Literature DB >> 27038550

Establishing moderators and biosignatures of antidepressant response in clinical care (EMBARC): Rationale and design.

Madhukar H Trivedi1, Patrick J McGrath2, Maurizio Fava3, Ramin V Parsey4, Benji T Kurian5, Mary L Phillips6, Maria A Oquendo2, Gerard Bruder2, Diego Pizzagalli7, Marisa Toups5, Crystal Cooper5, Phil Adams2, Sarah Weyandt5, David W Morris5, Bruce D Grannemann5, R Todd Ogden8, Randy Buckner9, Melvin McInnis10, Helena C Kraemer11, Eva Petkova12, Thomas J Carmody5, Myrna M Weissman2.   

Abstract

UNLABELLED: Remission rates for Major Depressive Disorder (MDD) are low and unpredictable for any given antidepressant. No biological or clinical marker has demonstrated sufficient ability to match individuals to efficacious treatment. Biosignatures developed from the systematic exploration of multiple biological markers, which optimize treatment selection for individuals (moderators) and provide early indication of ultimate treatment response (mediators) are needed. The rationale and design of a multi-site, placebo-controlled randomized clinical trial of sertraline examining moderators and mediators of treatment response is described. The target sample is 300 participants with early onset (≤30 years) recurrent MDD. Non-responders to an 8-week trial are switched double blind to either bupropion (for sertraline non-responders) or sertraline (for placebo non-responders) for an additional 8 weeks. Clinical moderators include anxious depression, early trauma, gender, melancholic and atypical depression, anger attacks, Axis II disorder, hypersomnia/fatigue, and chronicity of depression. Biological moderator and mediators include cerebral cortical thickness, task-based fMRI (reward and emotion conflict), resting connectivity, diffusion tensor imaging (DTI), arterial spin labeling (ASL), electroencephalograpy (EEG), cortical evoked potentials, and behavioral/cognitive tasks evaluated at baseline and week 1, except DTI, assessed only at baseline. The study is designed to standardize assessment of biomarkers across multiple sites as well as institute replicable quality control methods, and to use advanced data analytic methods to integrate these markers. A Differential Depression Treatment Response Index (DTRI) will be developed. The data, including biological samples (DNA, RNA, and plasma collected before and during treatment), will become available in a public scientific repository. CLINICAL TRIAL REGISTRATION: Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care for Depression (EMBARC). Identifier: NCT01407094. URL: http://clinicaltrials.gov/show/NCT01407094.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Antidepressant response; Biosignatures; EMBARC; Mediators; Moderators; Sertraline

Mesh:

Substances:

Year:  2016        PMID: 27038550      PMCID: PMC6100771          DOI: 10.1016/j.jpsychires.2016.03.001

Source DB:  PubMed          Journal:  J Psychiatr Res        ISSN: 0022-3956            Impact factor:   4.791


  93 in total

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Authors:  Madhukar H Trivedi; A John Rush; Stephen R Wisniewski; Andrew A Nierenberg; Diane Warden; Louise Ritz; Grayson Norquist; Robert H Howland; Barry Lebowitz; Patrick J McGrath; Kathy Shores-Wilson; Melanie M Biggs; G K Balasubramani; Maurizio Fava
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3.  Electroencephalographic alpha measures predict therapeutic response to a selective serotonin reuptake inhibitor antidepressant: pre- and post-treatment findings.

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Journal:  Biol Psychiatry       Date:  2007-12-03       Impact factor: 13.382

4.  Estimation and extrapolation of optimal treatment and testing strategies.

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Journal:  Stat Med       Date:  2008-10-15       Impact factor: 2.373

5.  Discovering, comparing, and combining moderators of treatment on outcome after randomized clinical trials: a parametric approach.

Authors:  Helena Chmura Kraemer
Journal:  Stat Med       Date:  2013-01-10       Impact factor: 2.373

6.  Moderators, mediators, and other predictors of risperidone response in children with autistic disorder and irritability.

Authors:  L Eugene Arnold; Cristan Farmer; Helena Chmura Kraemer; Mark Davies; Andrea Witwer; Shirley Chuang; Robert DiSilvestro; Christopher J McDougle; James McCracken; Benedetto Vitiello; Michael G Aman; Lawrence Scahill; David J Posey; Naomi B Swiezy
Journal:  J Child Adolesc Psychopharmacol       Date:  2010-04       Impact factor: 2.576

7.  The intensity dependence of the auditory evoked N1 component as a predictor of response to Citalopram treatment in patients with major depression.

Authors:  Thomas Linka; Bernhard W Müller; Stefan Bender; Gudrun Sartory
Journal:  Neurosci Lett       Date:  2004-09-09       Impact factor: 3.046

8.  Serotonin transporter genetic variation and the response of the human amygdala.

Authors:  Ahmad R Hariri; Venkata S Mattay; Alessandro Tessitore; Bhaskar Kolachana; Francesco Fera; David Goldman; Michael F Egan; Daniel R Weinberger
Journal:  Science       Date:  2002-07-19       Impact factor: 47.728

9.  Individual differences in reinforcement learning: behavioral, electrophysiological, and neuroimaging correlates.

Authors:  Diane L Santesso; Daniel G Dillon; Jeffrey L Birk; Avram J Holmes; Elena Goetz; Ryan Bogdan; Diego A Pizzagalli
Journal:  Neuroimage       Date:  2008-07-02       Impact factor: 6.556

10.  Individual differences in trait anhedonia: a structural and functional magnetic resonance imaging study in non-clinical subjects.

Authors:  P-O Harvey; J Pruessner; Y Czechowska; M Lepage
Journal:  Mol Psychiatry       Date:  2007-05-15       Impact factor: 15.992

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  82 in total

1.  Diagnostic classification of unipolar depression based on resting-state functional connectivity MRI: effects of generalization to a diverse sample.

Authors:  Benedikt Sundermann; Stephan Feder; Heike Wersching; Anja Teuber; Wolfram Schwindt; Harald Kugel; Walter Heindel; Volker Arolt; Klaus Berger; Bettina Pfleiderer
Journal:  J Neural Transm (Vienna)       Date:  2016-12-31       Impact factor: 3.575

2.  A comparison of structural connectivity in anxious depression versus non-anxious depression.

Authors:  Lauren Delaparte; Fang-Cheng Yeh; Phil Adams; Ashley Malchow; Madhukar H Trivedi; Maria A Oquendo; Thilo Deckersbach; Todd Ogden; Diego A Pizzagalli; Maurizio Fava; Crystal Cooper; Melvin McInnis; Benji T Kurian; Myrna M Weissman; Patrick J McGrath; Daniel N Klein; Ramin V Parsey; Christine DeLorenzo
Journal:  J Psychiatr Res       Date:  2017-01-24       Impact factor: 4.791

3.  Individual Differences in Response to Antidepressants: A Meta-analysis of Placebo-Controlled Randomized Clinical Trials.

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4.  Sex differences in the association of baseline c-reactive protein (CRP) and acute-phase treatment outcomes in major depressive disorder: Findings from the EMBARC study.

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Journal:  J Psychiatr Res       Date:  2019-03-20       Impact factor: 4.791

5.  Right patient, right treatment, right time: biosignatures and precision medicine in depression.

Authors:  Madhukar H Trivedi
Journal:  World Psychiatry       Date:  2016-10       Impact factor: 49.548

Review 6.  Potential Use of MicroRNA for Monitoring Therapeutic Response to Antidepressants.

Authors:  Raoul Belzeaux; Rixing Lin; Gustavo Turecki
Journal:  CNS Drugs       Date:  2017-04       Impact factor: 5.749

7.  Pretreatment and early-treatment cortical thickness is associated with SSRI treatment response in major depressive disorder.

Authors:  Elizabeth A Bartlett; Christine DeLorenzo; Priya Sharma; Jie Yang; Mengru Zhang; Eva Petkova; Myrna Weissman; Patrick J McGrath; Maurizio Fava; R Todd Ogden; Benji T Kurian; Ashley Malchow; Crystal M Cooper; Joseph M Trombello; Melvin McInnis; Phillip Adams; Maria A Oquendo; Diego A Pizzagalli; Madhukar Trivedi; Ramin V Parsey
Journal:  Neuropsychopharmacology       Date:  2018-06-19       Impact factor: 7.853

8.  Recent Findings of the Comparative Efficacy and Tolerability of Antidepressants for Major Depressive Disorder: Do We Now Know What to Prescribe?

Authors:  Matthew V Rudorfer
Journal:  CNS Drugs       Date:  2018-09       Impact factor: 5.749

9.  Temporal stability of posterior EEG alpha over twelve years.

Authors:  Craig E Tenke; Jürgen Kayser; Jorge E Alvarenga; Karen S Abraham; Virginia Warner; Ardesheer Talati; Myrna M Weissman; Gerard E Bruder
Journal:  Clin Neurophysiol       Date:  2018-04-16       Impact factor: 3.708

10.  Electroencephalographic Biomarkers for Treatment Response Prediction in Major Depressive Illness: A Meta-Analysis.

Authors:  Alik S Widge; M Taha Bilge; Rebecca Montana; Weilynn Chang; Carolyn I Rodriguez; Thilo Deckersbach; Linda L Carpenter; Ned H Kalin; Charles B Nemeroff
Journal:  Am J Psychiatry       Date:  2018-10-03       Impact factor: 18.112

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