Tags

Type your tag names separated by a space and hit enter

Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors.
Transl Psychiatry. 2020 Jun 27; 10(1):208.TP

Abstract

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.

Authors+Show Affiliations

Sagol Brain Institute Tel-Aviv, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel. Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel.Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel. Department of Statistics and Operations Research, Tel-Aviv University, Tel-Aviv, Israel.Sagol Brain Institute Tel-Aviv, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel. Faculty of Social Sciences, School of Psychological Sciences, Tel-Aviv University, Tel-Aviv, Israel.Department of Psychology, University of Haifa, Haifa, Israel.Laboratory of Early Markers of Neurodegeneration (LEMON), Department of Neurology, Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel. Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel.Sagol Brain Institute Tel-Aviv, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel. Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel. Institute of Pain Medicine, Department of Anesthesiology and Critical Care Medicine, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel. Pain Management & Neuromodulation Centre, Guy's & St Thomas' NHS Foundation Trust, London, UK.Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel. Department of Emergency Medicine, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel.Department of Psychiatry, Texas A&M Health Science Center, Bryan, TX, USA.Department of Psychiatry, NYU Langone Medical Center, New York, NY, USA.Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel. ybenja@tauex.tau.ac.il. Department of Statistics and Operations Research, Tel-Aviv University, Tel-Aviv, Israel. ybenja@tauex.tau.ac.il.Sagol Brain Institute Tel-Aviv, Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, Tel-Aviv, Israel. talma@tlvmc.gov.il. Sagol School of Neuroscience, Tel-Aviv University, Tel-Aviv, Israel. talma@tlvmc.gov.il. Faculty of Social Sciences, School of Psychological Sciences, Tel-Aviv University, Tel-Aviv, Israel. talma@tlvmc.gov.il. Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel. talma@tlvmc.gov.il.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

32594097

Citation

Ben-Zion, Ziv, et al. "Multi-domain Potential Biomarkers for Post-traumatic Stress Disorder (PTSD) Severity in Recent Trauma Survivors." Translational Psychiatry, vol. 10, no. 1, 2020, p. 208.
Ben-Zion Z, Zeevi Y, Keynan NJ, et al. Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors. Transl Psychiatry. 2020;10(1):208.
Ben-Zion, Z., Zeevi, Y., Keynan, N. J., Admon, R., Kozlovski, T., Sharon, H., Halpern, P., Liberzon, I., Shalev, A. Y., Benjamini, Y., & Hendler, T. (2020). Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors. Translational Psychiatry, 10(1), 208. https://doi.org/10.1038/s41398-020-00898-z
Ben-Zion Z, et al. Multi-domain Potential Biomarkers for Post-traumatic Stress Disorder (PTSD) Severity in Recent Trauma Survivors. Transl Psychiatry. 2020 Jun 27;10(1):208. PubMed PMID: 32594097.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors. AU - Ben-Zion,Ziv, AU - Zeevi,Yoav, AU - Keynan,Nimrod Jackob, AU - Admon,Roee, AU - Kozlovski,Tal, AU - Sharon,Haggai, AU - Halpern,Pinchas, AU - Liberzon,Israel, AU - Shalev,Arieh Y, AU - Benjamini,Yoav, AU - Hendler,Talma, Y1 - 2020/06/27/ PY - 2019/08/26/received PY - 2020/06/02/accepted PY - 2020/05/28/revised PY - 2020/6/29/entrez PY - 2020/7/1/pubmed PY - 2020/7/1/medline SP - 208 EP - 208 JF - Translational psychiatry JO - Transl Psychiatry VL - 10 IS - 1 N2 - 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. SN - 2158-3188 UR - https://www.unboundmedicine.com/medline/citation/32594097/Multi-domain_potential_biomarkers_for_post-traumatic_stress_disorder_(PTSD)_severity_in_recent_trauma_survivors L2 - http://dx.doi.org/10.1038/s41398-020-00898-z DB - PRIME DP - Unbound Medicine ER -
Try the Free App:
Prime PubMed app for iOS iPhone iPad
Prime PubMed app for Android
Prime PubMed is provided
free to individuals by:
Unbound Medicine.