Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study
Abstract Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which patients will respond to CBT may assist in desig...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2023-05-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-35179-4 |
| _version_ | 1827939894790455296 |
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| author | Benjamin Schwartzmann Lena C. Quilty Prabhjot Dhami Rudolf Uher Timothy A. Allen Stefan Kloiber Raymond W. Lam Benicio N. Frey Roumen Milev Daniel J. Müller Claudio N. Soares Jane A. Foster Susan Rotzinger Sidney H. Kennedy Faranak Farzan |
| author_facet | Benjamin Schwartzmann Lena C. Quilty Prabhjot Dhami Rudolf Uher Timothy A. Allen Stefan Kloiber Raymond W. Lam Benicio N. Frey Roumen Milev Daniel J. Müller Claudio N. Soares Jane A. Foster Susan Rotzinger Sidney H. Kennedy Faranak Farzan |
| author_sort | Benjamin Schwartzmann |
| collection | DOAJ |
| description | Abstract Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which patients will respond to CBT may assist in designing optimal treatment allocation strategies. In a Canadian Biomarker Integration Network for Depression (CAN-BIND) study, forty-one adults with depression were recruited to undergo a 16-week course of CBT with thirty having resting-state electroencephalography (EEG) recorded at baseline and week 2 of therapy. Successful clinical response to CBT was defined as a 50% or greater reduction in Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to post-treatment completion. EEG relative power spectral measures were analyzed at baseline, week 2, and as early changes from baseline to week 2. At baseline, lower relative delta (0.5–4 Hz) power was observed in responders. This difference was predictive of successful clinical response to CBT. Furthermore, responders exhibited an early increase in relative delta power and a decrease in relative alpha (8–12 Hz) power compared to non-responders. These changes were also found to be good predictors of response to the therapy. These findings showed the potential utility of resting-state EEG in predicting CBT outcomes. They also further reinforce the promise of an EEG-based clinical decision-making tool to support treatment decisions for each patient. |
| first_indexed | 2024-03-13T09:01:26Z |
| format | Article |
| id | doaj.art-40d35cf6aa3e4b00bfc2b664c56cefa4 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-13T09:01:26Z |
| publishDate | 2023-05-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-40d35cf6aa3e4b00bfc2b664c56cefa42023-05-28T11:16:37ZengNature PortfolioScientific Reports2045-23222023-05-0113111210.1038/s41598-023-35179-4Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression studyBenjamin Schwartzmann0Lena C. Quilty1Prabhjot Dhami2Rudolf Uher3Timothy A. Allen4Stefan Kloiber5Raymond W. Lam6Benicio N. Frey7Roumen Milev8Daniel J. Müller9Claudio N. Soares10Jane A. Foster11Susan Rotzinger12Sidney H. Kennedy13Faranak Farzan14eBrain Lab, School of Mechatronic Systems Engineering, Simon Fraser UniversityUniversity of TorontoeBrain Lab, School of Mechatronic Systems Engineering, Simon Fraser UniversityDepartment of Psychiatry, Dalhousie UniversityCentre for Addiction and Mental HealthUniversity of TorontoDepartment of Psychiatry, University of British ColumbiaDepartment of Psychiatry and Behavioural Neurosciences, McMaster UniversityDepartment of Psychiatry, Providence Care, Queen’s UniversityUniversity of TorontoDepartment of Psychiatry, Providence Care, Queen’s UniversityDepartment of Psychiatry and Behavioural Neurosciences, McMaster UniversityUniversity of TorontoUniversity of TorontoeBrain Lab, School of Mechatronic Systems Engineering, Simon Fraser UniversityAbstract Cognitive behavioral therapy (CBT) is often recommended as a first-line treatment in depression. However, access to CBT remains limited, and up to 50% of patients do not benefit from this therapy. Identifying biomarkers that can predict which patients will respond to CBT may assist in designing optimal treatment allocation strategies. In a Canadian Biomarker Integration Network for Depression (CAN-BIND) study, forty-one adults with depression were recruited to undergo a 16-week course of CBT with thirty having resting-state electroencephalography (EEG) recorded at baseline and week 2 of therapy. Successful clinical response to CBT was defined as a 50% or greater reduction in Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to post-treatment completion. EEG relative power spectral measures were analyzed at baseline, week 2, and as early changes from baseline to week 2. At baseline, lower relative delta (0.5–4 Hz) power was observed in responders. This difference was predictive of successful clinical response to CBT. Furthermore, responders exhibited an early increase in relative delta power and a decrease in relative alpha (8–12 Hz) power compared to non-responders. These changes were also found to be good predictors of response to the therapy. These findings showed the potential utility of resting-state EEG in predicting CBT outcomes. They also further reinforce the promise of an EEG-based clinical decision-making tool to support treatment decisions for each patient.https://doi.org/10.1038/s41598-023-35179-4 |
| spellingShingle | Benjamin Schwartzmann Lena C. Quilty Prabhjot Dhami Rudolf Uher Timothy A. Allen Stefan Kloiber Raymond W. Lam Benicio N. Frey Roumen Milev Daniel J. Müller Claudio N. Soares Jane A. Foster Susan Rotzinger Sidney H. Kennedy Faranak Farzan Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study Scientific Reports |
| title | Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study |
| title_full | Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study |
| title_fullStr | Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study |
| title_full_unstemmed | Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study |
| title_short | Resting-state EEG delta and alpha power predict response to cognitive behavioral therapy in depression: a Canadian biomarker integration network for depression study |
| title_sort | resting state eeg delta and alpha power predict response to cognitive behavioral therapy in depression a canadian biomarker integration network for depression study |
| url | https://doi.org/10.1038/s41598-023-35179-4 |
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