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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., Introduction Treatment of major depressive disorder (MDD) is evidence-based, but treatment selection is not personalized to the features of an individual's illness. (1) The discovery of biomarkers --or predictors--of treatment [...]

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. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Psychiatry is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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. [ABSTRACT FROM AUTHOR]

Objective: Serotonergic psychedelics are re-emerging as potential novel treatments for several psychiatric disorders including major depressive disorder. The Canadian Network for Mood and Anxiety Treatments (CANMAT) convened a task force to review the evidence and provide a consensus recommendation for the clinical use of psychedelic treatments for major depressive disorder. Methods: A systematic review was conducted to identify contemporary clinical trials of serotonergic psychedelics for the treatment of major depressive disorder and cancer-related depression. Studies published between January 1990 and July 2021 were identified using combinations of search terms, inspection of bibliographies and review of other psychedelic reviews and consensus statements. The levels of evidence for efficacy were graded according to the Canadian Network for Mood and Anxiety Treatments criteria. Results: Only psilocybin and ayahuasca have contemporary clinical trials evaluating antidepressant effects. Two pilot studies showed preliminary positive effects of single-dose ayahuasca for treatment-resistant depression (Level 3 evidence). Small randomized controlled trials of psilocybin combined with psychotherapy showed superiority to waitlist controls and comparable efficacy and safety to an active comparator (escitalopram with supportive psychotherapy) in major depressive disorder, with additional randomized controlled trials showing efficacy specifically in cancer-related depression (Level 3 evidence). There was only one open-label trial of psilocybin in treatment-resistant unipolar depression (Level 4 evidence). Small sample sizes and functional unblinding were major limitations in all studies. Adverse events associated with psychedelics, including psychological (e.g., psychotomimetic effects) and physical (e.g., nausea, emesis and headaches) effects, were generally transient. Conclusions: There is currently only low-level evidence to support the efficacy and safety of psychedelics for major depressive disorder. In Canada, as of 2022, psilocybin remains an experimental option that is only available through clinical trials or the special access program. As such, Canadian Network for Mood and Anxiety Treatments considers psilocybin an experimental treatment and recommends its use primarily within clinical trials, or, less commonly, through the special access program in rare, special circumstances. [ABSTRACT FROM AUTHOR]

Exposure to stressful life events and individual differences in the personality trait neuroticism are important risk factors that interact to predict major depressive disorder (MDD). Less is known about their effect on treatment response in depression. Here, we examine whether stressful life events experienced prior to and during treatment interact with neuroticism to predict response to 16‐week pharmacotherapy for MDD. Participants included 159 outpatients with MDD who were initially treated with 8 weeks of escitalopram. Those who responded to the initial treatment continued on escitalopram monotherapy, whereas non‐responders received 8 weeks of adjunctive aripiprazole. Personality was assessed using the NEO‐Five Factor Inventory, and stressful life events were assessed using the Life Events and Difficulties Schedule, a rigorous contextual interview that includes independent ratings of threatening life events. High baseline neuroticism was associated with a lower likelihood of response when patients experienced one or more negative life events before treatment. Secondary analyses indicated that this effect was specific to neuroticism, and not better accounted for by its self‐criticism or negative affect facets. Our results suggest that assessing personality and stressful life events at baseline can help clinicians assess which patients will respond to antidepressant therapy and which may need treatment augmentation. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Psychiatry is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Introduction Many individuals with major depressive disorder (MDD) do not respond to initial antidepressant monotherapy. Adjunctive aripiprazole is recommended for treatment non-response; however, the impacts on quality of life (QoL) for individuals who receive this second-line treatment strategy have not been described. Methods We evaluated secondary QoL outcomes in patients with MDD (n=179). After 8 weeks of escitalopram, non-responders (<50% decrease in clinician-rated depression) were treated with adjunctive aripiprazole for 8 weeks (n=97); responders continued escitalopram (n=82). A repeated-measures ANOVA evaluated change in Quality of Life Enjoyment and Satisfaction Short Form scores. QoL was described relative to normative benchmarks. Results Escitalopram responders experienced the most QoL improvements in the first treatment phase. For non-responders, QoL improved with a large effect during adjunctive aripiprazole treatment. At the endpoint, 47% of patients achieving symptomatic remission still had impaired QoL. Discussion Individuals who were treated with adjunctive aripiprazole after non-response to escitalopram experienced improved QoL, but a substantial degree of QoL impairment persisted. Since QoL deficits may predict MDD recurrence, attention to ways to support this outcome is required. [ABSTRACT FROM AUTHOR]

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. Caspani et al. report on sex-specific plasma lipoproteins predictive of response to two commonly used antidepressants. The authors show that lipoproteins belonging to the same main class but differing in size and density exhibit distinct associations with depression and with response to pharmacotherapy, highlighting the importance of evaluating lipoprotein subclass in depression research. [ABSTRACT FROM AUTHOR]

Objectives: Antidepressants are first-line treatments for major depressive disorder (MDD), but 40–60% of patients will not respond, hence, predicting response would be a major clinical advance. Machine learning algorithms hold promise to predict treatment outcomes based on clinical symptoms and episode features. We sought to independently replicate recent machine learning methodology predicting antidepressant outcomes using the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) dataset, and then externally validate these methods to train models using data from the Canadian Biomarker Integration Network in Depression (CAN-BIND-1) dataset. Methods: We replicated methodology from Nie et al (2018) using common algorithms based on linear regressions and decision trees to predict treatment-resistant depression (TRD, defined as failing to respond to 2 or more antidepressants) in the STAR*D dataset. We then trained and externally validated models using the clinical features found in both datasets to predict response (≥50% reduction on the Quick Inventory for Depressive Symptomatology, Self-Rated [QIDS-SR]) and remission (endpoint QIDS-SR score ≤5) in the CAN-BIND-1 dataset. We evaluated additional models to investigate how different outcomes and features may affect prediction performance. Results: Our replicated models predicted TRD in the STAR*D dataset with slightly better balanced accuracy than Nie et al (70%-73% versus 64%-71%, respectively). Prediction performance on our external methodology validation on the CAN-BIND-1 dataset varied depending on outcome; performance was worse for response (best balanced accuracy 65%) compared to remission (77%). Using the smaller set of features found in both datasets generally improved prediction performance when evaluated on the STAR*D dataset. Conclusion: We successfully replicated prior work predicting antidepressant treatment outcomes using machine learning methods and clinical data. We found similar prediction performance using these methods on an external database, although prediction of remission was better than prediction of response. Future work is needed to improve prediction performance to be clinically useful. [ABSTRACT FROM AUTHOR]

Background: Non-response to first-line treatment for major depressive disorder (MDD) is common; for such individuals, quality of life (QoL) impairments can be severe. Identifying predictors of QoL changes may support the management of cases with persistent depressive symptoms despite adequate initial pharmacological/psychological treatment.Objective: The present study aimed to explore predictors of domain-specific QoL improvement following adjunctive aripiprazole treatment for inadequate response to initial antidepressant therapy.Methods: We evaluated secondary QoL outcomes from a CAN-BIND (Canadian Biomarker Integration Network in Depression) study in patients with MDD who did not respond to an initial 8 weeks of escitalopram and received a further 8 weeks of adjunctive aripiprazole (n = 96). Physical, psychological, social, and environmental QoL domains were assessed using the World Health Organization QoL Scale Brief Version (WHOQOL-BREF). Clinician-rated depressive symptoms were assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS). Functioning was measured with the Sheehan Disability Scale (SDS). Satisfaction with medication was assessed with a single item from the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (Q-LES-Q-SF). Exploratory t-tests were used to describe domain score changes. A hierarchical linear regression was used to explore demographic, clinical, and treatment-related predictors of improvement.Results: Across domains, QoL improved with adjunctive aripiprazole treatment. Satisfaction with medication and MADRS and SDS scores similarly improved. Symptom reduction was a predictor for positive change to physical and psychological QoL; functioning improvements were predictive of increases to all QoL domains. Satisfaction with medication predicted improvements to physical and psychological domains, whereas number of medication trials was a predictor of worsening QoL in the physical domain.Conclusion: The final model explained the most variance in psychological (68%) and physical (67%) QoL. Less variance was explained for environmental (43%) and social QoL (33%), highlighting a need for further exploration of predictors in these domains. Strategies such as functional remediation may have potential to support QoL for individuals with persistent depressive symptoms.Clinical Trials Registry: ClinicalTrials.gov identifier: NCT016557. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Psychiatry is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Patients with major depressive disorder (MDD) display cognitive deficits in acutely depressed and remitted states. Childhood maltreatment is associated with cognitive dysfunction in adults, but its impact on cognition and treatment related cognitive outcomes in adult MDD has received little consideration. We investigate whether, compared to patients without maltreatment and healthy participants, adult MDD patients with childhood maltreatment display greater cognitive deficits in acute depression, lower treatment-associated cognitive improvements, and lower cognitive performance in remission. Methods: Healthy and acutely depressed MDD participants were enrolled in a multi-center MDD predictive marker discovery trial. MDD participants received 16 weeks of standardized antidepressant treatment. Maltreatment and cognition were assessed with the Childhood Experience of Care and Abuse interview and the CNS Vital Signs battery, respectively. Cognitive scores and change from baseline to week 16 were compared amongst MDD participants with (DM+, n = 93) and without maltreatment (DM−, n = 90), and healthy participants with (HM+, n = 22) and without maltreatment (HM−, n = 80). Separate analyses in MDD participants who remitted were conducted. Results: DM+ had lower baseline global cognition, processing speed, and memory v. HM−, with no significant baseline differences amongst DM−, HM+, and HM− groups. There were no significant between-group differences in cognitive change over 16 weeks. Post-treatment remitted DM+, but not remitted DM−, scored significantly lower than HM− in working memory and processing speed. Conclusions: Childhood maltreatment was associated with cognitive deficits in depressed and remitted adults with MDD. Maltreatment may be a risk factor for more severe and persistent cognitive deficits in adult MDD. [ABSTRACT FROM AUTHOR]

(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 eflects, 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. [ABSTRACT FROM AUTHOR]

Background: In an effort to optimize patient outcomes, considerable attention is being devoted to identifying patient characteristics associated with major depressive disorder (MDD) and its responsiveness to treatment. In the current study, we extend this work by evaluating whether early change in these sensitivities is associated with response to antidepressant treatment for MDD. Methods: Participants included 210 patients with MDD who were treated with 8 weeks of escitalopram and 112 healthy comparison participants. Of the original 210 patients, 90 non-responders received adjunctive aripiprazole for an additional 8 weeks. Symptoms of depression and anhedonia were assessed at the beginning of treatment and 8 weeks later in both samples. Reward and punishment sensitivity were assessed using the BIS/BAS scales measured at the initiation of treatment and 2 weeks later. Results: Individuals with MDD exhibited higher punishment sensitivity and lower reward sensitivity compared with healthy comparison participants. Change in reward sensitivity during the first 2 weeks of treatment was associated with improved depressive symptoms and anhedonia following 8 weeks of treatment with escitalopram. Similarly, improvement in reward responsiveness during the first 2 weeks of adjunctive therapy with aripiprazole was associated with fewer symptoms of depression at post-treatment. Conclusions: Findings highlight the predictive utility of early change in reward sensitivity during antidepressant treatment for major depression. In a clinical setting, a lack of change in early reward processing may signal a need to modify a patient's treatment plan with alternative or augmented treatment approaches. [ABSTRACT FROM AUTHOR]

Background: Patients suffering from depression experience significant mood, anxiety, and cognitive symptoms. Currently, most antidepressants work by altering neurotransmitter activity in the brain to improve these symptoms. However, in the last decade, research has revealed an extensive bidirectional communication network between the gastrointestinal tract and the central nervous system, referred to as the "gut-brain axis." Advances in this field have linked psychiatric disorders to changes in the microbiome, making it a potential target for novel antidepressant treatments. The aim of this review is to analyze the current body of research assessing the effects of probiotics, on symptoms of depression in humans. Methods: A systematic search of five databases was performed and study selection was completed using the preferred reporting items for systematic reviews and meta-analyses process. Results: Ten studies met criteria and were analyzed for effects on mood, anxiety, and cognition. Five studies assessed mood symptoms, seven studies assessed anxiety symptoms, and three studies assessed cognition. The majority of the studies found positive results on all measures of depressive symptoms; however, the strain of probiotic, the dosing, and duration of treatment varied widely and no studies assessed sleep. Conclusion: The evidence for probiotics alleviating depressive symptoms is compelling but additional double-blind randomized control trials in clinical populations are warranted to further assess efficacy. [ABSTRACT FROM AUTHOR]

Background: The Canadian Network for Mood and Anxiety Treatments (CANMAT) conducted a revision of the 2009 guidelines by updating the evidence and recommendations. The scope of the 2016 guidelines remains the management of major depressive disorder (MDD) in adults, with a target audience of psychiatrists and other mental health professionals.Methods: Using the question-answer format, we conducted a systematic literature search focusing on systematic reviews and meta-analyses. Evidence was graded using CANMAT-defined criteria for level of evidence. Recommendations for lines of treatment were based on the quality of evidence and clinical expert consensus. "Pharmacological Treatments" is the third of six sections of the 2016 guidelines. With little new information on older medications, treatment recommendations focus on second-generation antidepressants.Results: Evidence-informed responses are given for 21 questions under 4 broad categories: 1) principles of pharmacological management, including individualized assessment of patient and medication factors for antidepressant selection, regular and frequent monitoring, and assessing clinical and functional outcomes with measurement-based care; 2) comparative aspects of antidepressant medications based on efficacy, tolerability, and safety, including summaries of newly approved drugs since 2009; 3) practical approaches to pharmacological management, including drug-drug interactions and maintenance recommendations; and 4) managing inadequate response and treatment resistance, with a focus on switching antidepressants, applying adjunctive treatments, and new and emerging agents.Conclusions: Evidence-based pharmacological treatments are available for first-line treatment of MDD and for management of inadequate response. However, given the limitations of the evidence base, pharmacological management of MDD still depends on tailoring treatments to the patient. [ABSTRACT FROM AUTHOR]

Background: Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD. Methods: CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response. Discussion: From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Psychiatry is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The management of depression remains a constant challenge in clinical practice. This is largely due to the fact that initial treatments frequently do not lead to remission and recovery. The current treatment approach involves lengthy trial-and-error periods. It would be beneficial to have early reliable predictors to determine whether patients will respond to treatment or not. Electroencephalography (EEG) derived biomarkers namely change in the activity of EEG frequency bands, hemispheric alpha asymmetry, theta cordance, the antidepressant treatment response index (ATR) and evoked potentials have all been shown to predict response to a variety of antidepressant medications. However, the neurobiology in support of this association has been largely unexplored. In this review, we discuss biological mechanisms for each EEG derived biomarker predictive of treatment response. Validating such biomarkers will not only greatly aid clinicians in selecting antidepressant treatment for individual patients but will also provide a critical step in drug discovery. [ABSTRACT FROM AUTHOR]

Objectives: Bipolar disorder (BD) is a disabling and often chronic condition. Patients with BD suffer from depression at least one-third of the time, but they do not always respond well to conventional mood stabilizers. Attempts to treat them with antidepressants can provoke a switch to mania or increased cycling. Our open-label trial aimed to assess the long-term response of patients with bipolar depression to the addition of quetiapine to their usual treatment. Our study also sought to assess the safety and tolerability of quetiapine in patients with BD.Method: To meet inclusion criteria for the study, patients had a DSM-IV diagnosis of type I or II BD, were aged 18 years and older, currently suffered from depression with a score of > 18 on the Hamilton Depression Rating Scale (HDRS), and had no change in antidepressant use for at least 3 weeks prior to the study. We added quetiapine to patients' medication and attempted to increase the dosage to at least 400 mg daily. Outcome was measured at baseline and once monthly for 12 months on the HDRS, the Young Mania Rating Scale, the Clinical Global Impression Scale (CGI), and the Abnormal Involuntary Movement Scale.Results: There were 19 patients enrolled in the study (6 men and 13 women), 2 of whom dropped out because they could not tolerate the drug. Seventeen completed at least 2 assessments, and 7 patients completed the full 12-month trial. Data for the 17 patients (that is, last observation carried forward) at 12 months shows HDRS scores reduced from 27.2 to 12.1 and CGI scores reduced from 4.7 to 2.6.Conclusions: Quetiapine seems to be helpful to and relatively well tolerated by patients with bipolar depression when it is added to their usual treatment. There is, however, a need for controlled trials. [ABSTRACT FROM AUTHOR]

Abstract: Purpose of study: To investigate whether the addition of triiodothyronine (T3) helps relieve depressive symptoms in non-hypothyroid major depressive disorder patients who failed to respond to an adequate course of standard SSRI antidepressant treatments. Methods: Patients who fulfilled the DSM-IV criteria for non-psychotic major depression, able to give informed consent, and failed to show satisfactory antidepressant response after a minimum of six weeks adequate treatment were recruited. To enter the study their Hamilton Depression (17-item HAMD) score had to be 18 or more, thyroid-stimulating hormone (TSH) value within the normal range, and a normal thyrotropin releasing hormone-stimulation test (TRH-ST). All patients continued taking the same SSRI which they had been taking before they entered the study. At the completion of TRH-SH they were all started on 25 μg of T3 and the dose was increased to 50 μg within a week when tolerated; they continued the combination of T3 and the SSRI for a minimum of three weeks. Results: Twelve patients, comprising eight females and four males, entered the study. One female patient withdrew during the first week of side effects, eleven patients completed the trial. The patients ranged from 26 to 77 years of age, with the mean age for males and females being 52.3 and 45.1 years, respectively. Five patients were taking sertraline (mean dose=130 mg/day) and 4 were taking citalopram (mean dose=50 mg/day), two were on fluvoxamine (150 mg/day) and one patient was on 40 mg of paroxetine. The women took a mean daily dose of 40.6 μg of T3 for a mean duration of 3.75 weeks, while the men were on a mean daily dose of 43.8 μg of T3 for 3.5 weeks. T3 augmentation was associated with a statistically significant drop (p <.003) in the mean HAMD at end of the three weeks compared to baseline scores. Five patients (42%) showed ≥50% improvement on HAMD scores, with three achieving full remission (HAMD scores≤7) at the end of the study. There were no reliable differences between responders and non-responders in baseline HAMD scores, number of previous antidepressant trials, gender or Δmax TSH. Conclusion: T3 augmentation resulted in improvement of mood scores. The responders'' rate of 42% in our study is comparable to the response rates reported using T3 or lithium to augment tricyclic antidepressants or other combination strategies used to treat resistant depression. Even though one patient withdrew prematurely due to side effects, the remaining 11 patients tolerated the addition of T3 very well. With the availability of T3, a viable, safe, inexpensive and effective augmentation treatment, the recent trend of replacing T3 with other novel strategies appears unwarranted. [Copyright &y& Elsevier]

Objective: To review the literature for reported cases of mania related to discontinuing antidepressant treatment, as well as for possible explanations of this phenomenon, and to present a case report.Method: We undertook a literature review through the PubMed index, using the key words mania, antidepressant withdrawal, and antidepressants in bipolar disorder. We reviewed 11 articles featuring 23 cases. Where available, we noted and tabulated certain parameters for both bipolar disorder (BD) and unipolar depression. We use a case example to illustrate the phenomenon of mania induced by antidepressant withdrawal.Results: For patients with unipolar depression, we found 17 reported cases of mania induced by antidepressant withdrawal. Antidepressants implicated included tricyclic antidepressants (TCAs) (12/17), monoamine oxidase inhibitors (MAOIs) (2/17), trazodone (1/17), mirtazapine (1/17), and paroxetine (1/17). For patients with BD, we found 19 reported cases of mania induced by antidepressant withdrawal, including our own case example. Of these, selective serotonin reuptake inhibitors (SSRIs) (10/19), TCAs (4/19), MAOIs (2/19), and serotonin norepinephrine reuptake inhibitors (SNRIs) (2/19) were implicated.Conclusion: Our case report supports the observation of antidepressant withdrawal-induced mania in patients with BD. It is distinguishable from antidepressant-induced mania, physiological drug withdrawal, and mania as a natural course of the illness. Many theories have been put forward to explain this occurrence. Noradrenergic hyperactivity and "withdrawal-induced cholinergic overdrive and the cholinergic-monoaminergic system" are the 2 most investigated and supported models. The former is limited by poor clinical correlation and the latter by its applicability only to anticholinergic drugs. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: This study aims to compare the effectiveness of EEG frequency band activity including interhemispheric asymmetry and prefrontal theta cordance in predicting response to escitalopram therapy at 8-weeks post-treatment, in a multi-site initiative.Methods: Resting state 64-channel EEG data were recorded from 44 patients with a diagnosis of major depressive disorder (MDD) as part of a larger, multisite discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). Clinical response was measured at 8-weeks post-treatment as change from baseline Montgomery-Asberg Depression Rating Scale (MADRS) score of 50% or more. EEG measures were analyzed at (1) pre-treatment baseline (2) 2 weeks post-treatment and (3) as an ''early change" variable defined as change in EEG from baseline to 2 weeks post-treatment.Results: At baseline, treatment responders showed elevated absolute alpha power in the left hemisphere while non-responders showed the opposite. Responders further exhibited a cortical asymmetry in the parietal region. Groups also differed in pre-treatment relative delta power with responders showing greater power in the right hemisphere over the left while non-responders showed the opposite. At 2 weeks post-treatment, responders exhibited greater absolute beta power in the left hemisphere relative to the right and the opposite was noted for non-responders. A reverse pattern was noted for absolute and relative delta power at 2 weeks post-treatment. Responders exhibited early reductions in relative alpha power and early increments in relative theta power. Non-responders showed a significant early increase in prefrontal theta cordance.Conclusions: Hemispheric asymmetries in the alpha and delta bands at baseline and at 2 weeks post-treatment have moderately strong predictive utility in predicting response to antidepressant treatment. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Clinical practice guidelines (CPG) are an important tool for implementation of evidence-based clinical care. Despite clinical trials showing lack of efficacy of some agents in bipolar disorder (BD), they are still frequently prescribed in clinical practice. The objective of this study was to systematically review the CPG recommendations on pharmacological interventions with evidence against their use due to lack of efficacy data and/or due to serious safety concerns.Methods: A systematic literature search identified 29 guidelines published by national and international organizations during the 1994-2020 period. Information was extracted regarding how the recommendations framed non-use of treatments in particular clinical situations as well as the actual recommendation in the guideline.Results: Twenty-three guidelines (79%) mentioned at least one non-recommended treatment. The terms used to qualify recommendations varied amongst guidelines and included: "not recommended" "no recommendation" and "negative evidence". Lamotrigine, topiramate and gabapentin were commonly cited as non-recommended treatments for mania and most CPG did not recommend monotherapy with antidepressants, aripiprazole, risperidone, and ziprasidone for treatment of acute bipolar depression. Most guidelines made recommendations about lack of efficacy data or potential harm in treatments for BD but there is a significant variation in the way this information is conveyed to the reader.Limitations: Non-recommended treatments were based on their use for BD episodes or maintenance but specific medications may benefit patients when treating comorbid conditions.Conclusions: The absence of a uniform language and recommendations in current guidelines may be an additional complicating factor in the implementation of evidence-based treatments in BD. [ABSTRACT FROM AUTHOR]

Background: Major Depressive Disorder (MDD) is characterized by objective and subjective cognitive deficits. Discrepancies between objective and subjective cognitive performance can reflect under- to over-estimations of cognitive abilities, and these discrepancies are referred to as cognitive self-appraisals. Despite evidence that low self-appraisals are associated with depression, the modifiability of self-appraisals and their association with treatment outcome remains unclear. The current study examined whether self-appraisals change following antidepressant treatment. Furthermore, we investigated the association of self-appraisals with treatment outcome.Methods: As part of the CAN-BIND-1 clinical trial, 154 patients with MDD completed measures of objective and subjective cognitive abilities, depressive symptoms, and functional outcomes (work productivity, psychosocial functioning, and quality of life) at baseline and post-escitalopram treatment. Self-appraisals were calculated based on discrepancies between objective and subjective cognitive abilities, with higher scores indicating overestimation of cognitive abilities.Results: Baseline self-appraisals were not predictive of treatment outcomes. However, self-appraisals increased from pre- to post-treatment. Moreover, pre-post treatment increases in self-appraisals were associated with positive treatment response and remission, decreases in depressive symptoms, and improvements in work productivity, psychosocial functioning, and quality of life.Limitations: The pre-post intervention design precluded examining the temporal precedence of change in self-appraisals versus depressive symptoms and functional outcomes.Conclusions: Findings are the first to demonstrate that self-appraisals are treatment-sensitive and are associated with treatment outcomes and recovery from MDD. Cognitive self-appraisals may represent a key marker of treatment response and a valuable target for assessment and intervention, as well as a potential mechanism underlying risk and recovery. [ABSTRACT FROM AUTHOR]

• Limited research on changes in insomnia symptoms with antidepressant pharmacotherapy. • We investigated the course of insomnia symptoms during acute treatment of MDD. • MDD patients were treated with open-label escitalopram (10–20 mg/day) for 8-weeks. • Remitters had lower QIDS-SR sleep-onset and mid-nocturnal insomnia scores. • Remitters also had lower PSQI sleep quality score than non-remitters. Despite considerable efforts to study the relationship between insomnia and depression, there is minimal research investigating whether insomnia symptoms change over time during a course of antidepressant pharmacotherapy. This study investigated the course of insomnia symptoms during the acute treatment of major depressive disorder (MDD) using a secondary analysis of data from MDD patients (N = 180) who were treated with open-label escitalopram (10–20 mg/day) for 8-weeks. Montgomery-Asberg Depression Rating Scale without sleep item (modified-MADRS) assessed depression and Self-reported Quick Inventory Depressive Scale (QIDS-SR) measured subjective sleep-onset, mid-nocturnal, and early-morning insomnia throughout 8-weeks of treatment. Pittsburgh Sleep Quality Index (PSQI) was used to assess subjective sleep quality, duration, onset latency, and efficiency throughout 8-weeks of treatment. Remission of depression was defined as modified-MADRS ≤10 at week-8. Mixed model repeated measures (MMRMs) were conducted with remission status as an independent variable and each sleep variable as a dependent variable. MMRMs demonstrated that remitters had significantly lower QIDS-SR sleep-onset and mid-nocturnal insomnia scores as well as a significantly lower PSQI sleep quality score than non-remitters throughout 8-weeks of treatment. Monitoring subjective sleep-onset and mid-nocturnal insomnia during the course of treatment with serotonergic antidepressants may be useful for predicting acute remission of depression. [ABSTRACT FROM AUTHOR]

Background: Psychostimulants have been used in the treatment of depression, with mixed results. This meta-analysis examines the efficacy and tolerability of the stimulant Lisdexamfetamine (LDX) as an add-on strategy in those with MDD who have failed to respond to an antidepressant.Method: Randomized control trials were identified and extracted from Pubmed; Web of Science; PsychINFO; and Cochrane Library. The efficacy of LDX was evaluated using Hedges' g and Odds Ratio, whereas Risk Difference was used to assess the safety and tolerability of LDX.Results: Four studies met inclusion criteria. LDX did not demonstrate superiority in efficacy relative to placebo as indicated by a Hedges' g score of 0.126 (95% CI -0.040-0.291; p = 0.136) for mean change in Montgomery-Asberg Depression Rating Scale. Odds ratios of 1.206 (95% CI 0.745-1.954; p = 0.446) and 1.244 (95% CI 0.959-1.614; p = 0.1) were found for remission and response rates respectively. Risk differences of -0.1 (95% CI -0.155-(-0.045); p < 0.001) indicated a 10% increase chance of developing treatment-emergent adverse events (TEAE) in the LDX group. There was no significant difference in risk for developing serious or severe TEAE and discontinuing treatment due to TEAE.Limitations: The number of included studies was small and only one metric was available for analysis of antidepressant efficacy of LDX.Conclusions: LDX when used as antidepressant augmentation produced a small effect in improving depressive symptoms that approached trend-level significance and demonstrated comparable tolerability to placebo. Further studies are needed to determine the optimal clinical subset of depressive symptoms responsive to LDX augmentation. [ABSTRACT FROM AUTHOR]