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Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol
BACKGROUND: Between 30 and 50% of patients with major depressive disorder (MDD) do not respond sufficiently to antidepressant regimens. The conventional pharmacological treatments predominantly target serotonergic brain signaling but better tools to predict treatment response and identify relevant s...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7391965/ https://www.ncbi.nlm.nih.gov/pubmed/32792991 http://dx.doi.org/10.3389/fpsyt.2020.00641 |
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author | Köhler-Forsberg, Kristin Jorgensen, Anders Dam, Vibeke H. Stenbæk, Dea Siggaard Fisher, Patrick M. Ip, Cheng-Teng Ganz, Melanie Poulsen, Henrik Enghusen Giraldi, Annamaria Ozenne, Brice Jørgensen, Martin Balslev Knudsen, Gitte Moos Frokjaer, Vibe Gedsoe |
author_facet | Köhler-Forsberg, Kristin Jorgensen, Anders Dam, Vibeke H. Stenbæk, Dea Siggaard Fisher, Patrick M. Ip, Cheng-Teng Ganz, Melanie Poulsen, Henrik Enghusen Giraldi, Annamaria Ozenne, Brice Jørgensen, Martin Balslev Knudsen, Gitte Moos Frokjaer, Vibe Gedsoe |
author_sort | Köhler-Forsberg, Kristin |
collection | PubMed |
description | BACKGROUND: Between 30 and 50% of patients with major depressive disorder (MDD) do not respond sufficiently to antidepressant regimens. The conventional pharmacological treatments predominantly target serotonergic brain signaling but better tools to predict treatment response and identify relevant subgroups of MDD are needed to support individualized and mechanistically targeted treatment strategies. The aim of this study is to investigate antidepressant-free patients with MDD using neuroimaging, electrophysiological, molecular, cognitive, and clinical examinations and evaluate their ability to predict clinical response to SSRI treatment as individual or combined predictors. METHODS: We will include 100 untreated patients with moderate to severe depression (>17 on the Hamilton Depression Rating Scale 17) in a non-randomized open clinical trial. We will collect data from serotonin 4 receptor positron emission tomography (PET) brain scans, functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), cognitive tests, psychometry, and peripheral biomarkers, before (at baseline), during, and after 12 weeks of standard antidepressant treatment. Patients will be treated with escitalopram, and in case of non-response at week 4 or intolerable side effects, offered to switch to a second line treatment with duloxetine. Our primary outcome (treatment response) is assessed using the Hamilton depression rating subscale 6-item scores at week 8, compared to baseline. In a subset of the patients (n = ~40), we will re-assess the neurobiological response (using PET, fMRI, and EEG) 8 weeks after initiated pharmacological antidepressant treatment, to map neurobiological signatures of treatment responses. Data from matched controls will either be collected or is already available from other cohorts. DISCUSSION: The extensive investigational program with follow-up in this large cohort of participants provides a unique possibility to (a) uncover potential biomarkers for antidepressant treatment response, (b) apply the findings for future stratification of MDD, (c) advance the understanding of pathophysiological underpinnings of MDD, and (d) uncover how putative biomarkers change in response to 8 weeks of pharmacological antidepressant treatment. Our data can pave the way for a precision medicine approach for optimized treatment of MDD and also provides a resource for future research and data sharing. CLINICAL TRIAL REGISTRATION: The study was registered at clinicaltrials.gov prior to initiation (NCT02869035; 08.16.2016, URL: https://clinicaltrials.gov/ct2/results?cond=&term=NCT02869035&cntry=&state=&city=&dist=) |
format | Online Article Text |
id | pubmed-7391965 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73919652020-08-12 Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol Köhler-Forsberg, Kristin Jorgensen, Anders Dam, Vibeke H. Stenbæk, Dea Siggaard Fisher, Patrick M. Ip, Cheng-Teng Ganz, Melanie Poulsen, Henrik Enghusen Giraldi, Annamaria Ozenne, Brice Jørgensen, Martin Balslev Knudsen, Gitte Moos Frokjaer, Vibe Gedsoe Front Psychiatry Psychiatry BACKGROUND: Between 30 and 50% of patients with major depressive disorder (MDD) do not respond sufficiently to antidepressant regimens. The conventional pharmacological treatments predominantly target serotonergic brain signaling but better tools to predict treatment response and identify relevant subgroups of MDD are needed to support individualized and mechanistically targeted treatment strategies. The aim of this study is to investigate antidepressant-free patients with MDD using neuroimaging, electrophysiological, molecular, cognitive, and clinical examinations and evaluate their ability to predict clinical response to SSRI treatment as individual or combined predictors. METHODS: We will include 100 untreated patients with moderate to severe depression (>17 on the Hamilton Depression Rating Scale 17) in a non-randomized open clinical trial. We will collect data from serotonin 4 receptor positron emission tomography (PET) brain scans, functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), cognitive tests, psychometry, and peripheral biomarkers, before (at baseline), during, and after 12 weeks of standard antidepressant treatment. Patients will be treated with escitalopram, and in case of non-response at week 4 or intolerable side effects, offered to switch to a second line treatment with duloxetine. Our primary outcome (treatment response) is assessed using the Hamilton depression rating subscale 6-item scores at week 8, compared to baseline. In a subset of the patients (n = ~40), we will re-assess the neurobiological response (using PET, fMRI, and EEG) 8 weeks after initiated pharmacological antidepressant treatment, to map neurobiological signatures of treatment responses. Data from matched controls will either be collected or is already available from other cohorts. DISCUSSION: The extensive investigational program with follow-up in this large cohort of participants provides a unique possibility to (a) uncover potential biomarkers for antidepressant treatment response, (b) apply the findings for future stratification of MDD, (c) advance the understanding of pathophysiological underpinnings of MDD, and (d) uncover how putative biomarkers change in response to 8 weeks of pharmacological antidepressant treatment. Our data can pave the way for a precision medicine approach for optimized treatment of MDD and also provides a resource for future research and data sharing. CLINICAL TRIAL REGISTRATION: The study was registered at clinicaltrials.gov prior to initiation (NCT02869035; 08.16.2016, URL: https://clinicaltrials.gov/ct2/results?cond=&term=NCT02869035&cntry=&state=&city=&dist=) Frontiers Media S.A. 2020-07-23 /pmc/articles/PMC7391965/ /pubmed/32792991 http://dx.doi.org/10.3389/fpsyt.2020.00641 Text en Copyright © 2020 Köhler-Forsberg, Jorgensen, Dam, Stenbæk, Fisher, Ip, Ganz, Poulsen, Giraldi, Ozenne, Jørgensen, Knudsen and Frokjaer http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychiatry Köhler-Forsberg, Kristin Jorgensen, Anders Dam, Vibeke H. Stenbæk, Dea Siggaard Fisher, Patrick M. Ip, Cheng-Teng Ganz, Melanie Poulsen, Henrik Enghusen Giraldi, Annamaria Ozenne, Brice Jørgensen, Martin Balslev Knudsen, Gitte Moos Frokjaer, Vibe Gedsoe Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol |
title | Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol |
title_full | Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol |
title_fullStr | Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol |
title_full_unstemmed | Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol |
title_short | Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol |
title_sort | predicting treatment outcome in major depressive disorder using serotonin 4 receptor pet brain imaging, functional mri, cognitive-, eeg-based, and peripheral biomarkers: a neuropharm open label clinical trial protocol |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7391965/ https://www.ncbi.nlm.nih.gov/pubmed/32792991 http://dx.doi.org/10.3389/fpsyt.2020.00641 |
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