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BMC Syst Biol. 2011 Dec 22;5:202. doi: 10.1186/1752-0509-5-202.

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

Author information

1
Department of Microbiology, University of Washington, Seattle WA, USA.

Abstract

BACKGROUND:

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.

RESULTS:

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.

CONCLUSIONS:

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.

PMID:
22189154
PMCID:
PMC3297540
DOI:
10.1186/1752-0509-5-202
[Indexed for MEDLINE]
Free PMC Article

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