@article{pmid38823590,

title = {The impact of antidepressant treatment on the network structure of neurocognition and core emotional depressive symptoms among depressed individuals with a history of suicide attempt: An 8-week clinical study},

author = {Stéphane Richard-Devantoy and Marcelo T Berlim and Nicolas Garel and Ayla Inja and Gustavo Turecki},

doi = {10.1016/j.jad.2024.05.111},

issn = {1573-2517},

year  = {2024},

date = {2024-05-01},

journal = {J Affect Disord},

volume = {361},

pages = {425--433},

abstract = {BACKGROUND: A more in-depth understanding of the relationship between depressive symptoms, neurocognition and suicidal behavior could provide insights into the prognosis and treatment of major depressive disorder (MDD) and suicide. We conducted a network analysis among depressed patients examining associations between history of suicide attempt (HSA), core emotional major depression disorder, and key neurocognitive domains.nnMETHOD: Depressed patients (n = 120) aged 18-65 years were recruited from a larger randomized clinical trial conducted at the Douglas Institute in Montreal, Canada. They were randomly assigned to receive one of two antidepressant treatments (i.e., escitalopram or desvenlafaxine) for 8 weeks. Core emotional MDD and key neurocognitive domains were assessed pre-post treatment.nnRESULTS: At baseline, an association between history of suicide attempt (HSA) and phonemic verbal fluency (PVF) suggested that HSA patients reported lower levels of the latter. After 8 weeks of antidepressant treatment, HSA became conditionally independent from PVF. Similar results were found for both the HAM-D and the QIDS-SR core emotional MDD/neurocognitive networks.nnCONCLUSION: Network analysis revealed a pre-treatment relationship between a HSA and decreased phonemic VF among depressed patients, which was no longer present after 8 weeks of antidepressant treatment.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32312344,

title = {The network structure of core depressive symptom-domains in major depressive disorder following antidepressant treatment: a randomized clinical trial},

author = {Marcelo T Berlim and Stephane Richard-Devantoy and Nicole Rodrigues Dos Santos and Gustavo Turecki},

doi = {10.1017/S0033291720001002},

issn = {1469-8978},

year  = {2021},

date = {2021-10-01},

journal = {Psychol Med},

volume = {51},

number = {14},

pages = {2399--2413},

abstract = {BACKGROUND: Network analysis (NA) conceptualizes psychiatric disorders as complex dynamic systems of mutually interacting symptoms. Major depressive disorder (MDD) is a heterogeneous clinical condition, and very few studies to date have assessed putative changes in its psychopathological network structure in response to antidepressant (AD) treatment.nnMETHODS: In this randomized trial with adult depressed outpatients (n = 151), we estimated Gaussian graphical models among nine core MDD symptom-domains before and after 8 weeks of treatment with either escitalopram or desvenlafaxine. Networks were examined with the measures of cross-sectional and longitudinal structure and connectivity, centrality and predictability as well as stability and accuracy.nnRESULTS: At baseline, the most connected MDD symptom-domains were fatigue-cognitive disturbance, whereas at week 8 they were depressed mood-suicidality. Overall, the most central MDD symptom-domains at baseline and week 8 were, respectively, fatigue and depressed mood; in contrast, the most peripheral symptom-domain across both timepoints was appetite/weight disturbance. Furthermore, the psychopathological network at week 8 was significantly more interconnected than at baseline, and they were also structurally dissimilar.nnCONCLUSION: Our findings highlight the utility of focusing on the dynamic interaction between depressive symptoms to better understand how the treatment with ADs unfolds over time. In addition, depressed mood, fatigue, and cognitive/psychomotor disturbance seem to be central MDD symptoms that may be viable targets for novel, focused therapeutic interventions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33355483,

title = {Repetitive Transcranial Magnetic Stimulation for the Treatment of Post-traumatic Stress Disorder: A Systematic Review and Network Meta-analysis: La Stimulation Magnétique Transcrânienne Répétitive Pour le Traitement du Trouble de Stress Post-Traumatique : Une Revue Systématique et une Méta-Analyse en Réseau},

author = {Alexander McGirr and Daniel J Devoe and Amelie Raedler and Chantel T Debert and Zahinoor Ismail and Marcelo T Berlim},

doi = {10.1177/0706743720982432},

issn = {1497-0015},

year  = {2021},

date = {2021-09-01},

journal = {Can J Psychiatry},

volume = {66},

number = {9},

pages = {763--773},

abstract = {BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is a promising treatment modality for Post-traumatic stress disorder (PTSD). Several targets and stimulation parameters have been investigated, and while previous meta-analyses have suggested that rTMS is efficacious, these have pooled different stimulation parameters and targets, and the relative efficacy of each is unknown.nnMETHODS: We therefore performed a systematic review and network meta-analysis of randomized controlled trials (RCTs) by searching MEDLINE, EMBASE, CENTRAL, and PsycINFO and retaining RCTs with at least 5 individuals per arm and clinician-rated PTSD symptoms (PROSPERO CRD42019134984). We adhered to PRISMA guidelines, and 2 independent reviewers screened studies for eligibility and extracted the primary outcome of clinician-rated PTSD symptoms. Dropouts were extracted as a proxy for acceptability. Random effects pairwise meta-analyses and a network meta-analysis were performed.nnRESULTS: We synthesize data from 10 RCTs with a total of 421 participants. Two rTMS interventions targeting the right dorsolateral prefrontal cortex (DLPFC) improved PTSD symptoms relative to sham: low-frequency stimulation (SMD = 0.70; 95% CI, 0.22 to 1.18) and high-frequency stimulation (SMD = 0.71; 95% CI, 0.11 to 1.31). Medial PFC dTMS, right DLPFC intermittent theta-burst stimulation, and left DLPFC high-frequency stimulation did not separate from sham. Dropouts as a proxy for acceptability revealed no differences between any of the active conditions or sham nor did any of the active conditions differ from each other.nnCONCLUSION: The current literature does not support efficacy differences between interventions; however, protocols stimulating the right DLPFC appear superior to sham. It is unclear whether this reflects heterogeneity in pathology requiring a personalized medicine approach or nonspecific mechanisms of rTMS.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31043062,

title = {[Not Available]},

author = {Daniel C Kopala-Sibley and Gabrielle B Chartier and Shiv Bhanot and Jaeden Cole and Peter Y Chan and Marcelo T Berlim and Alexander McGirr},

doi = {10.1177/0706743719839705},

issn = {1497-0015},

year  = {2020},

date = {2020-04-01},

journal = {Can J Psychiatry},

volume = {65},

number = {4},

pages = {264--272},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32242018,

title = {GPR56/ADGRG1 is associated with response to antidepressant treatment},

author = {Raoul Belzeaux and Victor Gorgievski and Laura M Fiori and Juan Pablo Lopez and Julien Grenier and Rixing Lin and Corina Nagy and El Chérif Ibrahim and Eduardo Gascon and Philippe Courtet and Stéphane Richard-Devantoy and Marcelo Berlim and Eduardo Chachamovich and Jean-François Théroux and Sylvie Dumas and Bruno Giros and Susan Rotzinger and Claudio N Soares and Jane A Foster and Naguib Mechawar and Gregory G Tall and Eleni T Tzavara and Sidney H Kennedy and Gustavo Turecki},

doi = {10.1038/s41467-020-15423-5},

issn = {2041-1723},

year  = {2020},

date = {2020-04-01},

journal = {Nat Commun},

volume = {11},

number = {1},

pages = {1635},

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

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33424654,

title = {Balance Problems, Paralysis, and Angina as Clinical Markers for Severity in Major Depression},

author = {Bill Qi and Kellie MacDonald and Marcelo T Berlim and Allan Fielding and Eric Lis and Nancy Low and Stéphane Richard-Devantoy and Valerie Tourjman and Gustavo Turecki and Yannis Trakadis},

doi = {10.3389/fpsyt.2020.567394},

issn = {1664-0640},

year  = {2020},

date = {2020-01-01},

journal = {Front Psychiatry},

volume = {11},

pages = {567394},

abstract = {Major depressive disorder (MDD) is a heterogeneous disorder. Our hypothesis is that neurological symptoms correlate with the severity of MDD symptoms. One hundred eighty-four outpatients with MDD completed a self-report questionnaire on past and present medical history. Patients were divided into three roughly equal depression severity levels based on scores from the APA Severity Measure for Depression-Adult ( = 66, 58, 60, for low, medium, high severity, respectively). We saw a significant and gradual increase in the frequency of "muscular paralysis" (1.5-5.2-16.7%) and "balance problems" (21.2-36.2-46.6%) from low to medium to high severity groups. We repeated the analysis using only the two most extreme severity categories: low severity (66 samples) vs. high severity (60 samples). High severity patients were also found to experience more "angina" symptoms than low severity patients (27.3 vs. 50%). The three significant clinical variables identified were introduced into a binary logistic regression model as the independent variables with high or low severity as the dependent variable. Both "muscular paralysis" and "balance problems" were significantly associated with increased severity of depression (odds ratio of 13.5 and 2.9, respectively), while "angina" was associated with an increase in severity with an odds ratio of 2.0, albeit not significantly. We show that neurological exam or clinical history could be useful biomarkers for depression severity. Our findings, if replicated, could lead to a simple clinical scale administered regularly for monitoring patients with MDD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30286415,

title = {A systematic meta-review of predictors of antidepressant treatment outcome in major depressive disorder},

author = {Kelly Perlman and David Benrimoh and Sonia Israel and Colleen Rollins and Eleanor Brown and Jingla-Fri Tunteng and Raymond You and Eunice You and Myriam Tanguay-Sela and Emily Snook and Marc Miresco and Marcelo T Berlim},

doi = {10.1016/j.jad.2018.09.067},

issn = {1573-2517},

year  = {2019},

date = {2019-01-01},

journal = {J Affect Disord},

volume = {243},

pages = {503--515},

abstract = {INTRODUCTION: The heterogeneity of symptoms and complex etiology of depression pose a significant challenge to the personalization of treatment. Meanwhile, the current application of generic treatment approaches to patients with vastly differing biological and clinical profiles is far from optimal. Here, we conduct a meta-review to identify predictors of response to antidepressant therapy in order to select robust input features for machine learning models of treatment response. These machine learning models will allow us to learn associations between patient features and treatment response which have predictive value at the individual patient level; this learning can be optimized by selecting high-quality input features for the model. While current research is difficult to directly apply to the clinic, machine learning models built using knowledge gleaned from current research may become useful clinical tools.nnMETHODS: The EMBASE and MEDLINE/PubMed online databases were searched from January 1996 to August 2017, using a combination of MeSH terms and keywords to identify relevant literature reviews. We identified a total of 1909 articles, wherein 199 articles met our inclusion criteria.nnRESULTS: An array of genetic, immune, endocrine, neuroimaging, sociodemographic, and symptom-based predictors of treatment response were extracted, varying widely in clinical utility.nnLIMITATIONS: Due to heterogeneous sample sizes, effect sizes, publication biases, and methodological disparities across reviews, we could not accurately assess the strength and directionality of every predictor.nnCONCLUSION: Notwithstanding our cautious interpretation of the results, we have identified a multitude of predictors that can be used to formulate a priori hypotheses regarding the input features for a computational model. We highlight the importance of large-scale research initiatives and clinically accessible biomarkers, as well as the need for replication studies of current findings. In addition, we provide recommendations for future improvement and standardization of research efforts in this field.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30098660,

title = {Clinical Usefulness of Therapeutic Neuromodulation for Major Depression: A Systematic Meta-Review of Recent Meta-Analyses},

author = {Alexander McGirr and Marcelo T Berlim},

doi = {10.1016/j.psc.2018.04.009},

issn = {1558-3147},

year  = {2018},

date = {2018-09-01},

journal = {Psychiatr Clin North Am},

volume = {41},

number = {3},

pages = {485--503},

abstract = {The authors conducted a meta-review of meta-analyses published in the past decade on therapeutic neuromodulation (ie, repetitive transcranial magnetic stimulation, transcranial direct current stimulation, vagus nerve stimulation and deep brain stimulation) for major depression. Active repetitive transcranial magnetic stimulation and transcranial direct current stimulation have been generally associated with small to moderate effect sizes vis-à-vis their efficacy and with similar acceptability compared with sham. Vagus nerve stimulation and deep brain stimulation (although more challenging to investigate) have demonstrated preliminary effectiveness, particularly during longer-term follow-up.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}