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Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors

Contemporary symptom-based diagnosis of post-traumatic stress disorder (PTSD) largely overlooks related neurobehavioral mechanisms and relies entirely on subjective interpersonal reporting. Previous studies associating biomarkers with PTSD have mostly used symptom-based diagnosis as the main outcome...

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Autores principales: Ben-Zion, Ziv, Zeevi, Yoav, Keynan, Nimrod Jackob, Admon, Roee, Kozlovski, Tal, Sharon, Haggai, Halpern, Pinchas, Liberzon, Israel, Shalev, Arieh Y., Benjamini, Yoav, Hendler, Talma
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320966/
https://www.ncbi.nlm.nih.gov/pubmed/32594097
http://dx.doi.org/10.1038/s41398-020-00898-z
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author Ben-Zion, Ziv
Zeevi, Yoav
Keynan, Nimrod Jackob
Admon, Roee
Kozlovski, Tal
Sharon, Haggai
Halpern, Pinchas
Liberzon, Israel
Shalev, Arieh Y.
Benjamini, Yoav
Hendler, Talma
author_facet Ben-Zion, Ziv
Zeevi, Yoav
Keynan, Nimrod Jackob
Admon, Roee
Kozlovski, Tal
Sharon, Haggai
Halpern, Pinchas
Liberzon, Israel
Shalev, Arieh Y.
Benjamini, Yoav
Hendler, Talma
author_sort Ben-Zion, Ziv
collection PubMed
description Contemporary symptom-based diagnosis of post-traumatic stress disorder (PTSD) largely overlooks related neurobehavioral mechanisms and relies entirely on subjective interpersonal reporting. Previous studies associating biomarkers with PTSD have mostly used symptom-based diagnosis as the main outcome measure, disregarding the wide variability and richness of PTSD phenotypical features. Here, we aimed to computationally derive potential biomarkers that could efficiently differentiate PTSD subtypes among recent trauma survivors. A three-staged semi-unsupervised method (“3C”) was used to firstly categorize individuals by current PTSD symptom severity, then derive clusters based on clinical features related to PTSD (e.g. anxiety and depression), and finally to classify participants’ cluster membership using objective multi-domain features. A total of 256 features were extracted from psychometrics, cognitive functioning, and both structural and functional MRI data, obtained from 101 adult civilians (age = 34.80 ± 11.95; 51 females) evaluated within 1 month of trauma exposure. The features that best differentiated cluster membership were assessed by importance analysis, classification tree, and ANOVA. Results revealed that entorhinal and rostral anterior cingulate cortices volumes (structural MRI domain), in-task amygdala’s functional connectivity with the insula and thalamus (functional MRI domain), executive function and cognitive flexibility (cognitive testing domain) best differentiated between two clusters associated with PTSD severity. Cross-validation established the results’ robustness and consistency within this sample. The neural and cognitive potential biomarkers revealed by the 3C analytics offer objective classifiers of post-traumatic morbidity shortly following trauma. They also map onto previously documented neurobehavioral mechanisms associated with PTSD and demonstrate the usefulness of standardized and objective measurements as differentiating clinical sub-classes shortly after trauma.
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spelling pubmed-73209662020-06-30 Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors Ben-Zion, Ziv Zeevi, Yoav Keynan, Nimrod Jackob Admon, Roee Kozlovski, Tal Sharon, Haggai Halpern, Pinchas Liberzon, Israel Shalev, Arieh Y. Benjamini, Yoav Hendler, Talma Transl Psychiatry Article Contemporary symptom-based diagnosis of post-traumatic stress disorder (PTSD) largely overlooks related neurobehavioral mechanisms and relies entirely on subjective interpersonal reporting. Previous studies associating biomarkers with PTSD have mostly used symptom-based diagnosis as the main outcome measure, disregarding the wide variability and richness of PTSD phenotypical features. Here, we aimed to computationally derive potential biomarkers that could efficiently differentiate PTSD subtypes among recent trauma survivors. A three-staged semi-unsupervised method (“3C”) was used to firstly categorize individuals by current PTSD symptom severity, then derive clusters based on clinical features related to PTSD (e.g. anxiety and depression), and finally to classify participants’ cluster membership using objective multi-domain features. A total of 256 features were extracted from psychometrics, cognitive functioning, and both structural and functional MRI data, obtained from 101 adult civilians (age = 34.80 ± 11.95; 51 females) evaluated within 1 month of trauma exposure. The features that best differentiated cluster membership were assessed by importance analysis, classification tree, and ANOVA. Results revealed that entorhinal and rostral anterior cingulate cortices volumes (structural MRI domain), in-task amygdala’s functional connectivity with the insula and thalamus (functional MRI domain), executive function and cognitive flexibility (cognitive testing domain) best differentiated between two clusters associated with PTSD severity. Cross-validation established the results’ robustness and consistency within this sample. The neural and cognitive potential biomarkers revealed by the 3C analytics offer objective classifiers of post-traumatic morbidity shortly following trauma. They also map onto previously documented neurobehavioral mechanisms associated with PTSD and demonstrate the usefulness of standardized and objective measurements as differentiating clinical sub-classes shortly after trauma. Nature Publishing Group UK 2020-06-27 /pmc/articles/PMC7320966/ /pubmed/32594097 http://dx.doi.org/10.1038/s41398-020-00898-z Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Ben-Zion, Ziv
Zeevi, Yoav
Keynan, Nimrod Jackob
Admon, Roee
Kozlovski, Tal
Sharon, Haggai
Halpern, Pinchas
Liberzon, Israel
Shalev, Arieh Y.
Benjamini, Yoav
Hendler, Talma
Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors
title Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors
title_full Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors
title_fullStr Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors
title_full_unstemmed Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors
title_short Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors
title_sort multi-domain potential biomarkers for post-traumatic stress disorder (ptsd) severity in recent trauma survivors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7320966/
https://www.ncbi.nlm.nih.gov/pubmed/32594097
http://dx.doi.org/10.1038/s41398-020-00898-z
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