A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.

Published

Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • Woods, CW; McClain, MT; Chen, M; Zaas, AK; Nicholson, BP; Varkey, J; Veldman, T; Kingsmore, SF; Huang, Y; Lambkin-Williams, R; Gilbert, AG; Hero, AO; Ramsburg, E; Glickman, S; Lucas, JE; Carin, L; Ginsburg, GS

Published Date

  • January 9, 2013

Published In

Volume / Issue

  • 8 / 1

Start / End Page

  • e52198 -

PubMed ID

  • 23326326

Pubmed Central ID

  • 23326326

Electronic International Standard Serial Number (EISSN)

  • 1932-6203

International Standard Serial Number (ISSN)

  • 1932-6203

Digital Object Identifier (DOI)

  • 10.1371/journal.pone.0052198

Language

  • eng