A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2.
dc.contributor.author | Woods, Christopher W | |
dc.contributor.author | McClain, Micah T | |
dc.contributor.author | Chen, Minhua | |
dc.contributor.author | Zaas, Aimee K | |
dc.contributor.author | Nicholson, Bradly P | |
dc.contributor.author | Varkey, Jay | |
dc.contributor.author | Veldman, Timothy | |
dc.contributor.author | Kingsmore, Stephen F | |
dc.contributor.author | Kingsmore, Stephen F | |
dc.contributor.author | Huang, Yongsheng | |
dc.contributor.author | Lambkin-Williams, Robert | |
dc.contributor.author | Gilbert, Anthony G | |
dc.contributor.author | Hero, Alfred O | |
dc.contributor.author | Ramsburg, Elizabeth | |
dc.contributor.author | Glickman, Seth | |
dc.contributor.author | Lucas, Joseph E | |
dc.contributor.author | Carin, Lawrence | |
dc.contributor.author | Ginsburg, Geoffrey S | |
dc.contributor.editor | Tse, Herman | |
dc.coverage.spatial | United States | |
dc.date.accessioned | 2014-07-22T16:09:16Z | |
dc.date.issued | 2013 | |
dc.description.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. | |
dc.identifier | ||
dc.identifier | PONE-D-12-19352 | |
dc.identifier.eissn | 1932-6203 | |
dc.identifier.uri | ||
dc.language | eng | |
dc.publisher | Public Library of Science (PLoS) | |
dc.relation.ispartof | PLoS One | |
dc.relation.isversionof | 10.1371/journal.pone.0052198 | |
dc.subject | Female | |
dc.subject | Host-Pathogen Interactions | |
dc.subject | Humans | |
dc.subject | Influenza A Virus, H1N1 Subtype | |
dc.subject | Influenza A Virus, H3N2 Subtype | |
dc.subject | Influenza, Human | |
dc.subject | Male | |
dc.subject | Middle Aged | |
dc.subject | Oligonucleotide Array Sequence Analysis | |
dc.subject | Reverse Transcriptase Polymerase Chain Reaction | |
dc.subject | Species Specificity | |
dc.subject | Time Factors | |
dc.subject | Transcriptome | |
dc.subject | Young Adult | |
dc.title | A host transcriptional signature for presymptomatic detection of infection in humans exposed to influenza H1N1 or H3N2. | |
dc.type | Journal article | |
duke.contributor.orcid | Woods, Christopher W|0000-0001-7240-2453 | |
duke.contributor.orcid | Ginsburg, Geoffrey S|0000-0003-4739-9808 | |
pubs.author-url | ||
pubs.begin-page | e52198 | |
pubs.issue | 1 | |
pubs.organisational-group | Basic Science Departments | |
pubs.organisational-group | Biomedical Engineering | |
pubs.organisational-group | Biostatistics & Bioinformatics | |
pubs.organisational-group | Clinical Science Departments | |
pubs.organisational-group | Duke | |
pubs.organisational-group | Duke Cancer Institute | |
pubs.organisational-group | Electrical and Computer Engineering | |
pubs.organisational-group | Global Health Institute | |
pubs.organisational-group | Institutes and Centers | |
pubs.organisational-group | Institutes and Provost's Academic Units | |
pubs.organisational-group | Medicine | |
pubs.organisational-group | Medicine, Cardiology | |
pubs.organisational-group | Medicine, Infectious Diseases | |
pubs.organisational-group | Molecular Genetics and Microbiology | |
pubs.organisational-group | Pathology | |
pubs.organisational-group | Pratt School of Engineering | |
pubs.organisational-group | School of Medicine | |
pubs.organisational-group | School of Nursing | |
pubs.organisational-group | School of Nursing - Secondary Group | |
pubs.organisational-group | Social Science Research Institute | |
pubs.organisational-group | University Institutes and Centers | |
pubs.publication-status | Published | |
pubs.volume | 8 |
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