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Immunity. 2015 Dec 15;43(6):1199-211. doi: 10.1016/j.immuni.2015.11.003.

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

Author information

1
Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, CA 94305, USA.
2
Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, CA 94305, USA; Division of Biomedical Informatics, Department of Medicine, Stanford University, Stanford, CA 94305, USA.
3
Institute for Immunity, Transplantation, and Infection, Stanford University, Stanford, CA 94305, USA; Division of Biomedical Informatics, Department of Medicine, Stanford University, Stanford, CA 94305, USA. Electronic address: pkhatri@stanford.edu.

Abstract

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.

PMID:
26682989
PMCID:
PMC4684904
DOI:
10.1016/j.immuni.2015.11.003
[Indexed for MEDLINE]
Free PMC Article

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