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 Safety and Efficacy of Microbial Ecosystem Therapeutic-2 in People With Major Depression: Protocol for a Phase 2, Double-Blind, Placebo-Controlled Study

Background

The gut-brain axis is a bidirectional signaling pathway between the gastrointestinal tract and the brain; it is being studied because of its potential influence in mediating mood, anxiety, and other neuropsychiatric symptoms. Previous research examining the effects of gut microbiota on neuropsychiatric disorders suggests that gut repopulation treatments such as probiotics, microbe therapy, and fecal microbiota transplantation show promising results in treating symptoms of anxiety and depression. This study explores the use of an alternative gut repopulation treatment to fecal microbiota transplantation, known as Microbial Ecosystem Therapeutic (MET)-2, as an intervention against symptoms of depression. MET-2 is a daily, orally administered capsule containing 40 bacterial strains purified from a single healthy donor.

Objective

The primary aim of this study is to assess changes in mood in people with major depression that occur pre-, post-, and during the administration of MET-2. The secondary aims are to assess changes in anxiety symptoms, blood biomarker concentrations, and the level of repopulation of healthy gut bacteria as a response to treatment.

Methods

In this study, we will recruit 60 adults aged between 18 and 45 years old with major depression and randomly assign them to treatment or placebo groups. Patients in the treatment group will receive MET-2 once a day for 6 weeks, whereas patients in the placebo group will receive a matching placebo for 6 weeks. Participants will complete biweekly visits during the treatment period and a follow-up visit at 2 weeks post treatment. As a primary outcome measure, participants’ mood will be assessed using the Montgomery-Asberg Depression Rating Scale. Secondary outcome measures include changes in mood, anxiety, early stress, gastrointestinal symptoms, and tolerability of MET-2 treatment using a series of clinical scales and changes in blood markers, particularly immunoglobulins (Igs; IgA, IgG, and IgM) and inflammatory markers (C-reactive protein, tumor necrosis factor-α, transforming growth factor-β, interleukin-6, and interleukin-10). Changes in the relative abundance, diversity, and level of engraftment in fecal samples will be assessed using 16S rRNA sequencing. All data will be integrated to identify biomarkers that could indicate disease state or predict improvement in depressive symptoms in response to MET-2 treatment.

Results

Given the association between the gut microbiome and depression, we hypothesized that participants receiving MET-2 would experience greater improvement in depressive symptoms than those receiving placebo owing to the recolonization of the gut microbiome with healthy bacteria modulating the gut-brain axis connection.

Conclusions

This study is the first of its kind to evaluate the safety and efficacy of a microbial therapy such as MET-2 in comparison with placebo for major depressive disorder. We hope that this study will also reveal the potential capabilities of microbial therapies to treat other psychiatric illnesses and mood disorders.

Trial Registration

ClinicalTrials.gov NCT04602715; https://clinicaltrials.gov/ct2/show/NCT04602715

International Registered Report Identifier (IRRID)

DERR1-10.2196/31439

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.

Baseline Functional Connectivity in Resting State Networks Associated with Depression and Remission Status after 16 Weeks of Pharmacotherapy: A CAN-BIND Report

Understanding the neural underpinnings of major depressive disorder (MDD) and its treatment could improve treatment outcomes. So far, findings are variable and large sample replications scarce. We aimed to replicate and extend altered functional connectivity associated with MDD and pharmacotherapy outcomes in a large, multisite sample. Resting-state fMRI data were collected from 129 patients and 99 controls through the Canadian Biomarker Integration Network in Depression. Symptoms were assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS). Connectivity was measured as correlations between four seeds (anterior and posterior cingulate cortex, insula and dorsolateral prefrontal cortex) and all other brain voxels. Partial least squares was used to compare connectivity prior to treatment between patients and controls, and between patients reaching remission (MADRS ≤ 10) early (within 8 weeks), late (within 16 weeks), or not at all. We replicated previous findings of altered connectivity in patients. In addition, baseline connectivity of the anterior/posterior cingulate and insula seeds differentiated patients with different treatment outcomes. The stability of these differences was established in the largest single-site subsample. Our replication and extension of altered connectivity highlighted previously reported and new differences between patients and controls, and revealed features that might predict remission prior to pharmacotherapy. Trial registration:  ClinicalTrials.gov: NCT01655706.

Using Electronically Delivered Therapy and Brain Imaging to Understand OCD Pathophysiology: Pilot Protocol

BACKGROUND

Obsessive-compulsive disorder (OCD) is a debilitating and prevalent anxiety disorder. While the basal ganglia and frontal cortex are the most hypothesized brain regions involved, the exact pathophysiology is unknown. By observing the effects of proven treatments on brain activation levels, the cause of OCD can be better understood. Currently, the gold standard treatment for OCD is cognitive behavioural therapy (CBT) with exposure and response prevention (ERP). However, this is often temporally and geographically inaccessible, time-consuming, and costly. Fortunately, CBT can be effectively delivered using the internet (e-CBT) due to its structured nature thus addressing these barriers.

OBJECTIVE

This study will implement an e-CBT program for OCD and observe its effects on brain activation levels using functional magnetic resonance imaging (fMRI). It is hypothesized that brain activation levels in the basal ganglia and frontal cortex will decrease following treatment.

METHODS

Individuals with OCD will be offered a 16-week e-CBT program with ERP mirroring in-person CBT content that will be administered through a secure online platform. Efficacy of treatment will be evaluated using clinically validated symptomology questionnaires at baseline, week 8, and post-treatment (week 16). Using fMRI at baseline and post-treatment, brain activation levels will be assessed at resting state, and while exposed to anxiety-inducing images (i.e., dirty dishes if cleanliness is an obsession). The effects of treatment on brain activation levels and the correlation between symptom changes and activation levels will be analyzed.

RESULTS

The study received initial ethics approval in December 2020 and participant recruitment began in January 2021. Participant recruitment has been conducted through social media advertisements, physical advertisements, and physician referrals. To date, there have been 5 participants recruited. Data collection is expected to conclude by January 2022, and data analysis is expected to be completed by February 2022.

CONCLUSIONS

The findings from this study can further our understanding of the causation of OCD, helping to develop more effective treatments for this disorder.

CLINICALTRIAL

ClinicalTrials.gov NCT04630197; clinicaltrials.gov/ct2/show/NCT04630197.

Exploring brain connectivity changes in major depressive disorder using functional-structural data fusion: A CAN-BIND-1 study

There is a growing interest in examining the wealth of data generated by fusing functional and structural imaging information sources. These approaches may have clinical utility in identifying disruptions in the brain networks that underlie major depressive disorder (MDD). We combined an existing software toolbox with a mathematically dense statistical method to produce a novel processing pipeline for the fast and easy implementation of data fusion analysis (FATCAT‐awFC). The novel FATCAT‐awFC pipeline was then utilized to identify connectivity (conventional functional, conventional structural and anatomically weighted functional connectivy) changes in MDD patients compared to healthy comparison participants (HC). Data were acquired from the Canadian Biomarker Integration Network for Depression (CAN‐BIND‐1) study. Large‐scale resting‐state networks were assessed. We found statistically significant anatomically‐weighted functional connectivity (awFC) group differences in the default mode network and the ventral attention network, with a modest effect size (d < 0.4). Functional and structural connectivity seemed to overlap in significance between one region‐pair within the default mode network. By combining structural and functional data, awFC served to heighten or reduce the magnitude of connectivity differences in various regions distinguishing MDD from HC. This method can help us more fully understand the interconnected nature of structural and functional connectivity as it relates to depression.

Combining Ketamine and Internet-Based Cognitive Behavioral Therapy for the Treatment of Posttraumatic Stress Disorder: Protocol for a Randomized Controlled Trial

Background

Over one third of patients with posttraumatic stress disorder (PTSD) do not respond to current interventions. Ketamine presents a potential treatment option; however, its effects are temporary. Administering ketamine alongside psychotherapy is one potential means of prolonging its effects; however, only a few studies have investigated this treatment method to date, and none have tested ketamine with internet-based or electronically delivered cognitive behavioral therapy (e-CBT).

Objective

This open-label randomized controlled trial aims to assess the efficacy of a combined treatment method of subanesthetic intravenous ketamine and e-CBT for treating patients with PTSD.

Methods

In total, 20 patients with refractory PTSD recruited from a community clinic will be randomly assigned to either an experimental group (n=10), receiving a combination of ketamine and therapist-administered e-CBT over 14 weeks, or a waitlist control group (n=10), receiving the experimental treatment after 14 weeks. Both groups will be assessed for the symptoms of PTSD and comorbid disorders before treatment, at two midway points, and at the end of the experiment.

Results

PTSD symptoms of participants in the experimental group are expected to improve significantly more than those of participants in the waitlist control group (P=.05) with a large effect size (η²=0.14).

Conclusions

This is the first study to assess the relationship between e-CBT and ketamine and their combined ability to treat refractory PTSD. If successful, this study will open web-based, asynchronous therapeutic options for patients with PTSD and will provide new insights into the functional role of glutamate in trauma-related disorders as well as in learning, memory, and fear extinction.

Trial Registration

ClinicalTrials.gov NCT04771767; https://clinicaltrials.gov/ct2/show/NCT04771767.

International Registered Report Identifier (IRRID)

PRR1-10.2196/30334

White matter microstructure in youth at risk for serious mental illness: A comparative analysis

Identifying biomarkers of serious mental illness, such as altered white matter microstructure, can aid in early diagnosis and treatment. White matter microstructure was assessed using constrained spherical deconvolution of diffusion imaging data in a sample of 219 youth (age 12-25 years, 64.84% female) across 8 sites. Participants were classified as healthy controls (HC; n = 47), familial risk for serious mental illness (n = 31), mild-symptoms (n = 37), attenuated syndromes (n = 66), or discrete disorder (n = 38) based on clinical assessments. Fractional anisotropy (FA) and mean diffusivity (MD) values were derived for the whole brain white matter, forceps minor, anterior cingulate, anterior thalamic radiations (ATR), inferior fronto-occipital fasciculus, superior longitudinal fasciculus (SLF), and uncinate fasciculus (UF). Linear mixed effects models showed a significant effect of age on MD of the left ATR, left SLF, and left UF, and a significant effect of group on FA for all tracts examined. For most tracts, the discrete disorder group had significantly lower FA than other groups, and the attenuated syndromes group had higher FA compared to HC, with few differences between the remaining groups. White matter differences in MDD are most evident in individuals following illness onset, as few significant differences were observed in the risk phase.

Repetitive Transcranial Magnetic Stimulation For The Treatment of Chronic Tinnitus: A Preliminary Study of The Influence of Traumatic Brain Injury on Treatment Response

This study aims to test whether the efficacy of repetitive Transcranial Magnetic Stimulation (rTMS) differs between patients who developed tinnitus following a traumatic brain injury (TBI), and those without a history of TBI. This was a parallel pilot, open-label, non-randomized, clinical trial to compare the efficacy of low frequency rTMS on tinnitus symptoms in patients with and without a TBI history. Patients with moderate to severe tinnitus symptoms based on the Tinnitus Handicap Inventory (THI) and the Tinnitus Functional Index (TFI) were enrolled in the study. Validated questionnaires (THI and TFI) were used to quantify the severity of tinnitus symptoms and hearing impairment (Hearing Handicap Index - HHI) before and after ten sessions of rTMS of the left primary auditory cortex. Hearing threshold levels as well as speech reception and speech discrimination thresholds were also compared. The number of patients who experienced a reduction in their subjective tinnitus symptoms was greater and sustained longer in patients without a history of TBI. The same was seen with subjective symptoms of hearing impairment. In conclusion, our preliminary results suggest tinnitus patients without a history of TBI respond better to low frequency rTMS than those with a history of TBI, suggesting that treatments could be more effective if tailored to tinnitus etiology.

Multisite Comparison of MRI Defacing Software Across Multiple Cohorts

With improvements to both scan quality and facial recognition software, there is an increased risk of participants being identified by a 3D render of their structural neuroimaging scans, even when all other personal information has been removed. To prevent this, facial features should be removed before data are shared or openly released, but while there are several publicly available software algorithms to do this, there has been no comprehensive review of their accuracy within the general population. To address this, we tested multiple algorithms on 300 scans from three neuroscience research projects, funded in part by the Ontario Brain Institute, to cover a wide range of ages (3-85 years) and multiple patient cohorts. While skull stripping is more thorough at removing identifiable features, we focused mainly on defacing software, as skull stripping also removes potentially useful information, which may be required for future analyses. We tested six publicly available algorithms (afni_refacer, deepdefacer, mri_deface, mridefacer, pydeface, quickshear), with one skull stripper (FreeSurfer) included for comparison. Accuracy was measured through a pass/fail system with two criteria; one, that all facial features had been removed and two, that no brain tissue was removed in the process. A subset of defaced scans were also run through several preprocessing pipelines to ensure that none of the algorithms would alter the resulting outputs. We found that the success rates varied strongly between defacers, with afni_refacer (89%) and pydeface (83%) having the highest rates, overall. In both cases, the primary source of failure came from a single dataset that the defacer appeared to struggle with - the youngest cohort (3-20 years) for afni_refacer and the oldest (44-85 years) for pydeface, demonstrating that defacer performance not only depends on the data provided, but that this effect varies between algorithms. While there were some very minor differences between the preprocessing results for defaced and original scans, none of these were significant and were within the range of variation between using different NIfTI converters, or using raw DICOM files.

Using the Online Psychotherapy Tool to Address Mental Health Problems in the Context of the COVID-19 Pandemic: Protocol for an Electronically Delivered Cognitive Behavioral Therapy Program

Background

The considerable rise of mental health challenges during the COVID-19 pandemic has had detrimental effects on the public health sector and economy. To meet the overwhelming and growing demand for mental health care, innovative approaches must be employed to significantly expand mental health care delivery capacity. Although it is not feasible to increase the number of mental health care providers or hours they work in the short term, improving their time efficiency may be a viable solution. Virtually and digitally delivering psychotherapy, which has been shown to be efficient and clinically effective, might be a good method for addressing this growing demand.

Objective

This research protocol aims to evaluate the feasibility and efficacy of using an online, digital, asynchronous care model to treat mental health issues that are started or aggravated by stressors associated with the COVID-19 pandemic.

Methods

This nonrandomized controlled trial intervention will be delivered through the Online Psychotherapy Tool, a secure, cloud-based, digital mental health platform. Participants will be offered a 9-week electronically delivered cognitive behavioral therapy program that is tailored to address mental health problems in the context of the COVID-19 pandemic. This program will involve weekly self-guided educational material that provides an overview of behavioral skills and weekly homework. Participants (N=80) will receive personalized feedback from and weekly interaction with a therapist throughout the course of the program. The efficacy of the program will be evaluated using clinically validated symptomology questionnaires, which are to be completed by participants at baseline, week 5, and posttreatment. Inclusion criteria includes the capacity to consent; a primary diagnosis of generalized anxiety disorder or major depressive disorder, with symptoms that started or worsened during the COVID-19 pandemic; the ability to speak and read English; and consistent and reliable access to the internet. Exclusion criteria includes active psychosis, acute mania, severe alcohol or substance use disorder, and active suicidal or homicidal ideation.

Results

This study received funding in May 2020. Ethics approval was received in June 2020. The recruitment of participants began in June 2020. Participant recruitment is being conducted via social media, web-based communities, and physician referrals. To date, 58 participants have been recruited (intervention group: n=35; control group: n=23). Data collection is expected to conclude by the end of 2020. Analyses (ie, linear regression analysis for continuous outcomes and binomial regression analysis for categorical outcomes) are expected to be completed by February 2021.

Conclusions

If proven feasible, this care delivery method could increase care capacity by up to fourfold. The findings from this study can potentially influence clinical practices and policies and increase accessibility to care during the COVID-19 pandemic, without sacrificing the quality of care.

Trial Registration

ClinicalTrials.gov NCT04476667; https://clinicaltrials.gov/ct2/show/NCT04476667

International Registered Report Identifier (IRRID)

DERR1-10.2196/24913

International Consortium on the Genetics of Electroconvulsive Therapy and Severe Depressive Disorders (Gen-ECT-ic)

Recent genome-wide association studies have demonstrated that the genetic burden associated with depression correlates with depression severity. Therefore, conducting genetic studies of patients at the most severe end of the depressive disorder spectrum, those with treatment-resistant depression and who are prescribed electroconvulsive therapy (ECT), could lead to a better understanding of the genetic underpinnings of depression. Despite ECT being one of the most effective forms of treatment for severe depressive disorders, it is usually placed at the end of treatment algorithms of current guidelines. This is perhaps because ECT has controlled risk and logistical demands including use of general anaesthesia and muscle relaxants and side-effects such as short-term memory impairment. Better understanding of the genetics and biology of ECT response and of cognitive side-effects could lead to more personalized treatment decisions. To enhance the understanding of the genomics of severe depression and ECT response, researchers and ECT providers from around the world and from various depression or ECT networks, but not limited to, such as the Psychiatric Genomics Consortium, the Clinical Alliance and Research in ECT, and the National Network of Depression Centers have formed the Genetics of ECT International Consortium (Gen-ECT-ic). Gen-ECT-ic will organize the largest clinical and genetic collection to date to study the genomics of severe depressive disorders and response to ECT, aiming for 30,000 patients worldwide using a GWAS approach. At this stage it will be the largest genomic study on treatment response in depression. Retrospective data abstraction and prospective data collection will be facilitated by a uniform data collection approach that is flexible and will incorporate data from many clinical practices. Gen-ECT-ic invites all ECT providers and researchers to join its efforts.

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.

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.

Effect of fecal microbiota transplant on symptoms of psychiatric disorders: a systematic review

BACKGROUND

The Gut-Brain-Axis is a bidirectional signaling pathway between the gastrointestinal (GI) tract and the brain. The hundreds of trillions of microorganisms populating the gastrointestinal tract are thought to modulate this connection, and have far reaching effects on the immune system, central and autonomic nervous systems, and GI functioning. These interactions Diagnostic and statistical manual of mental disorders have also been linked to various psychiatric illnesses such as depression, anxiety, substance abuse, autism spectrum disorder, and eating disorders. It is hypothesized that techniques aimed at strengthening and repopulating the gut microbiome, such as Fecal Microbiota Transplant (FMT), may be useful in the prevention and treatment of psychiatric illnesses.

METHODS

A systematic search of five databases was conducted using key terms related to FMT and psychiatric illnesses. All results were then evaluated based on specific eligibility criteria.

RESULTS

Twenty-one studies met the eligibility criteria and were analysed for reported changes in mood and behavioural measures indicative of psychiatric wellbeing. The studies included were either entirely clinical (n = 8), preclinical with human donors (n = 9), or entirely preclinical (n = 11). All studies found a decrease in depressive and anxiety-like symptoms and behaviours resulting from the transplantation of healthy microbiota. The inverse was also found, with the transmission of depressive and anxiety-like symptoms and behaviours resulting from the transplantation of microbiota from psychiatrically ill donors to healthy recipients.

CONCLUSION

There appears to be strong evidence for the treatment and transmission of psychiatric illnesses through FMT. Further research with larger sample sizes and stronger scientific design is warranted in order to fully determine the efficacy and safety of this potential treatment. Registered on PROSPERO, IRD: CRD42019126795.

The Safety, Efficacy, and Tolerability of Microbial Ecosystem Therapeutic-2 in People With Major Depression and/or Generalized Anxiety Disorder: Protocol for a Phase 1, Open-Label Study

BACKGROUND

The bidirectional signaling between the gut microbiota and the brain, known as the gut-brain axis, is being heavily explored in current neuropsychiatric research. Analyses of the human gut microbiota have shown considerable individual variability in bacterial content, which is hypothesized to influence brain function, and potentially mood and anxiety symptoms, through gut-brain axis communication. Preclinical and clinical research examining these effects suggests that fecal microbiota transplant (FMT) may aid in improving the severity of depression and anxiety symptoms by recolonizing the gastrointestinal (GI) tract with healthy bacteria. The microbial ecosystem therapeutic (ie, microbial ecosystem therapeutic-2 [MET-2]) used in this study is an alternative treatment to FMT, which comprises 40 different strains of gut bacteria from a healthy donor.

OBJECTIVE

The primary objective of this study is to assess subjective changes in mood and anxiety symptoms before, during, and after administration of MET-2. The secondary objectives of this study are to assess the changes in metabolic functioning and the level of repopulation of healthy gut bacteria, the safety and tolerability of MET-2, and the effects of early stress on biomarkers of depression/anxiety and the response to treatment.

METHODS

Adults experiencing depressive or anxiety symptoms will be recruited from the Kingston area. These participants will orally consume an encapsulated MET-2 once daily-containing 40 strains of purified and laboratory-grown bacteria from a single healthy donor-for 8 weeks, followed by a 2-week treatment-free follow-up period. Participants will undergo a series of clinical assessments measuring mood, anxiety, and GI symptoms using validated clinical scales and questionnaires. Molecular data will be collected from blood and fecal samples to assess metabolic changes, neurotransmitter levels, inflammatory markers, and the level of engraftment of the fecal samples that may predict outcomes in depression or anxiety.

RESULTS

Given the association between the gut bacteria and the risk factors of depression, we expect to observe an improvement in the severity of depressive and anxiety symptoms following treatment, and we expect that this improvement is mediated by the recolonization of the GI tract with healthy bacteria. The recruitment for this study has been completed, and the data obtained are currently being analyzed.

CONCLUSIONS

This is the first time MET-2 is being tested in psychiatric indications, specifically depression and anxiety. As such, this may be the first study to show the potential effects of microbial therapy in alleviating psychiatric symptoms as well as its safety and tolerability.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/17223.

Three insights on psychoneuroimmunology of mood disorders to be taken from the COVID-19 pandemic

In the recent months, the world was taken by surprise by the outbreak of a coronavirus (SARS-CoV-2) pandemic (COVID-19). The COVID-19 pandemic is a unique opportunity to advance the understanding of the association of respiratory viruses with mood disorders and suicide. In this editorial, we explore three insights to the neuropsychoneuroimmunology of mood disorders that could be taken from the COVID-19 pandemic.

Reliability of a functional magnetic resonance imaging task of emotional conflict in healthy participants

Task-based functional neuroimaging methods are increasingly being used to identify biomarkers of treatment response in psychiatric disorders. To facilitate meaningful interpretation of neural correlates of tasks and their potential changes with treatment over time, understanding the reliability of the blood-oxygen-level dependent (BOLD) signal of such tasks is essential. We assessed test-retest reliability of an emotional conflict task in healthy participants collected as part of the Canadian Biomarker Integration Network in Depression. Data for 36 participants, scanned at three time points (weeks 0, 2, and 8) were analyzed, and intra-class correlation coefficients (ICC) were used to quantify reliability. We observed moderate reliability (median ICC values between 0.5 and 0.6), within occipital, parietal, and temporal regions, specifically for conditions of lower cognitive complexity, that is, face, congruent or incongruent trials. For these conditions, activation was also observed within frontal and sub-cortical regions, however, their reliability was poor (median ICC < 0.2). Clinically relevant prognostic markers based on task-based fMRI require high predictive accuracy at an individual level. For this to be achieved, reliability of BOLD responses needs to be high. We have shown that reliability of the BOLD response to an emotional conflict task in healthy individuals is moderate. Implications of these findings to further inform studies of treatment effects and biomarker discovery are discussed.

Reverse translation of major depressive disorder symptoms: A framework for the behavioural phenotyping of putative biomarkers

BACKGROUND

Reverse translating putative biomarkers of depression from patients to animals is complex because Major Depressive Disorder (MDD) is a highly heterogenous condition. This review proposes an approach to reverse translation based on relating relevant bio-behavioural functions in laboratory rodents to MDD symptoms.

METHODS

This systematic review outlines symptom clusters assessed by psychometric tests of MDD and antidepressant treatment response including the Montgomery-Åsberg Depression Rating Scale, the Hamilton Depression Rating Scale, and the Beck Depression Inventory. Symptoms were related to relevant behavioural assays in laboratory rodents.

RESULTS

The resulting battery of tests includes passive coping, anxiety-like behaviours, sleep, caloric intake, cognition, psychomotor functions, hedonic reactivity and aversive learning. These assays are discussed alongside relevant clinical symptoms of MDD, providing a framework through which reverse translation of a biomarker can be interpreted.

LIMITATIONS

Certain aspects of MDD may not be quantified by tests in laboratory rodents, and their biological significance may not always be of clinical relevance.

CONCLUSIONS

Using this reverse translation approach, it is possible to clarify the functional significance of a putative biomarker in rodents and hence translate its contribution to specific clinical symptoms, or clusters of symptoms.

Neurostimulation in Anxiety Disorders, Post-traumatic Stress Disorder, and Obsessive-Compulsive Disorder

Many pharmacological treatments were proved effective in the treatment of panic disorder (PD), generalized anxiety disorder (GAD), social anxiety disorder (SAD), post-traumatic stress disorder (PTSD), and obsessive-compulsive disorder (OCD); still many patients do not achieve remission with these treatments. Neurostimulation techniques have been studied as promising alternatives or augmentation treatments to pharmacological and psychological therapies. The most studied neurostimulation method for anxiety disorders, PTSD, and OCD was repetitive transcranial magnetic stimulation (rTMS). This neurostimulation technique had the highest level of evidence for GAD. There were also randomized sham-controlled trials indicating that rTMS may be effective in the treatment of PTSD and OCD, but there were conflicting findings regarding these two disorders. There is indication that rTMS may be effective in the treatment of panic disorder, but the level of evidence is low. Deep brain stimulation (DBS) was most studied for treatment of OCD, but the randomized sham-controlled trials had mixed findings. Preliminary findings indicate that DBS could be affective for PTSD. There is weak evidence indicating that electroconvulsive therapy, transcranial direct current stimulation, vagus nerve stimulation, and trigeminal nerve stimulation could be effective in the treatment of anxiety disorders, PTSD, and OCD. Regarding these disorders, there is no support in the current literature for the use of neurostimulation in clinical practice. Large high-quality studies are warranted.

An investigation of cortical thickness and antidepressant response in major depressive disorder: A CAN-BIND study report

Major depressive disorder (MDD) is considered a highly heterogeneous clinical and neurobiological mental disorder. We employed a novel layered treatment design to investigate whether cortical thickness features at baseline differentiated treatment responders from non-responders after 8 and 16 weeks of a standardized sequential antidepressant treatment. Secondary analyses examined baseline differences between MDD and controls as a replication analysis and longitudinal changes in thickness after 8 weeks of escitalopram treatment. 181 MDD and 95 healthy comparison (HC) participants were studied. After 8 weeks of escitalopram treatment (10-20 mg/d, flexible dosage), responders (>50% decrease in Montgomery-Åsberg Depression Scale score) were continued on escitalopram; non-responders received adjunctive aripiprazole (2-10 mg/d, flexible dosage). MDD participants were classified into subgroups according to their response profiles at weeks 8 and 16. Baseline group differences in cortical thickness were analyzed with FreeSurfer between HC and MDD groups as well as between response groups. Two-stage longitudinal processing was used to investigate 8-week escitalopram treatment-related changes in cortical thickness. Compared to HC, the MDD group exhibited thinner cortex in the left rostral middle frontal cortex [MNI(X,Y,Z=-29,9,54.5,-7.7); CWP=0.0002]. No baseline differences in cortical thickness were observed between responders and non-responders based on week-8 or week-16 response profile. No changes in cortical thickness was observed after 8 weeks of escitalopram monotherapy. In a two-step 16-week sequential clinical trial we found that baseline cortical thickness does not appear to be associated to clinical response to pharmacotherapy at 8 or 16 weeks.

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.

Hippocampal tail volume as a predictive biomarker of antidepressant treatment outcomes in patients with major depressive disorder: a CAN-BIND report

Finding a clinically useful neuroimaging biomarker that can predict treatment response in patients with major depressive disorder (MDD) is challenging, in part because of poor reproducibility and generalizability of findings across studies. Previous work has suggested that posterior hippocampal volumes in depressed patients may be associated with antidepressant treatment outcomes. The primary purpose of this investigation was to examine further whether posterior hippocampal volumes predict remission following antidepressant treatment. Magnetic resonance imaging (MRI) scans from 196 patients with MDD and 110 healthy participants were obtained as part of the first study in the Canadian Biomarker Integration Network in Depression program (CAN-BIND 1) in which patients were treated for 16 weeks with open-label medication. Hippocampal volumes were measured using both a manual segmentation protocol and FreeSurfer 6.0. Baseline hippocampal tail (Ht) volumes were significantly smaller in patients with depression compared to healthy participants. Larger baseline Ht volumes were positively associated with remission status at weeks 8 and 16. Participants who achieved early sustained remission had significantly greater Ht volumes compared to those who did not achieve remission by week 16. Ht volume is a prognostic biomarker for antidepressant treatment outcomes in patients with MDD.