Search

Summary: Sleep disturbances are commonly reported in patients with treatment‐resistant depression (TRD). Available data have shown that intravenous (IV) ketamine is an effective treatment for patients with TRD and growing data suggest ketamine may improve overall sleep architecture. In the present study, we evaluated whether changes in sleep symptoms mediated the anti‐depressive and/or anti‐suicidal effects of IV ketamine and whether improvement in sleep correlated with a higher likelihood of achieving response or remission. Adults with TRD received four infusions of IV ketamine at a community‐based clinic. Total depressive symptom severity was measured with the Quick Inventory Depressive Symptoms Self‐Report 16‐Item (QIDS‐SR16) at baseline and was repeated across four infusions. Suicidal ideation (SI) and four sleep symptoms were measured using the SI item and the five sleep items on the QIDS‐SR16. A total of 323 patients with TRD received IV ketamine. Self‐reported improvements in insomnia, night‐time restlessness, hypersomnia, early morning waking, and total sleep were significant partial mediators to the improvements observed in depression severity. Similarly, insomnia, night‐time restlessness, early morning waking and total sleep improvements mediated the reduction of IV ketamine on SI. All sleep items, except for hypersomnia, were associated with an increased likelihood of achieving response or remission. Notably, each point improvement in total sleep score was significantly associated with achieving responder/remitter status (odds ratio 3.29, 95% confidence interval 2.00–5.41). Insomnia, sleep restlessness, early morning waking and total sleep improvements were significant mediators of antidepressant and anti‐suicidal improvements in patients with TRD receiving IV ketamine. [ABSTRACT FROM AUTHOR]

Objectives: Clinical staging is widely used in medicine to map disease progression, inform prognosis, and guide treatment decisions; in psychiatry, however, staging remains a hypothetical construct. To facilitate future research in bipolar disorders (BD), a well‐defined nomenclature is needed, especially since diagnosis is often imprecise with blurred boundaries, and a full understanding of pathophysiology is lacking. Methods: Under the auspices of the International Society of Bipolar Disorders, a Task Force of international experts was convened to review, discuss, and integrate findings from the scientific literature relevant to the development of a consensus staging model and standardize a terminology that could be used to advance future research including staging of BD and related disorders. Results: Consensus opinion and areas of uncertainty or difference were identified in regard to terms referring to staging as it may apply to BD, to at‐risk status and subthreshold stages, and to various clinical stages of BD as it is currently diagnosed. Conclusion: The use of a standardized nomenclature about the clinical stages of BD will facilitate communication about research on clinical and pathological components of this heterogeneous group of disorders. The concepts presented are based on current evidence, but the template provided allows for further refinements as etiological advances come to light. [ABSTRACT FROM AUTHOR]

Objective: To determine the effectiveness of intravenous (IV) ketamine on anxiety, irritability, agitation, and suicidality, in adults with treatment‐resistant major depressive disorder (MDD) or bipolar disorder (BD). Method: Adults (N = 201) with treatment‐resistant MDD or BD received repeat‐dose IV ketamine treatment at a community‐based clinic. Mixed features were measured using symptoms of anxiety, irritability, and agitation (AIA), as measured by the Generalized Anxiety Disorder‐7 (GAD‐7) scale. The Quick Inventory for Depressive Symptomatology Self‐Report‐16 (QIDS‐SR16) was used to measure overall treatment response, and the QIDS‐SR16 suicidal ideation (SI) item was used to measure change in SI symptoms with ketamine treatment. The anxiety, irritability, and agitation items on the GAD‐7 were used to assess effectiveness of IV ketamine in treating symptoms of mixed features. Results: In this retrospective analysis, 113 participants met AIA criteria. Participants with AIA experienced a significantly greater reduction in overall depressive symptoms (F(1, 558) = 9.49, P =.002), SI (F(1, 558) = 3.103, P =.079), anxiety (F(1, 198) = 5.52, P =.007), irritability (F(1, 198) = 28.35, P <.001), and agitation as measured by "trouble relaxing" (F(1, 198) = 6.70, P =.010) from baseline compared to the non‐AIA group, regardless of number of treatments received. Conclusions: Our preliminary results suggest that IV ketamine is effective in rapidly treating AIA and SI in adults with treatment‐resistant mood disorders. This observation suggests that IV ketamine could be considered a treatment alternative for adults with MDD or BD presenting with mixed features. [ABSTRACT FROM AUTHOR]

Antidepressant medications are the first-line treatment option for moderate to severe major depressive disorder. However, most antidepressants have numerous documented adverse events, including cardiometabolic effects and weight gain, which are major public health concerns. Antidepressant agents provide varying risk of associated weight gain, including significant within-class differences. Some agents, such as mirtazapine, show significant levels of weight gain, while others, such as bupropion, demonstrate weight-loss effects. Current findings suggest the role of histamine and serotonin off-target appetite-promoting pathways in adverse weight-gain effects. Therefore, controlling for undesired weight effects is an important consideration for the selection of antidepressants. [ABSTRACT FROM AUTHOR]

Objectives: Metabolically based distinctions for disturbances in glucose and insulin may provide meaningful insights both clinically and mechanistically. Methods: Data were derived from 352 subjects of previously completed clinical studies with a mood disorder (MD) (bipolar disorder: n = 179, major depressive disorder: n = 173) and 218 healthy controls from the Comprehensive Assessment of Long‐Term Effects of Reducing Intake of Energy. We conducted a factor analysis to replicate a priori dissociable factors informed by glucose and insulin levels and indices of insulin resistance and beta‐cell function: elevated insulin and insulin resistance ("insulin‐IR"), and increased fasting glucose and reduced insulin secretion ("glucotoxicity"). Cluster analyses were conducted, separately in men and women, to evaluate the clinical relevance of subtyping individuals with MDs using insulin‐IR and glucotoxicity (GT) factor scores. Results: Factors insulin‐IR and GT explained 92.64% and 92.09% of the variance in men and women respectively. Three clusters were replicated in men and women separately: metabolically healthy (MH), high GT, and insulin‐resistant (IR). After adjusting for age, gender, study cohort, MD diagnosis, and antipsychotics use, body mass index (BMI) and mean arterial pressure were higher in IR‐ vs GT‐ or MH‐clustered individuals; GT‐clustered individuals had more metabolic syndrome components and higher C‐reactive protein. Glucotoxic‐clustered subjects reported greater impairments in cognitive function and global functioning when compared to MH‐ or IR‐clustered subjects. Conclusions: Using simple, cost‐effective, and accessible measures, we identified stable, gender‐convergent, subgroups of individuals that significantly diverged on measures of cognitive dysfunction, self‐reported anhedonia, functional disability, BMI, and blood pressure. [ABSTRACT FROM AUTHOR]

With establishing biomarker fingerprints longitudinally in a reliable and reproducible manner will open the door for reliable stratification methods to determine the BD subgroup that would respond to anti-inflammatory treatments with potential disease-modifying effects. Bipolar disorder (BD) is a major cause of morbidity and mortality, and it is the leading cause of disability worldwide. The interaction between inflammatory processes and mood disorders has been extensively investigated.3 Convergent results from largely cross-sectional epidemiological and clinical studies indicate a subpopulation of BD has a biotype of chronic low-grade inflammation. [Extracted from the article]

Objectives: The International Society for Bipolar Disorders Big Data Task Force assembled leading researchers in the field of bipolar disorder (BD), machine learning, and big data with extensive experience to evaluate the rationale of machine learning and big data analytics strategies for BD. Method: A task force was convened to examine and integrate findings from the scientific literature related to machine learning and big data based studies to clarify terminology and to describe challenges and potential applications in the field of BD. We also systematically searched PubMed, Embase, and Web of Science for articles published up to January 2019 that used machine learning in BD. Results: The results suggested that big data analytics has the potential to provide risk calculators to aid in treatment decisions and predict clinical prognosis, including suicidality, for individual patients. This approach can advance diagnosis by enabling discovery of more relevant data‐driven phenotypes, as well as by predicting transition to the disorder in high‐risk unaffected subjects. We also discuss the most frequent challenges that big data analytics applications can face, such as heterogeneity, lack of external validation and replication of some studies, cost and non‐stationary distribution of the data, and lack of appropriate funding. Conclusion: Machine learning‐based studies, including atheoretical data‐driven big data approaches, provide an opportunity to more accurately detect those who are at risk, parse‐relevant phenotypes as well as inform treatment selection and prognosis. However, several methodological challenges need to be addressed in order to translate research findings to clinical settings. [ABSTRACT FROM AUTHOR]

This study (registered with PROSPERO, CRD42018085967) compares the efficacy (i.e. pro‐cognitive effects) and acceptability of antidiabetic agents for Alzheimer's disease (AD) and mild cognitive impairment (MCI). Cochrane Library (CENTRAL), PubMed/MEDLINE, EMBASE and PsycINFO were searched from inception to January 15, 2018 for randomized controlled trials comparing antidiabetic agents with placebo and/or another active antidiabetic agent for the treatment of AD or MCI. Nineteen eligible studies (n = 4855) evaluating the effects of 6 different antidiabetic drugs (i.e. intranasal insulin, pioglitazone, rosiglitazone, metformin, sitagliptin and liraglutide) were included. The results of 29 pairwise comparisons indicated that cognition was significantly improved in subjects treated with antidiabetic agents compared with placebo. Pioglitazone 15 to 30 mg demonstrated the greatest efficacy compared to placebo in network meta‐analysis. No significant differences in acceptability were identified when comparing agents with each other and with placebo. The current findings indicate a pro‐cognitive class effect of antidiabetic agents in AD/MCI. Other antidiabetic agents should also be investigated in future studies. [ABSTRACT FROM AUTHOR]

Abstract: Objectives: There is a need for a brief, reliable, valid, and sensitive assessment tool for screening cognitive deficits in patients with Major Depressive Disorders. This paper examines the psychometric characteristics of THINC‐it, a cognitive assessment tool composed of four objective measures of cognition and a self‐rated assessment, in subjects without mental disorders. Methods: N = 100 healthy controls with no current or past history of depression were tested on four sequential assessments to examine temporal stability, reliability, and convergent validity of the THINC‐it tests. We examined temporal reliability across 1 week and stability via three consecutive assessments. Consistency of assessment by the study rater (intrarater reliability) was calculated using the data from the second and third of these consecutive assessments. Results: Test–retest reliability correlations varied between Pearson's r = 0.75 and 0.8. Intrarater reliability between 0.7 and 0.93. Stability for the primary measure for each test yielded within‐subject standard deviation values between 5.9 and 11.23 for accuracy measures and 0.735 and 17.3 seconds for latency measures. Convergent validity for three tasks was in the acceptable range, but low for the Symbol Check task. Conclusions: Analysis shows high levels of reliability and stability. Levels of convergent validity were modest but acceptable in the case of all but one test. [ABSTRACT FROM AUTHOR]

Objectives: To compare frontal‐striatal brain volumes between offspring of individuals with bipolar disorder (BD) and healthy controls; to investigate the associations of body mass index (BMI) and age with brain volumes; and to assess the moderating effects of BMI and age on the relationship between risk status and structural brain differences. Methods: We cross‐sectionally assessed structural regional and global brain volumes using magnetic resonance imaging and BMI among 53 BD offspring subjects, stratified by risk status, and 23 non‐BD offspring controls (aged 8‐28 years). Analyses of variance and covariance and linear regression analyses were conducted to investigate the associations between BMI and measures of brain volume, as well as the interaction effects between age, BMI, and risk status on brain volumes. Results: After adjusting for age, sex, and intracranial volume, higher BD risk status was associated with lower bilateral cerebellar cortical and right pars orbitalis volumes. Higher BMI was significantly associated with greater brain volumes in frontal and subcortical structures. A significant interaction effect between BMI and risk status was observed in right middle frontal volume. The moderating effect of BMI on brain volume was most robustly observed among subjects aged 14‐19 years and less robustly observed among those aged 20‐28 years; BMI and brain volumes were negatively correlated among subjects aged 8‐13 years. Conclusions: Alterations in brain structures in individuals at risk for BD may be moderated by BMI. Obesity among individuals with a family history of BD may confer additional risk, particularly in mid‐adolescence. [ABSTRACT FROM AUTHOR]

Aim This study aimed to compare plasma copeptin levels, the c-terminal of provasopressin, between individuals with bipolar disorder (BD) and healthy controls and to assess the relation between copeptin and metabolic parameters. Methods We measured plasma levels of copeptin in individuals with BD ( n = 55) and healthy controls ( n = 21). Information related to psychiatric/medical history, as well as to metabolic comorbidities and laboratorial parameters was also captured. Insulin resistance and β-cell function in basal state were calculated from fasting plasma glucose and C-peptide using the HOMA2 calculator. Impaired glucose metabolism was defined as pre-diabetes or type 2 diabetes mellitus. Copeptin, adiponectin, and leptin plasma levels were determined by enzyme-linked immunosorbent assay. Results Plasma copeptin levels were lower in individuals with BD, relative to healthy controls ( P < 0.001). There were significant interactions between BD and plasma copeptin on β-cell function (rate ratio [RR] = 1.048; P = 0.030) and on leptin levels (RR = 1.087; P = 0.012), indicating that there was a positive correlation between these markers in the BD group, but a negative one in healthy controls. Finally, in individuals with BD only, the association between β-cell function, body mass index (RR = 1.007; P < 0.001), and insulin resistance (RR = 1.001; P = 0.037) was moderated by copeptin levels. Conclusion Copeptin levels were lower in individuals with BD than in healthy controls. There were differential associations between copeptin and metabolic parameters within the BD and healthy control subgroups, suggesting an association between abnormal copeptin and metabolic dysregulation only in the BD population. [ABSTRACT FROM AUTHOR]

Objectives The objectives of the study were to determine if adjunctive minocycline mitigates depressive symptom severity and improves cognitive function in individuals with bipolar I/ II disorder ( BD). The study also aimed to determine if changes in depressive and/or cognitive symptoms over the course of treatment were associated with changes in circulating inflammatory cytokine levels. Methods A total of 29 (intention-to-treat: n=27) adults meeting DSM- IV- TR criteria for a major depressive episode as part of bipolar I or II disorder (i.e. Hamilton Depression Rating Scale 17-item [ HAMD-17] ≥20) were enrolled in an 8-week, open-label study with adjunctive minocycline (100 mg bid). The primary outcome measure was the Montgomery−Åsberg Depression Rating Scale ( MADRS). The HAMD-17, Clinical Global Impression-Severity ( CGI-S), cognitive test composite scores and plasma cytokines were secondary outcome measures. Plasma cytokines were measured with the 30 V-Plex Immunoassay from Meso Scale Discovery. Results Adjunctive minocycline was associated with a reduction in depressive symptom severity from baseline to week 8 on the MADRS ( P<.001, d=0.835), HAMD-17 ( P<.001, d=0.949) and CGI-S ( P<.001, d=1.09). Improvement in psychomotor speed, but not verbal memory or executive function, was observed only amongst individuals exhibiting a reduction in depression severity ( P=.007, d=0.826). Levels of interleukin ( IL)-12/23p40 ( P=.002) were increased, while levels of IL-12p70 ( P=.001) and C-C motif chemokine ligand 26 (CCL26) ( P<.001) were reduced from baseline to week 8. A reduction in CCL26 levels was associated with a less favourable treatment response ( P<.001). Conclusions Results from the pilot study suggest that adjunctive minocycline may exert antidepressant effects in individuals with bipolar depression, possibly by targeting inflammatory cytokines. [ABSTRACT FROM AUTHOR]

Background The burden of illness associated with bipolar disorder ( BD) warrants early pre-emption/prevention. Prediction models limited to psychiatric phenomenology have insufficient predictive power. Herein, we aimed to evaluate whether the presence of overweight/obesity is associated with greater cognitive decline in individuals at high risk ( HR) or ultra high risk ( UHR) for BD. Methods We conducted a retrospective analysis to investigate the moderational role of body mass index ( BMI) on measures of cognitive function. Subjects between the ages of 8 and 28 years with a positive family history of BD were compared to age-matched controls with a negative family history of BD. Subjects with at least one biological parent with bipolar I/ II disorder were further stratified into UHR or HR status by the presence or absence, respectively, of subthreshold hypomanic, major depressive, attenuated psychotic, and/or attention-deficit/hyperactivity disorder symptoms. Results A total of 36 individuals at HR for BD, 33 individuals at UHR for BD, and 48 age-matched controls were included in the analysis. Higher BMI was significantly associated with lower performance on measures of processing speed (i.e. Brief Assessment of Cognition in Schizophrenia−symbol coding: r=−.186, P=.047) and attention/vigilance (i.e. Continuous Performance Test−Identical Pairs: r=−.257, P=.006). There were trends for negative correlations between BMI and measures of working memory (i.e. Wechsler Memory Scale- III Spatial Span: r=−0.177, P=.059) and overall cognitive function (i.e. Measurement and Treatment Research to Improve Cognition in Schizophrenia composite score: r=−.157, P=.097). Negative associations between BMI and cognitive performance were significantly stronger in the UHR group than in the HR group, when compared to controls. Conclusions Individuals at varying degrees of risk for BD exhibit greater cognitive impairment as a function of co-existing overweight/obesity. Prediction models for BD may be substantively informed by including information related to overweight/obesity and, perhaps, other general medical conditions that share pathology with BD. Our findings herein, as well as the salutary effects of bariatric surgery on measures of cognitive function in obese populations, provide the rationale for hypothesizing that mitigating excess weight in individuals at elevated risk for BD may forestall or prevent declaration of illness. [ABSTRACT FROM AUTHOR]

Objectives Accumulating evidence indicates that oxidative stress and neurotrophins have a bidirectional relationship. In this post hoc, exploratory analysis, we investigated the association between plasma brain-derived neurotrophic factor (BDNF) levels and activities of the antioxidant enzymes glutathione peroxidase (GPx) and superoxide dismutase (SOD) in individuals with bipolar disorder (BD) and healthy controls. Methods We measured plasma levels of BDNF and activities of GPx and SOD in individuals with BD (n=59) and healthy controls (n=26). Information related to current and past psychiatric/medical history, as well as to metabolic comorbidities, was also reported. Results There were negative correlations between BDNF, GPx ( r=−.449, P≤.001) and GPx/SOD ratio ( r=−.503, P<.001), and a positive correlation between BDNF and SOD ( r=.254, P=.020). There was a moderating effect of body mass index (BMI) on the association between BDNF and GPx/SOD rate ratio [(RR)=1.002, P=.034]; interactions between impaired glucose metabolism (IGM), GPx (RR=1.016, P=.033), and GPx/SOD ratio (RR=1.026, P=.002) were also observed. These results were significant in models that included age, gender, alcohol, tobacco and medication use. Conclusions There was a robust and independent correlation between peripheral BDNF and antioxidant enzyme activities in individuals with BD, which was moderated by metabolic comorbidities. These results reinforce the concept that these systems are associated and further extend knowledge of the putative effect of metabolic comorbidities in the pathophysiological substrates of BD. [ABSTRACT FROM AUTHOR]

Objectives The neurotrophin brain-derived neurotrophic factor ( BDNF) has been proposed as a potential biomarker in bipolar disorder ( BD). However, current evidence is limited and results have been highly heterogeneous. This study aimed to assess the moderating effect of impaired glucose metabolism ( IGM) on plasma levels of BDNF in individuals with BD, and on the relationship between BDNF and variables of illness course. Methods We measured and compared the plasma levels of BDNF in individuals with BD (n=57) and healthy controls (n=26). IGM was operationalized as pre-diabetes or type 2 diabetes mellitus. Information related to current and past psychiatric/medical history, as well as prescription of pharmacological treatments was also captured. Results Individuals with BD had lower levels of BDNF, relative to healthy controls, after adjustment for age, gender, current medications, smoking, alcohol use, and IGM ( P=.046). There was no effect of IGM ( P=.860) and no interaction between BD diagnosis and IGM ( P=.893). Peripheral BDNF levels were positively correlated with lifetime depressive episodes ( P<.001), psychiatric hospitalizations ( P=.001) and suicide attempts ( P=.021). IGM moderated the association between BDNF and the number of previous mood episodes ( P<.001), wherein there was a positive correlation in euglycemic participants and a negative correlation in individuals with IGM. Conclusions BD is independently associated with lower levels of BDNF; IGM may modify the relationship between BDNF and BD course, suggesting an interactive effect of BDNF with metabolic status on illness progression. [ABSTRACT FROM AUTHOR]

Objective Inflammation has been implicated in the risk, pathophysiology, and progression of mood disorders and, as such, has become a target of interest in the treatment of bipolar disorder ( BD). Therefore, the objective of the current qualitative and quantitative review was to determine the overall antidepressant effect of adjunctive anti-inflammatory agents in the treatment of bipolar depression. Methods Completed and ongoing clinical trials of anti-inflammatory agents for BD published prior to 15 May 15 2015 were identified through searching the PubMed, Embase, Psych INFO, and Clinicaltrials.gov databases. Data from randomized controlled trials ( RCTs) assessing the antidepressant effect of adjunctive mechanistically diverse anti-inflammatory agents were pooled to determine standard mean differences ( SMDs) compared with standard therapy alone. Results Ten RCTs were identified for qualitative review. Eight RCTs (n = 312) assessing adjunctive nonsteroidal anti-inflammatory drugs (n = 53), omega-3 polyunsaturated fatty acids (n = 140), N-acetylcysteine (n = 76), and pioglitazone (n = 44) in the treatment of BD met the inclusion criteria for quantitative analysis. The overall effect size of adjunctive anti-inflammatory agents on depressive symptoms was −0.40 (95% confidence interval −0.14 to −0.65, p = 0.002), indicative of a moderate and statistically significant antidepressant effect. The heterogeneity of the pooled sample was low ( I² = 14%, p = 0.32). No manic/hypomanic induction or significant treatment-emergent adverse events were reported. Conclusions Overall, a moderate antidepressant effect was observed for adjunctive anti-inflammatory agents compared with conventional therapy alone in the treatment of bipolar depression. The small number of studies, diversity of agents, and small sample sizes limited interpretation of the current analysis. [ABSTRACT FROM AUTHOR]

Objective To provide a strategic framework for the prevention of bipolar disorder ( BD) that incorporates a 'Big Data' approach to risk assessment for BD. Methods Computerized databases (e.g., Pubmed, PsychInfo, and MedlinePlus) were used to access English-language articles published between 1966 and 2012 with the search terms bipolar disorder, prodrome, 'Big Data', and biomarkers cross-referenced with genomics/genetics, transcriptomics, proteomics, metabolomics, inflammation, oxidative stress, neurotrophic factors, cytokines, cognition, neurocognition, and neuroimaging. Papers were selected from the initial search if the primary outcome(s) of interest was (were) categorized in any of the following domains: (i) 'omics' (e.g., genomics), (ii) molecular, (iii) neuroimaging, and (iv) neurocognitive. Results The current strategic approach to identifying individuals at risk for BD, with an emphasis on phenotypic information and family history, has insufficient predictive validity and is clinically inadequate. The heterogeneous clinical presentation of BD, as well as its pathoetiological complexity, suggests that it is unlikely that a single biomarker (or an exclusive biomarker approach) will sufficiently augment currently inadequate phenotypic-centric prediction models. We propose a 'Big Data'- bioinformatics approach that integrates vast and complex phenotypic, anamnestic, behavioral, family, and personal 'omics' profiling. Bioinformatic processing approaches, utilizing cloud- and grid-enabled computing, are now capable of analyzing data on the order of tera-, peta-, and exabytes, providing hitherto unheard of opportunities to fundamentally revolutionize how psychiatric disorders are predicted, prevented, and treated. High-throughput networks dedicated to research on, and the treatment of, BD, integrating both adult and younger populations, will be essential to sufficiently enroll adequate samples of individuals across the neurodevelopmental trajectory in studies to enable the characterization and prevention of this heterogeneous disorder. Conclusions Advances in bioinformatics using a 'Big Data' approach provide an opportunity for novel insights regarding the pathoetiology of BD. The coordinated integration of research centers, inclusive of mixed-age populations, is a promising strategic direction for advancing this line of neuropsychiatric research. [ABSTRACT FROM AUTHOR]