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Background: Convergent evidence implicates gut microbiota in human health and disease. Hitherto, relatively few studies have evaluated the gut microbiota profile in individuals with bipolar disorder (BD) relative to healthy controls (HC). Methods: Fecal samples were collected from subjects (aged 18–65) meeting DSM-5-defined criteria for BD and age- and sex-matched HC without current or past history of mental or major medical disorders. Samples were sequenced using Illumina sequencing and association of specific taxa and co-occurrence of taxa with sample groups including the effect of diet was assessed using cluster analysis and analysis of communities of microorganisms (ANCOM). Nutritional composition was evaluated using the Dietary Questionnaire for Epidemiological Studies (DQES v2) Food Frequency Questionnaire. Results: Forty-six subjects were enrolled (n=23 BD, n=23 HC). Cluster analyses did not identify any significant differences between BD and HC (p=0.38). Lower microbiota diversity was observed among BD subjects relative to HC (p=0.04). A greater abundance of a Clostridiaceae OTU was observed among BD subjects when compared to HC and of Collinsella among BD-II subjects relative to BD-I. Cluster analysis revealed that neither diagnosis (p=0.38) nor diet (p=0.43) had a significant effect on overall gut microbiota composition. Limitations: This study has a small sample size and insufficient control for some potential moderating factors (e.g. psychotropic medication and smoking). Conclusion: This study suggests that individuals with BD may have a distinct gut microbiota profile compared to healthy controls, with a greater abundance of Clostridiaceae and Collinsella. These findings need to be replicated in future studies with larger sample sizes. [ABSTRACT FROM AUTHOR]

Background: Herein, we sought to determine the sensitivity to change in cognitive function, as measured by the THINC-it tool, in a sample of adults with major depressive disorder (MDD) receiving standardized antidepressant therapy. Methods: Adults meeting the DSM-5 criteria for MDD with at least moderate depressive symptom severity [ i.e. , Montgomery Åsberg Depression Rating Scale (MADRS) total score ≥ 20] were treated with open-label vortioxetine (10–20 mg/day, flexibly-dosed) for 8 weeks. The previously validated THINC-it tool was the primary dependent measure. The THINC-it tool was validated against the paper and pencil version of the Digit Symbol Substitution Test (DSST) and the Trails Making Test B (TMTB). Results: After 8 weeks of treatment, adults with MDD exhibited improvement in cognitive function relative to healthy controls (e.g. , processing speed) (p = 0.031). A subdomain measure of working memory (i.e. , symbol check; SC) exhibited significant improvement at Weeks 2 and 8 in latency (p = 0.032), SC accuracy (p = 0.046), and objective z-score (p = 0.001) independent of depressive symptoms. A linear regression analysis determined that the THINC-it tool measures of processing speed, as well as executive function were significantly associated with changes observed on the pencil and paper version the Digit Symbol Substitution Test (DSST) (p = 0.002) and in Trails Making Test B (TMTB) (p = 0.003), respectively. Conclusion: The THINC-it tool demonstrates sensitivity to change in adults with MDD and is highly correlated with improvements on pencil and paper versions of DSST and TMTB. Clinical Trial Registration: ClinicalTrials.gov, identifier NCT03053362. [ABSTRACT FROM AUTHOR]

Background Despite the widespread use of antidepressants in clinical practice, the current trial-and-error approach to medication selection contributes to treatment failure and underscores the need to identify reliable predictors of antidepressant response. Since changes in measures of cognition have been reported to occur early in treatment and prior to improvements in overall mood symptoms, the present review aims to determine whether early changes in measures of cognition can predict response in individuals with MDD. Methods A systematic review of studies evaluating early cognitive change as a predictor of later treatment response in MDD was conducted using PubMed/Medline, Embase and PsychINFO. Results A total of seven articles were identified. The available evidence suggests the early changes in cognition may predict treatment response in individuals with MDD. This was shown across antidepressant classes (i.e., SSRIs, SNRIs, NRIs, melatonergic antidepressants) and forms of therapy (i.e., pharmacotherapy, rTMS). The results depict an emerging trend towards early changes in facial emotion recognition (i.e., a hot cognitive process) as a predictor of treatment outcome. Limitations Our qualitative analysis reflects a very limited number of studies. Moreover, there was significant heterogeneity in the evaluation of cognition across studies. Future research should aim to parse out this heterogeneity by evaluating the relative predictive value of different measures of cognition. Conclusion The identification of reliable early treatment predictors of antidepressant response would be clinically significant, enabling clinicians to more accurately evaluate the efficacy of selected treatment avenues. [ABSTRACT FROM AUTHOR]

Cognitive dysfunction is a symptomatic domain identified across many mental disorders. Cognitive deficits in individuals with major depressive disorder (MDD) contribute significantly to occupational and functional disability. Notably, cognitive subdomains such as learning and memory, executive functioning, processing speed, and attention and concentration are significantly impaired during, and between, episodes in individuals with MDD. Most antidepressants have not been developed and/or evaluated for their ability to directly and independently ameliorate cognitive deficits. Multiple interacting neurobiological mechanisms (eg, neuroinflammation) are implicated as subserving cognitive deficits in MDD. A testable hypothesis, with preliminary support, posits that improving performance across cognitive domains in individuals with MDD may improve psychosocial function, workplace function, quality of life, and other patient-reported outcomes, independent of effects on core mood symptoms. Herein we aim to (1) provide a rationale for prioritizing cognitive deficits as a therapeutic target, (2) briefly discuss the neurobiological substrates subserving cognitive dysfunction, and (3) provide an update on current and future treatment avenues.