Efficacy Of Antidepressant Treatment Research Articles

Association between 5-HTR1A gene C-1019G polymorphism and antidepressant response in patients with major depressive disorder: A meta-analysis.

Major depressive disorder (MDD) is a substantial global health concern, and its treatment is complicated by the variability in individual response to antidepressants. To consolidate research and clarify the impact of genetic variation on MDD treatment outcomes. Adhering to Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a systematic search across PubMed, EMBASE, Web of Science, and the Cochrane Library was conducted without date restrictions, utilizing key terms related to MDD, serotonin 1A receptor polymorphism (5-HTR1A), C-1019G polymorphism, and antidepressant response. Studies meeting inclusion criteria were thoroughly screened, and quality assessed using the Newcastle-Ottawa Scale. Statistical analyses, including χ 2 and I² values, were used to evaluate heterogeneity and fixed-effect or random-effect models were applied accordingly. The initial search yielded 1216 articles, with 11 studies meeting criteria for inclusion. Analysis of various genetic models showed no significant association between the 5-HTR1A C-1019G polymorphism and antidepressant efficacy. The heterogeneity was low to moderate, and no publication bias was detected through funnel plot symmetry and Egger's and Begg's tests. This meta-analysis does not support a significant association between the 5-HTR1A C-1019G polymorphism and the efficacy of antidepressant treatment in MDD. The findings call for further research with larger cohorts to substantiate these results and enhance the understanding of antidepressant pharmacogenetics.

Impact of MAOA Gene Polymorphism on the Efficacy of Antidepressant Treatment and Craving Severity for Betel Quid Use Disorder.

Betel quid (BQ) use disorder (BUD) is prevalent in many Asian countries, impacting approximately 600 million people. We conducted a randomized clinical trial to analyze the impact of MAOA genetic variations on the severity of BQ craving. This was measured using DSM-5 criteria and the Yale-Brown Obsessive-Compulsive Scale modified for betel quid use (Y-BOCS-BQ). Participants were grouped according to the severity of BUD and MAOA gene single-nucleotide polymorphism (SNP) rs5953210 genotypes. The Y-BOCS-BQ scores were assessed at baseline (week 0) and during follow-up at weeks 2, 4, 6, and 8. The AA genotype group showed significantly greater reductions in Y-BOCS-BQ at weeks 2 (p = 0.0194), 4 (p = 0.0078), 6 (p = 0.0277), and 8 (p = 0.0376) compared to the GG genotype group. Additionally, within the antidepressant group, the AA genotype showed significant reductions in the Y-BOCS-BQ scores at weeks 2 (p = 0.0313), 4 (p = 0.0134), 6 (p = 0.0061), and 8 (p = 0.0241) compared to the GG genotype. The statistical analysis revealed a significant interaction between the treatment and placebo groups based on MAOA genotypes, with the AA genotype in the treatment group exhibiting a more pronounced decrease in Y-BOCS-BQ score (p interaction <0.05) at week 6. Our study highlights the importance of considering genetic factors when developing personalized treatment plans for BUD.

Transcriptional signatures of early-life stress and antidepressant treatment efficacy.

Individuals with a history of early-life stress (ELS) tend to have an altered course of depression and lower treatment response rates. Research suggests that ELS alters brain development, but the molecular changes in the brain following ELS that may mediate altered antidepressant response have not been systematically studied. Sex and gender also impact the risk of depression and treatment response. Here, we leveraged existing RNA sequencing datasets from 1) blood samples from depressed female- and male-identifying patients treated with escitalopram or desvenlafaxine and assessed for treatment response or failure; 2) the nucleus accumbens (NAc) of female and male mice exposed to ELS and/or adult stress; and 3) the NAc of mice after adult stress, antidepressant treatment with imipramine or ketamine, and assessed for treatment response or failure. We find that transcriptomic signatures of adult stress after a history of ELS correspond with transcriptomic signatures of treatment nonresponse, across species and multiple classes of antidepressants. Transcriptomic correspondence with treatment outcome was stronger among females and weaker among males. We next pharmacologically tested these predictions in our mouse model of early-life and adult social defeat stress and treatment with either chronic escitalopram or acute ketamine. Among female mice, the strongest predictor of behavior was an interaction between ELS and ketamine treatment. Among males, however, early experience and treatment were poor predictors of behavior, mirroring our bioinformatic predictions. These studies provide neurobiological evidence for molecular adaptations in the brain related to sex and ELS that contribute to antidepressant treatment response.

A Comparative Efficacy of Antidepressants in the Treatment of Major Depressive Disorder: A Systematic Review and Meta-Analysis

Major Depressive Disorder (MDD) affects about 280, 000, 000 people globally, with a higher incidence among females than males. The increasing incidence implicates health burdens and clinical dilemmas regarding the low efficacy of the existing antidepressants. A literature search was performed on electronic databases, PubMed, the Cochrane Library of Randomized Trials, Scopus, and ProQuest, for studies reporting the efficacy of an SNRI (Desvenlafaxine 50 mg/d), a serotonin modulator (Vortioxetine 10-20 mg/d), and an aminoketone antidepressant (Bupropion). Study selection focused on randomized controlled trials (RCTs) and observational studies. All statistical analyses and visualization were performed using the Review Manager (RevMan) software and Python programming. The random effects model, ANOVA test, and Cohen’s d were used for statistical analyses. The present meta-analysis involved 17 studies, including 11, 533 participants. The results aligned with previous studies and accounts provided by literature regarding the efficacy of antidepressants used to manage MDD. Five studies, including 2, 377 MDD patients, reported a statistically significant outcome, that Desvenlafaxine 50 mg/d reduced MDD’s severity than placebo (OR: 0.52, 95% CI [0.44, 0.62], P &lt; 0.00001, I2 = 0%). Three studies involving 742 MDD patients reported the efficacy of dextromethorphan-bupropion (AXS-50). The reduction of MADRS scores in the treatment group was statistically insignificant, with high variability, favouring the placebo (OR of 1.85 [95% CI: 0.93, 3.70], p = 0.08, I2 = 79%). Additionally, Vortioxetine 10-20 mg/d produced adverse effects, headache, vomiting, nausea, diarrhea, dizziness, nasopharyngitis, somnolence, and suicidal ideation among 6, 669 MDD patients reported by the 9 studies. The finding was statistically significant but with a high variability OR: 15.25, 95% CI [12.55, 18.52], P &lt; 0.00001, I2 = 98%). A preliminary analysis of evidence collected following Desvenlafaxine, AXS-50, and Vortioxetine administration yielded compelling evidence on the efficacy of antidepressants in MDD treatment. Desvenlafaxine and AXS-50 reported reduced severity and symptomatology in MDD, respectively. On the other hand, Vortioxetine implicated adverse effects, which are common with most antidepressants. Despite adverse effects like headache, vomiting, nausea, diarrhea, dizziness, nasopharyngitis, somnolence, and suicidal ideation, antidepressants used to treat MDD yield clinically satisfying outcomes like decreased severity of depression and relief from symptoms. Clinicians should monitor patients to take care of any adverse effects resulting from the treatments. Keywords: Antidepressant efficacy, adverse effects, major depressive disorder, MDD symptomatology, severity, improved outcomes.

Prediction of Early Antidepressant Efficacy in Patients with Major Depressive Disorder Based on Multidimensional Features of rs-fMRI and P11 Gene DNA Methylation: Prédiction de l'efficacité précoce d'un antidépresseur chez des patients souffrant du trouble dépressif majeur d'après les caractéristiques multidimensionnelles de la méthylation de l'ADN du gène P11 et de la IRMf-rs.

This study established a machine learning model based on the multidimensional data of resting-state functional activity of the brain and P11 gene DNA methylation to predict the early efficacy of antidepressant treatment in patients with major depressive disorder (MDD). A total of 98 Han Chinese MDD were analysed in this study. Patients were divided into 51 responders and 47 nonresponders according to whether the Hamilton Depression Rating Scale-17 items (HAMD-17) reduction rate was ≥50% after 2 weeks of antidepressant treatment. At baseline, the Illumina HiSeq Platform was used to detect the methylation of 74 CpG sites of the P11 gene in peripheral blood samples. Resting-state functional magnetic resonance imaging (rs-fMRI) scan detected the amplitude of low-frequency fluctuations (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) in 116 brain regions. The least absolute shrinkage and selection operator analysis method was used to perform feature reduction and feature selection. Four typical machine learning methods were used to establish support vector machine (SVM), random forest (RF), Naïve Bayes (NB), and logistic regression (LR) prediction models based on different combinations of functional activity of the brain, P11 gene DNA methylation and clinical/demographic features after screening. The SVM model based on ALFF, ReHo, FC, P11 methylation, and clinical/demographic features showed the best performance, with 95.92% predictive accuracy and 0.9967 area under the receiver operating characteristic curve, which was better than RF, NB, and LR models. The multidimensional data features combining rs-fMRI, DNA methylation, and clinical/demographic features can predict the early antidepressant efficacy in MDD.

A Comparative Efficacy of Antidepressants in the Treatment of Major Depressive Disorder: A Systematic Review and Meta-Analysis

Study background &amp; objective: Major Depressive Disorder (MDD) affects about 280, 000, 000 people globally, with a higher incidence among females than males. The increasing incidence implicates health burdens and clinical dilemmas regarding the low efficacy of the existing antidepressants. Methods: A literature search was performed on electronic databases, PubMed, the Cochrane Library of Randomized Trials, Scopus, and ProQuest, for studies reporting the efficacy of an SNRI (Desvenlafaxine 50 mg/d), a serotonin modulator (Vortioxetine 10-20 mg/d), and an aminoketone antidepressant (Bupropion). Study selection focused on randomized controlled trials (RCTs) and observational studies. All statistical analyses and visualization were performed using the Review Manager (RevMan) software and Python programming. The random effects model, ANOVA test, and Cohen’s d were used for statistical analyses. Results: The present meta-analysis involved 17 studies, including 11, 533 participants. The results aligned with previous studies and accounts provided by literature regarding the efficacy of antidepressants used to manage MDD. Five studies, including 2, 377 MDD patients, reported a statistically significant outcome, that Desvenlafaxine 50 mg/d reduced MDD’s severity than placebo (OR: 0.52, 95% CI [0.44, 0.62], P &lt; 0.00001, I2 = 0%). Three studies involving 742 MDD patients reported the efficacy of dextromethorphan-bupropion (AXS-50). The reduction of MADRS scores in the treatment group was statistically insignificant, with high variability, favouring the placebo (OR of 1.85 [95% CI: 0.93, 3.70], p = 0.08, I2 = 79%). Additionally, Vortioxetine 10-20 mg/d produced adverse effects, headache, vomiting, nausea, diarrhea, dizziness, nasopharyngitis, somnolence, and suicidal ideation among 6, 669 MDD patients reported by the 9 studies. The finding was statistically significant but with a high variability OR: 15.25, 95% CI [12.55, 18.52], P &lt; 0.00001, I2 = 98%). Discussion: A preliminary analysis of evidence collected following Desvenlafaxine, AXS-50, and Vortioxetine administration yielded compelling evidence on the efficacy of antidepressants in MDD treatment. Desvenlafaxine and AXS-50 reported reduced severity and symptomatology in MDD, respectively. On the other hand, Vortioxetine implicated adverse effects, which are common with most antidepressants. Conclusion: Despite adverse effects like headache, vomiting, nausea, diarrhea, dizziness, nasopharyngitis, somnolence, and suicidal ideation, antidepressants used to treat MDD yield clinically satisfying outcomes like decreased severity of depression and relief from symptoms. Clinicians should monitor patients to take care of any adverse effects resulting from the treatments.

Sex matters: acute functional connectivity changes as markers of remission in late-life depression differ by sex.

The efficacy of antidepressant treatment in late-life is modest, a problem magnified by an aging population and increased prevalence of depression. Understanding the neurobiological mechanisms of treatment response in late-life depression (LLD) is imperative. Despite established sex differences in depression and neural circuits, sex differences associated with fMRI markers of antidepressant treatment response are underexplored. In this analysis, we assess the role of sex on the relationship of acute functional connectivity changes with treatment response in LLD. Resting state fMRI scans were collected at baseline and day one of SSRI/SNRI treatment for 80 LLD participants. One-day changes in functional connectivity (differential connectivity) were related to remission status after 12 weeks. Sex differences in differential connectivity profiles that distinguished remitters from non-remitters were assessed. A random forest classifier was used to predict the remission status with models containing various combinations of demographic, clinical, symptomatological, and connectivity measures. Model performance was assessed with area under the curve, and variable importance was assessed with permutation importance. The differential connectivity profile associated with remission status differed significantly by sex. We observed evidence for a difference in one-day connectivity changes between remitters and non-remitters in males but not females. Additionally, prediction of remission was significantly improved in male-only and female-only models over pooled models. Predictions of treatment outcome based on early changes in functional connectivity show marked differences between sexes and should be considered in future MR-based treatment decision-making algorithms.

Chronic fluoxetine treatment in socially-isolated rats modulates the prefrontal cortex synaptoproteome

Exposure to chronic social isolation (CSIS) and synapse dysfunction have been implicated in the etiology of major depressive disorder (MDD). Fluoxetine (Flx) has been widely used to treat MDD, but its mechanisms of action remain elusive. We employed comparative synaptoproteomics to investigate the changes in the levels of proteins and molecular signaling pathways in prefrontal cortical samples of adult male Wistar rats exposed to CSIS, a rat model of depression, and CSIS rats treated with chronic Flx and controls, using liquid chromatography coupled to tandem mass spectrometry. Flx-treated control rats showed a decreased level of proteins involved in vesicle-mediated transport, and a predominantly increased level of exocytosis-associated proteins. CSIS significantly reduced the level of proteins involved in the ATP metabolic process, clathrin-dependent endocytosis, and proteolysis. Flx treatment in CSIS rats stimulated synaptic vesicle trafficking by increasing the regulation of exo/endocytosis-associated proteins, proteins involved in synaptic plasticity including neurogenesis, Cox5a, mitochondria-associated proteins involved in oxidative phosphorylation, and ion transport proteins (Slc8a2, Atp1b2). Flx treatment resulted in an increased synaptic vesicle dynamic, plasticity and mitochondrial functionality, and a suppression of CSIS-induced impairment of these processes. Biological significanceIdentifying biomarkers of MDD and treatment response is the goal of many studies. Contemporary studies have shown that many molecular alterations associated with the pathophysiology of MDD reside within the synapse. As part of this research, a growing importance is the use of proteomics, as monitoring the changes in protein levels enables the identification of (possible) biochemical pathways and processes of importance for the development of depressive-like behavior and the efficacy of antidepressant treatments. We profiled proteomic changes representative of the development of CSIS-induced depressive-like behavior and the antidepressant effects of Flx. Our study has identified synaptosomal proteins and altered molecular pathways that may be potential markers of prefrontal cortical synaptic dysfunction associated with depressive-like behavior, and further clarified the mechanisms of depressive-like behavior and mode of action of Flx. Our findings indicate potential PFC synaptic targets for antidepressant treatment.

Significant Differences and Experimental Designs Do Not Necessarily Imply Clinical Relevance: Effect Sizes and Causality Claims in Antidepressant Treatments.

Clinical trials are the backbone of medical scientific research. However, this experimental strategy has some drawbacks. We focused on two issues: (a) The internal validity ensured by clinical trial procedures does not necessarily allow for generalization of efficacy results to causal claims about effectiveness in the population. (b) Statistical significance does not imply clinical or practical significance; p-values should be supplemented with effect size (ES) estimators and an interpretation of the magnitude of the effects found. We conducted a systematic review (from 2000 to 2020) on Scopus, PubMed, and four ProQuest databases, including PsycINFO. We searched for experimental studies with significant effects of pharmacological treatments on depressive symptoms, measured with a specific scale for depression. We assessed the claims of effectiveness, and reporting and interpreting of effect sizes in a small, unbiased sample of clinical trials (n = 10). Only 30% of the studies acknowledged that efficacy does not necessarily translate to effectiveness. Only 20% reported ES indices, and only 40% interpreted the magnitude of their findings. We encourage reflection on the applicability of results derived from clinical trials about the efficacy of antidepressant treatments, which often influence daily clinical decision-making. Comparing experimental results of antidepressants with supplementary observational studies can provide clinicians with greater flexibility in prescribing medication based on patient characteristics. Furthermore, the ES of a treatment should be considered, as treatments with a small effect may be worthwhile in certain circumstances, while treatments with a large effect may be justified despite additional costs or complications. Therefore, researchers are encouraged to report and interpret ES and explicitly discuss the suitability of their sample for the clinical population to which the antidepressant treatment will be applied.

Microbiota-Gut-Brain Axis Regulation of Adult Hippocampal Neurogenesis.

The birth, maturation, and integration of new neurons in the adult hippocampus regulates specific learning and memory processes, responses to stress, and antidepressant treatment efficacy. This process of adult hippocampal neurogenesis is sensitive to environmental stimuli, including peripheral signals from certain cytokines, hormones, and metabolites, which can promote or hinder the production and survival of new hippocampal neurons. The trillions of microorganisms resident to the gastrointestinal tract, collectively known as the gut microbiota, also demonstrate the ability to modulate adult hippocampal neurogenesis. In doing so, the microbiota-gut-brain axis can influence brain functions regulated by adult hippocampal neurogenesis. Unlike the hippocampus, the gut microbiota is highly accessible to direct interventions, such as prebiotics, probiotics, and antibiotics, and can be manipulated by lifestyle choices including diet. Therefore, understanding the pathways by which the gut microbiota shapes hippocampal neurogenesis may reveal novel targets for non-invasive therapeutics to treat disorders in which alterations in hippocampal neurogenesis have been implicated. This review first outlines the factors which influence both the gut microbiome and adult hippocampal neurogenesis, with cognizance that these effects might happen either independently or due to microbiota-driven mechanisms. We then highlight approaches for investigating the regulation of adult hippocampal neurogenesis by the microbiota-gut-brain axis. Finally, we summarize the current evidence demonstrating the gut microbiota's ability to influence adult hippocampal neurogenesis, including mechanisms driven through immune pathways, microbial metabolites, endocrine signalling, and the nervous system, and postulate implications for these effects in disease onset and treatment.

Assessing the efficacy of antidepressant treatment in opioid-dependent patients undergoing methadone maintenance treatment: A literature review

Introduction. Opioid dependence and co-occurring depressive disorders represent a significant clinical challenge within the field of psychiatry, necessitating effective interventions to improve patient outcomes. Antidepressant treatment has emerged as a potential therapeutic approach, yet its efficacy in the context of Methadone Maintenance Treatment (MMT) remains inconclusive. Methods. To address this critical knowledge gap, a comprehensive literature review was conducted. Databases including PubMed, the National Institutes of Health (NIH), Google Scholar, and Cochrane Drugs and Alcohol Reviews were meticulously searched for relevant publications from January 2010 to June 2022, using targeted keywords (“antidepressants,” “opioid addiction,” “methadone”). Results. The review uncovered a complex landscape of studies, highlighting the challenges in evaluating the efficacy of antidepressant treatment in opioid-dependent individuals receiving MMT. While some investigations have reported modest benefits in alleviating depressive symptoms, others remain inconclusive or contradictory. Desvenlafaxine, a dualaction antidepressant, demonstrated some effectiveness in this population, suggesting a potential treatment option. However, these findings necessitate further exploration through large-scale, complex studies with a focus on diverse patient populations. Discussion. The multifaceted nature of opioid dependence, comorbid depressive disorders, and the complexities of MMT underscore the challenges in ascertaining treatment outcomes definitively. Additionally, the potential for adverse effects and drug interactions, particularly in cases of relapse, complicates the therapeutic landscape. Patients often resort to self-medicating depressive symptoms with other substances, further clouding the interpretation of treatment results. Conclusion. The literature review reveals the need for continued research to elucidate the role of antidepressant treatment in opioid-dependent patients undergoing MMT. As patients’ needs vary widely, a comprehensive approach to managing affective symptoms should encompass not only pharmacotherapy but also various psychotherapeutic and social interventions. By addressing these complexities, future research may pave the way for more tailored and effective treatment strategies, ultimately enhancing the well-being of individuals grappling with the dual burdens of opioid dependence and depressive disorders within the MMT context.

Confirmatory Efficacy and Safety Trial of Magnetic Seizure Therapy for Depression (CREST-MST): study protocol for a randomized non-inferiority trial of magnetic seizure therapy versus electroconvulsive therapy

BackgroundElectroconvulsive therapy (ECT) is well-established and effective for treatment-resistant depression (TRD), but in Canada and the USA, less than 1% of patients with TRD receive ECT mainly due to its cognitive adverse effects (i.e. amnesia). Thus, new treatment alternatives for TRD are urgently needed. One such treatment is magnetic seizure therapy (MST). ECT involves applying a train of high-frequency electrical stimuli to induce a seizure, whereas MST involves applying a train of high-frequency magnetic stimuli to induce a seizure.MethodsIn this manuscript, we introduce our international, two-site, double-blinded, randomized, non-inferiority clinical trial to develop MST as an effective and safe treatment for TRD. This trial will compare the efficacy of MST to right unilateral ultra-brief pulse width electroconvulsive therapy (RUL-UB-ECT) with a combined primary endpoint of remission of depression and superior cognitive adverse effects in 260 patients with TRD. Amelioration of suicidal ideation will be assessed as a secondary endpoint. Inpatients or outpatients, over 18 years of age with a MINI International Neuropsychiatric Interview (MINI) diagnosis of non-psychotic major depressive disorder (MDD) can be enrolled in the study provided that they meet illness severity and full eligibility criteria. Participants are randomized to receive MST or RUL-UB ECT, 2-3 days per week over seven weeks, or a maximum of 21 treatments. The study will involve before-, during-, and after-treatment assessments of depression severity, suicidal ideation, subjective side-effects, and cognitive performance consistent with an intent-to-treat study design approach.DiscussionPositive results from this trial could have an immediate and tremendous impact for patients with TRD. If MST demonstrates comparable antidepressant treatment efficacy to ECT, but with greater cognitive safety, it could rapidly be adopted into clinical practice. Indeed, given that the administration of MST is nearly identical to ECT, the majority of ECT facilities in North America could readily adopt MST. Furthermore, the potential for cognitive safety could lead to improved treatment acceptability. Healthcare providers, patients and care partners, and policymakers would therefore demand this form of convulsive therapy.Trial statusEnrollment for this study began on June 26, 2018, and is estimated to complete recruitment by July 2024. At the time of submission, we have enrolled and randomized 117 participants.Trial registrationClinicalTrials.gov NCT03191058, Registered on June 19, 2017.Primary sponsor:Daniel Blumberger (DMB), Principal InvestigatorDaniel.Blumberger@camh.ca, 416-535-8501 x 33662Contact for public queries: DMB, Daniel.Blumberger@camh.caContact for scientific queries: ZJD, Zdaskalakis@health.ucsd.edu

Measuring brain glucose metabolism in order to predict response to antidepressant or placebo: A randomized clinical trial

There is critical need for a clinically useful tool to predict antidepressant treatment outcome in major depressive disorder (MDD) to reduce suffering and mortality. This analysis sought to build upon previously reported antidepressant treatment efficacy prediction from 2-[18F]-fluorodeoxyglucose - Positron Emission Tomography (FDG-PET) using metabolic rate of glucose uptake (MRGlu) from dynamic FDG-PET imaging with the goal of translation to clinical utility. This investigation is a randomized, double-blind placebo-controlled trial. All participants were diagnosed with MDD and received an FDG-PET scan before randomization and after treatment. Hamilton Depression Rating Scale (HDRS-17) was completed in participants diagnosed with MDD before and after 8 weeks of escitalopram, or placebo. MRGlu (mg/(min*100 ml)) was estimated within the raphe nuclei, right insula, and left ventral Prefrontal Cortex in 63 individuals. Linear regression was used to examine the association between pretreatment MRGlu and percent decrease in HDRS-17. Additionally, the association between percent decrease in HDRS-17 and percent change in MRGlu between pretreatment scan and post-treatment scan was examined. Covariates were treatment type (SSRI/placebo), handedness, sex, and age. Depression severity decrease (n = 63) was not significantly associated with pretreatment MRGlu in the raphe nuclei (β = -2.61e-03 [-0.26, 0.25], p = 0.98), right insula (β = 0.05 [-0.23, 0.32], p = 0.72), or ventral prefrontal cortex (β = 0.06 [-0.23, 0.34], p = 0.68) where β is the standardized estimated coefficient, with a 95% confidence interval, or in whole brain voxelwise analysis (family-wise error correction, alpha = 0.05). MRGlu percent change was not significantly associated with depression severity decrease (n = 58) before multiple comparison correction in the RN (β = 0.20 [-0.07, 0.47], p = 0.15), right insula (β = 0.24 [-0.03, 0.51], p = 0.08), or vPFC (β = 0.22 [-0.06, 0.50], p = 0.12). We propose that FDG-PET imaging does not indicate a clinically relevant biomarker of escitalopram or placebo treatment response in heterogeneous major depressive disorder cohorts. Future directions include focusing on potential biologically-based subtypes of major depressive disorder by implementing biomarker stratified designs.

Cortisol and Major Depressive Disorder-Translating Findings From Humans to Animal Models and Back.

Major depressive disorder (MDD) is a global problem for which current pharmacotherapies are not completely effective. Hypothalamic–pituitary–adrenal (HPA) axis dysfunction has long been associated with MDD; however, the value of assessing cortisol as a biological benchmark of the pathophysiology or treatment of MDD is still debated. In this review, we critically evaluate the relationship between HPA axis dysfunction and cortisol level in relation to MDD subtype, stress, gender and treatment regime, as well as in rodent models. We find that an elevated cortisol response to stress is associated with acute and severe, but not mild or atypical, forms of MDD. Furthermore, the increased incidence of MDD in females is associated with greater cortisol response variability rather than higher baseline levels of cortisol. Despite almost all current MDD treatments influencing cortisol levels, we could find no convincing relationship between cortisol level and therapeutic response in either a clinical or preclinical setting. Thus, we argue that the absolute level of cortisol is unreliable for predicting the efficacy of antidepressant treatment. We propose that future preclinical models should reliably produce exaggerated HPA axis responses to acute or chronic stress a priori, which may, or may not, alter baseline cortisol levels, while also modelling the core symptoms of MDD that can be targeted for reversal. Combining genetic and environmental risk factors in such a model, together with the interrogation of the resultant molecular, cellular, and behavioral changes, promises a new mechanistic understanding of MDD and focused therapeutic strategies.

Brain regulation of emotional conflict predicts antidepressant treatment response for depression.

The efficacy of antidepressant treatment for depression is controversial due to only modest superiority demonstrated over placebo. However, neurobiological heterogeneity within depression may limit overall antidepressant efficacy. We sought to identify a neurobiological phenotype responsive to antidepressant treatment by testing pretreatment brain activation during response to, and regulation of, emotional conflict as a moderator of the clinical benefit of the antidepressant sertraline versus placebo. Using neuroimaging data from a large randomized controlled trial, we found widespread moderation of clinical benefits by brain activity during regulation of emotional conflict, in which greater down-regulation of conflict-responsive regions predicted better sertraline outcomes. Treatment-predictive machine learning utilizing brain metrics outperformed a model trained on clinical and demographic variables. Our findings demonstrate antidepressant response is predicted by brain activity underlying a key self-regulatory emotional capacity. Leveraging brain-based measures in psychiatry will forge a path toward better treatment personalization, refined mechanistic insights, and improved outcomes.Trial RegistrationEstablishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC),

Identification of major depressive disorder and prediction of treatment response using functional connectivity between the prefrontal cortices and subgenual anterior cingulate: A real-world study

BackgroundMajor depressive disorder (MDD) is associated with a heavy disease burden due to the difficulty in diagnosing the disorder and the uncertainty of treatment outcomes. Previous studies have demonstrated the value of functional connectivity (FC) between the dorsolateral prefrontal cortex (DLPFC) and the subgenual anterior cingulate cortex (sgACC) in the identification of MDD and the prediction of antidepressant efficacy. In the present study, we aimed to investigate whether FC is helpful in discriminating patients from healthy controls and in predicting treatment outcome. MethodsSeventy-six medication-free patients with MDD and 28 healthy controls were enrolled in the study. Magnetoencephalography (MEG) and the Hamilton Rating Score for Depression (HRSD-17) were administered at baseline. Then, the HRSD-17 was assessed weekly until each patient met the remission criteria, defined as a total HRSD-17 score ≤ 7. Time-dependent Cox regression analysis was used to evaluate the association between FC and the incidence of remission. ResultsHealthy controls and MDD patients had opposite FC patterns; this may be helpful for identifying MDD (AUC = 0.8, p < 0.001, sensitivity 85.7%, specificity 67.9%). Alpha connectivity between the DLPFC and sgACC (HR 1.858, 95%CI 1.013–3.408, p = 0.045) was found to be an independent factor associated with better final antidepressant outcome. LimitationsThis study was conducted in a small sample of subjects. Further, the direction of regulation between the DLPFC and sgACC was not considered. ConclusionsFC may help identify depression and may be related to the severity of depressive symptoms and predict the efficacy of antidepressant treatment.

Increased serum levels of sortilin-derived propeptide after electroconvulsive therapy in treatment-resistant depressed patients.

PurposeSortilin-derived propeptide (PE) and its synthetic analog spadin show strong antidepressant activity in rodents and, therefore, could be used as a biomarker to evaluate the clinical efficacy of antidepressant treatments. The aim of this study was to determine whether electroconvulsive therapy (ECT) modulates serum PE concentration in patients with treatment-resistant depression (TRD).Patients and methodsForty-five patients with major depressive disorder, who met the Diagnostic and Statistical Manual of Mental Disorders-IV criteria, were selected for this study.ResultsWe did not observe any difference in the PE levels between TRD patients and controls (z=0.10, P=0.92), but we found a strong significant increase between the PE levels measured just before (T0) and about 1 month (T2) after ECT (z=−2.82, P=0.005). A significant difference between T0 and T2 was observed only in responders (z=−2.59, P=0.01), whereas no effect was found in nonresponders (z=−1.27, P=0.20). Interestingly, we found a significant correlation between the increase in PE levels and decrease in Montgomery -Åsberg Depression Rating Scale scores for the total patient sample (P=0.03).ConclusionThis study indicates for the first time that ECT affects serum PE concentration in responders and, therefore, could contribute to the evaluation of the therapy success.

P.2.010 - In search for predictive biomarkers: dissecting the molecular pathways in brain and blood underlying poor and good antidepressant treatment response

Major depression poses a serious social and economic threat to modern societies, as it accounts for more lost productivity compared with any other disorder. There are currently two major problems calling for innovative research approaches: 1. The absence of biomarkers predicting antidepressant response and 2. The lack of conceptually novel antidepressant compounds. Identification of biomarkers could allow patient stratification and enable the selection of pathophysiologically distinct patient subgroups to allow optimized treatment choices based on biology. In search for conceptually novel antidepressants, the hippocampal dentate gyrus is a region of particular interest, as there is a large body of evidence suggesting that stimulation of neurogenesis by antidepressant drugs could be one of their major common targets [1,2]. Aiming to identify the molecular pathways shaping response to antidepressant treatment and to identify predictors for antidepressant response, we used our animal experimental approach to model heterogeneity in response to antidepressant treatment (Carillo-Roa et al., PLoS BIOL, in revision). Male, adult DBA/2J mice show a strong innate anxiety and depression-like phenotype. Mice were treated for 14 days with customized pills containing either paroxetine or vehicle, providing a stress-free and oral treatment paradigm. Efficacy of antidepressant treatment was measured using the Forced Swim Test and results analyzed using a Student’s t-test. For the identification of peripheral biosignatures predicting response, we collected blood samples at baseline and following 14 days of treatment (longitudinal design), whereas for the identification of novel antidepressant targets, we specifically dissected the hippocampal dentate gyrus using a microdissecion protocol for native hippocampal tissue. We extracted stranded total RNA from dentate gyrus samples (paroxetine vs vehicle and good vs poor responders) and whole blood samples (baseline and 14 days in good vs poor responders) and sequenced. Analysis of differentially expressed genes (DESeq analysis) was conducted applying Benjamini-Hochberg correction with a padj 2.68, and fold changes >1.5. Pathway analysis was conducted using STRING software. qPCR of selected genes was conducted and analyzed using delta-delta-ct method. Paroxetine treatment led to antidepressant-like (p With this study, we provide additional strong evidence that neurogenesis drives antidepressant treatment effects and determines response status in rodents. We also expect to identify transcriptome signatures predictive of later antidepressant response in whole blood. Finally, we aim at validating our murine predictive biomarkers in human studies on antidepressant response.

Efficacy of Antidepressants for Depression in Alzheimer's Disease: Systematic Review and Meta-Analysis.

Background: Depression is common in people with Alzheimer’s disease (AD) affecting overall outcomes and decreasing quality of life. Although depression in AD is primarily treated with antidepressants, there are few randomized controlled trials (RCTs) assessing efficacy and results have been conflicting.Objectives: To systematically review evidence on efficacy of antidepressant treatments for depression in AD.Methods: Systematic review and meta-analysis of double blind RCTs comparing antidepressants versus placebo for depression in AD. We searched MEDLINE, CINAHL, EMBASE, PsycINFO, the Cochrane Controlled Trials Register and on line national and international registers. Primary outcomes were treatment response and depressive symptoms. Secondary outcomes were cognition, acceptability, and tolerability. Risk of bias was also assessed.Results: Seven studies met inclusion criteria. Three compared sertraline with placebo; one compared both sertraline and mirtazapine to placebo; imipramine, fluoxetine, and clomipramine were evaluated in one study each. In terms of response to treatment (6 studies, 297 patients treated with antidepressants and 223 with placebo), no statistically significant difference between antidepressants and placebo was found (odds ratio (OR) 1.95, 95% CI 0.97–3.92). We found no significant drug-placebo difference for depressive symptoms (5 studies, 311 patients, SMD –0.13; 95% CI –0.49 to 0.24). Overall quality of the evidence was moderate because of methodological limitations in studies and the small number of trials.Conclusion: Despite the importance of depression in people with AD, few RCTs are available on efficacy of antidepressants, limiting clear conclusions of their potential role. There is a need for further high quality RCTs.

Reevaluating the Efficacy and Predictability of Antidepressant Treatments

Depressive severity is typically measured according to total scores on questionnaires that include a diverse range of symptoms despite convincing evidence that depression is not a unitary construct. When evaluated according to aggregate measurements, treatment efficacy is generally modest and differences in efficacy between antidepressant therapies are small. To determine the efficacy of antidepressant treatments on empirically defined groups of symptoms and examine the replicability of these groups. Patient-reported data on patients with depression from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial (n = 4039) were used to identify clusters of symptoms in a depressive symptom checklist. The findings were then replicated using the Combining Medications to Enhance Depression Outcomes (CO-MED) trial (n = 640). Mixed-effects regression analysis was then performed to determine whether observed symptom clusters have differential response trajectories using intent-to-treat data from both trials (n = 4706) along with 7 additional placebo and active-comparator phase 3 trials of duloxetine (n = 2515). Finally, outcomes for each cluster were estimated separately using machine-learning approaches. The study was conducted from October 28, 2014, to May 19, 2016. Twelve items from the self-reported Quick Inventory of Depressive Symptomatology (QIDS-SR) scale and 14 items from the clinician-rated Hamilton Depression (HAM-D) rating scale. Higher scores on the measures indicate greater severity of the symptoms. Of the 4706 patients included in the first analysis, 1722 (36.6%) were male; mean (SD) age was 41.2 (13.3) years. Of the 2515 patients included in the second analysis, 855 (34.0%) were male; mean age was 42.65 (12.17) years. Three symptom clusters in the QIDS-SR scale were identified at baseline in STAR*D. This 3-cluster solution was replicated in CO-MED and was similar for the HAM-D scale. Antidepressants in general (8 of 9 treatments) were more effective for core emotional symptoms than for sleep or atypical symptoms. Differences in efficacy between drugs were often greater than the difference in efficacy between treatments and placebo. For example, high-dose duloxetine outperformed escitalopram in treating core emotional symptoms (effect size, 2.3 HAM-D points during 8 weeks, 95% CI, 1.6 to 3.1; P < .001), but escitalopram was not significantly different from placebo (effect size, 0.03 HAM-D points; 95% CI, -0.7 to 0.8; P = .94). Two common checklists used to measure depressive severity can produce statistically reliable clusters of symptoms. These clusters differ in their responsiveness to treatment both within and across different antidepressant medications. Selecting the best drug for a given cluster may have a bigger benefit than that gained by use of an active compound vs a placebo.