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
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...
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| Vydané v: | Frontiers in psychiatry Ročník 11; s. 641 |
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| Hlavní autori: | , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
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Switzerland
Frontiers Media S.A
23.07.2020
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| ISSN: | 1664-0640, 1664-0640 |
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| Abstract | 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.
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.
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.
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=). |
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| AbstractList | BackgroundBetween 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.MethodsWe 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.DiscussionThe 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 RegistrationThe 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=) 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.BACKGROUNDBetween 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.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.METHODSWe 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.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.DISCUSSIONThe 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.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=).CLINICAL TRIAL REGISTRATIONThe 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=). 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. 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. 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. 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=). |
| Author | Köhler-Forsberg, Kristin Dam, Vibeke H. Ip, Cheng-Teng Fisher, Patrick M. Stenbæk, Dea Siggaard Jorgensen, Anders Ganz, Melanie Jørgensen, Martin Balslev Giraldi, Annamaria Ozenne, Brice Knudsen, Gitte Moos Poulsen, Henrik Enghusen Frokjaer, Vibe Gedsoe |
| AuthorAffiliation | 6 Department of Computer Science, University of Copenhagen , Copenhagen , Denmark 9 Section of Biostatistics, Department of Public Health, University of Copenhagen , Copenhagen , Denmark 3 Department of Psychiatry, Psychiatric Centre Copenhagen , Copenhagen , Denmark 7 Department of Pharmacology, University of Copenhagen , Copenhagen , Denmark 4 Faculty of Health and Medical Sciences, University of Copenhagen , Denmark 2 Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen , Denmark 1 Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet , Copenhagen , Denmark 8 Sexological Clinic, Psychiatric Center Copenhagen, Department of Clinical Medicine, University of Copenhagen , Copenhagen , Denmark 5 Department of Clinical Pharmacology, H. Lundbeck A/S , Valby , Denmark |
| AuthorAffiliation_xml | – name: 3 Department of Psychiatry, Psychiatric Centre Copenhagen , Copenhagen , Denmark – name: 5 Department of Clinical Pharmacology, H. Lundbeck A/S , Valby , Denmark – name: 6 Department of Computer Science, University of Copenhagen , Copenhagen , Denmark – name: 7 Department of Pharmacology, University of Copenhagen , Copenhagen , Denmark – name: 1 Neurobiology Research Unit, Copenhagen University Hospital, Rigshospitalet , Copenhagen , Denmark – name: 9 Section of Biostatistics, Department of Public Health, University of Copenhagen , Copenhagen , Denmark – name: 8 Sexological Clinic, Psychiatric Center Copenhagen, Department of Clinical Medicine, University of Copenhagen , Copenhagen , Denmark – name: 2 Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen , Copenhagen , Denmark – name: 4 Faculty of Health and Medical Sciences, University of Copenhagen , Denmark |
| Author_xml | – sequence: 1 givenname: Kristin surname: Köhler-Forsberg fullname: Köhler-Forsberg, Kristin – sequence: 2 givenname: Anders surname: Jorgensen fullname: Jorgensen, Anders – sequence: 3 givenname: Vibeke H. surname: Dam fullname: Dam, Vibeke H. – sequence: 4 givenname: Dea Siggaard surname: Stenbæk fullname: Stenbæk, Dea Siggaard – sequence: 5 givenname: Patrick M. surname: Fisher fullname: Fisher, Patrick M. – sequence: 6 givenname: Cheng-Teng surname: Ip fullname: Ip, Cheng-Teng – sequence: 7 givenname: Melanie surname: Ganz fullname: Ganz, Melanie – sequence: 8 givenname: Henrik Enghusen surname: Poulsen fullname: Poulsen, Henrik Enghusen – sequence: 9 givenname: Annamaria surname: Giraldi fullname: Giraldi, Annamaria – sequence: 10 givenname: Brice surname: Ozenne fullname: Ozenne, Brice – sequence: 11 givenname: Martin Balslev surname: Jørgensen fullname: Jørgensen, Martin Balslev – sequence: 12 givenname: Gitte Moos surname: Knudsen fullname: Knudsen, Gitte Moos – sequence: 13 givenname: Vibe Gedsoe surname: Frokjaer fullname: Frokjaer, Vibe Gedsoe |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/32792991$$D View this record in MEDLINE/PubMed |
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| Copyright | Copyright © 2020 Köhler-Forsberg, Jorgensen, Dam, Stenbæk, Fisher, Ip, Ganz, Poulsen, Giraldi, Ozenne, Jørgensen, Knudsen and Frokjaer. Copyright © 2020 Köhler-Forsberg, Jorgensen, Dam, Stenbæk, Fisher, Ip, Ganz, Poulsen, Giraldi, Ozenne, Jørgensen, Knudsen and Frokjaer 2020 Köhler-Forsberg, Jorgensen, Dam, Stenbæk, Fisher, Ip, Ganz, Poulsen, Giraldi, Ozenne, Jørgensen, Knudsen and Frokjaer |
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| Keywords | cognition major depressive disorder treatment response biomarker positron emission tomography serotonin 4 receptor electroencephalogram functional magnetic resonance imaging |
| Language | English |
| License | Copyright © 2020 Köhler-Forsberg, Jorgensen, Dam, Stenbæk, Fisher, Ip, Ganz, Poulsen, Giraldi, Ozenne, Jørgensen, Knudsen and Frokjaer. 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. |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Reviewed by: Jeffrey Miller, Columbia University, United States; Tianmei Si, Peking University Sixth Hospital, China Edited by: Maria S. Garcia-Gutierrez, Miguel Hernández University of Elche, Spain This article was submitted to Molecular Psychiatry, a section of the journal Frontiers in Psychiatry |
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| PublicationDate | 2020-07-23 |
| PublicationDateYYYYMMDD | 2020-07-23 |
| PublicationDate_xml | – month: 07 year: 2020 text: 2020-07-23 day: 23 |
| PublicationDecade | 2020 |
| PublicationPlace | Switzerland |
| PublicationPlace_xml | – name: Switzerland |
| PublicationTitle | Frontiers in psychiatry |
| PublicationTitleAlternate | Front Psychiatry |
| PublicationYear | 2020 |
| Publisher | Frontiers Media S.A |
| Publisher_xml | – name: Frontiers Media S.A |
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| SubjectTerms | biomarker functional magnetic resonance imaging major depressive disorder positron emission tomography Psychiatry serotonin 4 receptor treatment response |
| 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 |
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