Influence of CYP2C19, CYP2D6, and ABCB1 Gene Variants and Serum Levels of Escitalopram and Aripiprazole on Treatment-Emergent Sexual Dysfunction: A Canadian Biomarker Integration Network in Depression 1 (CAN-BIND 1) Study

OBJECTIVES

Treatment-emergent sexual dysfunction is frequently reported by individuals with major depressive disorder (MDD) on antidepressants, which negatively impacts treatment adherence and efficacy. We investigated the association of polymorphisms in pharmacokinetic genes encoding cytochrome-P450 drug-metabolizing enzymes, CYP2C19 and CYP2D6, and the transmembrane efflux pump, P-glycoprotein (i.e., ABCB1), on treatment-emergent changes in sexual function (SF) and sexual satisfaction (SS) in the Canadian Biomarker Integration Network in Depression 1 (CAN-BIND-1) sample.

METHODS

A total of 178 adults with MDD received treatment with escitalopram (ESC) from weeks 0-8 (Phase I). At week 8, nonresponders were augmented with aripiprazole (ARI) (i.e., ESC + ARI, n = 91), while responders continued ESC (i.e., ESC-Only, n = 80) from weeks 8-16 (Phase II). SF and SS were evaluated using the sex effects (SexFX) scale at weeks 0, 8, and 16. We assessed the primary outcomes, SF and SS change for weeks 0-8 and 8-16, using repeated measures mixed-effects models.

RESULTS

In ESC-Only, CYP2C19 intermediate metabolizer (IM) + poor metabolizers (PMs) showed treatment-related improvements in sexual arousal, a subdomain of SF, from weeks 8-16, relative to CYP2C19 normal metabolizers (NMs) who showed a decline, F(2,54) = 8.00, p < 0.001, q = 0.048. Specifically, CYP2C19 IM + PMs reported less difficulty with having and sustaining vaginal lubrication in females and erection in males, compared to NMs. Furthermore, ESC-Only females with higher concentrations of ESC metabolite, S-desmethylcitalopram (S-DCT), and S-DCT/ESC ratio in serum demonstrated more decline in SF (r = -0.42, p = 0.004, q = 0.034) and SS (r = -0.43, p = 0.003, q = 0.034), respectively, which was not observed in males. ESC-Only females also demonstrated a trend for a correlation between S-DCT and sexual arousal change in the same direction (r = -0.39, p = 0.009, q = 0.052).

CONCLUSIONS

CYP2C19 metabolizer phenotypes may be influencing changes in sexual arousal related to ESC monotherapy. Thus, preemptive genotyping of CYP2C19 may help to guide selection of treatment that circumvents selective serotonin reuptake inhibitor-related sexual dysfunction thereby improving outcomes for patients. Additionally, further research is warranted to clarify the role of S-DCT in the mechanisms underlying ESC-related changes in SF and SS. This CAN-BIND-1 study was registered on clinicaltrials.gov (Identifier: NCT01655706) on 27 July 2012.

Mood Disorders: The Gut Bacteriome and Beyond

Knowledge of the microbiome-gut-brain axis has revolutionized the field of psychiatry. It is now well recognized that the gut bacteriome is associated with, and likely influences, the pathogenesis of mental disorders, including major depressive disorder and bipolar disorder. However, while substantial advances in the field of microbiome science have been made, we have likely only scratched the surface in our understanding of how these ecosystems might contribute to mental disorder pathophysiology. Beyond the gut bacteriome, research into lesser explored components of the gut microbiome, including the gut virome, mycobiome, archaeome, and parasitome, is increasingly suggesting relevance in psychiatry. The contribution of microbiomes beyond the gut, including the oral, lung, and small intestinal microbiomes, to human health and pathology should not be overlooked. Increasing both our awareness and understanding of these less traversed fields of research are critical to improving the therapeutic benefits of treatments targeting the gut microbiome, including fecal microbiome transplantation, postbiotics and biogenics, and dietary intervention. Interdisciplinary collaborations integrating systems biology approaches are required to fully elucidate how these different microbial components and distinct microbial niches interact with each other and their human hosts. Excitingly, we may be at the start of the next microbiome revolution and thus one step closer to informing the field of precision psychiatry to improve outcomes for those living with mental illness.

Relation of hippocampal volume and SGK1 gene expression to treatment remission in major depression is moderated by childhood maltreatment: A CAN-BIND-1 report

Preclinical research implicates stress-induced upregulation of the enzyme, serum- and glucocorticoid-regulated kinase 1 (SGK1), in reduced hippocampal volume. In the current study, we tested the hypothesis that greater SGK1 mRNA expression in humans would be associated with lower hippocampal volume, but only among those with a history of prolonged stress exposure, operationalized as childhood maltreatment (physical, sexual, and/or emotional abuse). Further, we examined whether baseline levels of SGK1 and hippocampal volume, or changes in these markers over the course of antidepressant treatment, would predict treatment outcomes in adults with major depression [MDD]. We assessed SGK1 mRNA expression from peripheral blood, and left and right hippocampal volume at baseline, as well as change in these markers over the first 8 weeks of a 16-week open-label trial of escitalopram as part of the Canadian Biomarker Integration Network in Depression program (MDD [n = 161] and healthy comparison participants [n = 91]). Childhood maltreatment was assessed via contextual interview with standardized ratings. In the full sample at baseline, greater SGK1 expression was associated with lower hippocampal volume, but only among those with more severe childhood maltreatment. In individuals with MDD, decreases in SGK1 expression predicted lower remission rates at week 16, again only among those with more severe maltreatment. Decreases in hippocampal volume predicted lower week 16 remission for those with low childhood maltreatment. These results suggest that both glucocorticoid-related neurobiological mechanisms of the stress response and history of childhood stress exposure may be critical to understanding differential treatment outcomes in MDD. ClinicalTrials.gov: NCT01655706 Canadian Biomarker Integration Network for Depression Study.

Pro-inflammatory markers are associated with response to sequential pharmacotherapy in major depressive disorder: a CAN-BIND-1 report

OBJECTIVE

There is limited literature on associations between inflammatory tone and response to sequential pharmacotherapies in major depressive disorder (MDD).

METHODS

In a 16-week open-label clinical trial, 211 participants with MDD were treated with escitalopram 10-20 mg daily for 8 weeks. Responders continued escitalopram while non-responders received adjunctive aripiprazole 2-10 mg daily for 8 weeks. Plasma levels of pro-inflammatory markers-C-reactive protein, interleukin (IL)-1β, IL-6, IL-17, interferon-gamma (IFN)-Γ, tumor necrosis factor (TNF)-α, and Chemokine C-C motif ligand-2 (CCL-2)-measured at baseline, and after 2, 8 and 16 weeks were included in logistic regression analyzes to assess associations between inflammatory markers and treatment response.

RESULTS

Pre-treatment IFN-Γ and CCL-2 levels were significantly associated with a lower of odds of response to escitalopram at 8 weeks. Increases in CCL-2 levels from weeks 8 to 16 in escitalopram non-responders were significantly associated with higher odds of non-response to adjunctive aripiprazole at week 16.

CONCLUSION

Higher pre-treatment levels of IFN-Γ and CCL-2 were associated with non-response to escitalopram. Increasing levels of these pro-inflammatory markers may be associated with non-response to adjunctive aripiprazole. These findings require validation in independent clinical populations.

Consideration of vaping products as an alternative to adult smoking: a narrative review

Tobacco harm reduction is a public health approach to reduce the impact of cigarette smoking on individuals. Non-combustible alternatives to cigarettes, such as electronic cigarettes (e-cigarettes), deliver nicotine to the user in the absence of combustion. The absence of combustion in e-cigarettes reduces the level of harmful or potentially harmful chemicals in the aerosol generated. This narrative review examines the published literature that studied the chemistry of e-cigarette aerosols, the related toxicology in cell culture and animal models, as well as clinical studies that investigated short- and long-term changes in biomarkers of smoke exposure after switching to e-cigarettes. In the context of the literature reviewed, the evidence supports the harm reduction potential for adult smokers who switch to e-cigarettes.

A standardized workflow for long-term longitudinal actigraphy data processing using one year of continuous actigraphy from the CAN-BIND Wellness Monitoring Study

Monitoring sleep and activity through wearable devices such as wrist-worn actigraphs has the potential for long-term measurement in the individual's own environment. Long periods of data collection require a complex approach, including standardized pre-processing and data trimming, and robust algorithms to address non-wear and missing data. In this study, we used a data-driven approach to quality control, pre-processing and analysis of longitudinal actigraphy data collected over the course of 1 year in a sample of 95 participants. We implemented a data processing pipeline using open-source packages for longitudinal data thereby providing a framework for treating missing data patterns, non-wear scoring, sleep/wake scoring, and conducted a sensitivity analysis to demonstrate the impact of non-wear and missing data on the relationship between sleep variables and depressive symptoms. Compliance with actigraph wear decreased over time, with missing data proportion increasing from a mean of 4.8% in the first week to 23.6% at the end of the 12 months of data collection. Sensitivity analyses demonstrated the importance of defining a pre-processing threshold, as it substantially impacts the predictive value of variables on sleep-related outcomes. We developed a novel non-wear algorithm which outperformed several other algorithms and a capacitive wear sensor in quality control. These findings provide essential insight informing study design in digital health research.

Developing an Electroencephalography-Based Model for Predicting Response to Antidepressant Medication

Importance

Untreated depression is a growing public health concern, with patients often facing a prolonged trial-and-error process in search of effective treatment. Developing a predictive model for treatment response in clinical practice remains challenging.

Objective

To establish a model based on electroencephalography (EEG) to predict response to 2 distinct selective serotonin reuptake inhibitor (SSRI) medications.

Design, Setting, and Participants

This prognostic study developed a predictive model using EEG data collected between 2011 and 2017 from 2 independent cohorts of participants with depression: 1 from the first Canadian Biomarker Integration Network in Depression (CAN-BIND) group and the other from the Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) consortium. Eligible participants included those aged 18 to 65 years who had a diagnosis of major depressive disorder. Data were analyzed from January to December 2022.

Exposures

In an open-label trial, CAN-BIND participants received an 8-week treatment regimen of escitalopram treatment (10-20 mg), and EMBARC participants were randomized in a double-blind trial to receive an 8-week sertraline (50-200 mg) treatment or placebo treatment.

Main Outcomes and Measures

The model's performance was estimated using balanced accuracy, specificity, and sensitivity metrics. The model used data from the CAN-BIND cohort for internal validation, and data from the treatment group of the EMBARC cohort for external validation. At week 8, response to treatment was defined as a 50% or greater reduction in the primary, clinician-rated scale of depression severity.

Results

The CAN-BIND cohort included 125 participants (mean [SD] age, 36.4 [13.0] years; 78 [62.4%] women), and the EMBARC sertraline treatment group included 105 participants (mean [SD] age, 38.4 [13.8] years; 72 [68.6%] women). The model achieved a balanced accuracy of 64.2% (95% CI, 55.8%-72.6%), sensitivity of 66.1% (95% CI, 53.7%-78.5%), and specificity of 62.3% (95% CI, 50.1%-73.8%) during internal validation with CAN-BIND. During external validation with EMBARC, the model achieved a balanced accuracy of 63.7% (95% CI, 54.5%-72.8%), sensitivity of 58.8% (95% CI, 45.3%-72.3%), and specificity of 68.5% (95% CI, 56.1%-80.9%). Additionally, the balanced accuracy for the EMBARC placebo group (118 participants) was 48.7% (95% CI, 39.3%-58.0%), the sensitivity was 50.0% (95% CI, 35.2%-64.8%), and the specificity was 47.3% (95% CI, 35.9%-58.7%), suggesting the model's specificity in predicting SSRIs treatment response.

Conclusions and Relevance

In this prognostic study, an EEG-based model was developed and validated in 2 independent cohorts. The model showed promising accuracy in predicting treatment response to 2 distinct SSRIs, suggesting potential applications for personalized depression treatment.

Prediction of depression treatment outcome from multimodal data: a CAN-BIND-1 report

BACKGROUND

Prediction of treatment outcomes is a key step in improving the treatment of major depressive disorder (MDD). The Canadian Biomarker Integration Network in Depression (CAN-BIND) aims to predict antidepressant treatment outcomes through analyses of clinical assessment, neuroimaging, and blood biomarkers.

METHODS

In the CAN-BIND-1 dataset of 192 adults with MDD and outcomes of treatment with escitalopram, we applied machine learning models in a nested cross-validation framework. Across 210 analyses, we examined combinations of predictive variables from three modalities, measured at baseline and after 2 weeks of treatment, and five machine learning methods with and without feature selection. To optimize the predictors-to-observations ratio, we followed a tiered approach with 134 and 1152 variables in tier 1 and tier 2 respectively.

RESULTS

A combination of baseline tier 1 clinical, neuroimaging, and molecular variables predicted response with a mean balanced accuracy of 0.57 (best model mean 0.62) compared to 0.54 (best model mean 0.61) in single modality models. Adding week 2 predictors improved the prediction of response to a mean balanced accuracy of 0.59 (best model mean 0.66). Adding tier 2 features did not improve prediction.

CONCLUSIONS

A combination of clinical, neuroimaging, and molecular data improves the prediction of treatment outcomes over single modality measurement. The addition of measurements from the early stages of treatment adds precision. Present results are limited by lack of external validation. To achieve clinically meaningful prediction, the multimodal measurement should be scaled up to larger samples and the robustness of prediction tested in an external validation dataset.

The Differential Relation of Emotional, Physical, and Sexual Abuse Histories to Antidepressant Treatment Remission and Persistence of Anhedonia in Major Depression: A CAN-BIND-1 Report

OBJECTIVE

Childhood maltreatment is a potent enviromarker of risk for poor response to antidepressant medication (ADM). However, childhood maltreatment is a heterogeneous construct that includes distinct exposures that have distinct neurobiological and psychological correlates. The purpose of the current study is to examine the differential associations of emotional, physical, and sexual maltreatment to ADM outcome and to examine the unique role of anhedonia in driving poor response in patients with specific maltreatment histories.

METHODS

In a multicentre clinical trial of major depression, 164 individuals were assessed for childhood emotional, physical, and sexual maltreatment with a contextual interview with independent, standardized ratings. All individuals received 8 weeks of escitalopram, with nonresponders subsequently also receiving augmentation with aripiprazole, with outcomes measured with depression rating scales and an anhedonia scale.

RESULTS

Greater severity of emotional maltreatment perpetrated by the mother was a significant and direct predictor of lower odds of week 16 remission (odds ratio [OR] = 1.68, P = 0.02). In contrast, the relations of paternal-perpetrated emotional maltreatment and physical maltreatment to week 16 remission were indirect, mediated through greater severity of anhedonia at week 8.

CONCLUSIONS

We identify emotional maltreatment as a specific early exposure that places patients at the greatest risk for nonremission following pharmacological treatment. Further, we suggest that anhedonia is a key symptom domain driving nonremission in patients with particular maltreatment histories.

SNORD90 induces glutamatergic signaling following treatment with monoaminergic antidepressants

Pharmacotherapies for the treatment of major depressive disorder were serendipitously discovered almost seven decades ago. From this discovery, scientists pinpointed the monoaminergic system as the primary target associated with symptom alleviation. As a result, most antidepressants have been engineered to act on the monoaminergic system more selectively, primarily on serotonin, in an effort to increase treatment response and reduce unfavorable side effects. However, slow and inconsistent clinical responses continue to be observed with these available treatments. Recent findings point to the glutamatergic system as a target for rapid acting antidepressants. Investigating different cohorts of depressed individuals treated with serotonergic and other monoaminergic antidepressants, we found that the expression of a small nucleolar RNA, SNORD90, was elevated following treatment response. When we increased Snord90 levels in the mouse anterior cingulate cortex (ACC), a brain region regulating mood responses, we observed antidepressive-like behaviors. We identified neuregulin 3 (NRG3) as one of the targets of SNORD90, which we show is regulated through the accumulation of N6-methyladenosine modifications leading to YTHDF2-mediated RNA decay. We further demonstrate that a decrease in NRG3 expression resulted in increased glutamatergic release in the mouse ACC. These findings support a molecular link between monoaminergic antidepressant treatment and glutamatergic neurotransmission.

Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study

Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which patients will respond to CBT may assist in designing optimal treatment allocation strategies. In a Canadian Biomarker Integration Network for Depression (CAN-BIND) study, forty-one adults with depression were recruited to undergo a 16-week course of CBT with thirty having resting-state electroencephalography (EEG) recorded at baseline and week 2 of therapy. Successful clinical response to CBT was defined as a 50% or greater reduction in Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to post-treatment completion. EEG relative power spectral measures were analyzed at baseline, week 2, and as early changes from baseline to week 2. At baseline, lower relative delta (0.5-4 Hz) power was observed in responders. This difference was predictive of successful clinical response to CBT. Furthermore, responders exhibited an early increase in relative delta power and a decrease in relative alpha (8-12 Hz) power compared to non-responders. These changes were also found to be good predictors of response to the therapy. These findings showed the potential utility of resting-state EEG in predicting CBT outcomes. They also further reinforce the promise of an EEG-based clinical decision-making tool to support treatment decisions for each patient.

Leveraging the microbiome to understand clinical heterogeneity in depression: findings from the T-RAD study

Alterations in the gut microbiome have been linked to a variety of mental illnesses including anxiety and depression. This study utilized advanced bioinformatics tools that integrated both the compositional and community nature of gut microbiota to investigate how gut microbiota influence clinical symptoms in a sample of participants with depression. Gut microbiota of 179 participants with major depressive disorder (MDD) in the Texas Resilience Against Depression (T-RAD) study were analyzed by 16S rRNA gene sequencing of stool samples. Severity of anxiety, depression, and anhedonia symptoms were assessed with General Anxiety Disorder - 7 item scale, Patient Health 9-item Questionnaire, and Dimensional Anhedonia Rating Scale, respectively. Using weighted correlation network analysis, a data-driven approach, three co-occurrence networks of bacterial taxa were identified. One of these co-occurrence networks was significantly associated with clinical features including depression and anxiety. The hub taxa associated with this co-occurrence module -one Ruminococcaceae family taxon, one Clostridiales vadinBB60 group family taxon, and one Christencenellaceae family taxon- were connected to several additional butyrate-producing bacteria suggesting that deficits in butyrate production may contribute to clinical symptoms. Therefore, by considering the community nature of the gut microbiome in a real world clinical sample, this study identified a gut microbial co-occurrence network that was significantly associated with clinical anxiety in a cohort of depressed individuals.

Assessment of a multisite standardized biospecimen collection protocol for immune phenotyping in neurodevelopmental disorders

Multisite collection and preservation of peripheral blood mononuclear cells (PBMCs) for centralized analysis is an indispensable strategy for large cohort immune phenotyping studies. However, the absence of cross-site standardized protocols introduces unnecessary sample variance. Here we describe the protocol implemented by the Province of Ontario Neurodevelopmental Disorders (POND) Network's immune platform for the multisite collection, processing, and cryopreservation of PBMCs. We outline quality control standards and evaluate the performance of our PBMC processing and storage protocol. We also describe the Child Immune History Questionnaire results, an assessment tool evaluating pre-existing immune conditions in children with neurodevelopmental disorders (NDDs). Cell viability was assessed in samples from 178 participants based on strict quality control criteria. Overall, 83.1% of samples passed quality control standards. Samples collected and processed at the same site had higher quality control pass rates than samples that were collected and subsequently shipped to another site for processing. We investigated if freezer time impacted sample viability and found no difference in mean freezer time between samples that passed and failed quality control. The Child Immune History Questionnaire had a response rate of 87.1%. The described protocol produces viable samples that may be used in future immune phenotyping experiments.

Response Inhibition and Predicting Response to Pharmacological and Cognitive Behavioral Therapy Treatments for Major Depressive Disorder: A Canadian Biomarker Integration Network for Depression Study

BACKGROUND

Major depressive disorder (MDD) is associated with various cognitive impairments, including response inhibition. Deficits in response inhibition may also underlie poor antidepressant treatment response. Recent studies revealed that the neurobiological correlates of response inhibition can predict response to pharmacological treatments. However, the generalizability of this finding to first-line nonpharmacological treatments, particularly cognitive behavioral therapy, remains to be investigated.

METHODS

Data from two independent treatment protocols were combined, one in which 65 patients with MDD underwent treatment with escitalopram, and the other in which 41 patients with MDD underwent a course of cognitive behavioral therapy. A total of 25 healthy control subjects were also recruited. Neural correlates of response inhibition were captured by participants completing a Go/NoGo task during electroencephalography recording. Response inhibition-related measures of interest included the amplitudes of the N2 and P3 event-related potentials.

RESULTS

Pretreatment P3 amplitude, which has been linked to both the motor and cognitive aspects of response inhibition, was a significant predictor of change in depressive symptoms following escitalopram and cognitive behavioral therapy treatment. A greater pretreatment P3 amplitude was associated with a greater reduction in depressive severity. In addition, the pretreatment P3 amplitude was found to be significantly greater at baseline in remitters than in nonremitters and healthy control subjects.

CONCLUSIONS

The integrity of response inhibition may be critical for a successful course of pharmacological or psychological treatment for MDD. Electrophysiological correlates of response inhibition may have utility as a general prognostic marker of treatment response in MDD. Future studies may investigate the benefit of preceding first-line treatments with interventions that improve response inhibition in MDD.

ABCB1 Gene Variants and Antidepressant Treatment Outcomes: A Systematic Review and Meta-Analysis Including Results from the CAN-BIND-1 Study

The P-glycoprotein efflux pump, encoded by the ABCB1 gene, has been shown to alter concentrations of various antidepressants in the brain. In this study, we conducted a systematic review and meta-analysis to investigate the association between six ABCB1 single-nucleotide polymorphisms (SNPs; rs1045642, rs2032582, rs1128503, rs2032583, rs2235015, and rs2235040) and antidepressant treatment outcomes in individuals with major depressive disorder (MDD), including new data from the Canadian Biomarker and Integration Network for Depression (CAN-BIND-1) cohort. For the CAN-BIND-1 sample, we applied regression models to investigate the association between ABCB1 SNPs and antidepressant treatment response, remission, tolerability, and antidepressant serum levels. For the meta-analysis, we systematically summarized pharmacogenetic evidence of the association between ABCB1 SNPs and antidepressant treatment outcomes. Studies were included in the meta-analysis if they investigated at least one ABCB1 SNP in individuals with MDD treated with at least one antidepressant. We did not find a significant association between ABCB1 SNPs and antidepressant treatment outcomes in the CAN-BIND-1 sample. A total of 39 studies were included in the systematic review. In the meta-analysis, we observed a significant association between rs1128503 and treatment response (T vs. C-allele, odds ratio = 1.30, 95% confidence interval = 1.15-1.48, P value (adjusted) = 0.024, n = 2,526). We did not find associations among the six SNPs and treatment remission nor tolerability. Our findings provide limited evidence for an association between common ABCB1 SNPs and antidepressant outcomes, which do not support the implementation of ABCB1 genotyping to inform antidepressant treatment at this time. Future research, especially on rs1128503, is recommended.

Microbe-Immune-Stress Interactions Impact Behaviour during Postnatal Development

Decades of research have established the role of microbiota-brain communication in behaviour and brain function. Studies have shown that microbiota composition and diversity are influenced by a variety of factors including host genetics, diet, and other environmental exposures, with implications for the immunological and neurobiological development of the host organism. To further understand early-life interactions between environment, genetic factors, the microbiome and the central nervous system, we investigated the impact of postnatal stress in C57Bl/6 wild type and T-cell deficient mice on microbe-brain interactions and behaviour. Mice were exposed to immune challenge with lipopolysaccharide (LPS) at postnatal day (P) 3 and maternal separation at P9 (16 h overnight). Behavioural assessment of growth and development as well as behaviour (righting reflex, ultrasonic vocalizations in response to brief maternal separation, open field, sociability, and grooming) was conducted. Microbiota diversity and composition of fecal samples collected at P24 revealed reduced alpha diversity in T-cell-deficient mice as well as genotype- and stress-related taxa. Notably, integrated analyses of microbiota and behaviour in the context of immunocompromise revealed key behavioural related taxa that may be important to brain development. These findings are important to determining the influence of genetic and environmental factors on gut microbiota and advances our understanding microbiome-brain signaling pathways on neurodevelopment and behaviour.

Acute and chronic stress predict anti-depressant treatment outcome and naturalistic course of major depression: A CAN-BIND report

BACKGROUND

In treatment studies of major depressive disorder (MDD), exposure to major life events predicts less symptom improvement and greater likelihood of relapse. In contrast, the impact of minor life events has received less attention. We hypothesized that the impact of minor events on symptom improvement and risk of relapse would be heightened in the presence of concurrent chronic stress. We also hypothesized that major events would predict less symptom improvement and greater risk of relapse independently of chronic stress.

METHODS

Adult patients experiencing an episode of MDD were enrolled into a 16-week trial with antidepressant treatments (n = 156). Forty-three fully remitted patients agreed to participate in a naturalistic 18-month follow-up, and 30 had full data for analyses. Life events and chronic stressors were assessed using a contextual life stress interview.

RESULTS

Greater exposure to minor events predicted greater improvement in symptoms during acute treatment, but this relation was specific to those who reported greater severity of chronic stress. During follow-up, however, major life events predicted increased risk of relapse, and this effect was not moderated by chronic stress.

LIMITATION

High attrition rates led to a small sample size for the follow-up analyses.

CONCLUSIONS

Exposure to minor events may provide an opportunity to practice problem-solving skills, thereby facilitating symptom improvement. Nevertheless, acute treatment did not protect patients from relapse when they subsequently faced major events during follow-up. Therefore, adjunctive strategies may be needed to enhance outcomes during pharmacotherapy, consolidating benefits from acute treatment and providing skills to prevent relapse.

Effects of CYP2C19 and CYP2D6 gene variants on escitalopram and aripiprazole treatment outcome and serum levels: results from the CAN-BIND 1 study

Cytochrome P450 drug-metabolizing enzymes may contribute to interindividual differences in antidepressant outcomes. We investigated the effects of CYP2C19 and CYP2D6 gene variants on response, tolerability, and serum concentrations. Patients (N = 178) were treated with escitalopram (ESC) from weeks 0-8 (Phase I), and at week 8, either continued ESC if they were responders or were augmented with aripiprazole (ARI) if they were non-responders (<50% reduction in Montgomery-Åsberg Depression Rating Scale from baseline) for weeks 8-16 (Phase II). Our results showed that amongst patients on ESC-Only, CYP2C19 intermediate and poor metabolizers (IM + PMs), with reduced or null enzyme function, trended towards significantly lower symptom improvement during Phase II compared to normal metabolizers (NMs), which was not observed in ESC + ARI. We further showed that CYP2D6 NMs and IM + PMs had a higher likelihood of reporting a treatment-related central nervous system side effect in ESC-Only and ESC + ARI, respectively. The differences in the findings between ESC-Only and ESC + ARI may be due to the altered pharmacokinetics of ESC by ARI coadministration in ESC + ARI. We provided evidence for this postulation when we showed that in ESC-Only, CYP2C19 and CYP2D6 IM + PMs demonstrated significantly higher ESC concentrations at Weeks 10 and 16 compared to NMs. In contrast, ESC + ARI showed an association with CYP2C19 but not with CYP2D6 metabolizer group. Instead, ESC + ARI showed an association between CYP2D6 metabolizer group and ARI metabolite-to-drug ratio suggesting potential competition between ESC and ARI for CYP2D6. Our findings suggest that dosing based on CYP2C19 and CYP2D6 genotyping could improve safety and outcome in patients on ESC monotherapy.

"One Degree of Separation": A Mixed-Methods Evaluation of Canadian Mental Health Care User and Provider Experiences With Remote Care During COVID-19

OBJECTIVES

The COVID-19 pandemic has contributed to a shift from in-person to remote mental health care. While remote care methods have long existed, their widespread use is unprecedented. There is little research about mental health care user and provider experiences with this transition, and no published studies to date have compared satisfaction between these groups.

METHODS

Canadian mental health care users (n = 332) and providers (n = 107) completed an online self-report survey from October 2020 to February 2021 hosted by the Canadian Biomarker Integration Network in Depression. Using a mixed-methods approach, participants were asked about their use of remote care, including satisfaction, barriers to use, helpful and unhelpful factors, and suggestions for improvement.

RESULTS

Overall, 59% to 63% of health care users and 59% of health care providers were satisfied with remote care. Users reported the greatest satisfaction with the convenience of remote care, while providers were most satisfied with the speed of provision of care; all groups were least satisfied with therapeutic rapport. Health care providers were less satisfied with the user-friendliness of remote care (P < 0.001) than users, while health care users were less satisfied than providers with continuity of care (P < 0.001). The use of a video-based platform was associated with remote care satisfaction among health care users (P < 0.02), and qualitative responses support the importance of visual cues in maintaining therapeutic rapport remotely. The majority of users (55%) and providers (87%) reported a likelihood of using remote care after the pandemic.

CONCLUSIONS

Remote mental health care is generally accepted by both users and providers, and the majority would consider using remote care following the pandemic. Suggestions for improvement include greater use of video, increased attention to body language and eye contact, consistency with in-person care, as well as increased provider training and administrative support.

Immune characterization of suicidal behavior in female adolescents

Background

To address the need to identify potential markers of suicide behavior for adolescents (ages 12-18 years), mass cytometry was used to explore the cellular mechanisms that may underpin immune dysregulation in adolescents with recent suicidal behavior.

Methods

Peripheral blood mononuclear cell (PBMC) samples from 10 female adolescents with a recent suicide attempt and 4 healthy female adolescents were used. A panel of 30 antibodies was analyzed using mass cytometry. We used two complementary approaches to 1) identify the cell types that significantly differed between the two groups, and 2) explore differences in the expression profile of markers on the surface of these cells. Mass cytometry data were investigated using (Center for Disease Control, 2021) Opt-SNE for dimension reduced (Curtin and Heron, 2019), FlowSOM for clustering, and (Bridge et al., 2006) EgdeR and SAM for statistical analyses.

Results

Opt-SNE (a data driven clustering analysis) identified 15 clusters of distinct cell types. From these 15 clusters, cluster 5 (classical monocytes) had statistically lower abundance in suicidal adolescents as compared to healthy controls, whereas cluster 7 (gamma-delta T cells) had statistically higher abundance in suicidal adolescents compared to healthy control. Furthermore, across the 15 cell types, chemokine receptors, CXCR3 (cluster 5) and CXCR5 (clusters 4, 5, 7, and 9), had an elevated expression profile in those with a recent suicide attempt versus healthy controls.

Conclusion

This report demonstrates the utility of high dimensional cell phenotyping in psychiatric disorders and provides preliminary evidence for distinct immune dysfunctions in adolescents with recent suicide attempts as compared to healthy controls.

Identification of Endocannabinoid Predictors of Treatment Outcomes in Major Depressive Disorder: A Secondary Analysis of the First Canadian Biomarker Integration Network in Depression (CAN-BIND 1) Study

INTRODUCTION

An increasing number of studies are examining the link between the endocannabinoidome and major depressive disorder (MDD). We conducted an exploratory analysis of this system to identify potential markers of treatment outcomes.

METHODS

The dataset of the Canadian Biomarker Integration Network in Depression-1 study, consisting of 180 patients with MDD treated for eight weeks with escitalopram followed by eight weeks with escitalopram alone or augmented with aripiprazole was analyzed. Association between response Montgomery-Asberg Depression Rating Scale (MADRS; score reduction≥50%) or remission (MADRS score≤10) at weeks 8 and 16 and single nucleotide polymorphisms (SNPs), methylation, and mRNA levels of 33 endocannabinoid markers were examined. A standard genome-wide association studies protocol was used for identifying SNPs, and logistic regression was used to assess methylation and mRNA levels.

RESULTS

Lower methylation of CpG islands of the diacylglycerol lipase alpha gene (DAGLA) was associated with non-remission at week 16 (DAGLA; OR=0.337, p<0.003, q=0.050). Methylation of DAGLA was correlated with improvement in Clinical Global Impression (p=0.026), Quick Inventory of Depressive Symptomatology (p=0.010), and Snaith-Hamilton Pleasure scales (p=0.028). We did not find any association between SNPs or mRNA levels and treatment outcomes.

DISCUSSION

Methylation of DAGLA is a promising candidate as a marker of treatment outcomes for MDD and needs to be explored further.

Modulating brain function with microbiota

Microbial metabolites identified in animal models and human neurological diseases could be therapeutic targets.

Microbe-Immune Crosstalk: Evidence That T Cells Influence the Development of the Brain Metabolome

Cross-talk between the immune system and the brain is essential to neuronal development, neuronal excitability, neuroplasticity, and neurotransmission. Gut microbiota are essential to immune system development and immune function; hence, it is essential to consider more broadly the microbiota-immune-brain axis in neurodevelopment. The gut, brain, and microbial metabolomes obtained from C57Bl/6 and T-cell-deficient mice across four developmental timepoints (postnatal day 17, 24, 28, and 84) were studied by 1H NMR spectroscopy. 16S rRNA gene sequencing was performed on cecal and fecal samples. In the absence of T-cells, the developmental trajectory of the gut microbiota and of the host's metabolic profile was altered. The novel insights from this work include (1) the requirement of functional T-cells for the normal trajectory of microbiotal development and the metabolic maturation of the supra-organism, (2) the potential role for Muribaculaceae taxa in modulating the cecal availability of metabolites previously implicated with a role in the gut-brain axis in T-cell deficient mice, and (3) the impact of T-cell-deficiency on central levels of neuroactive metabolites.

Common Data Elements to Facilitate Sharing and Re-use of Participant-Level Data: Assessment of Psychiatric Comorbidity Across Brain Disorders

The Ontario Brain Institute's "Brain-CODE" is a large-scale informatics platform designed to support the collection, storage and integration of diverse types of data across several brain disorders as a means to understand underlying causes of brain dysfunction and developing novel approaches to treatment. By providing access to aggregated datasets on participants with and without different brain disorders, Brain-CODE will facilitate analyses both within and across diseases and cover multiple brain disorders and a wide array of data, including clinical, neuroimaging, and molecular. To help achieve these goals, consensus methodology was used to identify a set of core demographic and clinical variables that should be routinely collected across all participating programs. Establishment of Common Data Elements within Brain-CODE is critical to enable a high degree of consistency in data collection across studies and thus optimize the ability of investigators to analyze pooled participant-level data within and across brain disorders. Results are also presented using selected common data elements pooled across three studies to better understand psychiatric comorbidity in neurological disease (Alzheimer's disease/amnesic mild cognitive impairment, amyotrophic lateral sclerosis, cerebrovascular disease, frontotemporal dementia, and Parkinson's disease).

Machine learning in the prediction of depression treatment outcomes: a systematic review and meta-analysis

BACKGROUND

Multiple treatments are effective for major depressive disorder (MDD), but the outcomes of each treatment vary broadly among individuals. Accurate prediction of outcomes is needed to help select a treatment that is likely to work for a given person. We aim to examine the performance of machine learning methods in delivering replicable predictions of treatment outcomes.

METHODS

Of 7732 non-duplicate records identified through literature search, we retained 59 eligible reports and extracted data on sample, treatment, predictors, machine learning method, and treatment outcome prediction. A minimum sample size of 100 and an adequate validation method were used to identify adequate-quality studies. The effects of study features on prediction accuracy were tested with mixed-effects models. Fifty-four of the studies provided accuracy estimates or other estimates that allowed calculation of balanced accuracy of predicting outcomes of treatment.

RESULTS

Eight adequate-quality studies reported a mean accuracy of 0.63 [95% confidence interval (CI) 0.56-0.71], which was significantly lower than a mean accuracy of 0.75 (95% CI 0.72-0.78) in the other 46 studies. Among the adequate-quality studies, accuracies were higher when predicting treatment resistance (0.69) and lower when predicting remission (0.60) or response (0.56). The choice of machine learning method, feature selection, and the ratio of features to individuals were not associated with reported accuracy.

CONCLUSIONS

The negative relationship between study quality and prediction accuracy, combined with a lack of independent replication, invites caution when evaluating the potential of machine learning applications for personalizing the treatment of depression.

Neuron-derived extracellular vesicles enriched from plasma show altered size and miRNA cargo as a function of antidepressant drug response

Previous work has demonstrated that microRNAs (miRNAs) change as a function of antidepressant treatment (ADT) response. However, it is unclear how representative these peripherally detected miRNA changes are to those occurring in the brain. This study aimed to use peripherally extracted neuron-derived extracellular vesicles (NDEV) to circumvent these limitations and investigate neuronal miRNA changes associated with antidepressant response. Samples were collected at two time points (baseline and after 8 weeks of follow-up) from depressed patients who responded (N = 20) and did not respond (N = 20) to escitalopram treatment, as well as controls (N = 20). Total extracellular vesicles (EVs) were extracted from plasma, and then further enriched for NDEV by immunoprecipitation with L1CAM. EVs and NDEVs were characterized, and NDEV miRNA cargo was extracted and sequenced. Subsequently, studies in cell lines and postmortem tissue were conducted. Characterization of NDEVs revealed that they were smaller than other EVs isolated from plasma (p < 0.0001), had brain-specific neuronal markers, and contained miRNAs enriched for brain functions (p < 0.0001) Furthermore, NDEVs from depressed patients were smaller than controls (p < 0.05), and NDEV size increased with ADT response (p < 0.01). Finally, changes in NDEV cargo, specifically changes in miR-21-5p, miR-30d-5p, and miR-486-5p together (p < 0.01), were associated with ADT response. Targets of these three miRNAs were altered in brain tissue from depressed individuals (p < 0.05). Together, this study indicates that changes in peripherally isolated NDEV can act as both a clinically accessible and informative biomarker of ADT response specifically through size and cargo.

Metabolic variables associated with response to cognitive behavioural therapy for depression in females: A Canadian biomarker integration network for depression (CAN-BIND) study

INTRODUCTION

Cognitive behavioural therapy (CBT) is an established first-line treatment for depression; however, it remains unclear which factors predict a positive outcome with this approach. Prior work suggests that co-morbid obesity predicts a poorer response to antidepressant medication. The current study examined whether there is an association between weight parameters and improvement of depressive symptoms with CBT.

METHODS

This was a secondary analysis of data from the "Clinical and Biological Markers of Response to Cognitive Behavioural Therapy for Depression - 6" (CANBIND-6; https://clinicaltrials.gov/ct2/show/NCT02883257) study. Adult participants (n = 41) with a diagnosis of Major Depressive Disorder (MDD) or Persistent Depressive Disorder (PDD) were recruited from an outpatient tertiary psychiatric centre in Canada. Participants completed 20 individual sessions of CBT over 16 weeks. The primary measure for treatment outcome was the Montgomery-Åsberg Depression Rating Scale (MADRS) total score at week 16.

RESULTS

Thirty-seven participants completed assessments pre and post CBT. Baseline weight parameters were not correlated with treatment response to CBT in the entire group. There was a significant sex*waist circumference (WC) (B:-1.34; p = 0.004) and sex*body mass index (BMI) interaction (B:-2.03; p:0.009). In female participants, baseline waist circumference, but not BMI, significantly predicted week 16 MADRS after controlling for age and baseline MADRS (B:0.422 p:0.049).

LIMITATIONS

The major limitation of our preliminary finding is the small sample size.

CONCLUSION

Our preliminary findings suggest that higher waist circumference may be associated with a better treatment response to CBT for depression in females. This result could be of clinical relevance and warrants further investigation in larger and independent samples.

Hypothalamus volume and DNA methylation of stress axis genes in major depressive disorder: A CAN-BIND study report

Dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis is considered one of the mechanisms underlying the development of major depressive disorder (MDD), but the exact nature of this dysfunction is unknown. We investigated the relationship between hypothalamus volume (HV) and blood-derived DNA methylation in MDD. We obtained brain MRI, clinical and molecular data from 181 unmedicated MDD and 90 healthy control (HC) participants. MDD participants received a 16-week standardized antidepressant treatment protocol, as part of the first Canadian Biomarker Integration Network in Depression (CAN-BIND) study. We collected bilateral HV measures via manual segmentation by two independent raters. DNA methylation and RNA sequencing were performed for three key HPA axis-regulating genes coding for the corticotropin-binding protein (CRHBP), glucocorticoid receptor (NR3C1) and FK506 binding protein 5 (FKBP5). We used elastic net regression to perform variable selection and assess predictive ability of methylation variables on HV. Left HV was negatively associated with duration of current episode (ρ = -0.17, p = 0.035). We did not observe significant differences in HV between MDD and HC or any associations between HV and treatment response at weeks 8 or 16, overall depression severity, illness duration or childhood maltreatment. We also did not observe any differentially methylated CpG sites between MDD and HC groups. After assessing functionality by correlating methylation levels with RNA expression of the respective genes, we observed that the number of functionally relevant CpG sites differed between MDD and HC groups in FKBP5 (χ² = 77.25, p < 0.0001) and NR3C1 (χ² = 7.29, p = 0.007). Cross-referencing functionally relevant CpG sites to those that were highly ranked in predicting HV in elastic net modeling identified one site from FKBP5 (cg03591753) and one from NR3C1 (cg20728768) within the MDD group. Stronger associations between DNA methylation, gene expression and HV in MDD suggest a novel putative molecular pathway of stress-related sensitivity in depression. Future studies should consider utilizing the epigenome and ultra-high field MR data which would allow the investigation of HV sub-fields.

The Relationship Between the Gut Microbiome-Immune System-Brain Axis and Major Depressive Disorder

Major depressive disorder (MDD) is a prominent cause of disability worldwide. Current antidepressant drugs produce full remission in only about one-third of MDD patients and there are no biomarkers to guide physicians in selecting the best treatment for individuals. There is an urgency to learn more about the etiology of MDD and to identify new targets that will lead to improved therapy and hopefully aid in predicting and preventing MDD. There has been extensive interest in the roles of the immune system and the gut microbiome in MDD and in how these systems interact. Gut microbes can contribute to the nature of immune responses, and a chronic inflammatory state may lead to increased responsiveness to stress and to development of MDD. The gut microbiome-immune system-brain axis is bidirectional, is sensitive to stress and is important in development of stress-related disorders such as MDD. Communication between the gut and brain involves the enteric nervous system (ENS), the autonomic nervous system (ANS), neuroendocrine signaling systems and the immune system, and all of these can interact with the gut microbiota. Preclinical studies and preliminary clinical investigations have reported improved mood with administration of probiotics and prebiotics, but large, carefully controlled clinical trials are now necessary to evaluate their effectiveness in treating MDD. The roles that several gut microbe-derived molecules such as neurotransmitters, short chain fatty acids and tryptophan play in MDD are reviewed briefly. Challenges and potential future directions associated with studying this important axis as it relates to MDD are discussed.

Treatment-emergent and trajectory-based peripheral gene expression markers of antidepressant response

Identifying biomarkers of antidepressant response may advance personalized treatment of major depressive disorder (MDD). We aimed to identify longitudinal changes in gene expression associated with response to antidepressants in a sample of MDD patients treated with escitalopram. Patients (N = 153) from the CAN-BIND-1 cohort were treated for 8 weeks, and depressive symptoms were assessed using the Montgomery-Åsberg Depression Rating Scale at 0, 2, 4, 6, and 8 weeks. We identified three groups of patients according to response status: early responders (22.9%), later responders (32.0%), and nonresponders (45.1%). RNA sequencing was performed in blood obtained at weeks 0, 2, and 8. RNA expression was modeled using growth models, and differences in the longitudinal changes in expression according to response were investigated using multiple regression models. The expression of RNAs related to response was investigated in the brains of depressed individuals, as well as in neuronal cells in vitro. We identified four RNAs (CERCAM, DARS-AS1, FAM228B, HBEGF) whose change over time was independently associated with a response status. For all except HBEGF, responders showed higher expression over time, compared to nonresponders. While the change in all RNAs differentiated early responders from nonresponders, changes in DARS-AS1 and HBEGF also differentiated later responders from nonresponders. Additionally, HBEGF was downregulated in the brains of depressed individuals, and increased in response to escitalopram treatment in vitro. In conclusion, using longitudinal assessments of gene expression, we provide insights into biological processes involved in the intermediate stages of escitalopram response, highlighting several genes with potential utility as biomarkers of antidepressant response.

Metabolomic signatures associated with depression and predictors of antidepressant response in humans: A CAN-BIND-1 report

One of the biggest challenges in treating depression is the heterogeneous and qualitative nature of its clinical presentations. This highlights the need to find quantitative molecular markers to tailor existing treatment strategies to the individual's biological system. In this study, high-resolution metabolic phenotyping of urine and plasma samples from the CAN-BIND study collected before treatment with two common pharmacological strategies, escitalopram and aripiprazole, was performed. Here we show that a panel of LDL and HDL subfractions were negatively correlated with depression in males. For treatment response, lower baseline concentrations of apolipoprotein A1 and HDL were predictive of escitalopram response in males, while higher baseline concentrations of apolipoprotein A2, HDL and VLDL subfractions were predictive of aripiprazole response in females. These findings support the potential of metabolomics in precision medicine and the possibility of identifying personalized interventions for depression.

Microbiota-immune alterations in adolescents following early life adversity: A proof of concept study

Early adverse care has long-term impacts on physical and mental health. The influence of rearing conditions on the infant's gut microbiota and its relationship with developmental health has become more evident. The microbiome is essential for normal growth and metabolism, and the signaling from the gut to the brain may underlie individual differences in resilience later in life. Microbial diversity and composition were determined using 16S rRNA gene amplicon sequencing in fecal samples from 17 adolescents adopted internationally from orphanages into the United States and 18 adolescents reared in birth families who had similar educational and income levels. Analyses focused on diversity of the microbial community structure and differences in the abundance of specific bacterial taxa. Blood samples were used to immunophenotype the numbers of several T-cell subsets and cytomegalovirus (CMV) seropositivity. Negative binomial regression analysis revealed several operational taxonomic units that were significantly different based on early rearing conditions and CMV seropositivity. There were significant associations between the relative abundance of certain taxa, the percentages of T-cell subsets in circulation, and CMV seropositivity. These findings demonstrate a possible link between the gut microbiota and associations with immune alterations initiated by early life adversity.

Intestinal permeability correlates with behavioural severity in very young children with ASD: A preliminary study

Systemic inflammation is known to alter behaviour, and since it has been reported that individuals with autism spectrum disorder (ASD) have higher levels of circulating cytokines, it has been hypothesized that systemic inflammation may exacerbate behaviours characteristic of ASD. The acute phase proteins α-2-macroglobulin, C-reactive protein, haptoglobin, serum amyloid P, serum amyloid A, ferritin and tissue plasminogen activator, as well as markers of intestinal permeability (intestinal fatty acid binding protein and lipopolysaccharide) were quantitated in the plasma of very young children with ASD. Behaviour severity was measured using the Autism Diagnostic Interview-Revised (ADI-R), the Autism Diagnostic Observation Schedule (ADOS) and the Vineland Adaptive Behaviour Scale (VABS). An increase in circulating I-FABP correlated with more severe deficits in communication, communication + social interaction as well as maladaptive behaviour. The acute phase protein haptoglobin was associated with more severe social interaction and communication + social interaction. In summary, I-FABP, a marker of intestinal epithelial damage, was associated with more severe behavioural phenotypes in very young children with ASD. In addition, the acute phase protein, haptoglobin, was associated with behaviour.

Is Anxiety Associated with the Gut Microbiota?

Understanding how the microbiome influences health and disease has emerged as an important area of research across all domains of biomedical and health sciences. An extensive body of work in animal models has established a link between the gut microbiome and anxiety-like behaviour. Foundational work on germ-free mice provided the catalyst for neuroscientists to consider the microbiota-brain axis and brain health. Research manipulating the microbiome, including use of germ-free mice, antibiotics, and probiotics, provide evidence that the microbiota influences stress systems and in particular anxiety-like behaviour. Consideration of anxiety-like behaviour in animal models of metabolic and inflammatory disorders expands the scope of the work and correlates in clinical studies are emerging. This chapter highlights the work done to date in animal studies and reviews the recent clinical literature translating these observations to anxiety disorders.

The effect of early life immune challenge on adult forced swim test performance and hippocampal neurogenesis

Many psychiatric diseases can be considered neurodevelopmental in nature and accumulating evidence links immune system dysfunction to disease etiology. Yet, it is currently unknown how the immune system alters brain function through development to increase susceptibility to psychiatric illness. Neonatal immune challenge in rodents is a neurodevelopmental model that has been associated with long-term molecular and behavioural changes in stress-reactivity. As enhanced stress-reactivity is associated with the emergence of depressive-like behaviours concurrent with hippocampal pathology, we measured depressive-like behaviour in the forced swim test and hippocampal neurogenesis in adult mice neonatally exposed to lipopolysaccharide LPS; 0.05 mg/kg, i.p. on postnatal days 3 and 5. As there are important functional differences along the ventral-dorsal hippocampus axis, ventral and dorsal hippocampal neurogenesis were measured separately. Our findings reveal a sexually-dimorphic response to early-life LPS challenge. Male LPS-mice spent less time immobile in the forced swim test, suggesting altered reactivity to swim stress. This was accompanied by an increase in doublecortin-positive cells in the dorsal hippocampus of female mice. These findings demonstrate that exposure to an immune challenge during critical developmental time periods leads to long-term sexually-dimorphic alterations in stress-reactivity that are accompanied by changes to adult hippocampal neurogenesis.

Diet and depression: exploring the biological mechanisms of action

The field of nutritional psychiatry has generated observational and efficacy data supporting a role for healthy dietary patterns in depression onset and symptom management. To guide future clinical trials and targeted dietary therapies, this review provides an overview of what is currently known regarding underlying mechanisms of action by which diet may influence mental and brain health. The mechanisms of action associating diet with health outcomes are complex, multifaceted, interacting, and not restricted to any one biological pathway. Numerous pathways were identified through which diet could plausibly affect mental health. These include modulation of pathways involved in inflammation, oxidative stress, epigenetics, mitochondrial dysfunction, the gut microbiota, tryptophan-kynurenine metabolism, the HPA axis, neurogenesis and BDNF, epigenetics, and obesity. However, the nascent nature of the nutritional psychiatry field to date means that the existing literature identified in this review is largely comprised of preclinical animal studies. To fully identify and elucidate complex mechanisms of action, intervention studies that assess markers related to these pathways within clinically diagnosed human populations are needed.

The Effects of Probiotics on Symptoms of Depression: Protocol for a Double-Blind Randomized Placebo-Controlled Trial

BACKGROUND

A growing body of evidence has linked mental health outcomes to the gut microbiome. This has led to the investigation of the GI tract as a target for novel treatments and interventions for depression, including probiotic supplementation. Our recent pilot study provided the first evidence of probiotics improving symptoms of depression in treatment-naive depressed patients. To further support and expand upon this evidence, data from the pilot study were used to plan a 16-week, double-blind, randomized, placebo-controlled trial to assess the effects of probiotics on depression. Here, we report the protocol for this trial.

METHODS

Participants diagnosed with depression will orally consume a probiotic supplement containing Lactobacillus helveticus and Bifidobacterium longum or placebo once daily. Participants will undergo assessments measuring clinical outcomes using a battery of validated clinical scales and questionnaires. Sleep architecture and quality will be measured using polysomnography. Neuroimaging data will be collected using magnetic resonance imaging to examine functional and structural neurophysiological changes. Molecular data will be collected from blood, stool, and urine samples to examine cytokine levels and explore potential genes and proteins that may predict outcomes in depression.

RESULTS

We expect results to replicate and expand on our pilot data demonstrating that probiotics may be effective in alleviating symptoms of depression, and to find biomarkers that will predict these outcomes.

CONCLUSIONS

The findings from this study will add to the growing body of research in this emerging field, which eventually may provide evidence for probiotics having a role in alleviating symptoms of depression.

THE DEPRESSION INVENTORY DEVELOPMENT SCALE: Assessment of Psychometric Properties Using Classical and Modern Measurement Theory in a CAN-BIND Trial

Objective: The goal of the Depression Inventory Development (DID) project is to develop a comprehensive and psychometrically sound rating scale for major depressive disorder (MDD) that reflects current diagnostic criteria and conceptualizations of depression. We report here the evaluation of the current DID item bank using Classical Test Theory (CTT), Item Response Theory (IRT) and Rasch Measurement Theory (RMT). Methods: The present study was part of a larger multisite, open-label study conducted by the Canadian Biomarker Integration Network in Depression (ClinicalTrials.gov: NCT01655706). Trained raters administered the 32 DID items at each of two visits (MDD: baseline, n=211 and Week 8, n=177; healthy participants: baseline, n=112 and Week 8, n=104). The DID's "grid" structure operationalizes intensity and frequency of each item, with clear symptom definitions and a structured interview guide, with the current iteration assessing symptoms related to anhedonia, cognition, fatigue, general malaise, motivation, anxiety, negative thinking, pain, and appetite. Participants were also administered the Montgomery- Åsberg Depression Rating Scale (MADRS) and Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR) that allowed DID items to be evaluated against existing "benchmark" items. CTT was used to assess data quality/reliability (i.e., missing data, skewness, scoring frequency, internal consistency), IRT to assess individual item performance by modelling an item's ability to discriminate levels of depressive severity (as assessed by the MADRS), and RMT to assess how the items perform together as a scale to capture a range of depressive severity (item targeting). These analyses together provided empirical evidence to base decisions on which DID items to remove, modify, or advance. Results: Of the 32 DID items evaluated, eight items were identified by CTT as problematic, displaying low variability in the range of responses, floor effects, and/or skewness; and four items were identified by IRT to show poor discriminative properties that would limit their clinical utility. Five additional items were deemed to be redundant. The remaining 15 DID items all fit the Rasch model, with person and item difficulty estimates indicating satisfactory item targeting, with lower precision in participants with mild levels of depression. These 15 DID items also showed good internal consistency (alpha=0.95 and inter-item correlations ranging from r=0.49 to r=0.84) and all items were sensitive to change following antidepressant treatment (baseline vs. Week 8). RMT revealed problematic item targeting for the MADRS and QIDSSR, including an absence of MADRS items targeting participants with mild/moderate depression and an absence of QIDS-SR items targeting participants with mild or severe depression. Conclusion: The present study applied CTT, IRT, and RMT to assess the measurement properties of the DID items and identify those that should be advanced, modified, or removed. Of the 32 items evaluated, 15 items showed good measurement properties. These items (along with previously evaluated items) will provide the basis for validation of a penultimate DID scale assessing anhedonia, cognitive slowing, concentration, executive function, recent memory, drive, emotional fatigue, guilt, self-esteem, hopelessness, tension, rumination, irritability, reduced appetite, insomnia, sadness, worry, suicidality, and depressed mood. The strategies adopted by the DID process provide a framework for rating scale development and validation.

Microbes and mental health: Can the microbiome help explain clinical heterogeneity in psychiatry?

Trillions of microbes cover the surfaces of our bodies and inhabit our gastrointestinal tract. In the past decade, research efforts examining the role of the microbiome in mental health have moved to the forefront of neuroscience and psychiatry. Based on a foundation of animal studies demonstrating the vital role for microbiota-brain communication in brain development, behavior, and brain function over the life span, clinical studies have started to consider the microbiome in psychiatric disorders. The composition, diversity and function of commensal microbes is influenced by genetic, lifestyle, and environmental factors. This review provides an overview of the factors contributing to individual differences in the microbiome, reviews recent work in psychiatric disorders, and considers what is needed to advance a better understanding of how the microbiome impacts mental health which may help us understand the heterogeneity observed in clinical psychiatric populations.

Symptom Dimension of Interest-Activity Indicates Need for Aripiprazole Augmentation of Escitalopram in Major Depressive Disorder: A CAN-BIND-1 Report

OBJECTIVE

Differential predictors of response to alternative treatment options are needed to improve the outcomes in major depressive disorder. The symptom dimension comprising loss of interest and reduced activity has been reported as a predictor of poor outcome of treatment with antidepressants. We hypothesized that augmentation with partial dopamine agonist aripiprazole will be effective for individuals with pronounced interest-activity symptoms.

METHODS

We tested the hypothesis in the 2-phase Canadian Biomarker Integration Network in Depression trial 1 (CAN-BIND-1). All participants had a primary diagnosis of major depressive disorder confirmed with the Mini-International Neuropsychiatric Interview. In phase 1, 188 individuals received escitalopram monotherapy 10-20 mg daily for 8 weeks. In phase 2, nonresponders received augmentation with aripiprazole 2-10 mg daily while responders continued escitalopram monotherapy for another 8 weeks. Outcomes were measured with the Montgomery-Åsberg Depression Rating Scale (MADRS) every 2 weeks. Effects of baseline interest-activity symptoms on outcomes were tested in repeated-measures mixed-effects models.

RESULTS

Higher baseline interest-activity score (indicative of more severe loss of interest and reduction in activity) predicted worse outcome of escitalopram monotherapy in phase 1 (b = 1.75; 95% CI, 0.45 to 3.05; P = .009), but the association disappeared with the augmentation option in phase 2 (b = -0.19; 95% CI, -1.30 to 0.92; P = .739). A significant interaction between the baseline interest-activity score and aripiprazole reflected the opposite direction of the relationship between baseline interest-activity score and degree of improvement with escitalopram monotherapy versus aripiprazole augmentation (b = -1.60; 95% CI, -2.35 to -0.84; P < .001).

CONCLUSIONS

Individuals with prominent loss of interest and reduction in activity benefit less from escitalopram monotherapy and more from aripiprazole augmentation. Future trials may test the benefits of early prodopaminergic augmentation guided by interest-activity symptoms.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT01655706.

Loss of T cells influences sex differences in stress-related gene expression

Deficiencies in the adaptive immune system have been linked to anxiety-like behaviours and stress reactivity. Mice lacking T lymphocytes through knockout of the T cell receptor (TCR) β and δ chains were compared to wild type C57Bl/6 mice. Central stress circuitry gene expression was assessed following repeated restraint stress. TCRβ-/-δ-/- mice showed an increased baseline plasma corticosterone and exaggerated changes in stress-related gene expression after repeated restraint stress. Sexual dimorphic stress responses were observed in wild-type C57Bl/6 mice but not in TCRβ-/-δ-/- mice. These data suggest that T cell-brain interactions influence sex-differences in CNS stress circuitry and stress reactivity.

Validation study of microRNAs previously associated with antidepressant response in older adults treated for late-life depression with venlafaxine

BACKGROUND

MicroRNAs (miRNAs) are small 22 nucleotides long, non-coding RNAs that are potential biomarkers for antidepressant treatment response. We aimed to replicate previous associations of miRNAs with antidepressant treatment response in a sample of older adults diagnosed with late-life depression.

METHODS

Our sample included 184 older adults diagnosed with moderately severe depression that received open-label venlafaxine (up to 300 mg/day) for approximately 12 weeks. We quantified miRNA expression levels at baseline and week 12 for miRNAs miR-1202, miR-135a-5p, miR-16-5p, miR-146a-5p, miR-146b-5p, miR-425-3p, and miR-24-3p to explore their association with remission status, response trajectories, and time-to-remission.

RESULTS

At T0 and T12, there were no differences in miRNA expression levels between remitters and non-remitters. However, remitters showed a trend toward higher baseline miR-135a-5p (Median = 11.3 [9.9, 15.7], p = .083). Prior to correction, baseline miR-135a-5p expression levels showed an association with remission status (OR = 1.8 [1.0, 3.3], p = .037). Individuals with higher baseline miR-135a-5p showed better response trajectories (F = 4.5, FDR-corrected p = 4.4 × 10^-4), particularly at weeks 10 and 12 (p < .05). In addition, individuals with higher miR-135a-5p expression reached remission faster than those with lower expression (HR = 0.6 [0.4, 0.9], FDR-corrected p = .055).

LIMITATIONS

Although the sample size was relatively modest, our findings are consistent with the literature suggesting that higher miR-135a-5p levels may be associated with better antidepressant treatment response.

CONCLUSIONS

However, the miRNA signature of antidepressant response in older adults may be different as compared to younger adults.

GPR56/ADGRG1 is associated with response to antidepressant treatment

It remains unclear why many patients with depression do not respond to antidepressant treatment. In three cohorts of individuals with depression and treated with serotonin-norepinephrine reuptake inhibitor (N = 424) we show that responders, but not non-responders, display an increase of GPR56 mRNA in the blood. In a small group of subjects we also show that GPR56 is downregulated in the PFC of individuals with depression that died by suicide. In mice, we show that chronic stress-induced Gpr56 downregulation in the blood and prefrontal cortex (PFC), which is accompanied by depression-like behavior, and can be reversed by antidepressant treatment. Gpr56 knockdown in mouse PFC is associated with depressive-like behaviors, executive dysfunction and poor response to antidepressant treatment. GPR56 peptide agonists have antidepressant-like effects and upregulated AKT/GSK3/EIF4 pathways. Our findings uncover a potential role of GPR56 in antidepressant response.

Use of Machine Learning for Predicting Escitalopram Treatment Outcome From Electroencephalography Recordings in Adult Patients With Depression

IMPORTANCE

Social and economic costs of depression are exacerbated by prolonged periods spent identifying treatments that would be effective for a particular patient. Thus, a tool that reliably predicts an individual patient's response to treatment could significantly reduce the burden of depression.

OBJECTIVE

To estimate how accurately an outcome of escitalopram treatment can be predicted from electroencephalographic (EEG) data on patients with depression.

DESIGN, SETTING, AND PARTICIPANTS

This prognostic study used a support vector machine classifier to predict treatment outcome using data from the first Canadian Biomarker Integration Network in Depression (CAN-BIND-1) study. The CAN-BIND-1 study comprised 180 patients (aged 18-60 years) diagnosed with major depressive disorder who had completed 8 weeks of treatment. Of this group, 122 patients had EEG data recorded before the treatment; 115 also had EEG data recorded after the first 2 weeks of treatment.

INTERVENTIONS

All participants completed 8 weeks of open-label escitalopram (10-20 mg) treatment.

MAIN OUTCOMES AND MEASURES

The ability of EEG data to predict treatment outcome, measured as accuracy, specificity, and sensitivity of the classifier at baseline and after the first 2 weeks of treatment. The treatment outcome was defined in terms of change in symptom severity, measured by the Montgomery-Åsberg Depression Rating Scale, before and after 8 weeks of treatment. A patient was designated as a responder if the Montgomery-Åsberg Depression Rating Scale score decreased by at least 50% during the 8 weeks and as a nonresponder if the score decrease was less than 50%.

RESULTS

Of the 122 participants who completed a baseline EEG recording (mean [SD] age, 36.3 [12.7] years; 76 [62.3%] female), the classifier was able to identify responders with an estimated accuracy of 79.2% (sensitivity, 67.3%; specificity, 91.0%) when using only the baseline EEG data. For a subset of 115 participants who had additional EEG data recorded after the first 2 weeks of treatment, use of these data increased the accuracy to 82.4% (sensitivity, 79.2%; specificity, 85.5%).

CONCLUSIONS AND RELEVANCE

These findings demonstrate the potential utility of EEG as a treatment planning tool for escitalopram therapy. Further development of the classification tools presented in this study holds the promise of expediting the search for optimal treatment for each patient.

Association Between Side Effects and Blood microRNA Expression Levels and Their Targeted Pathways in Patients With Major Depressive Disorder Treated by a Selective Serotonin Reuptake Inhibitor, Escitalopram: A CAN-BIND-1 Report

INTRODUCTION

Antidepressant drugs are effective therapies for major depressive disorder; however, they are frequently associated with side effects. Although there is some evidence for a relationship between genetic variation and side effects, little is known regarding the role of dynamic molecular factors as moderators of side effects. The aim of this study was to assess microRNA (miRNA) changes associated with side effects during escitalopram treatment and their downstream effects on target gene expression.

METHODS

A total 160 patients with major depressive disorder from the CAN-BIND-1 cohort were included. Side effects were assessed with the Toronto Side Effect Scale after 2 weeks of treatment with escitalopram. We assessed the relationship between side effects and changes in peripheral expression of miRNAs between baseline and week 2. For miRNA whose expression changed, we used target prediction algorithms to identify putative messenger RNA (mRNA) targets and assessed their expression.

RESULTS

Nausea was experienced by 42.5% of patients. We identified 45 miRNAs whose expression changed on initiation of escitalopram treatment, of which 10 displayed a negative association with intensity of nausea (miR15b-5p, miR17-5p, miR20a-5p, miR20b-5p, miR103a-3p, miR103b, miR106a-5p, miR182-5p, miR185-5p, and miR660-5p). Additionally, we found negative associations between 4 microRNAs (miR20a-5p, miR106a-5p, miR185-5p, miR660-5p) and mRNA targets. The expression of the miR185-5p target, CAMK2δ was significantly decreased [log 2 mean = -0.048 (0.233)] between weeks 0 and 2 (P = .01)].

CONCLUSIONS

We identified an overexpression of miR185-5p during escitalopram treatment of major depressive disorder, which was negatively associated with intensity of nausea, and identified a potential mRNA target that may mediate this effect.

Integrated genome-wide methylation and expression analyses reveal functional predictors of response to antidepressants

Major depressive disorder (MDD) is primarily treated with antidepressants, yet many patients fail to respond adequately, and identifying antidepressant response biomarkers is thus of clinical significance. Some hypothesis-driven investigations of epigenetic markers for treatment response have been previously made, but genome-wide approaches remain unexplored. Healthy participants (n = 112) and MDD patients (n = 211) between 18-60 years old were recruited for an 8-week trial of escitalopram treatment. Responders and non-responders were identified using differential Montgomery-Åsberg Depression Rating Scale scores before and after treatment. Genome-wide DNA methylation and gene expression analyses were assessed using the Infinium MethylationEPIC Beadchip and HumanHT-12 v4 Expression Beadchip, respectively, on pre-treatment peripheral blood DNA and RNA samples. Differentially methylated positions (DMPs) located in regions of differentially expressed genes between responders (n = 82) and non-responders (n = 95) were identified, and technically validated using a targeted sequencing approach. Three DMPs located in the genes CHN2 (cg23687322, p = 0.00043 and cg06926818, p = 0.0014) and JAK2 (cg08339825, p = 0.00021) were the most significantly associated with mRNA expression changes and subsequently validated. Replication was then conducted with non-responders (n = 76) and responders (n = 71) in an external cohort that underwent a similar antidepressant trial. One CHN2 site (cg06926818; p = 0.03) was successfully replicated. Our findings indicate that differential methylation at CpG sites upstream of the CHN2 and JAK2 TSS regions are possible peripheral predictors of antidepressant treatment response. Future studies can provide further insight on robustness of our candidate biomarkers, and greater characterization of functional components.

Gut microbial metabolites in depression: understanding the biochemical mechanisms

Gastrointestinal and central function are intrinsically connected by the gut microbiota, an ecosystem that has co-evolved with the host to expand its biotransformational capabilities and interact with host physiological processes by means of its metabolic products. Abnormalities in this microbiota-gut-brain axis have emerged as a key component in the pathophysiology of depression, leading to more research attempting to understand the neuroactive potential of the products of gut microbial metabolism. This review explores the potential for the gut microbiota to contribute to depression and focuses on the role that microbially-derived molecules – neurotransmitters, short-chain fatty acids, indoles, bile acids, choline metabolites, lactate and vitamins – play in the context of emotional behavior. The future of gut-brain axis research lies is moving away from association, towards the mechanisms underlying the relationship between the gut bacteria and depressive behavior. We propose that direct and indirect mechanisms exist through which gut microbial metabolites affect depressive behavior: these include (i) direct stimulation of central receptors, (ii) peripheral stimulation of neural, endocrine, and immune mediators, and (iii) epigenetic regulation of histone acetylation and DNA methylation. Elucidating these mechanisms is essential to expand our understanding of the etiology of depression, and to develop new strategies to harness the beneficial psychotropic effects of these molecules. Overall, the review highlights the potential for dietary interventions to represent such novel therapeutic strategies for major depressive disorder.

The Canadian Biomarker Integration Network in Depression (CAN-BIND): magnetic resonance imaging protocols

Studies of clinical populations that combine MRI data generated at multiple sites are increasingly common. The Canadian Biomarker Integration Network in Depression (CAN-BIND; www.canbind.ca) is a national depression research program that includes multimodal neuroimaging collected at several sites across Canada. The purpose of the current paper is to provide detailed information on the imaging protocols used in a number of CAN-BIND studies. The CAN-BIND program implemented a series of platform-specific MRI protocols, including a suite of prescribed structural and functional MRI sequences supported by real-time monitoring for adherence and quality control. The imaging data are retained in an established informatics and databasing platform. Approximately 1300 participants are being recruited, including almost 1000 with depression. These include participants treated with antidepressant medications, transcranial magnetic stimulation, cognitive behavioural therapy and cognitive remediation therapy. Our ability to analyze the large number of imaging variables available may be limited by the sample size of the substudies. The CAN-BIND program includes a multimodal imaging database supported by extensive clinical, demographic, neuropsychological and biological data from people with major depression. It is a resource for Canadian investigators who are interested in understanding whether aspects of neuroimaging — alone or in combination with other variables — can predict the outcomes of various treatment modalities.