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Diagnostic blood RNA profiles for human acute spinal cord injury
Diagnosis of spinal cord injury (SCI) severity at the ultra-acute stage is of great importance for emergency clinical care of patients as well as for potential enrollment into clinical trials. The lack of a diagnostic biomarker for SCI has played a major role in the poor results of clinical trials....
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Rockefeller University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7852457/ https://www.ncbi.nlm.nih.gov/pubmed/33512429 http://dx.doi.org/10.1084/jem.20201795 |
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author | Kyritsis, Nikos Torres-Espín, Abel Schupp, Patrick G. Huie, J. Russell Chou, Austin Duong-Fernandez, Xuan Thomas, Leigh H. Tsolinas, Rachel E. Hemmerle, Debra D. Pascual, Lisa U. Singh, Vineeta Pan, Jonathan Z. Talbott, Jason F. Whetstone, William D. Burke, John F. DiGiorgio, Anthony M. Weinstein, Philip R. Manley, Geoffrey T. Dhall, Sanjay S. Ferguson, Adam R. Oldham, Michael C. Bresnahan, Jacqueline C. Beattie, Michael S. |
author_facet | Kyritsis, Nikos Torres-Espín, Abel Schupp, Patrick G. Huie, J. Russell Chou, Austin Duong-Fernandez, Xuan Thomas, Leigh H. Tsolinas, Rachel E. Hemmerle, Debra D. Pascual, Lisa U. Singh, Vineeta Pan, Jonathan Z. Talbott, Jason F. Whetstone, William D. Burke, John F. DiGiorgio, Anthony M. Weinstein, Philip R. Manley, Geoffrey T. Dhall, Sanjay S. Ferguson, Adam R. Oldham, Michael C. Bresnahan, Jacqueline C. Beattie, Michael S. |
author_sort | Kyritsis, Nikos |
collection | PubMed |
description | Diagnosis of spinal cord injury (SCI) severity at the ultra-acute stage is of great importance for emergency clinical care of patients as well as for potential enrollment into clinical trials. The lack of a diagnostic biomarker for SCI has played a major role in the poor results of clinical trials. We analyzed global gene expression in peripheral white blood cells during the acute injury phase and identified 197 genes whose expression changed after SCI compared with healthy and trauma controls and in direct relation to SCI severity. Unsupervised coexpression network analysis identified several gene modules that predicted injury severity (AIS grades) with an overall accuracy of 72.7% and included signatures of immune cell subtypes. Specifically, for complete SCIs (AIS A), ROC analysis showed impressive specificity and sensitivity (AUC: 0.865). Similar precision was also shown for AIS D SCIs (AUC: 0.938). Our findings indicate that global transcriptomic changes in peripheral blood cells have diagnostic and potentially prognostic value for SCI severity. |
format | Online Article Text |
id | pubmed-7852457 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Rockefeller University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-78524572021-02-04 Diagnostic blood RNA profiles for human acute spinal cord injury Kyritsis, Nikos Torres-Espín, Abel Schupp, Patrick G. Huie, J. Russell Chou, Austin Duong-Fernandez, Xuan Thomas, Leigh H. Tsolinas, Rachel E. Hemmerle, Debra D. Pascual, Lisa U. Singh, Vineeta Pan, Jonathan Z. Talbott, Jason F. Whetstone, William D. Burke, John F. DiGiorgio, Anthony M. Weinstein, Philip R. Manley, Geoffrey T. Dhall, Sanjay S. Ferguson, Adam R. Oldham, Michael C. Bresnahan, Jacqueline C. Beattie, Michael S. J Exp Med Brief Definitive Report Diagnosis of spinal cord injury (SCI) severity at the ultra-acute stage is of great importance for emergency clinical care of patients as well as for potential enrollment into clinical trials. The lack of a diagnostic biomarker for SCI has played a major role in the poor results of clinical trials. We analyzed global gene expression in peripheral white blood cells during the acute injury phase and identified 197 genes whose expression changed after SCI compared with healthy and trauma controls and in direct relation to SCI severity. Unsupervised coexpression network analysis identified several gene modules that predicted injury severity (AIS grades) with an overall accuracy of 72.7% and included signatures of immune cell subtypes. Specifically, for complete SCIs (AIS A), ROC analysis showed impressive specificity and sensitivity (AUC: 0.865). Similar precision was also shown for AIS D SCIs (AUC: 0.938). Our findings indicate that global transcriptomic changes in peripheral blood cells have diagnostic and potentially prognostic value for SCI severity. Rockefeller University Press 2021-01-29 /pmc/articles/PMC7852457/ /pubmed/33512429 http://dx.doi.org/10.1084/jem.20201795 Text en © 2021 Kyritsis et al. https://creativecommons.org/licenses/by/4.0/This article is available under a Creative Commons License (Attribution 4.0 International, as described at https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Brief Definitive Report Kyritsis, Nikos Torres-Espín, Abel Schupp, Patrick G. Huie, J. Russell Chou, Austin Duong-Fernandez, Xuan Thomas, Leigh H. Tsolinas, Rachel E. Hemmerle, Debra D. Pascual, Lisa U. Singh, Vineeta Pan, Jonathan Z. Talbott, Jason F. Whetstone, William D. Burke, John F. DiGiorgio, Anthony M. Weinstein, Philip R. Manley, Geoffrey T. Dhall, Sanjay S. Ferguson, Adam R. Oldham, Michael C. Bresnahan, Jacqueline C. Beattie, Michael S. Diagnostic blood RNA profiles for human acute spinal cord injury |
title | Diagnostic blood RNA profiles for human acute spinal cord injury |
title_full | Diagnostic blood RNA profiles for human acute spinal cord injury |
title_fullStr | Diagnostic blood RNA profiles for human acute spinal cord injury |
title_full_unstemmed | Diagnostic blood RNA profiles for human acute spinal cord injury |
title_short | Diagnostic blood RNA profiles for human acute spinal cord injury |
title_sort | diagnostic blood rna profiles for human acute spinal cord injury |
topic | Brief Definitive Report |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7852457/ https://www.ncbi.nlm.nih.gov/pubmed/33512429 http://dx.doi.org/10.1084/jem.20201795 |
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