A Host Transcriptional Signature for Presymptomatic Detection of Infection in Humans Exposed to Influenza H1N1 or H3N2

Christopher W. Woods, Micah T. McClain, Minhua Chen, Aimee K. Zaas, Bradly P. Nicholson, Jay Varkey, Timothy Veldman, Stephen F. Kingsmore, Yongsheng Huang, Robert Lambkin-Williams, Anthony G. Gilbert, Alfred O. Hero, Elizabeth Ramsburg, Seth Glickman, Joseph E. Lucas, Lawrence Carin, Geoffrey S. Ginsburg

Research output: Contribution to journalArticlepeer-review

108 Scopus citations

Abstract

There is great potential for host-based gene expression analysis to impact the early diagnosis of infectious diseases. In particular, the influenza pandemic of 2009 highlighted the challenges and limitations of traditional pathogen-based testing for suspected upper respiratory viral infection. We inoculated human volunteers with either influenza A (A/Brisbane/59/2007 (H1N1) or A/Wisconsin/67/2005 (H3N2)), and assayed the peripheral blood transcriptome every 8 hours for 7 days. Of 41 inoculated volunteers, 18 (44%) developed symptomatic infection. Using unbiased sparse latent factor regression analysis, we generated a gene signature (or factor) for symptomatic influenza capable of detecting 94% of infected cases. This gene signature is detectable as early as 29 hours post-exposure and achieves maximal accuracy on average 43 hours (p = 0.003, H1N1) and 38 hours (p-value = 0.005, H3N2) before peak clinical symptoms. In order to test the relevance of these findings in naturally acquired disease, a composite influenza A signature built from these challenge studies was applied to Emergency Department patients where it discriminates between swine-origin influenza A/H1N1 (2009) infected and non-infected individuals with 92% accuracy. The host genomic response to Influenza infection is robust and may provide the means for detection before typical clinical symptoms are apparent. © 2013 Woods et al.
Original languageEnglish (US)
JournalPLoS ONE
Volume8
Issue number1
DOIs
StatePublished - Jan 9 2013
Externally publishedYes

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