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Background: Insulin resistance (IR) is a potential predictor of antidepressant treatment response. Aims: We assess changes in IR after antidepressant treatment and whether these changes have any effect on treatment response. Also, to see whether changes in IR mediates relationship between C-reactive protein (CRP) and antidepressant efficacy. Methods: This is a secondary analysis of an 8-week, open-label clinical trial with 95 adults experiencing a major depressive episode. Response to vortioxetine was measured using the Montgomery–Åsberg Depression Rating Scale (MADRS). Generalized estimating equation models were utilized for this intent-to-treat analysis. Results: When adjusted for age, sex, and body mass index, there was a significant increase in IR following treatment in the overall sample (p = 0.035). This finding was detected in treatment non-responders (p = 0.019), whereas it was not observed in responders (p = 0.329). Mediation analysis revealed that change in IR during treatment was responsible for change in MADRS as well as the relationship between baseline CRP and treatment response. Conclusions: Exacerbation of IR during antidepressant treatment mediated non-response. Conversely in treatment responders IR reduced. Like previous studies, baseline CRP moderated treatment response. This relationship was also mediated by changes in IR. These findings further elucidate the role of IR in terms of antidepressant response as well as potentially explain inflammation's relationship with the latter. [ABSTRACT FROM AUTHOR]

Background: Sleep disturbances are frequently reported in patients with major depressive disorder. We aimed to investigate the effects of vortioxetine on sleep quality and association between changes in sleep and treatment response.Methods: This study is a post-hoc analysis of a clinical trial that sought to evaluate the sensitivity to cognitive change of THINC-integrated tool in patients with major depressive disorder. In total, 92 patients (aged 18 to 65) meeting Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria for moderate or severe major depressive disorder and 54 healthy controls were included. All patients received open-label vortioxetine (10-20 mg/day, flexibly dosed) for 8 weeks. Herein, the primary outcomes of interest were changes in sleep, as measured by the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and Insomnia Severity Index, between weeks 0, 2, and 8. The association between changes in sleep and depressive symptom severity was secondarily assessed.Results: We observed that sleep, as indicated by scores of Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and Insomnia Severity Index, was significantly poorer in patients with major depressive disorder compared to healthy controls at weeks 0, 2, and 8 (p < 0.05). Among patients with major depressive disorder, we observed significant improvements on the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale and Insomnia Severity Index between weeks 0 and 8 (p < 0.05). We observed a significant association between improvements on the Pittsburgh Sleep Quality Index, Epworth Sleepiness Scale, and Insomnia Severity Index and improvement of depressive symptoms.Conclusion: Improvement of depressive symptoms in major depressive disorder patients treated with vortioxetine was associated with significant improvements in sleep. Furthermore, improvements in sleep were predictive of antidepressant response and were linearly correlated with improvement in overall depressive symptom severity. [ABSTRACT FROM AUTHOR]

Background: Anhedonia is a common, persistent, and disabling phenomenon in treated adults with Major Depressive Disorder (MDD). Hitherto, relatively few antidepressant agents have been evaluated with respect to their effect on anhedonia in MDD. Methods: This is a post-hoc analysis of a primary study that sought to evaluate the sensitivity to change of the THINC-integrated tool (THINC-it) in MDD (ClinicalTrials.gov Identifier: NCT03053362). Adults meeting DSM-5 criteria for MDD with at least moderate depressive symptom severity [i.e., Montgomery Åsberg Depression Rating Scale (MADRS) total score ≥20] were eligible. Subjects were recruited between October 2017 and August 2018 in Toronto, Ontario at the Brain and Cognition Discovery Foundation. All subjects received open-label vortioxetine (10–20 mg/day, flexibly-dosed) for 8 weeks. Herein, the primary outcome of interest was the change from baseline to endpoint in the Snaith-Hamilton Pleasure Scale (SHAPS) total score, as well as the MADRS anhedonia factor. The mediational effects of improvements in anhedonia on general function and quality of life, as measured by the Sheehan Disability Scale (SDS) and the 5-Item World Health Organization Well-Being Index (WHO-5), were secondarily assessed. Results: A total of 100 subjects with MDD were enrolled in the primary study and began treatment with vortioxetine. Vortioxetine significantly improved anhedonia as evidenced by significant baseline to endpoint improvements in SHAPS and MADRS anhedonia factor scores (p < 0.0001). Improvements in the SHAPS and the MADRS anhedonia factor correlated with improvements in general function (i.e., SDS) and quality of life (i.e., WHO-5) (p < 0.0001). Notably, improvements in anhedonia were found to mediate the association between improvements in overall depressive symptom severity (i.e., MADRS total score) and social functioning (i.e., social life component of the SDS) (p = 0.026). Conclusion: The unmet need in depression is to improve patient functioning and other patient-reported outcomes (e.g., quality of life). Antidepressant interventions capable of attenuating anhedonia as well as cognitive dysfunction in MDD may help in this regard, as improvement in these domains have been associated with improvement in psychosocial function and quality of life. [ABSTRACT FROM AUTHOR]

Background: To assess the effect of insulin resistance (IR) on treatment response to the antidepressant, vortioxetine, in patients with Major Depressive Disorder (MDD).Methods: This is a secondary analysis of an 8-week, open-label clinical trial. Ninety-five adults in a primary care setting experiencing a major depressive episode were included. Response to vortioxetine was measured using the THINC-integrated tool, Montgomery Åsberg Depression Rating Scale (MADRS), the Snaith-Hamilton Pleasure Scale (SHAPS), the Perceived Deficits Questionnaire (PDQ-5), and the Sheehan Disability Scale (SDS). Generalized estimating equation models were utilized for data analysis.Results: When adjusted for age, gender, dose, and BMI, there was a significant baseline IR by time interaction for SHAPS (p = 0.022), PDQ-5 (p = 0.037), and SDS (p = 0.013). Higher baseline IR predicted decreased early improvements in anhedonia. It also predicted poorer subjective assessments of cognition and increased functional impairment at the endpoint of treatment. For functional capacity (i.e. SDS) other covariates including severity of symptoms, illness course, other metabolic factors (e.g. cholesterol), and physical activity were included with no changes to the moderating effect of baseline IR.Limitations: This was a post-hoc analysis of a primarily non-diabetic sample. Also, only one agent was assessed.Conclusions: IR was a predictor of response to vortioxetine. This persisted after controlling for other factors including, but not limited to, BMI. These findings strengthen the link between depression and IR and may point to another novel metabolic predictor of response. These findings should be replicated using other antidepressants. [ABSTRACT FROM AUTHOR]

Background: No previous study has comprehensively reviewed the application of machine learning algorithms in mood disorders populations. Herein, we qualitatively and quantitatively evaluate previous studies of machine learning-devised models that predict therapeutic outcomes in mood disorders populations.Methods: We searched Ovid MEDLINE/PubMed from inception to February 8, 2018 for relevant studies that included adults with bipolar or unipolar depression; assessed therapeutic outcomes with a pharmacological, neuromodulatory, or manual-based psychotherapeutic intervention for depression; applied a machine learning algorithm; and reported predictors of therapeutic response. A random-effects meta-analysis of proportions and meta-regression analyses were conducted.Results: We identified 639 records: 75 full-text publications were assessed for eligibility; 26 studies (n=17,499) and 20 studies (n=6325) were included in qualitative and quantitative review, respectively. Classification algorithms were able to predict therapeutic outcomes with an overall accuracy of 0.82 (95% confidence interval [CI] of [0.77, 0.87]). Pooled estimates of classification accuracy were significantly greater (p < 0.01) in models informed by multiple data types (e.g., composite of phenomenological patient features and neuroimaging or peripheral gene expression data; pooled proportion [95% CI] = 0.93[0.86, 0.97]) when compared to models with lower-dimension data types (pooledproportion=0.68[0.62,0.74]to0.85[0.81,0.88]).Limitations: Most studies were retrospective; differences in machine learning algorithms and their implementation (e.g., cross-validation, hyperparameter tuning); cannot infer importance of individual variables fed into learning algorithm.Conclusions: Machine learning algorithms provide a powerful conceptual and analytic framework capable of integrating multiple data types and sources. An integrative approach may more effectively model neurobiological components as functional modules of pathophysiology embedded within the complex, social dynamics that influence the phenomenology of mental disorders. [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]

Highlights • Numerous studies indicate that probiotics have anti-inflammatory effects. • Immune-inflammatory modulation may mediate the antidepressant effects of probiotics. • Probiotics may be more effective in depressed subgroups with elevated inflammation. • Future studies should parse out the heterogeneous effects of different probiotics. Abstract During the past decade, there has been renewed interest in the relationship between brain-based disorders, the gut microbiota, and the possible beneficial effects of probiotics. Emerging evidence suggests that modifying the composition of the gut microbiota via probiotic supplementation may be a viable adjuvant treatment option for individuals with major depressive disorder (MDD). Convergent evidence indicates that persistent low-grade inflammatory activation is associated with the diagnosis of MDD as well as the severity of depressive symptoms and probability of treatment response. The objectives of this review are to (1) evaluate the evidence supporting an anti-inflammatory effect of probiotics and (2) describe immune system modulation as a potential mechanism for the therapeutic effects of probiotics in populations with MDD. A narrative review of studies investigating the effects of probiotics on systemic inflammation was conducted. Studies were identified using PubMed/Medline, Google Scholar, and clinicaltrials.gov (from inception to November 2017) using the following search terms (and/or variants): probiotic , inflammation , gut microbiota , and depression. The available evidence suggests that probiotics should be considered a promising adjuvant treatment to reduce the inflammatory activation commonly found in MDD. Several controversial points remain to be addressed including the role of leaky gut, the role of stress exposure, and the role of blood-brain-barrier permeability. Taken together, the results of this review suggest that probiotics may be a potentially beneficial, but insufficiently studied, antidepressant treatment intervention. [ABSTRACT FROM AUTHOR]