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Neurobiological Markers for Predicting Treatment Response in Patients with Bipolar Disorder
Predictive neurobiological markers for prognosis are essential but underemphasized for patients with bipolar disorder (BD), a neuroprogressive disorder. Hence, we developed models for predicting symptom and functioning changes. Sixty-one patients with BD were recruited and assessed using the Young M...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9775451/ https://www.ncbi.nlm.nih.gov/pubmed/36551802 http://dx.doi.org/10.3390/biomedicines10123047 |
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author | Chen, Yen-Ling Huang, Tzu-Hsuan Tu, Pei-Chi Bai, Ya-Mei Su, Tung-Ping Chen, Mu-Hong Hong, Jia-Sheng Wu, Yu-Te |
author_facet | Chen, Yen-Ling Huang, Tzu-Hsuan Tu, Pei-Chi Bai, Ya-Mei Su, Tung-Ping Chen, Mu-Hong Hong, Jia-Sheng Wu, Yu-Te |
author_sort | Chen, Yen-Ling |
collection | PubMed |
description | Predictive neurobiological markers for prognosis are essential but underemphasized for patients with bipolar disorder (BD), a neuroprogressive disorder. Hence, we developed models for predicting symptom and functioning changes. Sixty-one patients with BD were recruited and assessed using the Young Mania Rating Scale (YMRS), Montgomery–Åsberg Depression Rating Scale (MADRS), Positive and Negative Syndrome Scale (PANSS), UKU Side Effect Rating Scale (UKU), Personal and Social Performance Scale (PSP), and Global Assessment of Functioning scale both at baseline and after 1-year follow-up. The models for predicting the changes in symptom and functioning scores were trained using data on the brain morphology, functional connectivity, and cytokines collected at baseline. The correlation between the predicted and actual changes in the YMRS, MADRS, PANSS, and UKU scores was higher than 0.86 (q < 0.05). Connections from subcortical and cerebellar regions were considered for predicting the changes in the YMRS, MADRS, and UKU scores. Moreover, connections of the motor network were considered for predicting the changes in the YMRS and MADRS scores. The neurobiological markers for predicting treatment-response symptoms and functioning changes were consistent with the neuropathology of BD and with the differences found between treatment responders and nonresponders. |
format | Online Article Text |
id | pubmed-9775451 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-97754512022-12-23 Neurobiological Markers for Predicting Treatment Response in Patients with Bipolar Disorder Chen, Yen-Ling Huang, Tzu-Hsuan Tu, Pei-Chi Bai, Ya-Mei Su, Tung-Ping Chen, Mu-Hong Hong, Jia-Sheng Wu, Yu-Te Biomedicines Article Predictive neurobiological markers for prognosis are essential but underemphasized for patients with bipolar disorder (BD), a neuroprogressive disorder. Hence, we developed models for predicting symptom and functioning changes. Sixty-one patients with BD were recruited and assessed using the Young Mania Rating Scale (YMRS), Montgomery–Åsberg Depression Rating Scale (MADRS), Positive and Negative Syndrome Scale (PANSS), UKU Side Effect Rating Scale (UKU), Personal and Social Performance Scale (PSP), and Global Assessment of Functioning scale both at baseline and after 1-year follow-up. The models for predicting the changes in symptom and functioning scores were trained using data on the brain morphology, functional connectivity, and cytokines collected at baseline. The correlation between the predicted and actual changes in the YMRS, MADRS, PANSS, and UKU scores was higher than 0.86 (q < 0.05). Connections from subcortical and cerebellar regions were considered for predicting the changes in the YMRS, MADRS, and UKU scores. Moreover, connections of the motor network were considered for predicting the changes in the YMRS and MADRS scores. The neurobiological markers for predicting treatment-response symptoms and functioning changes were consistent with the neuropathology of BD and with the differences found between treatment responders and nonresponders. MDPI 2022-11-25 /pmc/articles/PMC9775451/ /pubmed/36551802 http://dx.doi.org/10.3390/biomedicines10123047 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chen, Yen-Ling Huang, Tzu-Hsuan Tu, Pei-Chi Bai, Ya-Mei Su, Tung-Ping Chen, Mu-Hong Hong, Jia-Sheng Wu, Yu-Te Neurobiological Markers for Predicting Treatment Response in Patients with Bipolar Disorder |
title | Neurobiological Markers for Predicting Treatment Response in Patients with Bipolar Disorder |
title_full | Neurobiological Markers for Predicting Treatment Response in Patients with Bipolar Disorder |
title_fullStr | Neurobiological Markers for Predicting Treatment Response in Patients with Bipolar Disorder |
title_full_unstemmed | Neurobiological Markers for Predicting Treatment Response in Patients with Bipolar Disorder |
title_short | Neurobiological Markers for Predicting Treatment Response in Patients with Bipolar Disorder |
title_sort | neurobiological markers for predicting treatment response in patients with bipolar disorder |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9775451/ https://www.ncbi.nlm.nih.gov/pubmed/36551802 http://dx.doi.org/10.3390/biomedicines10123047 |
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