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A chemokine gene expression signature derived from meta-analysis predicts the pathogenicity of viral respiratory infections

BMC systems biology, 2011-12, Vol.5 (202), p.202-202, Article 202 [Peer Reviewed Journal]

COPYRIGHT 2011 BioMed Central Ltd. ;COPYRIGHT 2011 BioMed Central Ltd. ;2011 Chang et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. ;Distributed under a Creative Commons Attribution 4.0 International License ;Copyright ©2011 Chang et al; licensee BioMed Central Ltd. 2011 Chang et al; licensee BioMed Central Ltd. ;ISSN: 1752-0509 ;EISSN: 1752-0509 ;DOI: 10.1186/1752-0509-5-202 ;PMID: 22189154

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Title:
A chemokine gene expression signature derived from meta-analysis predicts the pathogenicity of viral respiratory infections
Author: Chang, Stewart T ; Tchitchek, Nicolas ; Ghosh, Debashis ; Benecke, Arndt ; Katze, Michael G
Subjects: Analysis ; Avian flu ; Avian influenza ; Avian influenza viruses ; Chemokines ; Chemokines - genetics ; Chemokines - metabolism ; Cluster Analysis ; Gene expression ; Gene Expression Profiling ; Gene Expression Regulation, Viral - genetics ; Genes ; Genetic aspects ; Genetic research ; Health aspects ; Humans ; Influenza A Virus, H1N1 Subtype - genetics ; Influenza A Virus, H1N1 Subtype - metabolism ; Influenza A Virus, H1N1 Subtype - pathogenicity ; Influenza A Virus, H5N1 Subtype - genetics ; Influenza A Virus, H5N1 Subtype - metabolism ; Influenza A Virus, H5N1 Subtype - pathogenicity ; Life Sciences ; Lung diseases ; Medical research ; Medicine, Experimental ; Meta-analysis ; Methods ; Mortality ; Pandemics ; Physiological aspects ; Principal components analysis ; Ratios ; Respiratory Tract Infections - immunology ; Respiratory Tract Infections - virology ; Risk factors ; Severe acute respiratory syndrome ; Severe acute respiratory syndrome-related coronavirus - genetics ; Severe acute respiratory syndrome-related coronavirus - metabolism ; Severe acute respiratory syndrome-related coronavirus - pathogenicity ; Studies ; Viral infections ; Virulence ; Virus diseases
Is Part Of: BMC systems biology, 2011-12, Vol.5 (202), p.202-202, Article 202
Description: During respiratory viral infections host injury occurs due in part to inappropriate host responses. In this study we sought to uncover the host transcriptional responses underlying differences between high- and low-pathogenic infections. From a compendium of 12 studies that included responses to influenza A subtype H5N1, reconstructed 1918 influenza A virus, and SARS coronavirus, we used meta-analysis to derive multiple gene expression signatures. We compared these signatures by their capacity to segregate biological conditions by pathogenicity and predict pathogenicity in a test data set. The highest-performing signature was expressed as a continuum in low-, medium-, and high-pathogenicity samples, suggesting a direct, analog relationship between expression and pathogenicity. This signature comprised 57 genes including a subnetwork of chemokines, implicating dysregulated cell recruitment in injury. Highly pathogenic viruses elicit expression of many of the same key genes as lower pathogenic viruses but to a higher degree. This increased degree of expression may result in the uncontrolled co-localization of inflammatory cell types and lead to irreversible host damage.
Publisher: England: BioMed Central Ltd
Language: English
Identifier: ISSN: 1752-0509
EISSN: 1752-0509
DOI: 10.1186/1752-0509-5-202
PMID: 22189154
Source: Hyper Article en Ligne (HAL) (Open Access)
GFMER Free Medical Journals
MEDLINE
PubMed Central
Alma/SFX Local Collection
Coronavirus Research Database
ProQuest Central
Springer Nature OA Free Journals

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A chemokine gene expression signature derived from meta-analysis predicts the pathogenicity of viral respiratory infections

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