 2 years. Method: A total of 145 adolescents (mean age, 15.6 years) with bipolar I or II disorder and a DSM-IV-TR manic, hypomanic, depressive, or mixed episode in the previous 3 months were randomly assigned, with family members, either to pharmacotherapy and family-focused treatment, consisting of psychoeducation (i.e. recognition and early intervention with prodromal symptoms), communication enhancement training, and problem-solving skills training, delivered in 21 sessions over 9 months; or to pharmacotherapy and three weekly sessions of enhanced care (family psychoeducation). Independent evaluators assessed participants at baseline, every 3 months during year 1, and every 6 months during year 2, using weekly ratings of mood. Results: Twenty-two participants (15.2%) withdrew shortly after randomization. Time to recovery or recurrence and proportion of weeks ill did not differ between the two treatment groups. Secondary analyses revealed that participants in family-focused treatment had less severe manic symptoms during year 2 than did those in enhanced care. Conclusions: After an illness episode, intensive psychotherapy combined with best-practice pharmacotherapy does not appear to confer advantages over brief psychotherapy and pharmacotherapy in hastening recovery or delaying recurrence among adolescents with bipolar disorder.

Craddock N, Sklar P.

Lancet 2013; 381:1654–1662

Studies of families and twins show the importance of genetic factors affecting susceptibility to bipolar disorder and suggest substantial genetic and phenotypic complexity. Robust and replicable genome-wide significant associations have recently been reported in genome-wide association studies at several common polymorphisms, including variants within the genes CACNA1C, ODZ4, and NCAN. Strong evidence exists for a polygenic contribution to risk (i.e. many risk alleles of small effect). A notable finding is the overlap of susceptibility between bipolar disorder and schizophrenia for several individual risk alleles and for the polygenic risk. By contrast, genomic structural variation seems to play a smaller part in bipolar disorder than it does in schizophrenia. Together, these genetic findings suggest directions for future studies to delineate the etiology and pathogenesis of bipolar disorder, indicate the need to re-evaluate our diagnostic classifications, and might eventually pave the way for major improvements in clinical management.

Reprinted with permission from Elsevier.

Deckersbach T, Peters AT, Sylvia L, Urdahl A, Magalhães PV, Otto MW, Frank E, Miklowitz DJ, Berk M, Kinrys G, Nierenberg A.

Am J Psychiatry 2014; 171:178–186

Objective: At least 50% of individuals with bipolar disorder have a lifetime anxiety disorder. Individuals with both bipolar disorder and a co-occurring anxiety disorder experience longer illness duration, greater illness severity, and poorer treatment response. The study explored whether comorbid lifetime anxiety in bipolar patients moderates psychotherapy treatment outcome. Method: In the Systematic Treatment Enhancement Program randomized controlled trial of psychotherapy for bipolar depression, participants received up to 30 sessions of intensive psychotherapy (family-focused therapy, interpersonal and social rhythm therapy, or cognitive-behavioral therapy) or collaborative care, a three-session comparison treatment, plus pharmacotherapy. Using the number needed to treat, we computed effect sizes to analyze the relationship between lifetime anxiety disorders and rates of recovery across treatment groups after 1 year. Results: A total of 269 patients (113 women) with a comorbid lifetime anxiety disorder (N=177) or without a comorbid lifetime anxiety disorder (N=92) were included in the analysis. Participants with a lifetime anxiety disorder were more likely to recover with psychotherapy than with collaborative care (66% compared with 49% recovered over 1 year; number needed to treat=5.88, small to medium effect). For patients without a lifetime anxiety disorder, there was no difference between rates of recovery in psychotherapy compared with collaborative care (64% compared with 62% recovered; number needed to treat=50, small effect). Participants with one lifetime anxiety disorder were likely to benefit from intensive psychotherapy compared with collaborative care (84% compared with 53% recovered; number needed to treat=3.22, medium to large effect), whereas patients with multiple anxiety disorders exhibited no difference in response to the two treatments (54% compared with 46% recovered; number needed to treat=12.5, small effect). Conclusions: Depressed patients with bipolar disorder and comorbid anxiety may be in particular need of additional psychotherapy for treating acute depression. These results need to be replicated in studies that stratify bipolar patients to treatments based on their anxiety comorbidity status.

Scott EM, Hermens DF, Naismith SL, Guastella AJ, De Regt T, White D, Lagopoulos J, Hickie IB.

J Affect Disord 2013; 144:208–215

Background: To facilitate early intervention, there is a need to distinguish unipolar versus bipolar illness trajectories in adolescents and young adults with adult-type mood disorders. Methods: Detailed clinical and neuropsychological evaluation of 308 young persons (aged 12 to 30 years) with moderately severe unipolar and bipolar affective disorders. Results: Almost 30% (90/308) of young people (mean age=19.4±4.4 yr) presenting for care with affective disorders met criteria for a bipolar-type syndrome (26% with bipolar I). Subjects with bipolar- and unipolar-type syndromes were of similar age (19.8 versus 19.2 yr) and reported comparable ages of onset (14.5 versus 14.3 yr). Clinically, those subjects with unipolar and bipolar-type disorders reported similar levels of psychological distress, depressive symptoms, current role impairment, neuropsychological dysfunction, and alcohol or other substance misuse. Subjects with unipolar disorders reported more social anxiety (p<0.01). Subjects with bipolar disorders were more likely to report a family history of bipolar (21% versus 11%; [χ(2)=4.0, p<0.05]) or psychotic (19% versus 9%; [χ(2)=5.5, p<0.05]), or substance misuse (35% versus 23%; [χ(2)=3.9, p<0.05]), but not depressive (48% versus 53%; χ(2)=0.3, p=0.582]) disorders. Conclusions: Young subjects with bipolar disorders were best discriminated by a family history of bipolar, psychotic, or substance use disorders. Early in the course of illness, clinical features of depression, or neuropsychological function, do not readily differentiate the two illness trajectories.

Reprinted with permission from Elsevier.

Swann AC, Lafer B, Perugi G, Frye MA, Bauer M, Bahk WM, Scott J, Ha K, Suppes T.

Am J Psychiatry 2013; 170:31–42

Objective: Episodes of bipolar disorder are defined as depressive or manic, but depressive and manic symptoms can combine in the same episode. Coexistence or rapid alternation of depressive and manic symptoms in the same episode may indicate a more severe form of bipolar disorder and may pose diagnostic and treatment challenges. However, definitions of mixed states, especially those with prominent depression, are not well established. Method: The authors performed literature searches for bipolar disorder, multivariate analyses, and the appearance of the terms “mixed” in any field; references selected from the articles found after the search were combined after a series of conferences among the authors. Results: The authors reviewed the evolution of the concept of mixed states and examined the symptom structure of mixed states studied as predominantly manic, predominantly depressive, and across both manic and depressive episodes, showing essentially parallel structures of mixed states based on manic or depressive episodes. The authors analyzed the relationships between mixed states and a severely recurrent course of illness in bipolar disorder, with early onset and increased co-occurring anxiety-, stress-, and substance-related disorders, and they used this information to derive proposed diagnostic criteria for research or clinical use. Conclusions: The definitions and properties of mixed states have generated controversy, but the stability of their characteristics over a range of clinical definitions and diagnostic methods shows that the concept of mixed states is robust. Distinct characteristics related to the course of illness emerge at relatively modest opposite polarity symptom levels in depressive or manic episodes.

Modabbernia A, Taslimi S, Brietzke E, Ashrafi M.

Biol Psychiatry 2013; 74:15–25

Background: We conducted a meta-analysis of studies comparing cytokine concentrations between patients with bipolar disorder (BD) and healthy control subjects (HCs). Methods: We searched ISI Web of Science, MEDLINE, BIOSIS Previews, Scopus, Current Contents Connect, and Biological Abstracts for relevant studies. Based on heterogeneity status, we used fixed-effect or restricted maximal likelihood model to perform meta-analysis. Results: Thirty studies with a total of 2599 participants (1351 BD and 1248 HCs) were eligible for the analysis. Concentrations of interleukin (IL)-4 (p=0.008), IL-6 (p=0.073), IL-10 (p=0.013), soluble IL-2 receptor (sIL-2R; p<0.001), sIL-6R (p=0.021), tumor necrosis factor (TNF)-α (p=0.010), soluble TNF receptor-1 (sTNFR1; p<0.001), and IL-1 receptor antagonist (p value in mania<0.001 and euthymia=0.021) were significantly elevated in patients compared with HCs. Moreover, IL-1β (p=0.059) and IL-6 (p=0.073) tended to show higher values in patients. Levels of IL-2 (p=0.156), interferon (INF)-γ (p=0.741), C-C motif ligand 2 (p=0.624), and IL-8 (p=0.952) did not significantly differ between patients and HCs. Subgroup analysis based on mitogen stimulation status partially or completely resolved heterogeneity for most of the cytokines. Concentrations of IL-2, IL-4, sIL-6R, and INF-γ were unrelated to medication status. Phasic difference was present for TNF-α, sTNFR1, sIL-2R, IL-6, and IL-1RA, whereas it was absent for IL-4 and IL-10. Conclusions: This meta-analysis provides evidence for significant elevation of proinflammatory, anti-inflammatory, and regulatory cytokines in BD.

Reprinted with permission from Elsevier.

Brietzke E, Mansur RB, Soczynska JK, Kapczinski F, Bressan RA, McIntyre RS.

J Affect Disord 2012;140:82–91

Background: The high prevalence, recurrence rate, chronicity, and illness burden in bipolar disorder (BD) are well documented. Moreover, insufficient response with conventional pharmacological and manual-based psychosocial interventions, as well as evidence of illness progression and acceleration, invite the need for early detection and primary prevention. Methods: Herein we comprehensively review extant studies reporting on a bipolar prodrome. The overarching aim is to propose a predictive algorithm (i.e. prediction of BD in at-risk populations) integrating genetic (i.e. family history), environmental (e.g. childhood maltreatment), and biological markers (i.e. BDNF, inflammatory, and oxidative stress markers). Computerized databases i.e. Pubmed, PsychInfo, Cochrane Library and Scielo were searched using the followed terms: bipolar disorder cross-referenced with prodromal, preclinical, at risk mental states, clinical high risk, ultra high risk, biomarkers, brain-derived neurotrophic factor, inflammation, cytokines, oxidative stress, prediction, and predictive model. Results: Available evidence indicates that a prodrome to bipolar disorder exists. Commonly encountered features preceding the onset of a manic episode are affective lability, irritability, anger, depression, anxiety, substance use disorders, sleep disorders, as well as disturbances in attention and cognition. Nonspecificity and insufficient sensitivity have hampered the development of an adequate prediction algorithm. Limitations: Limitations include biases associated with retrospective studies, poor characterization of clinical high risk, inadequacy of prospective studies regarding sample selection, and absence of specificity of risk states. Conclusion: We propose a hypothetical prediction algorithm that is combinatorial in approach that attempts to integrate family history, early adversity, and selected biomarkers.

Reprinted with permission from Elsevier.