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Integrated, Multi-cohort Analysis Identifies Conserved Transcriptional Signatures across Multiple Respiratory Viruses

Respiratory viral infections are a significant burden to healthcare worldwide. Many whole genome expression profiles have identified different respiratory viral infection signatures, but these have not translated to clinical practice. Here, we performed two integrated, multi-cohort analyses of publi...

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Autores principales: Andres-Terre, Marta, McGuire, Helen M., Pouliot, Yannick, Bongen, Erika, Sweeney, Timothy E., Tato, Cristina M., Khatri, Purvesh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4684904/
https://www.ncbi.nlm.nih.gov/pubmed/26682989
http://dx.doi.org/10.1016/j.immuni.2015.11.003
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author Andres-Terre, Marta
McGuire, Helen M.
Pouliot, Yannick
Bongen, Erika
Sweeney, Timothy E.
Tato, Cristina M.
Khatri, Purvesh
author_facet Andres-Terre, Marta
McGuire, Helen M.
Pouliot, Yannick
Bongen, Erika
Sweeney, Timothy E.
Tato, Cristina M.
Khatri, Purvesh
author_sort Andres-Terre, Marta
collection PubMed
description Respiratory viral infections are a significant burden to healthcare worldwide. Many whole genome expression profiles have identified different respiratory viral infection signatures, but these have not translated to clinical practice. Here, we performed two integrated, multi-cohort analyses of publicly available transcriptional data of viral infections. First, we identified a common host signature across different respiratory viral infections that could distinguish (1) individuals with viral infections from healthy controls and from those with bacterial infections, and (2) symptomatic from asymptomatic subjects prior to symptom onset in challenge studies. Second, we identified an influenza-specific host response signature that (1) could distinguish influenza-infected samples from those with bacterial and other respiratory viral infections, (2) was a diagnostic and prognostic marker in influenza-pneumonia patients and influenza challenge studies, and (3) was predictive of response to influenza vaccine. Our results have applications in the diagnosis, prognosis, and identification of drug targets in viral infections.
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spelling pubmed-46849042016-12-15 Integrated, Multi-cohort Analysis Identifies Conserved Transcriptional Signatures across Multiple Respiratory Viruses Andres-Terre, Marta McGuire, Helen M. Pouliot, Yannick Bongen, Erika Sweeney, Timothy E. Tato, Cristina M. Khatri, Purvesh Immunity Resource Respiratory viral infections are a significant burden to healthcare worldwide. Many whole genome expression profiles have identified different respiratory viral infection signatures, but these have not translated to clinical practice. Here, we performed two integrated, multi-cohort analyses of publicly available transcriptional data of viral infections. First, we identified a common host signature across different respiratory viral infections that could distinguish (1) individuals with viral infections from healthy controls and from those with bacterial infections, and (2) symptomatic from asymptomatic subjects prior to symptom onset in challenge studies. Second, we identified an influenza-specific host response signature that (1) could distinguish influenza-infected samples from those with bacterial and other respiratory viral infections, (2) was a diagnostic and prognostic marker in influenza-pneumonia patients and influenza challenge studies, and (3) was predictive of response to influenza vaccine. Our results have applications in the diagnosis, prognosis, and identification of drug targets in viral infections. Elsevier Inc. 2015-12-15 2015-12-17 /pmc/articles/PMC4684904/ /pubmed/26682989 http://dx.doi.org/10.1016/j.immuni.2015.11.003 Text en Copyright © 2015 Elsevier Inc. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Resource
Andres-Terre, Marta
McGuire, Helen M.
Pouliot, Yannick
Bongen, Erika
Sweeney, Timothy E.
Tato, Cristina M.
Khatri, Purvesh
Integrated, Multi-cohort Analysis Identifies Conserved Transcriptional Signatures across Multiple Respiratory Viruses
title Integrated, Multi-cohort Analysis Identifies Conserved Transcriptional Signatures across Multiple Respiratory Viruses
title_full Integrated, Multi-cohort Analysis Identifies Conserved Transcriptional Signatures across Multiple Respiratory Viruses
title_fullStr Integrated, Multi-cohort Analysis Identifies Conserved Transcriptional Signatures across Multiple Respiratory Viruses
title_full_unstemmed Integrated, Multi-cohort Analysis Identifies Conserved Transcriptional Signatures across Multiple Respiratory Viruses
title_short Integrated, Multi-cohort Analysis Identifies Conserved Transcriptional Signatures across Multiple Respiratory Viruses
title_sort integrated, multi-cohort analysis identifies conserved transcriptional signatures across multiple respiratory viruses
topic Resource
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4684904/
https://www.ncbi.nlm.nih.gov/pubmed/26682989
http://dx.doi.org/10.1016/j.immuni.2015.11.003
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